European Journal of Applied Physiology

, Volume 118, Issue 4, pp 691–728 | Cite as

Lactate metabolism: historical context, prior misinterpretations, and current understanding

  • Brian S. Ferguson
  • Matthew J. Rogatzki
  • Matthew L. Goodwin
  • Daniel A. Kane
  • Zachary Rightmire
  • L. Bruce Gladden
Invited Review


Lactate (La) has long been at the center of controversy in research, clinical, and athletic settings. Since its discovery in 1780, La has often been erroneously viewed as simply a hypoxic waste product with multiple deleterious effects. Not until the 1980s, with the introduction of the cell-to-cell lactate shuttle did a paradigm shift in our understanding of the role of La in metabolism begin. The evidence for La as a major player in the coordination of whole-body metabolism has since grown rapidly. La is a readily combusted fuel that is shuttled throughout the body, and it is a potent signal for angiogenesis irrespective of oxygen tension. Despite this, many fundamental discoveries about La are still working their way into mainstream research, clinical care, and practice. The purpose of this review is to synthesize current understanding of La metabolism via an appraisal of its robust experimental history, particularly in exercise physiology. That La production increases during dysoxia is beyond debate, but this condition is the exception rather than the rule. Fluctuations in blood [La] in health and disease are not typically due to low oxygen tension, a principle first demonstrated with exercise and now understood to varying degrees across disciplines. From its role in coordinating whole-body metabolism as a fuel to its role as a signaling molecule in tumors, the study of La metabolism continues to expand and holds potential for multiple clinical applications. This review highlights La’s central role in metabolism and amplifies our understanding of past research.


Lactate metabolism Lactate shuttle Hypoxia Glycolysis Cancer metabolism Astrocyte–neuron lactate shuttle Lactate threshold Mitochondria Fatigue and lactic acidosis Cytosolic redox 



Adenosine diphosphate


Astrocyte–neuron lactate shuttle


Adenosine triphosphate


Cytochrome c


Chaperone protein for MCT1


Cytosolic l-lactate dehydrogenase


Carbon dioxide


Coenzyme A;


Cytochrome oxidase complex IV


Method for determination of lactate threshold


Excitatory amino acid transporters


Gas exchange threshold


Glucose transporter


HCA1 G-protein coupled receptor 81


Gastrocnemius-superficial digital flexor muscle complex


Hydrogen ion, proton


Proton magnetic resonance spectroscopy


Isotopic bicarbonate


Hypoxia-inducible factor-1


Complex I/NADH oxidoreductase of the mitochondrial electron system


Complex III of the mitochondrial electron transport system


Complex IV/cytochrome c oxidase


Michaelis–Menten constant for concentration of substrate at half-maximal speed of a reaction or transport process


Lactate anion


Lactate anion concentration


Lactate dehydrogenase


Lactate-protected hypoglycemia


Lactate threshold


Lactate threshold as determined by the Dmax method


Malate–aspartate shuttle


Monocarboxylate transporter


Mitochondrial lactate dehydrogenase


Maximal lactate steady state


Mitochondrial pyruvate carrier


Oxidized nicotinamide adenine dinucleotide


Reduced nicotinamide adenine dinucleotide


Reduced nicotinamide adenine dinucleotide phosphate




Onset of blood lactate accumulation


Pyruvate dehydrogenase


Pyruvate dehydrogenase kinase 1


αPeroxisome proliferator activated receptor gamma coactivator-1α


Inorganic phosphate


Intracellular partial pressure of oxygen






Solute Carrier Family 16 proteins


Tricarboxylic acid cycle


Uncoupling protein 3


Complex V/ATP synthase

\(\dot {V}\)CO2

Carbon dioxide output per minute

\(\dot {V}\)O2

Oxygen uptake per minute

\(\dot {V}\)O2LT

Oxygen uptake per minute at the lactate threshold

\(\dot {V}\)O2max

Maximum oxygen uptake per minute

\(\dot {V}\)O2peak

Peak oxygen uptake per minute


Within the physiological pH range of muscle and blood, lactic acid (HLa) is more than 99% dissociated into lactate anions (La) and protons (H+). Therefore, it will generally be referred to as “La” in this review. Unless otherwise specified, the l(+) enantiomer of La is implied. Enantiomers are a pair of stereoisomers which are mirror images of each other. In the case of La (Fig. 1), the C2 carbon is asymmetrical (Chen et al. 2015) leading to enantiomers that are sometimes designated as l(+)La and d(−)La, although perhaps more correctly as (S)-La and (R)-La, respectively (Cahn et al. 1956). While there is some d(−)La in human tissues and blood from both endogenous and exogenous sources, the l(+) form is by far the most predominant and the one produced by glycolytic activity. Serum d(−)La concentration is between 0.013 and 0.2 mM in healthy humans (Hasegawa et al. 2003; Filiz et al. 2010) in comparison with l(+)La concentration on the order of 1.0 mM at rest and more than 15.0 mM after short duration maximal effort exercise.

Fig. 1

Enantiomers of lactate. Enantiomers are a pair of stereoisomers which are mirror images of each other. While there is some d(−)La in human tissues and blood from both endogenous and exogenous sources, the l(+) form is by far the most predominant and the one produced by glycolytic activity

The oft extolled, and persistent beliefs surrounding La can be found in numerous places, including popular fitness magazines, scientific literature, the athletic and coaching community, and clinical treatment. All too often, the framework of understanding has stemmed from centuries-old conclusions which initially found elevated [La] in both tissues and blood when O2 levels were lower than normal. Along the way, La has been accused of roles in muscle soreness and fatigue, some of which are debatable or demonstrably incorrect. In acute care situations, [La] remains a frequently utilized prognostic tool to stratify trauma patients (Parsikia et al. 2014) as well as to identify risk of mortality in the critically ill (Nichol et al. 2010), with many clinicians viewing La as a waste product of hypoxia. This misinterpretation regarding the source and/or cause of hyperlactatemia can have profound implications. These misconceptions stem from long-standing assertions that have pervaded the scientific literature for more than a century. The paradigm of “low O2 evokes high La” led to a simplistic converse deduction that “high La denotes low O2”, a position that was formed on the strength of research by Nobel laureates, Fletcher and Hopkins (1907), Hill et al. (1924), and Meyerhof (1930b, 1942) in the early twentieth century. Because La accumulates during strenuous exercise, the study of La metabolism has historically been closely tied to research into exercise energetics and fatigue. The “anaerobic threshold” concept (Wasserman and McIlroy 1964) reinforced this approach as well as the high La-low O2 paradigm. Today, despite numerous studies demonstrating the role of La as a metabolic fuel, and the discovery of many causative factors for La accumulation other than low O2, the lactate-O2 dogma persists in several research enclaves.

The aim of this paper is to review La through a historical lens, thereby gaining context for a broadening set of modern investigations and understanding. In many cases, the fundamental research that has brought our understanding to this point, and expanded that understanding into numerous disciplines, originated in the experiments of exercise physiologists investigating muscle energetics, most prominently the work of the George Brooks laboratory. This review will include: (1) a reevaluation of the recalcitrant view that La is always a product of inadequate tissue or cellular O2; (2) highlighting recent work which recognizes La as a viable metabolite for the brain; (3) a summary of the elegant linking of substrate utilization and metabolism now known as the astrocyte–neuron lactate shuttle that is built upon the foundation of the original cell-to-cell lactate shuttle composed by Brooks (1985b); (4) an examination of additional roles which elevate La beyond a simple metabolite to include signaling functions as a “Lactormone”; and (5) assessment of a resurgent interest in the role of La in cancer, in tumorigenesis, and in tumor metabolism.

In contrast to the dogma that has plagued La as a dead-end, fatigue-causing waste product, we will provide evidence of La as an energy intermediate that can be formed in tissues undergoing accelerated glycolysis and subsequently distributed throughout the body to be taken up as a combustible substrate by oxidizing tissues, or as a precursor for gluconeogenesis (e.g., in liver) or glycogenesis (e.g., in liver or resting, glycolytic skeletal muscle). Our current understanding is that La is a ubiquitous metabolic intermediate operating simultaneously as both the terminal product of glycolytic metabolism and the intermediary to complete oxidation of carbohydrates by oxidative phosphorylation. A consistent, key finding that we hope to impart from these diverse studies is the centrality of La as a metabolic intermediate within and between cells. A particularly unique contribution of this review is the inclusion of key historical developments and misinterpretations in the study of La metabolism as well as a critical appraisal of current, cutting-edge investigations in this area.

Early history of lactate

In 1780, a German-speaking Swedish apothecary and chemist, Carl Wilhelm Scheele (Fig. 2) discovered HLa/La in sour milk (Benninga 1990). The new acid was named ‘‘Mjölksyra,’’ meaning ‘‘acid of milk’’ (Benninga 1990). Scheele also discovered chlorine, manganese, arsenic acid, barium, molybdenum, tungsten, and fluorine along with numerous other compounds (West 2014). However, Scheele will likely be best remembered as the first “modern” discoverer of oxygen (O2), which he first called “vitriol air” (West 2014), and later “fire air” (Scheele and Bergman 1777; Scheele et al. 1780; Severinghaus 2016). He actually discovered O2 as early as 1772, more than a year before Joseph Priestley. Unfortunately, his experiments were not published until 1777, probably because of procrastination by Scheele as well as his friend and advocate, Torbern Bergman, who wrote an introduction to the book (Williams and Moyer 1982). There is also a more intriguing subtext to the story. In his Traité élementaire de chimie (Lavoisier 1789), Lavoisier falsely claimed that O2 was discovered at almost the same time “by Mr. Priestley, Mr. Scheele, and myself” (Severinghaus 2016). This was a lie, not only because Joseph Priestley had communicated his discovery to Lavoisier in 1774 in person, but also because Scheele had sent Lavoisier a letter in the same year describing his 1771 discovery of O2 (Grimaux 1890; Severinghaus 2016). This letter from Scheele to Lavoisier was kept hidden by Lavoisier and then by Lavoisier’s wife’s brother’s descendants for 219 years (Severinghaus 2016)! Amazingly, Scheele made his landmark discoveries over a short lifetime, dying at the age of 43 (West 2014). Severinghaus (2006) speculates that he died as a result of tasting his discoveries, including one which was sold widely as Scheele’s green cake frosting. The green color was due to arsenic, one of Scheele’s discoveries.

Fig. 2

Carl Wilhelm Scheele (1742–1786), discoverer of lactic acid and oxygen. Retrieved from (Lundgren 2014). Encyclopedia Britannica, Access data August 04, 2017

Despite the fact that von Muralt (1950) called the intervening years between the discovery of La in 1780 and the muscle studies of Fletcher and Hopkins in 1907 (Fletcher and Hopkins 1907), “the prelactic acid era,” there were some notable La-related discoveries during this period (Brooks and Gladden 2003). Certainly, the finding most relevant to exercise physiology was the result by Berzelius in 1807 (Berzelius 1848; Needham 1971) that La concentration ([La]) was elevated in “the muscles of hunted stags” (Gladden 2008a). Quoting Berzelius (Berzelius 1848), “As early as 1807, I analyzed the meat of freshly slaughtered animals, and found a free acid in the liquids drawn from it.” Apparently, Berzelius also convinced himself that the [La] in a muscle was proportional to the amount of exercise that the muscle had performed (Needham 1971). Berzelius and others believed that the La found in muscle was the same as that found in sour milk by Scheele in 1780 (Brin 1965). However, in 1848, Engelhardt (1848), and later Wislicenus (1873) reported different properties for muscle versus milk La (Brin 1965). Of course, we now know that animal tissues produce almost exclusively l(+)lactate, whereas microorganisms can produce d(-)lactate or sometimes a combination of d(−) and l(+); this can then lead to racemic mixtures in, for example, fermented milk (Lockwood et al. 1965; Caplice and Fitzgerald 1999).

As detailed by Kompanje et al. (2007), the presence of La in human blood under pathological conditions after death was first noted in 1843 and again in 1851 by Scherer (1843, 1851). Mosler and Körner (1862; Kompanje et al. 2007) note that blood from a living patient with leukemia was reported positive for La by Folwarczny in 1858; 5 years later, similar data were reported for blood from living patients with a number of different medical conditions (Folwarczny 1863; Kompanje et al. 2007). Failing to acknowledge prior research, Gaglio (1866) detected La in arterial blood freshly drawn from dogs and rabbits. In addition, neglecting previous work, Berlinerblau (1887) confirmed the report of Gaglio in mammalian and human venous blood (Kompanje et al. 2007).

The nineteenth century saw progress in understanding the metabolic sources of La in animals. In 1845, Hermann von Helmholtz (1845) reported findings that were consistent with La formation at the expense of glycogen (von Muralt 1950). In 1847, German chemist, von Liebig (1847), founder of the world’s first school of chemistry, noted the inevitable presence of La in muscle tissue from dead organisms (Kompanje et al. 2007). Interestingly, Claude Bernard (Bernard 1855), the discoverer of glycogen in 1859 (Bernard 1877; Needham 1971), found release of La from muscles excised from calf fetuses and placed in water at 15–20 °C and discussed its possible origin (Needham 1971). Shortly thereafter, as described by Fletcher and Hopkins (1907), Kompanje et al. (2007), and Needham (1971), du Bois-Reymond (in several 1859 publications) noted that activity caused muscles to become acidic and actually related this finding to the increased [La] reported by Berzelius. Soon after (1864), Heidenhain (von Muralt 1950) reported that the amount of La increased with the amount of work done. In the next year, as reported by Fletcher and Hopkins (1907), Ranke concluded that resting muscle is alkaline but becomes acid after excision. Based on his experiments in 1877 and 1879, Nasse ultimately concluded that La is derived from glycogen (Nasse 1877, 1879; Needham 1971).

What appears above as a relatively linear, logical progression in the study of La in skeletal muscle is created by selective hindsight viewed through the lens of our current understanding. Quoting from the classic study of Fletcher and Hopkins (1907), just as Needham (Needham 1971) did: “there is hardly any important fact concerning the lactic acid formation in muscle which, advanced by one observer, has not been contradicted by some other.” As support for this assessment, Fletcher and Hopkins (1907) cite numerous studies reporting that La was not formed in response to either muscle contraction or rigor, and did not accompany muscle fatigue. The paper by Fletcher and Hopkins (1907) is a landmark classic that will be discussed in the next section on the relationship between La and hypoxia. Fletcher was mentor to A. V. Hill and in 1929, Hopkins was awarded the Nobel Prize for “his discovery of growth-stimulating vitamins” (Levinovitz and Ringertz 2001).

The “high La denotes low O2” paradigm

Research on disparate cell types established the fundamental concept that fermentation was markedly enhanced in the absence of O2. In 1861, Louis Pasteur observed that the growth of yeast per gram of sugar consumed was much greater under aerobic than anaerobic conditions (Pasteur 1861; Racker 1974; Barnett 2003). Subsequently, most investigators focused on the measurement of the products of fermentation (alcohol for yeast and La for skeletal muscle) under O2 versus no-O2 conditions (Racker 1974). In yeast, the decrease in sugar consumption upon the introduction of O2 was accompanied by a decrease in fermentation and, therefore, alcohol production. In skeletal muscle, this same phenomenon was later recognized as a decrease in glycogen breakdown and a decrease in La formation under aerobic as compared to anaerobic conditions (Meyerhof 1930b; Barnett 2003). Although Pasteur’s initial discovery occurred in 1861, it was not until 1926 that Warburg gave this phenomenon its name, the “Pasteur Effect” (Warburg 1926; Krebs 1972). The intermixing of metabolic research in different cell types in the 1920s is illustrated by the fact that Meyerhof and Warburg, to mention two giants in the field, both examined this Pasteur Effect in yeast, muscle, and other tissues (Barnett and Entian 2005). As quoted by Barnett (2003), von Euler and colleagues wrote in 1925, “…for some time we have been busy with developing the analogy between fermentative catabolism in yeast and anaerobic catabolism of carbohydrates in muscle” (von Euler et al. 1925).

The early twentieth century view of hypoxia as the necessary cause of La accumulation was promoted and reinforced by several notable contributions. Much of the uncertainty surrounding La formation in muscle at the end of the nineteenth century was due to methodological problems mainly associated with muscle glycogenolysis occurring during the muscle sampling and preparation process, prior to experimental study. In the aforementioned landmark study, Fletcher and Hopkins (1907) developed a method which prevented significant La formation in resting muscles before the extraction and analysis of the La. Subsequently, they were able to show that: (1) freshly excised resting muscle contains a low [La]; (2) [La] increases in excised, resting, anaerobic muscles; (3) La accumulates and [La] increases to high levels during stimulation of muscles to fatigue; and (4) most importantly in the present context, when fatigued muscles are placed in O2-rich environments, La disappears (Brooks and Gladden 2003). As noted above, Nobel Prize winner Otto Meyerhof also observed La accumulation in the absence of O2 and its removal upon the return of O2 (Meyerhof 1930a; Krebs 1972). Therefore, it was likely that in the context of the Pasteur Effect in skeletal muscle, Hill et al. (1924) postulated that La increased during muscular exercise because of a lack of O2 to remove the requisite La produced by the contracting muscles. This view of hypoxia as a cause of La accumulation was likely reinforced by the earlier studies of Araki and also Zillessen [cited by (Kompanje et al. 2007)] who had shown that interruption of the O2 supply to the muscles of mammals and birds promoted an increase in [La].

To be fair, we should note that researchers at that time thought that La formation was of a necessity an anaerobic process. Specifically, it was believed that O2 was required to combust some of the La that was produced during muscle activity back to some form of carbohydrate. If O2 was not available for this combustion, then [La] would rise. The state-of-the-art view of La metabolism in humans in the late 1920s is exemplified by Jervell’s experiments (Jervell 1928). He (Jervell 1928) reported numerous experiments in which he investigated the concentration of “lactic acid” in blood and urine under both physiologic and pathologic conditions. Two quotes serve to illustrate the prevailing idea that a lack of O2 was the reason for elevated [La]:

“During my clinical work, I was naturally induced to supplement the experimental investigations by examination of the lactic acid’s behavior in various pathological conditions. It was then deemed necessary to limit these examinations to those conditions, where owing to impeded intake of oxygen, we might expect to find hyperlactacidaemia.” And “If the oxygen supply…is for one or other reason too small, we may expect to find an increase in the quantity of lactic acid in the muscles.”

From the idea that La production and accumulation was due to inadequate O2 supply, it was only a simple, intuitive deduction to reach the converse conclusion that increased La production and concentration were the results of, and indicators of, hypoxia/dysoxia.

“Anaerobic” threshold

Some 40 years later, the idea that inadequate O2 causes La accumulation was the centerpiece of the “anaerobic threshold” concept as proposed by Wasserman and McIlroy (1964; Wasserman et al. 1973). Although overshadowed by Wasserman’s efforts, similar ideas were advanced independently by Hollman, Kinderman, Keul, and others (Kindermann et al. 1979; Stegmann et al. 1981; Hollmann 1985). In a letter of February 21, 2000 to G. A. Brooks, Wasserman described his motivations for investigating the “anaerobic threshold,” and specifically, non-invasive assessment techniques for pulmonary medicine (Brooks and Gladden 2003). In 1959, Wasserman was a postdoctoral fellow under Julius H. Comroe in the University of California, San Francisco (UCSF) Cardiology Research Institute. Recognizing the “epidemic” in cardiovascular disease, in November of 1960 Comroe challenged Wasserman to develop procedures for early detection of heart disease. Wasserman’s response was that evaluation “would be best done during exercise when the heart was being stressed…. The first sign of heart failure would be reflected in the failure of the circulation to deliver adequate O2 to the metabolizing tissues (exercising muscles). Since the muscle O2 requirement would be markedly increased by exercise, the failure of the heart to transport O2 adequately would result in lactic acidosis (Pasteur Effect).” (Wasserman letter of 2/21/2000 to Brooks). Aware of the earlier reports of Harrison and Pilcher (1930a, b) who showed increased CO2 production and reduced O2 uptake in heart-failure patients, Wasserman thought “it possible to investigate how to detect the \(\dot {V}\)O2 at which lactic acidosis developed during exercise, using non-invasive gas exchange techniques.” His experience at UCSF led to an appointment at Stanford, where Wasserman co-authored a paper with Malcolm B. McIlroy (Wasserman and McIlroy 1964) in which “anaerobic threshold” was determined as the \(\dot {V}\)O2 at which the respiratory exchange ratio (R) increased abruptly during a progressive incremental exercise test. It is informative to note that Wasserman discussed his research with D.B. Dill and credits Dill with inspiring the term “anaerobic threshold.” Wasserman showed Dill his data and the method of gas exchange he was using to “detect the work rate at which O2 transport was inadequate to prevent an exercise lactic acidosis.” Wasserman further states, “As close[ly] as I can remember, his [Dill’s] comment was that I was detecting the threshold of anaerobic metabolism during exercise by measuring exercise gas exchange. Thus, he put into words succinctly what I was trying to measure” (Wasserman letter of 2/21/2000 to Brooks), (Brooks and Gladden 2003). A fascinating aspect of Wasserman’s personal account of the “anaerobic threshold” concept is its connection to the 1920s concept of the Pasteur Effect and to the person of D. B. Dill who directed the Harvard Fatigue Laboratory from 1927 to 1947. In 1973, Wasserman et al. (1973) refined the concept in their classic paper, defining “anaerobic threshold” as the “level of work or O2 consumption just below that at which metabolic acidosis and the associated changes in gas exchange occur.” This non-invasive measure was in turn asserted to correspond to the work rate or \(\dot {V}\)O2 above which lactate systematically increased in response to an increase in work rate. This 1973 paper (Wasserman et al. 1973) generated great interest which continues to the present day with over 2,200 citations according to Google Scholar as of August 2, 2017.

For the subsequent span of over three decades, Wasserman and colleagues vigorously pursued the development of non-invasive technologies to identify the presence of lactic acidosis in graded clinical exercise protocols. Numerous gas exchange measures have been used over the years, and a full discussion is beyond the scope of the current review. In brief, the so-called V-slope method (Beaver et al. 1986) has become the preferred method for determining what is currently most appropriately referred to as the gas exchange threshold (GET). For the V-slope method of threshold detection, carbon dioxide output (\(\dot {V}\)CO2) is plotted against \(\dot {V}\)O2 and a computerized regression analysis detects the breakpoint in the relationship (Fig. 3). The coincidence of the GET with the lactate threshold (see below) as determined directly from the pattern of blood [La] has been heavily debated (Caiozzo et al. 1982; Davis et al. 1983; Green et al. 1983; Simon et al. 1983; Yeh et al. 1983; Gladden et al. 1985; Plato et al. 2008) and is also beyond the scope of the present review.

Fig. 3

V-slope method for determining the gas exchange threshold, redrawn with permission from (Beaver et al. 1986). Carbon dioxide output (\(\dot {V}\)CO2) is plotted against simultaneously determined oxygen uptake (\(\dot {V}\)O2) in a progressive incremental exercise test. The gas exchange threshold is detected by a mathematical algorithm that determines the intersection of the two straight lines that provide the best fit to the overall data set

While the Wasserman lab emphasized the non-invasive measurement of the “anaerobic threshold”, many other researchers focused on a direct assessment of the blood La response to exercise of varying intensities. As presaged by Owles (1930), during progressive, incremental exercise, blood [La] rises gradually at first and then more rapidly as the exercise becomes more intense; this idealized response is shown in Fig. 4. A primary issue in the study of data of this type has been the identification and interpretation of a single value that best represents this curvilinear blood La profile. As examples, Fig. 4 illustrates three of these methods; the lactate threshold (LT), the onset of blood La accumulation (OBLA), and Dmax (Wasserman et al. 1973, 1986; Gladden et al. 1985; Heck et al. 1985; Cheng et al. 1992; Bishop et al. 1998; Jones and Doust 1998; Nicholson and Sleivert 2001; Gladden 2004a; Faude et al. 2009). While these methods often do not provide the same quantitative value, they generally correlate well with each other, and each is highly correlated with endurance performance (Bishop et al. 1998; Jones and Doust 1998; Nicholson and Sleivert 2001). Depending on the particular protocol, the pattern of increase in blood [La] can differ from the idealized response shown in Fig. 4. As one example, some researchers report a second “breakpoint” in the response (e.g., Skinner and McLellan 1980). Nevertheless, we contend that the various indicators are correlated with each other.

Fig. 4

Idealized blood [La] response to progressive incremental exercise plotted against oxygen uptake (\(\dot {V}\)O2). Also illustrated are three single point measures often used to describe the response: the visually determined lactate threshold (LT) (Gladden et al. 1985), LT as determined by the Dmax method (LTD) (Cheng et al. 1992), and the onset of blood La accumulation (OBLA = 4 mM) (Heck et al. 1985).

Reprinted with permission from Gladden (2004a) Lactate metabolism during exercise. In Principles of Exercise Biochemistry, 3rd edn, ed. Poortmans JR, pp. 152–196. Karger, Basel

Biopsies from exercising muscles have shown that muscle [La] shows similar patterns to those of blood [La] although the exercising muscle [La] is generally higher than that in blood (Green et al. 1983; Gollnick et al. 1986). The blood [La] response to progressive exercise has in turn been related to the blood [La] levels that are measured in more prolonged, constant work rate exercise (Wasserman et al. 1967; Pringle and Jones 2002), and are, therefore, more closely related to endurance performance ability. Figure 5 provides a schematized view of this response. Exercise intensities which are below the LT typically result in a transient elevation of blood [La] which then declines to a lower level, sometimes returning to near the resting [La]. During exercise that elicits metabolic rates between LT (\(\dot {V}\)O2LT) and 50% of the difference between \(\dot {V}\)O2LT and \(\dot {V}\)O2peak {50%Δ = \(\dot {V}\)O2LT + 0.5 (\(\dot {V}\)O2peak\(\dot {V}\)O2LT)}, many subjects reach their maximal lactate steady state (MLSS) (Pringle and Jones 2002). MLSS is defined as the highest intensity of exercise that can be performed while maintaining a constant, but elevated blood [La] (Beneke and von Duvillard 1996; Jones and Doust 1998). Operationally, exercise intensities that are greater than the MLSS are identified as metabolic rates that result in an increase of more than 1.0 mM in blood [La] during the last 20 min of a 30-min constant work rate trial (Beneke and von Duvillard 1996; Jones and Doust 1998; Pringle and Jones 2002; Gladden 2004a). At work rates exceeding the MLSS, both blood [La] and \(\dot {V}\)O2 drift upward until exhaustion occurs. Although the drifts in [La] and \(\dot {V}\)O2 share a similar time course, there is apparently no cause-and-effect relationship between the two (Poole et al. 1994; Gaesser and Poole 1996; Billat et al. 1998). Despite the idealized representation in Fig. 5, there is a surprising range of blood [La]s at the MLSS; e.g., 1.5–6.3 mM (Pedersen et al. 2001). Several indices of physiological thresholds of exercise intensity occur at the same metabolic rate (i.e., \(\dot {V}\)O2) (Keir et al. 2015) or at least are highly correlated (Pringle and Jones 2002); these include critical power, muscle deoxyhemoglobin breakpoint, and the MLSS.

Fig. 5

Blood [La] response to constant work rate exercise at different intensities. Idealized data based on the reports of Wasserman et al. (1967, 1986) and Pringle and Jones (Pringle and Jones 2002) are plotted. Blood [La] responses for work rates below (< MLSS), at (= MLSS) and greater than (> MLSS) the maximal lactate steady state intensity are shown. Although the usual blood [La] at the MLSS is approximately 4 mM, this concentration can vary widely among individuals (Pedersen et al. 2001).

Reprinted with permission from Gladden (2004a) Lactate metabolism during exercise. In Principles of Exercise Biochemistry, 3rd edn, ed. Poortmans JR, pp. 152–196. Karger, Basel

Essentially, Wasserman’s anaerobic threshold hypothesis implies that the accumulation of La during muscular exercise is due to “dysoxia.” Dysoxia as defined by Connett et al. (1990) is a sufficiently low level of O2, such that cytochrome turnover is limited, and therefore, there is O2-limited oxidative phosphorylation. As will be detailed in the following sections, the preponderance of evidence argues against this paradigm, and therefore, whether determined either invasively via blood [La] or non-invasively via gas exchange, threshold measures should not be termed “anaerobic.”

Prime evidence for causative factors other than low O2

Today, it is well established that any increase in [La] typically represents something other than an O2 limitation; hypoxia-driven La accumulation is very much the exception rather than the rule. As reviewed by Barnard and Holloszy (2003), results of experiments conducted in 1885 by Rubner and Frey should have raised questions about the relationship between La and O2. These investigators perfused mammalian muscles with oxygenated blood and observed La release despite the presence of apparently sufficient O2. Zuntz (1911; Barnard and Holloszy 2003) actually discussed these results in 1911, but remained convinced that hypoxic conditions were a prerequisite for La accumulation. Intriguingly, Zuntz proposed that some parts of the muscles might have been hypoxic because of arterial blood clots or narrowing of blood vessels (Zuntz 1911; Barnard and Holloszy 2003); perhaps, an early suggestion of “occult hypoperfusion” (see below). In a different arena of research in the 1920s, the Cori’s (Cori and Cori 1925) and Warburg (Warburg et al. 1927) carried out whole animal experiments, demonstrating that limbs bearing tumors had high venous [La] despite presumed normoxic conditions. Glucose-avid, La-producing tumors in normoxic conditions were eventually labeled as demonstrating a “Warburg effect.” Recent interest in tumor metabolism has proven this to be much less straightforward than originally described, as it is now proposed that there may be thousands of cancer genotypes (Lundberg 2011) yielding a much smaller but still large number of cancer phenotypes, and even among the same tumor type, La uptake or output can vary markedly with arterial [La] (Sauer and Dauchy 1985). However, the Cori’s and Warburg (Cori and Cori 1925; Warburg et al. 1927) provided early experimental animal evidence that La production and/or accumulation need not be linked obligatorily with hypoxia. The Warburg effect was thought to be characteristic of some tumors, but not reflective of any normal physiology (after all, why would there be increased [La] in normoxia?). As a result of this thinking and perhaps the isolation of research into silos, the Cori’s and Warburg’s intriguing results were never transposed to the field of exercise metabolism as a challenge to the prevailing dogma of the next approximately 60 years.

It was not until the 1960s that evidence against the notion of low O2 as a prerequisite for La production and accumulation began to gain traction. During the same era, when Wasserman and colleagues were detailing the “anaerobic threshold,” other investigations were underway that argued against an O2 limitation as the causative factor for La accumulation. Utilizing a canine gastrocnemius-superficial digital flexor complex (GS) in situ, Stainsby and Welch (Stainsby and Welch 1966) aimed to investigate La production in response to various steady contraction rates. Surprisingly, they found that net La output by the contracting GS was always transient (Fig. 6). During contractions over periods of 40–60 min, net La output peaked and declined within 15–20 min, even becoming net La uptake as the contractions continued at a constant stimulation rate. If hypoxia were the cause of La production in contracting muscle, then why would net La output decline to near zero or even revert to net La uptake with continued contractions at an unchanged metabolic rate and unchanged O2 delivery (Brooks and Gladden 2003)?

Fig. 6

Net La output and uptake across an isolated, blood-perfused, contracting skeletal muscle (canine gastrocnemius-superficial digital flexor complex; N = 5) at rest and during contractions at 5 twitches per sec over a period of 1 hour, followed by 30 min of recovery. Net La output is positive on the y-axis and net La uptake is negative. Note that net La output during contractions peaks at approximately 10 min and then declines and often becomes net uptake as the contractions continue. See text for additional details.

Redrawn with permission from Welch and Stainsby (1967)

To answer this question, Stainsby forged a collaboration with Frans Jöbsis who, with Britton Chance, had invented the surface fluorescence method for NAD+/NADH detection (Brooks and Gladden 2003). Using this NAD+/NADH fluorescence technique in the isolated canine GS, Jöbsis and Stainsby (1968) found that the redox pair was highly reduced at rest but became highly oxidized quickly after the onset of contractions, suggesting an adequate O2 supply for oxidative phosphorylation. If O2 is inadequate, oxidative phosphorylation will be restrained and the electron transport chain will “back up” thus causing a reduction in the NAD+/NADH redox couple. Therefore, the net La output at contraction onset that Stainsby and Welch had previously observed, could not be explained by hypoxic/dysoxic stimulation of anaerobic glycolysis (Jöbsis and Stainsby 1968). Certainly, these experiments are subject to criticism on several grounds (Gladden 1996) including the fact that the surface fluorometry technique is unable to distinguish between NADH and NADPH (Akerboom et al. 1979; Unkefer et al. 1983; Katz and Sahlin 1988) or to distinguish between redox changes within the mitochondria versus the cytosol (Kushmerick 1983; Paddle 1985; Katz and Sahlin 1988), the former being much more reduced (Williamson et al. 1967; Jones and Sies 2015). Nevertheless, the totality of the Stainsby studies promoted a re-consideration of the relationship between La production and hypoxia.

The next major blows against dysoxia as the cause of La production by contracting/exercising skeletal muscle involved measures of intracellular partial pressure of O2 (PiO2). Granted that a sufficiently low O2 level resulting in dysoxia will limit mitochondrial oxidative phosphorylation, a prime question results: how much O2 is enough to prevent inhibition and allow normal mitochondrial function? Studies in isolated mitochondria and whole cells contend that PiO2 in the range of 0.5 to 2.0 Torr is sufficient for maximal mitochondrial oxidative phosphorylation (Chance and Williams 1956; Wilson et al. 1988; Connett et al. 1990; Gnaiger et al. 1995; Gnaiger and Kuznetsov 2002). Direct exploration into potential O2-limited muscle La production was initially provided by measuring myoglobin saturation (and thereby PiO2) via cryomicrospectroscopy combined with measures of [La] from approximately the same cell populations in isolated, perfused dog gracilis muscle (Connett et al. 1984). At rest and during submaximal twitch contractions, approximating 10 and 70% of peak twitch \(\dot {V}\)O2 in this muscle, myoglobin saturation did not decrease in the first seconds of stimulation, remained greater than 5 mmHg at all sampling locations during transition from rest to contraction, and remained greater than 2 mmHg in the steady state (Connett et al. 1984). Over the same time course, muscle [La] rose from 1.2 mmol kg− 1 at rest to 2.0 mmol kg− 1 at the 10% \(\dot {V}\)O2peak contraction rate and to 5.7 mmol kg− 1 at the 70% \(\dot {V}\)O2peak contraction rate. While technical limitations of this cryomicrospectroscopy method were more fully revealed in later work (Voter and Gayeski 1995), the conclusions still stand. From their results, Connett et al. (1983, 1984, 1986) concluded that fully aerobic La accumulation occurs in red muscle and that the accumulation results from causes other than O2-limitation of mitochondrial ATP production.

More recently, proton magnetic resonance spectroscopy (1H-MRS) was used to determine myoglobin saturation during single-leg, maximal effort, quadriceps contractions in humans, concluding similarly that increased La efflux from the exercising muscle did not result from inadequate muscle PiO2 (Richardson et al. 1998). Even while breathing hypoxic gas (12% O2), local O2 tension was never low enough to unequivocally limit oxidative phosphorylation (Richardson et al. 1998). Furthermore, there was no correlation between net blood La efflux from the exercising quadriceps and PiO2 across a range of metabolic rates from 50 to 100% of \(\dot {V}\)O2max. The PiO2 data from this study are discussed in more detail below.

This evidence strongly suggests that frank dysoxia is not one of the causes of a rise in muscle and blood La levels at submaximal exercise intensities. The major, legitimate underlying mechanisms for the increase in [La] with increasing exercise intensity have been discussed in detail elsewhere (Gladden 1996, 2004a, b) and include accelerating glycolysis, failure of La removal to keep pace with La production [e.g., (Brooks 1985a)], and recruitment of fast twitch muscle fibers (Ivy et al. 1980; Armstrong 1988). Accelerated glycolysis will always result in an increase in La production because of the near-equilibrium nature of the lactate dehydrogenase (LDH) reaction, and because LDH has a much higher activity than the key regulatory enzymes of the glycolytic and oxidative pathways; thus, La is always the end-product of glycolysis (Kane 2014; Rogatzki et al. 2015; Schurr 2017).

Is there any role for hypoxia in the rising [La] with increasing exercise intensity?

Despite the fact that La accumulation has been observed consistently in the absence of dysoxia, an important question remains: does O2 play any role whatsoever in increasing [La] with increasing metabolic intensity? The short answer is that La production is not associated with a clearly defined dysoxic condition in skeletal muscle, but in an apparent inconsistency, La accumulation during exercise is significantly affected by perturbations in O2 delivery during heavy exercise. A fuller answer to the question follows.

Even though exercising skeletal muscle PiO2 does not decrease to the level of absolute inhibition of mitochondrial oxidative phosphorylation function, it is nevertheless true that skeletal muscle PiO2 declines with increasing exercise intensity. PiO2 is a difficult measurement to make during exercise. The most convincing data rely on derived values from myoglobin desaturation as determined via proton nuclear magnetic resonance spectroscopy (1H NMRS) along with accurate values of myoglobin P50. Using best evidence from this technique, how does PiO2 change as a function of exercise intensity? In studies of plantar flexion exercise in Jue’s laboratory (Molé et al. 1999; Chung et al. 2005), PiO2 was reported to decline progressively and linearly with increasing work rate, down to ≈ 3.1 Torr. However, in the majority of studies, most directed by Richardson and colleagues employing single-leg knee-extensor exercise, which limits activity to the quadriceps femoris muscle group, the nadir is reached at approximately 50–60% of \(\dot {V}\)O2max and remains there with further increases in exercise intensity (Richardson et al. 1998, 1999, 2001, 2002). Similar data have been reported by Vanderthommen et al. (2003). Figure 7 (Clanton et al. 2013) combines data from Molé et al. (1999) with those of Richardson et al. (2001) including the most reliable data available for resting PiO2 in which Richardson, in collaboration with Carlier (Richardson et al. 2006), employed a 4.0 T magnet to measure myoglobin desaturation. Notably, considering the different muscle groups studied, and the different protocols employed, the results are much more congruent than expected across laboratories and techniques. Overall, these data demonstrate that the largest reductions in PiO2 occur relatively early in incrementally increasing exercise, but reach a relative plateau in moderate-to-heavy exercise. Since we know that significant muscle La production occurs at exercise levels above a metabolic threshold of approximately 50–60% of \(\dot {V}\)O2max, it appears that La production is not associated with a clearly defined dysoxic condition in skeletal muscle, at least during single muscle group exercise.

Fig. 7

Intracellular PO2 (PiO2) versus metabolic rate using combined data of Molé et al. [(1999); solid squares] and Richardson et al. [(2001); solid circles]. Data from Richardson et al. (2006) working in Carlier’s lab were used as the resting value for both sets of data, so the square is overlying a circle. In addition, note that the reported PiO2 value at 100% of \(\dot {V}\)O2max was the same for both data sets, so again, the square is overlying the circle.

Reprinted with permission from Clanton et al. (2013)

Yet, paradoxically, La accumulation during heavy whole-body exercise is significantly affected by perturbations in O2 delivery. Wasserman reviewed this evidence (Wasserman 1984; Wasserman and Koike 1992), much of which dates well back before the turn of the century. When subjects inspire gas with a lower PO2, blood La levels are elevated during exercise [e.g., (Lundin and Ström 1947)]. For the same heavy work rate, blood [La] is higher in isovolemic anemia as compared to the normal, control state [e.g., (Woodson et al. 1978)]. Adding carbon monoxide (CO) to the inspired gas sufficient to bind 15–20% of the O2 binding sites on hemoglobin also increases blood [La] during exercise (Vogel and Gleser 1972). A reduction in circulating blood volume in normal subjects results in an increase in exercise [La] [e.g., (Fortney et al. 1981)]. Patients with a low cardiac output due to disease (Huckabee and Judson 1958), as well as normal subjects subjected to beta-blockade via propranolol (Twentyman et al. 1981) also display an exaggerated blood [La] response to exercise. Administration of an inotropic drug to cardiac patients with low exercise tolerance reduces the blood [La] increase during exercise (Siskind et al. 1981). Finally, it has been well demonstrated that breathing hyperoxic gases will cause a reduction in blood [La] during exercise [e.g., (Hogan et al. 1983)].

Therefore, even in the absence of apparent dysoxia, glycolytic metabolism and La production are at least somewhat O2 dependent. How could this be? Certainly, one possibility is that blood catecholamine concentrations are higher during hypoxic conditions (Mazzeo et al. 1991; Richardson et al. 1998; Mazzeo and Reeves 2003). However, an additional hypothesis relies on cellular changes in the [ADP]·[Pi]/[ATP] ratio that occur in high metabolic states as a mechanism for acute responses to hypoxia. This idea is illustrated in the hypothetical example shown in Fig. 8 (Clanton et al. 2013). Suppose an individual is exercising at approximately 55% of \(\dot {V}\)O2max (solid circle) and then transitions to a higher work rate, just above 70% \(\dot {V}\)O2max. Abundant evidence demonstrates that at the higher work rate, cytosolic [ADP] and [Pi] will be elevated, while [ATP] will perhaps be slightly decreased, leading to an increase in [ADP]·[Pi]/[ATP]. As such, the \(\dot {V}\)O2–PiO2 curve will be shifted upward, as indicated by arrow 1 and extensively reported by Wilson and colleagues (Wilson et al. 1979, 1988; Wilson 1994). However, based on the results of Molé et al. (1999) and Richardson et al. (2001), there will also be a decrease in PiO2 (arrow 2). This small reduction in PiO2 would then result in movement down the \(\dot {V}\)O2–PiO2 curve, thus reducing \(\dot {V}\)O2 (open circle). This reduction in \(\dot {V}\)O2 below the required level would result in additional accumulation of ADP and Pi, elevating [ADP]·[Pi]/[ATP] further, shifting the mitochondria to yet a higher \(\dot {V}\)O2–PiO2 curve (arrow 3). Ultimately, shifts to higher [ADP]·[Pi]/[ATP] ratios as energy consumption increases could lead to an equilibrium state, where PiO2 remains relatively constant, but \(\dot {V}\)O2 can continue to increase. This is consistent with observations of the relatively constant PiO2 in moderate-to-severe exercise, as shown in Fig. 7.

Fig. 8

Hypothetical pattern of metabolic dependence (La production) on intracellular PO2 (PiO2) during the transition from one exercise work rate to another. With increase in work rate (arrow 1), [ADP]·[Pi]/[ATP] increases. However, intracellular PO2 will likely also decrease with increased work rate (arrow 2). As a result, O2 uptake would be transiently insufficient to supply ATP at the required rate, leading to a further increase in [ADP]·[Pi]/[ATP] (arrow 3, from open circle to solid square) for adequate stimulation of oxidative phosphorylation. The connection to La metabolism is that the increases in [ADP]·[Pi]/[ATP] simultaneously accelerate glycolysis and, therefore, La production (see text for additional details).

Reprinted with permission from Clanton et al. (2013)

What connects the preceding discussion to increased glycolysis and La production in non-dysoxic muscle? The link is that any increase in [ADP]·[Pi]/[ATP] required to elevate \(\dot {V}\)O2 is a very powerful stimulus for glycolytic activity, independent of any changes in PiO2. Furthermore, as one moves to higher [ADP]·[Pi]/[ATP] levels, the O2 dependence of the \(\dot {V}\)O2–PiO2 curve becomes greater, as reviewed by Gnaiger et al. (2001), and Scandurra and Gnaiger (2010). With changes in available PiO2, the system can sustain a constant \(\dot {V}\)O2, but there will be resultant elevations in [ADP]·[Pi]/[ATP] which, in turn, stimulate glycolysis. The system is O2 sensitive, because as available O2 decreases or increases, it can increase or decrease the necessary elevations in [ADP]·[Pi]/[ATP] and thus also increase or decrease the glycolytic rate. There is experimental evidence to support this hypothesis as a mechanism for O2 dependence of La production [e.g., (Hogan et al. 1992a, b; Haseler et al. 1998; Richardson et al. 1998)]. These data support the hypothesis that it is not a limited oxidative phosphorylation engendered by a low dysoxic PiO2 that drives La production, but rather the elevations in [ADP]·[Pi]/[ATP] required to sustain metabolic rate and to drive mitochondrial respiration at the extant low PiO2.

One might ask if this requisite increase in La production and blood [La] represents an additional energy expenditure and, therefore, a decrease in efficiency. Quantification of energy expenditure due to La accumulation is fraught with difficulty (Gladden 2004a). The [La] varies among muscles due to differing degrees of recruitment for a given activity and blood [La] varies depending on the tissue being drained. Even if an average [La] could be determined, the dilution space is undefined and non-uniform. Nevertheless, using a series of assumptions, calculations based on the results of Bransford and Howley (1977) to account for energy provided by anaerobic glycolysis (i.e., net La accumulation) lead to an estimated decrease in efficiency of about 2% at approximately 90% of \(\dot {V}\)O2max. Note, however, that this calculation does not mean that the use of ATP synthesized via anaerobic pathways is inherently less efficient than the use of aerobically synthesized ATP (Gladden and Welch 1978). Careful measures of delta efficiency (Gaesser and Brooks 1975) at submaximal work rates (almost entirely aerobic) versus very heavy work rates (significant anaerobic contribution) suggest that delta efficiency decreases with increasing work rate, regardless of the contribution of anaerobic energy pathways (Gladden and Welch 1978).

It is very important to note here that if an individual is in a steady state in which the [La] is unchanging, there is no additional energy being provided above that determined via O2 consumption (Brooks 2012). Even though La is formed continuously from glycolysis, it is largely combusted as a fuel, thereby being accounted for by the measurement of O2 consumption (Brooks 2012).

Lactate and fatigue

Exercise and skeletal muscle fatigue are complex processes with numerous potential causes ranging from central nervous system function to the activity of myosin at the individual cross-bridge level (Gladden 2016). However, during intense muscle contractions or exercise, [La] increases dramatically and contributes significantly to a decrease in pH within the active muscles and in the case of whole-body exercise, the blood. During intense dynamic exercise, intracellular water [La] can reach 30 mM and intracellular pH can decline to the range of 6.2–6.5 (Sahlin et al. 1976; Debold et al. 2016). For a discussion of La’s role in acidosis, see a following section in this review. A complete discussion of the potential role of La and pH in fatigue would require a full review of its own, so we offer only an abbreviated discussion here.

Classic support for lactic acidosis as a cause of fatigue in human exercise was provided by imperfect studies that employed prior exercise to elevate [La] and decrease pH [e.g., (Klausen et al. 1972; Karlsson et al. 1975; Bangsbo and Juel 2006)]. As a detailed example, Yates, Gladden and Cresanta (Yates et al. 1983) had participants perform a 1-min maximal effort cycle ergometer task prior to isometrically maintaining 40% of maximum voluntary contraction (MVC) force to exhaustion with the elbow flexors. The prior exercise elevated blood [La] to 11 mM and decreased arterialized blood pH to 7.20. As a result, isometric endurance was reduced by 25%, although there was no effect of the prior exercise on MVC, peak rate of force increase, peak rate of force decrease, one-half contraction time, or one-half relaxation time.

Certainly, the lactate anion (La) could be a fatigue agent. For example, Hogan et al. (1995) reported that infusion of isolated canine gastrocnemius muscles with blood [La] at 12–15 mM caused a 15% decrease in twitch tension, even though muscle pH was not altered from control conditions. Supportive findings have been published for isolated muscles in vitro (Spangenburg et al. 1998), skinned muscle fibers (Andrews et al. 1996), and sarcoplasmic reticulum vesicles [e.g., (Favero et al. 1995; Spangenburg et al. 1998)]. In addition, Samaja et al. (1999) found that La apparently depressed developed pressure irreversibly in Langendorff perfused rat hearts; overall, the effects of elevated [La] were more deleterious than the effects of high [H+]. In contrast, other investigators have reported effects of 5% or less on muscle contractility in skinned mammalian muscle fibers [e.g., (Posterino et al. 2001)]. In fact, Allen et al. (2008) have summarized evidence against La and dismissed its potential role as a fatigue agent, largely on the basis of studies with skinned muscle fibers. Our view is that while the impact of high [La] per se in the fatigue phenomenon has been heavily challenged by investigations in vitro, it remains feasible that the La anion has a small but potentially significant deleterious effect in intact systems such as perfused skeletal muscle and heart and intact humans. We also note that while a 5% fatigue effect does not argue for a central role in the fatigue process, it is also not negligible.

What about acidosis and fatigue? In 2006 (Bangsbo and Juel 2006; Lamb and Stephenson 2006) and again in 2016 (Fitts 2016; Westerblad 2016), the role of decreased pH in fatigue was directly debated. Historically, lactic acid was viewed as one of the major causes of muscle and exercise fatigue (Fitts 1994). As early as 1929, Hill and Kupalov (Hill and Kupalov 1929) proposed lactic acid accumulation as the cause of fatigue during twitch contractions of frog sartorii at temperatures in the range of 14–20 °C. More recently, it has been noted that the negative effects of low pH on peak isometric force in studies of isolated muscle fibers are much smaller at higher temperatures such as 30 °C [see (Fitts 2016)]. However, research from the Fitts laboratory (Knuth et al. 2006; Nelson et al. 2014; Fitts 2016) has found that low pH (down to 6.2) at 30 °C depressed velocity and power of skinned muscle fibers by 30–35%! These deleterious effects were even greater in the presence of inorganic phosphate concentration ([Pi]) elevated to the level seen during intense exercise. The fatiguing effect of combined low pH and high [Pi] may be further increased in the presence of suboptimal [Ca2+] such as occurs during fatigue (Fitts 2016). Debold et al. (2016) have recently reviewed the fatiguing effects of elevated [H+], elevated [Pi], and decreased Ca2+ sensitivity determined from both isolated muscle fiber studies and investigations at the level of the contractile protein, myosin, and the muscle regulatory proteins, troponin, and tropomyosin.

Despite the evidence outlined in the previous paragraph and the prior dogma that acidosis is a major cause of fatigue, there is a plethora of data opposing this position (Lamb and Stephenson 2006; Westerblad 2016). Westerblad (2016) noted that there are several studies (Sahlin and Ren 1989; Westerblad and Allen 1992; Degroot et al. 1993) which failed to find a temporal correlation between acidosis and a decrease in muscle function and observed that fatigue can occur in the absence of acidosis. Another study from Westerblad’s laboratory (Bruton et al. 1998) reported that mouse muscle fibers did not fatigue more rapidly when they had been pre-acidified by 0.4 pH units. However, the major challenge to the notion of lactic acid as a fatigue agent has come from studies of isolated rat soleus muscles (Nielsen et al. 2001; De Paoli et al. 2007) and mechanically skinned rat extensor digitorum longus (EDL) muscle fibers (Pedersen et al. 2004); [see (Lamb and Stephenson 2006) for additional references]. These studies propose that increased [La] actually counteracts fatigue. These investigations first note that in one type of fatigue K+ builds up in the transverse-tubular (t) system and in the microenvironment of stimulated muscle fibers. This increase in [K+] leads to sarcolemmal depolarization which may slow or even prevent the recovery of Na+ channels from inactivation. This scenario would lead to a reduced amplitude of action potentials or maybe failure, thereby reducing muscle force production (Lamb and Stephenson 2006). In 2001, Nielsen et al. (2001) observed that incubation of isolated rat soleus muscles in 11 mM K+ reduced tetanic force by 75%, but this deficit was completely eliminated upon addition of 20 mM lactic acid. In 2004, Pedersen et al. (2004) performed a sophisticated study of mechanically skinned rat EDL muscle fibers, finding that in the presence of Cl, acidosis decreased Cl permeability thus preserving the propagation of action potentials into the t-tubules despite Na+ channel inactivation. Subsequently, de Paoli et al. (De Paoli et al. 2007) reported that a combination of 20 mM lactic acid and epinephrine offset an 85% reduction in force production by rat soleus muscles in the presence of an external 15 mM [K+]. The overall conclusion of these researchers and others is that lactic acidosis is actually beneficial in delaying the onset of fatigue (Lamb and Stephenson 2006).

What is the bottom line? During exercise intensities up to maximal lactate steady state (approximately 4 mM blood [La]), La likely provides an advantage, since it offers a means of distributing substrate and perhaps coordinating redox state among tissues (see discussion in a later section) with little change in pH (Gladden and Hogan 2006). The ability to produce and accumulate La is also critical to maximal effort performance particularly during periods of approximately 30–90 s (Gladden 2004a; Brooks 2012). In this context, La plus NAD+ formation from pyruvate and NADH via the LDH reaction regenerates the required substrate (NAD+) for the glyceraldehyde dehydrogenase reaction, permitting continued rapid glycolysis with the production of 1.5 ATP per glucosyl unit derived from glycogen. However, what about the fatigue effects of La and its concomitant acidosis? In our view, many studies of isolated muscles and fibers, although not all, disagree not on whether lactic acidosis is a negative factor for muscle function but on the primacy of acidosis as a cause of fatigue during high intensity contractions. In other words, lactic acidosis is likely not the primary cause of fatigue, but it is nevertheless an important factor. For example, even as he argues against the role of acidosis in skeletal muscle fatigue, Westerblad (2016) notes decreases of about 10% in maximum isometric force in skinned fiber studies due to acidosis. As Cairns and Lindinger (Cairns and Lindinger 2008) have noted, high intensity fatigue is likely due to multiple ionic interactions. Perhaps, a rundown of the transsarcolemmal K+ gradient is the major factor (Cairns and Lindinger 2008), but H+ and even La likely have negative effects, particularly in combination with other metabolites such as Pi (Debold et al. 2016; Fitts 2016). In addition, while there are views to the contrary, there is evidence that acidosis inhibits glycolysis (Parolin et al. 1999). At the whole-body level, it is possible that low tissue pH causes pain and that blood acidosis encourages arterial hemoglobin desaturation that can diminish aerobic performance (Gladden and Hogan 2006). Finally, alkalosis via sodium bicarbonate supplementation generally improves high intensity performance by 2–3% (Siegler et al. 2016). In toto, our conclusion is that both La and H+ likely have some negative effect on exercise performance, albeit they are not necessarily the major causes of fatigue.

Cell-to-cell lactate shuttle

With evidence mounting that hypoxia was not the primary cause of La production, and that La could in fact be used as a fuel by numerous tissues including both resting and contracting skeletal muscle, a paradigm shift occurred in the conceptualization of La metabolism during exercise. This paradigm shift was impelled (Brooks 1985b) and expounded by Brooks (2007, 2009, 2016), beginning in 1985 (Brooks 1985b) when he introduced the lactate shuttle, now known as the intercellular or cell-to-cell lactate shuttle. Key support for the cell-to-cell lactate shuttle came from a plethora of isotopic tracer studies by the Brooks laboratory which tracked the flow of carbon intermediates during rest, exercise, and recovery in combination with arteriovenous measures of net La exchange, and muscle biopsies (Bergman et al. 1999, 2000; Brooks 2002). In contrast to the dogma of the 19th and most of the twentieth century, which viewed La as a dead-end, fatigue-causing waste product, the now well-supported tenet of the cell-to-cell lactate shuttle emphasizes La as an energy intermediate that can be formed in tissues undergoing accelerated glycolysis and subsequently distributed throughout the body to be taken up as an energy substrate by oxidizing tissues or as a precursor for gluconeogenesis or glycogenesis. The whole of the evidence gleaned from studies of exercise metabolism is overwhelmingly supportive of this theory, and it is now the framework within which La metabolism is studied. Both the evidence and the concept have been extensively reviewed previously (Gladden 1996, 2004a, b, 2008b; Brooks 2000, 2002, 2007, 2009, 2016; Brooks and Gladden 2003), and will, therefore, be only summarized here. As extolled by Brooks (2007) and emphasized here, this theory is based on La exchanges: (a) between low-oxidative and high-oxidative skeletal muscle fibers allowing La to be oxidized within individual working muscles; (b) among contracting skeletal muscles producing La and other distant skeletal muscles that are at a lower metabolic rate (rest or submaximal exercise); (c) between contracting skeletal muscles and the heart; and (d) between tissues of net La release and gluconeogenesis or glyconeogenesis. Essentially, La is exchanged by tissues throughout the body, importantly including the brain (see below) as illustrated in Fig. 9.

Fig. 9

Cell-to-cell lactate shuttle, and the astrocyte–neuron lactate shuttle. Based on (Pellerin et al. 1998, Brooks 2002). As the rate of demand for ATP increases in exercising skeletal muscle, La accumulates and efflux from muscle fibers increases by means of MCTs (lower left). Within the exercising muscle, La is shuttled among heterogeneous fiber types, from glycolytic to oxidative fibers via MCTs (small blue squares in lower right). Alternatively, La may be carried in circulation to less, or slightly active skeletal muscle, where it is oxidized (CO2 + H2O) in oxidative fibers. In inactive glycolytic skeletal muscle fibers, La is converted chiefly to glycogen, with some oxidized in oxidative fibers. La is also carried in the blood to the liver, where it is either oxidized, or converted to glucose via gluconeogenesis. The newly formed glucose is either stored as glycogen, or released back into circulation (Cori cycle), where it can return to, for example, exercising muscle. Circulating La is also readily oxidized in cardiac fibers and brain. Within the brain, the astrocyte–neuron lactate shuttle (upper right panel) is the process by which astrocytes take up glucose from the microcirculation, converting the glucose to La via glycolysis. This astrocytic La diffuses from the astrocyte to an adjacent neuron by means of MCTs. In the neuron, the La is oxidized at the mitochondria (CO2 + H2O) to resynthesize ATP, and/or used for the cataplerotic production of amino acid neurotransmitters (NTs; e.g., glutamate, aspartate, and GABA)

Approximately 30 years after the work of Stainsby, Welch, and Jöbsis (Stainsby and Welch 1966; Welch and Stainsby 1967; Jöbsis and Stainsby 1968), Pagliassotti and Donovan (1990) and Gladden et al. (Gladden and Yates 1983; Gladden 1991; Gladden et al. 1992, 1994; Hamann et al. 2001; Kelley et al. 2002) provided clear evidence of net La uptake and metabolism by isolated, perfused skeletal muscle under both resting and contracting conditions. Among many studies in humans also showing net La release by some muscles with net La uptake by other muscles, those of Richter et al. (1988) and van Hall et al. (2003) are illustrative. In contracting muscle displaying a net uptake of La, the vast majority of the La is oxidized as a fuel (Mazzeo et al. 1986; Stanley et al. 1986; Bergman et al. 2000; Kelley et al. 2002).

La clamp studies in humans further illustrated the importance of La as both a fuel and a gluconeogenic substrate. Using a combination of [3-13C]lactate, H13CO3 and [6,6-2H2]glucose tracers, Miller et al. (2002a, b) maintained arterialized venous plasma [La] at approximately 4 mM in subjects exercising at a moderate exercise intensity (~ 55% \(\dot {V}\)O2peak). Overall, they (Miller et al. 2002a) found a significant increase in La oxidation accompanied by a decrease in glucose oxidation, suggesting that La competes successfully with glucose as a carbohydrate fuel source. In addition, the La clamp data of Miller et al. (2002b) and Roef et al. (2003) taken together demonstrated that La was an important gluconeogenic precursor at both low and moderate exercise intensities. These La clamp studies, along with many other investigations of different types, emphasize the role of La as arguably the most important substrate for gluconeogenesis, and of course, the key role of the liver [e.g., (Connor and Woods 1982; Nielsen et al. 2002)] as an important player in the cell-to-cell lactate shuttle.

Studies of cardiac muscle, a highly oxidative tissue, show that under conditions of elevated blood [La], elevated myocardial blood flow, and elevated myocardial metabolic rate; La can become the preferred fuel, accounting for as much as 60% of the myocardial substrate (Gertz et al. 1988; Stanley 1991). Essentially, all of this La taken up by the heart is oxidized as a fuel (Stanley 1991). The paramount importance of La as a fuel source for the heart is further seen when the heart is stressed via β-adrenergic stimulation (Lopaschuk et al. 2010), increased afterload (Wyatt et al. 1977), chronotropic challenge (Camici et al. 1989; Bagger et al. 2000), and shock (Kline et al. 2000).

The brain: part of the cell-to-cell lactate shuttle and site of the astrocyte–neuron lactate shuttle

While myocardial tissue has long been appreciated as a metabolic omnivore, capable of readily utilizing a variety of substrates, the long-standing model for brain metabolism identifies glucose as the predominant energy substrate in the adult brain (Sokoloff 1989). However, the newborn mammalian brain has been shown to utilize elevated blood La as a substrate, and additionally, consume circulating ketones during breastfeeding to meet a substantial portion of energy requirements (Pellerin 2010). Subsequent investigations with 13C nuclear magnetic resonance spectroscopy explored La metabolism in the resting brain, finding that with baseline physiological blood [La]s, approximately 10% of brain energy needs are met via oxidation of La, with the ability to oxidize more as circulating La levels rise (Boumezbeur et al. 2010).

In hindsight, the ability for neuronal tissue to function on alternate substrates seems intuitive for organismal success. As first suggested by the laboratory of Holmes and Holmes in the 1920s (Holmes and Holmes 1925a, b, 1926, 1927; Holmes 1930), later including Ashford and Holmes (1929), and recently reviewed by Schurr (2017), it is also now clear that in addition to glucose, the brain takes up La. However, a full appreciation of La as a viable substrate for the brain has only recently been realized. In this context, the recycling of La in exercising skeletal muscle served as an important model for exploration within the brain. Global brain uptake of La during exercise was reported as early as at least 1972 (Ahlborg and Wahren 1972). Almost 30 years later, Ide et al. observed an increase in La uptake by the brain during both exercise (Ide et al. 1999) and recovery from exercise (Ide et al. 2000). It is now well established that with intense exercise, the brain is activated and this, in conjunction with the accompanying elevated arterial blood [La], leads to a large increase in net La uptake which in fact becomes greater than glucose uptake (Ide and Secher 2000; Quistorff et al. 2008). At the conclusion of exercise to exhaustion, blood [La] was shown to be increased, while concentrations within the cerebral spinal fluid and brain were equivalent to baseline levels, ruling out La accumulation and indicating La utilization as a substrate (Dalsgaard et al. 2004). In euglycemic adult males, infusion of sodium La to levels mimicking mild exercise elicited net La uptake, with a concomitant reduction in glucose uptake of 17% versus control (Smith et al. 2003). Clearly, global brain La metabolism is a part of the cell-to-cell lactate shuttle. There is also evidence that regular physical activity slows age-related memory impairment (Tsai et al. 2016) and brain tissue loss with aging (Colcombe et al. 2003) leading to the notion that La may serve as a link between exercise and improvement of cognitive functions (Proia et al. 2016). Recently, Hashimoto et al. (2017) observed a significant correlation between executive function and La extraction by the brain following high intensity interval exercise. On the basis of their findings, they (Hashimoto et al. 2017) proposed that exercise training should be above the LT to foster brain activity.

Broadly, two conceptual hurdles hindered the consideration of La as a fuel for the brain. First, a limited appreciation that aerobic glycolysis, specifically cerebral glycolysis, terminates in La formation, and second, that La is an important substrate for the brain. In consideration of the first point, work from investigators in both skeletal and cardiac tissue provided a framework by defining the cell-to-cell lactate shuttle hypothesis, stating that La is shuttled from its place of formation to distant sites for mitochondrial oxidation (Brooks 1985b, 1998; Brooks et al. 1999b; Van Hall 2000; Chatham et al. 2001; Gladden 2004b). Further contributions from the field of muscle metabolism affirmed that La is always the end-product of glycolysis (Gladden 2004b; Rogatzki et al. 2015), and as elegantly summarized by Schurr, is the most feasible path when considered thermodynamically, chemically, and spatially (Schurr 2006). A second hurdle to overcome was development of an experimentally supported framework to explain how La could be utilized in the brain. Following the footsteps of the cell-to-cell lactate shuttle framed by Brooks (see discussion above), this conceptual framework has emerged as the Astrocyte–Neuron Lactate Shuttle (ANLS) hypothesis (Fig. 9), and in recent decades a body of evidence has grown to support La as an oxidizable substrate that is not only taken up from the blood but one that is also shuttled within the brain. This is a major arena of scientific discovery for which studies of metabolism during exercise paved the way.

Following the introduction of La shuttling by the Brooks group, early evidence suggested that La could support both normal synaptic function, and reactivate glucose-depleted synaptic quiescence in hippocampal slices (Schurr et al. 1988). This was furthered to conclude that La, rather than glucose (Schurr et al. 1997b), is shuttled to post-hypoxic neurons to recover function (Schurr et al. 1997c) and that the La is produced in glial cells (Schurr et al. 1997a). At approximately the same time that the supportive role of La was being elucidated in the brain, the ANLS framework for the contemporary view of neuroenergetics was posited (Magistretti and Pellerin 1996). This hypothesis suggests that in support of increased neuronal activity, astrocytes increase their rate of glucose uptake, glycolysis, and the subsequent release of La into the extracellular space, where it is then taken up by neurons for oxidation.

The conceptual evolution of La shuttling in brain cells has grown in complexity over the last two decades. Conventional metabolic theory suggests that the action potentials of neurons result in an influx of Na+ ions and an efflux of K+ ions activating Na+-K+-ATPase pumps. This consumes ATP while producing ADP, inorganic phosphate, and AMP, each of which further stimulate glycolysis, the TCA cycle, and oxidative phosphorylation. In contrast, the ANLS hypothesis describes a supportive metabolic milieu in which stimulated neurons release glutamate as an excitatory neurotransmitter (Pellerin and Magistretti 1994, 2003; Pellerin 2003; Bélanger et al. 2011). Increased activity at glutaminergic synapses leads to glutamate uptake by astrocytes through a co-transporter mechanism that carries one glutamate, three Na+, and one H+ inward, while a single K+ is exported out of the cell (Attwell 2000; Tsacopoulos 2002). In the new model, it is this transport activity which triggers the Na+–K+-ATPase activity to restore ionic balance, thus consuming ATP and triggering astrocyte metabolism. In the intracellular space, glutamate is converted to glutamine in an ATP-dependent reaction that is catalyzed by an astrocyte-specific glutamine synthetase (Mason 2017). Glutamine is released back to the extracellular space, where it is taken up by neurons and reconverted to glutamate by glutaminase (Bélanger et al. 2011). This process replenishes the pool of excitatory neurotransmitter, while the energy cost of the ATPase pumps and glutamine synthesis generate the classic stimuli for glycolysis and subsequent La production: decreased [ATP], increased [ADP], increased [Pi], and increased [AMP].

Within the ANLS hypothesis, there is a division of labor, whereby the astrocyte may be viewed as a supportive cell type responsible for the glycolytic production of La, which is subsequently processed oxidatively by the neurons when energy demands are increased. Several tenets of the ANLS hypothesis are corroborated by the identification of key players in the shuttling mechanism. First, neuronal glutamate release is facilitated by the excitatory amino acid transporters (EAATs) with EAAT3 expressed exclusively in neurons and glutamate uptake via the glia-specific EAAT1 and EAAT2 transporters (Bélanger et al. 2011; Mason 2017). This neuro-stimulatory trafficking of glutamate provides the impetus for increased metabolism and the shuttling of La within the brain.

Lactate dehydrogenase (LDH), the enzyme responsible for the interconversion of pyruvate and La, is expressed in five isozymes ranging from oxidative (LDH-1) to glycolytic (LDH-5). The LDH-5 subunit possesses a higher maximal velocity (Vmax) and is more commonly expressed in glycolytic tissues, often termed “muscle type”. LDH-1 is inhibited by pyruvate; thus, increased La in the presence of the LDH-1 isozyme is posited to favor return to pyruvate and ultimately oxidation; this isozyme is often termed “heart type”. LDH isozyme distribution correlates with substrate utilization with the LDH-5 isozyme predominating in astrocytes, while LDH-1 is more prevalent in neurons (Bittar et al. 1996) [note that a causative role for LDH isoforms remains a matter of debate (Rogatzki et al. 2015)]. Additional support is observed in the distribution of the monocarboxylate transporters (MCTs) in the brain. MCTs allow for monocarboxylate movement across cell barriers down their concentration gradients (see discussion below). MCT2 transporters are localized to neurons and associated with net La uptake, while the MCT4 subtype is expressed in astrocytes and associated with net La release. High-resolution immunocytochemical methods from rodent studies explored MCT distribution in distinctly oxidative versus glycolytic compartments and corroborated this MCT distribution lending support to the shuttling of glycolytically produced La from the astrocyte to the oxidative neuron (Bergersen 2007). However, to repeat a caveat from above, these locational–metabolic relationships are correlative and not necessarily causal.

A great deal of experimental support has been generated for the ANLS hypothesis of brain metabolism; however, it has not been unanimously accepted (Chih et al. 2001; Chih and Roberts 2003). A detailed summary was provided by Pellerin and Magistretti (Pellerin and Magistretti 2011) with review of both supportive, and critical, investigations concerning the ANLS hypothesis concluding that the ANLS model is a useful framework for further investigation to better understand the coupling of neuronal activity and energetics.

Lactate and volume transmission

In the CNS, focused synaptic action via “wired” transmission of electrical–chemical signals is a well described means by which cells communicate quickly. Another widespread form of inter-CNS communication involves activation of neurotransmitter systems over relatively large volumes and distances of the brain (Agnati et al. 1995; Zoli and Agnati 1996). Dubbed “volume transmission” by Agnati and Fuxe in 1986 (Fuxe et al. 2010), this mode of communication relies on diffusion and convection of chemical modulators through the brain’s extracellular fluid and cerebrospinal fluid. As such, volume transmission is conceptually similar to paracrine/autocrine signaling, and tends to elicit changes more slowly than wired transmission.

The list of potential agents of volume transmission is long, and includes monamines (Fuxe et al. 2010), glutamate (Okubo and Iino 2011), and l-DOPA (Gjedde et al. 1993; Ugrumov 2009). Evidence also suggests that La may act as a volume transmitter (Lauritzen et al. 2013; Tang et al. 2014; Morland et al. 2015). Bergersen & Gjedde (Bergersen and Gjedde 2012) forwarded the idea that by acting as a volume transmitter through either the GPR81 receptor (and subsequently altering intracellular cAMP levels), or by adjusting intracellular NAD+/NADH redox ratios (see section on whole-body cytosolic redox coupling via La), La could link the maintenance of brain energy status with cerebral blood flow. In this way, La would be viewed as a mediator of metabolic information rather than, or perhaps in addition to, a metabolic substrate.

Lactate transport across membranes

We now understand La as a ubiquitous metabolic intermediate operating as both the terminal product of glycolytic metabolism and the intermediary to complete oxidation of glucose by oxidative phosphorylation. In this framework, it is important to understand how La is rapidly mobilized from sites of production and taken up as a source of oxidizable or gluconeogenic/glyconeogenic substrate in remote tissues. For much of the last century, it was thought that La traveled in and out of muscle via simple diffusion [see (Gladden 1989) for review]. However: (1) large differences in [La] between blood and muscle during exercise and infusion; (2) saturation of transmembrane flux in response to an increasing [La] gradient; and (3) inhibition of La transport by chemical agents [see (Gladden 1989) for review] stimulated the search for a transporter. In the 1970s, the Halestrap laboratory reported that cyanohydroxycinnamate (CHC) specifically inhibited the proton-linked transport of La and pyruvate into human red blood cells (Halestrap and Denton 1974; Halestrap 1976). Over succeeding years, kinetics of the transporter as well as substrate and inhibitor specificities were characterized in detail by both the Deuticke (Deuticke 1982) and Halestrap (Poole and Halestrap 1993) groups. In 1990, Roth and Brooks (Roth and Brooks 1990a, b) were the first to study La flux into sarcolemmal vesicles in skeletal muscle. They demonstrated that sarcolemmal La transport was concentration dependent, saturable, stereospecific, competitively inhibited by other monocarboxylates, blocked by known inhibitors of monocarboxylate transport, sensitive to temperature, and stimulated by [H+] gradients. Their studies were at the forefront of an exponential increase of research on membrane transport of La.

Abundant research has now revealed that transmembrane La movement is broadly accomplished by the Solute Carrier Family 16 (SLC16) proteins, one of 52 SLC families (Jones and Morris 2016) with over 300 members (Merezhinskaya and Fishbein 2009). Specifically, MCTs are a family of transporters including 14 related proteins, only the first four of which are particularly important in the transport of La, pyruvate, and ketone bodies (Halestrap and Wilson 2012; Halestrap 2013). The rapidity of La exchange is dramatically enhanced by the activity of the MCTs. MCTs 1–4 are energy independent (i.e., passive) and facilitate metabolite flux down concentration gradients in conjunction with H+ ions (Halestrap and Wilson 2012). Concurrent advances in our understanding of the MCT family enabled the conceptual shift in our grasp of La as an intermediate in metabolism. Much of what is known concerning the transport of pyruvate and La into and out of cells came from investigations with red blood cells (RBCs) (Skelton et al. 1995, 1998), particularly the work of the Halestrap lab (Halestrap 1976, 2012; Poole and Halestrap 1992, 1993; Juel and Halestrap 1999; Halestrap and Meredith 2004; Ullah et al. 2006; Halestrap and Wilson 2012).

MCTs 1–4 are responsible for the proton linked exchange of MCTs across plasma membranes down their concentration gradients. Monocarboxylates; L–La, pyruvate, d-β-hydroxybutyrate, and acetoacetate are driven to enter or exit cells based on their concentration gradients as well as the H+ ion distribution (i.e., from low pH toward high pH) (Halestrap and Wilson 2012). It is important to note that the MCT isoforms are not independently responsible for influx or efflux, but rather, facilitate concentration-driven transport with regulation guided by expression, tissue distribution, and cellular location. MCT1 has the broadest tissue distribution (Merezhinskaya and Fishbein 2009) and is often, but not always, most highly expressed in cellular locations where net La uptake occurs such as heart and oxidative skeletal muscle. As noted by Halestrap and Wilson (2012), the major differences among MCTs 1–4 are their substrate and inhibitor affinities, the tissues in which they are expressed, and where they are located within cells. The predominant isomer of La found in humans is L–La for which MCT1 is stereoselective with Km approximating 3–5 mM for L–La and tenfold higher for d-lactate (Poole and Halestrap 1993). In comparison with MCT1, MCT2 has a higher affinity for both pyruvate (Km = 0.1 mM) and L–La (Km = 0.74 mM) (Bröer et al. 1998). MCT3 has similar kinetic properties to MCT1; however, it is restricted to the basal membrane of retinal pigment epithelium and choroid plexus epithelium (Bergersen et al. 1999; Philp et al. 2001). MCT4 is also widely expressed in tissues and has higher expression in tissues associated with net export of La such as fast glycolytic skeletal muscle, astrocytes, white blood cells, and chondrocytes (Juel and Halestrap 1999; Bonen 2001; Halestrap and Meredith 2004). The functional difference of MCT4 from MCT1 can be appreciated by the Km values for pyruvate and L–La of about 150 and 28 mM, respectively (Bröer et al. 1998; Halestrap and Wilson 2012), which presumably aids in cellular retention of pyruvate and limits loss of La to higher physiological concentrations.

In general, MCT1 expression is highly correlated with indices of oxidative metabolism in skeletal muscle, while MCT4 expression is correlated with indices of glycolytic metabolism (Juel and Halestrap 1999; Brooks 2000; Halestrap and Wilson 2012). It is also generally true that chronic changes in muscle activity cause corresponding changes in La transport. Endurance exercise training and chronic electrical activity increase La transport capability, whereas inactivity, due to denervation or hindlimb suspension as examples, causes a decrease in La transport capability [see (Juel and Halestrap 1999; Bonen 2001; Gladden 2004a; Halestrap and Wilson 2012) for review]. The main change in MCT isoform profile with exercise training or a high energy demand stimulus is an increase in MCT1 with MCT4 changes being much less (Gladden 2004a; Halestrap and Wilson 2012; Thomas et al. 2012). However, in some research, hypoxia appears to be a stimulus for increased MCT4 mRNA and protein expression in a variety of cells, an effect that is likely regulated by HIF-1α (Ullah et al. 2006; Halestrap and Wilson 2012). The response of MCTs to an acute exercise bout is less clear with some studies reporting an increase in MCT content (Green et al. 2002, 2008; Coles et al. 2004; Bickham et al. 2006), while others have reported either no change or a decrease in MCT content (Tonouchi et al. 2002; Bishop et al. 2007). Overall, Thomas et al. (2012) propose that there is a rapid decrease in membrane MCT1 and MCT4 content between 45 s and 10 min after exercise onset, no change from 30 to 80 min and an increase in MCT1 content 2 h after exercise onset. However, they (Thomas et al. 2012) correctly note that these MCT responses to acute exercise are based on only a small number of studies, thus further research is needed. There is also some evidence that MCT content and maximal La transport capability are not always in perfect concordance, and may be independently regulated (Thomas et al. 2012). As one considers the distribution of MCT isoforms and changes in their density and distribution with various stimuli, two caveats should always be considered: (1) the MCTs are not independent causative factors in La transport, because they are passive facilitators, regardless of isoform and (2) cells with a preponderance of MCT1 such as oxidative skeletal muscle fibers tend to have a much greater maximal La transport rate than do cells with a preponderance of MCT4 such as glycolytic skeletal muscle fibers (Juel et al. 1991; Bonen 2001; Juel 2001; Gladden 2004a). In this context, it is noteworthy that while MCT4 is associated with La efflux, its kinetic properties are such that it will likely be limiting to transmembrane transfer, leading to a [La] gradient from one side to the other (e.g., intracellular to extracellular in a La-producing cell).

Cytosol-to-mitochondria lactate shuttle

The cytosol-to-mitochondria lactate shuttle (Rogatzki et al. 2015) describes the continuous glycolytic production, and mitochondrial oxidation of La within the cell of its origin (Fig. 10) (Stainsby and Brooks 1990; Hashimoto et al. 2006; Gladden 2008a; Rogatzki et al. 2015). In this model, mitochondria oxidize La at or near the inner mitochondrial membrane, possibly by a La oxidation complex (Hashimoto et al. 2006), but not in the mitochondrial matrix. The NADH produced by mitochondrial LDH (mLDH) is reoxidized by the malate–aspartate shuttle (MAS) (Kane 2014), or possibly other electron shuttles (see below). While evidence for mitochondrial MCT1 (as per a La oxidation complex) is not unanimously accepted (Halestrap and Wilson 2012), pyruvate transport could be similarly accomplished via the mitochondrial pyruvate carrier. As mentioned previously, because of the high LDH activity in a diversity of tissues, as well as the equilibrium constant for LDH greatly favoring La, the predominant result of glycolysis is La (Kane 2014; Rogatzki et al. 2015; Schurr 2017). However, it should be noted that formation of La is not synonymous with La accumulation and increased [La]. In a manner analogous to the subcellular distributions of the cytosolic versus mitochondrial creatine kinase of the phosphocreatine shuttle, the mitochondrial reticulum (Glancy et al. 2015) (and its resident intermembrane or juxta-inner membrane LDH) serves as a sink for La, maintaining La flux irrespective of accumulation (Kane 2014; Rogatzki et al. 2015).

Fig. 10

Cytosol-to-mitochondria lactate shuttle (Rogatzki et al. 2015). Based on (Stainsby and Brooks 1990; Hashimoto et al. 2006; Gladden 2008a; Rogatzki et al. 2015) and combined from (Kane 2014; Rogatzki et al. 2015). The prominent activity of the near-equilibrium LDH ensures cytosolic La formation during most conditions, with rates increasing in parallel with increased glycolytic activity. The figure depicts a skeletal muscle, and not all cells necessarily exhibit all the processes depicted in the upper right. Compartmentations with glycolytic activity include association with the sarcolemmal Na+/K+ ATPase, glycolysis-related reactions, and the Ca2+-ATPase of the sarcoplasmic reticulum. La enters the mitochondrial intermembrane space through porins in the outer mitochondrial membrane. Here, mLDH oxidizes La to Pyr, reducing NAD+ to NADH. Pyr crosses the mitochondrial inner membrane via the MPC and/or MCT1, stabilized by CD147. Note: arguments against mitochondrial MCT have been made; see (Halestrap and Wilson 2012). The NADH generated by mLDH is reoxidized by the MAS, which shuttles reducing power across the inner mitochondrial membrane. This is necessary, because the inner mitochondrial membrane is impermeable to NAD+ and NADH. In the matrix, Pyr is oxidized by PDH to acetyl coA, which enters the TCA cycle, generating additional NADH. Oxidation of NADH at Complex I is a primary entry point of electrons into the mitochondrial electron transport system (ETS). The electrons are then passed to the mobile electron carrier Q, transported through Complex III, and then to Complex IV/COX via cytochrome c. The final electron acceptor at Complex IV in this schematic is molecular O2. The drops in free energy occurring across the ETS at complexes I, III, and IV are sufficient to drive the extrusion of H+ from the matrix into the intermembrane space, generating the proton motive force necessary to drive the synthesis of ATP at Complex V/ATP synthase. Omitted for clarity: Complex II/succinate dehydrogenase of the TCA/ETS, the glycerol 3-phosphate shuttle, the NAD(P) transhydrogenase, and stoichiometries of reactants and products for all reactions. ADP adenosine diphosphate, ATP adenosine triphosphate, C cytochrome c, CD147 chaperone protein for MCT1, cLDH cytosolic l-lactate dehydrogenase, CO 2 carbon dioxide, CoA coenzyme A, H + hydrogen ion, H 2 O water, I Complex I/NADH oxidoreductase of the mitochondrial electron system, III Complex III of the mitochondrial electron transport system, IV/COX complex IV/cytochrome c oxidase, La l-lactate; MAS malate–aspartate shuttle, MCT monocarboxylate transporter, mLDH mitochondrial l-lactate dehydrogenase, MPC mitochondrial pyruvate carrier, NAD + oxidized nicotinamide adenine dinucleotide, NADH reduced nicotinamide adenine dinucleotide, O 2 molecular oxygen, PDH pyruvate dehydrogenase complex, Pyr pyruvate, Q quinone, TCA tricarboxylic acid cycle, V Complex V/ATP synthase

Despite the seemingly straightforward concept of cytosol-to-mitochondria La shuttling, the nature of mitochondrial La metabolism remains a subject to which the following quotation of Fletcher and Hopkins (1907), cited earlier, might equally apply today: “there is hardly any important fact concerning the lactic acid formation in muscle which, advanced by one observer, has not been contradicted by some other.” A comprehensive treatment of this contentious issue is beyond the scope of this review (Brandt et al. 1987; Brooks et al. 1999b; Rasmussen et al. 2002; Sahlin et al. 2002; Ponsot et al. 2005; Hashimoto et al. 2006; Atlante et al. 2007; Schurr and Payne 2007; Yoshida et al. 2007; Lemire et al. 2008; Passarella et al. 2008, 2014; Gallagher et al. 2009; Elustondo et al. 2013; Jacobs et al. 2013; Schurr 2014; Herbst et al. 2017; Paventi et al. 2017). Suffice it to say that at present, discord exists about the precise functional location of mitochondrial LDH, but that the majority of the evidence indicates that LDH is not in the mitochondrial matrix (Baba and Sharma 1971; Brandt et al. 1987; Rasmussen et al. 2002; Sahlin et al. 2002; Ponsot et al. 2005; Hashimoto et al. 2006, 2008; Yoshida et al. 2007; Hashimoto and Brooks 2008; Elustondo et al. 2013; Jacobs et al. 2013; Herbst et al. 2017), and therefore, evidence does not favor an intracellular lactate shuttle as originally conceptualized (Brooks et al. 1999a, b).

However, it is important to recognize that progress around mitochondrial La metabolism has been complicated for two main reasons: (1) technical limitations in subcellular/cellular studies and (2) the potential differences among tissue and cell types. Spectrophotometric monitoring of NADH change, for example, has been used repeatedly in the study of La metabolism in mitochondria of diverse origin (Valenti et al. 2002; De Bari et al. 2004, 2010; Atlante et al. 2007; Pizzuto et al. 2012; Passarella et al. 2014; Paventi et al. 2017). This approach is problematic, not least, because NAD(H) is a cofactor in a myriad of biochemical reactions (Ying 2008), but also because the La/pyruvate redox couple is so closely linked to cytosolic, and not mitochondrial matrix NAD+/NADH; not to mention that the latter is orders of magnitude more reduced relative to the cytosol (Williamson et al. 1967; Jones and Sies 2015); see Sahlin et al. 2002 for discussion (Sahlin et al. 2002). Furthermore, the ability of intact mitochondria to oxidize exogenous NADH (to which the inner mitochondrial membrane is impermeable) is a consistent observation, first reported by Lehninger over 65 years ago (Lehninger 1951). Similarly, spectrophotometric monitoring of NADH change has been used to study the rotenone-insensitive, aerobic reoxidation of cytosolic NADH via cytochrome b5 reductase in cerebellar granular cells (Atlante et al. 1999) and liver outer mitochondrial membranes (Bernardi and Azzone 1981; Abbrescia et al. 2012), as well as the rotenone-sensitive, “exo-NADH oxidase system” in isolated cardiac (Rasmussen 1969; Jørgensen et al. 1985; Rasmussen and Rasmussen 1985; Nohl 1987) and skeletal muscle mitochondria (Szczesna-Kaczmarek et al. 1984; Rasmussen et al. 2001, 2003a, b). Interpreting NADH changes in a system in which LDH is not the exclusive NADH oxidoreductase is further complicated in the study of mitochondrial La metabolism by the liberal employment of the LDH inhibitor oxamate which also inhibits pyruvate transport (Martin-Requero et al. 1986) and the aspartate aminotransferase of the malate–aspartate shuttle (Rej 1979; Thornburg et al. 2008). Among the potentially unintended effects of other agents used, mersalyl is an inhibitor of outer mitochondrial membrane cytochrome b5 reductase (Bernardi and Azzone 1981); digitonin increases exogenous mitochondrial NADH oxidation in rat liver (Bodrova et al. 1998); and Triton X-100 increases exogenous mitochondrial NADH oxidation in pigeon heart (Rasmussen and Rasmussen 1985). Ironically, Szczesna-Kaczmarek et al. (Szczesna-Kaczmarek et al. 1984) even suggested a relationship between extramatrix La oxidation and the external mitochondrial NADH oxidation pathway in muscle; such a system would help explain stimulation of NAD+-dependent La oxidation with exogenous cytochrome c added after (Elustondo et al. 2013), but not before (Jacobs et al. 2013) adding La to permeabilized skeletal muscle fibers, as cytochrome c can transfer electrons between cytochrome b5 reductase of the outer mitochondrial membrane and cytochrome c oxidase (Complex IV) of the electron transport system.

Recently, Patti and associates (Chen et al. 2016) took a more direct approach, using high-resolution mass spectrometry to study mitochondrial metabolism of La in cultured immortalized cells derived from cervical (HeLa) and lung cancer (H460), as well as 3T3-L1 fibroblasts. Their work (Chen et al. 2016) supports the contention that La plays a predominantly anaplerotic/cataplerotic role in proliferating cells [vis-à-vis the Warburg/reverse-Warburg effects; (Warburg 1926)] and is consistent with notions of matrix LDH and a mitochondrial La carrier (Taylor 2017). Nevertheless, even they (Chen et al. 2016) admitted that they were unable to resolve exactly where La oxidation occurs in mitochondria. Because much of the previous research does not support matrix La oxidation, reconciling equivocal studies will require further investigation. As discussed in greater detail below, however (see “Lactate and cancer”), cancer and other proliferating cells exhibit metabolic phenotypes distinct from normal or differentiated tissue (Lunt and Vander Heiden 2011; San-Millán and Brooks 2017), and culture conditions do not replicate fully the tumor microenvironment in vivo (Goodwin et al. 2014). Nevertheless, a consistent, key finding that emerges among these diverse studies is the centrality of La as a metabolic intermediate within and between cells.

Whole-body cytosolic redox coupling via La

Recently, the Rabinowitz laboratory (Hui et al. 2017), using stable isotope techniques, rediscovered and reemphasized the cell-to-cell lactate shuttle. They (Hui et al. 2017) measured the turnover flux of 16 different carbon metabolites in mice under non-exercise conditions. Their major contribution was the observation that the circulatory turnover flux of La exceeds that of all other metabolites, being 10–150% greater than the rate of glucose turnover flux, depending on whether the mice were fed or post-absorptive. Furthermore, these investigators postulate that the rapid translocation of La across cell membranes (see discussion above) and its bulk circulation in the blood positions La to serve as a means of equating cytosolic NAD+/NADH ratios across tissues throughout the body. This is an intriguing, albeit not novel (Brooks 2009; Halestrap 2013; San-Millán and Brooks 2017) concept. The Rabinowitz group (Hui et al. 2017) further postulates that this redox function of the cell-to-cell lactate shuttle would permit the use of carbohydrate-derived energy without the necessity of glycolysis in some tissues, while other tissues could modulate glycolytic activity to support other needs such as cell proliferation, NADPH production via the pentose phosphate pathway, activity of brain neurons, and systemic glucose homeostasis (Vander Heiden et al. 2009). Halestrap (Halestrap 2013) explains that this process is possible because of the exclusively cytosolic location of LDH and the fact that the LDH reaction is close to equilibrium in most cells. Furthermore, due to these relationships, changes in the cytosolic La/pyruvate ratio can cause changes in the NAD+/NADH ratio and vice versa (Halestrap 2013).

We see merit in these proposals but note two additional, important factors. First, while La rapidly exchanges throughout the body, it equilibrates across permeable membranes in accordance with the [H+] (pH) gradient (Roos 1975; Gladden and Yates 1983; Roth and Brooks 1990a). Systemic pH is in turn regulated by a number of other factors [e.g., (Gladden 2008a; Stickland et al. 2013)]. Second, while the cell-to-cell lactate shuttle might coordinate cytosolic redox balance among tissues, it will not directly impact mitochondrial redox. This is because cytosolic and mitochondrial matrix redox states are not in equilibrium with each other (Sahlin et al. 2002). The major underlying reason for the separate NAD+/NADH ratios between these two compartments is that there are nonequilibrium steps for electron transfer across the inner mitochondrial membrane. For the malate–aspartate shuttle, the nonequilibrium step is the exchange of glutamate plus a proton from outside the inner mitochondrial membrane for aspartate from the mitochondrial matrix (Nicholls and Ferguson 2013). For the s,n-glycerophosphate shuttle, the nonequilibrium step is at the flavoprotein-linked sn-glycerophosphate dehydrogenase reaction within the inner mitochondrial membrane (Nicholls and Ferguson 2013). With regard to La exchange across the inner mitochondrial membrane, this is not a mechanism for redox equilibration because of the absence of LDH in the mitochondrial matrix as discussed in the previous section.

Lactate as a signaling molecule

The lactate/pyruvate ratio is the predominant cytosolic redox couple for NAD+/NADH. It should, therefore, not be surprising that the marked rises in [La] during times of cellular stress constitute a signaling molecule—a “lactormone” (Brooks 2009; San-Millán and Brooks 2017). In addition to serving as an oxidizable fuel itself, La also inhibits lipolysis (Gold et al. 1963), and proportionally down-regulates the oxidation and disposal of glucose [(Miller et al. 2002a, b); see discussion earlier]. It is thought that La achieves this lactormone-like regulation of metabolism by interacting with the G-protein coupled receptor GPR81 (a.k.a., HCA1) on fat cells to inhibit lipolysis (Liu et al. 2009). Though by comparison, its level of expression is much greater in adipose (Cai et al. 2008; Ahmed et al. 2010), GPR81 expression in brain (Bergersen and Gjedde 2012; Lauritzen et al. 2014), skeletal muscle (Ge et al. 2008; Kuei et al. 2011; Rooney and Trayhurn 2011), heart and other tissues (Liu et al. 2009), nevertheless, suggests important La signaling functions in these tissues which await complete description.

La can also elicit longer term influence over gene expression via hypoxia-inducible factor-1 (HIF-1), a transcription factor regarded as the master regulator of O2 homeostasis (Semenza 2004). When activated by hypoxia, HIF-1 regulates the expression of several genes coding for proteins involved in glycolysis, La handling, and metabolism. For example, HIF-1 activation increases pyruvate dehydrogenase kinase 1 (PDK1) content in mouse embryo fibroblasts (Kim et al. 2006), which inhibits pyruvate dehydrogenase (PDH), and stems flux away from pyruvate oxidation at PDH, instead leading to LDH-dependent La accumulation. HIF-1 also increases the content of some cell membrane glucose transporters (Wood et al. 1998; Chen et al. 2001; Mobasheri et al. 2005; Sakagami et al. 2014), and 11 enzymes of glycolysis (Semenza 2001), including the main rate-controlling enzyme phosphofructokinase (PFK). Increased glucose transport and glycolytic activity promote the formation and accumulation of La. HIF-1 also increases MCT4 content (Ullah et al. 2006), the isoform associated with La efflux from glycolytic skeletal muscle. Thus, HIF-1 activation leads to both the enhanced formation, and effective efflux of La. Interestingly, HIF-1 and La exhibit reciprocal activation, whereby La can activate HIF-1, and HIF-1 can promote the production of La. It has been proposed that reactive oxygen species may mediate the reciprocal activation of HIF-1 and La production (Nalbandian and Takeda 2016).

Peroxisome proliferator activated receptor gamma coactivator-1 α (PGC-1 α), a transcription coactivator widely regarded as the master regulator of mitochondrial biogenesis, also plays a role in regulating La metabolism. Upon binding to the estrogen-related receptor-α on an ldhb promotor, PGC-1 α promotes the transcription of lactate dehydrogenase isoform B (LDHB). Recently, Liang et al. (2016) demonstrated not only that exercise stimulated the expression of skeletal muscle LDHB, but that overexpression of ldhb in mice acts downstream of the PGC-1α/nuclear receptor regulatory circuit to increase markers of mitochondrial content. As with HIF-1, it has been theorized that La-associated reactive oxygen species (ROS) mediates these PGC-1 α-dependent adaptations (Nalbandian and Takeda 2016); though unlike the upregulation of PFK with La in hypoxia, La appears to downregulate PFK under normoxic conditions (Leite et al. 2007, 2011). In what may be another example of reciprocal activation, La also appears to upregulate expression and content of some of the same proteins upregulated by PGC-1 α, including MCT1 (Hashimoto et al. 2007; Hoshino et al. 2014) and COXIV (Hashimoto et al. 2007), as well as PDK4 and UCP3 (Kitaoka et al. 2016).

The lactormone function of La adds to the long and growing list of ways in which nature has integrated this unassuming molecule into a diversity of physiological processes. It should come as little surprise that as the tools of scientific inquiry advance, La will continue to feature prominently in areas of both physiology and pathophysiology (e.g., see section on the role of La in cancer).

Lactate and cell volume regulation

There is also evidence of a role for La in fluid volume regulation during heavy exercise. During moderate-to-intense exercise, hypotonic fluid is shifted out of the vascular compartment causing the plasma osmolarity to increase (Mack 2012). One of the main reasons for this fluid shift involves net water movement into contracting muscles due to increases in intracellular and interstitial osmolarity caused by increases in skeletal muscle intracellular and extracellular fluid [La]. For example, in humans exercising at 75% of \(\dot {V}\)O2peak to exhaustion, a three-phase pattern of plasma volume shifts is observed, the first of which (first 2 min of exercise) is thought to be due to increases in capillary pressure and osmotic pressures within the contracting muscle (Lindinger et al. 1994). The second phase of plasma volume decrease is associated with an increase in muscle metabolites such as La due to increased rates of glycolysis (Lindinger et al. 1994). The increase in extracellular osmolarity results in a volume loss in non-contracting cells; this is hypothesized to attenuate plasma fluid losses early in exercise (Lindinger et al. 2011). Opposing this loss of fluid, inactive skeletal muscle fibers exhibit a regulatory volume increase mediated by ion transport using the electroneutral Na-K-2Cl co-transporter (Lindinger et al. 2011); however, inward transport of La via MCT1 also contributes (Lindinger et al. 2013). Whether a similar role for La as a mediator of cell volume regulation exists in cells of the central nervous system has, to our knowledge, not been addressed. Conceivably such a role could exist because of the ease with which La permeates the blood–brain barrier, and the ubiquity of MCTs in brain cells.

In the eye, it has been suggested that MCTs 1 and 3 facilitate the volume of the subretinal space via transport of lactate and its attendant tonicity (Halestrap 2013), and evidence also supports direct transport of water with lactate (Zeuthen et al. 1996; Hamann et al. 2003; Li et al. 2016).

Lactate and cancer

The history of cancer is complicated and riddled with descriptions of masses dating back to as early as 1600 BC (The History of Cancer 2002). However, it was not until the 1920s that detailed experiments on tumor metabolism were first reported. As reviewed by Otto (Otto 2016), Warburg and Minami (Warburg and Minami 1923) placed tumors in Ringer solution and observed acidification upon addition of glucose. The acidification was indicated by color change from organic pH indicators, while La was measured in the solution chemically. Subsequently, Warburg placed slices of a rat hepatoma in a modified manometer and calculated La from the increase in CO2 formation during 30 min of incubation. Amazingly, the tumor slice produced La at a rate that was 70 times greater than that of normal liver, kidney, and heart tissue (Otto 2016)! This high La production rate was independent of the presence of O2. In 1925, the Cori’s (Cori and Cori 1925) reported that venous blood from a chicken wing with an implanted sarcoma had higher [La] and lower [glucose] than venous blood from the contralateral, non-tumor wing. Warburg (Warburg et al. 1927) next used a rat model to show that the artery feeding the tumor always had lower [La] and higher [glucose] than the vein draining it, consistent with La production by a tumor in presumably normoxic conditions. In 1972, Efraim Racker called this glucose-avid, La-producing behavior of tumor cells in the presence of adequate O2 supply, the “Warburg Effect” (Racker 1972). This effect is now well known in the study of cancer, and research on the topic has skyrocketed since approximately 2000. It has also sparked interest among researchers and clinicians as a target for treatment (Nijsten and van Dam 2009; Goodwin et al. 2015; Martinez-Outschoorn et al. 2017).

Our current understanding of tumor metabolism is exemplified by a report from Sonveaux et al. (Sonveaux et al. 2008). These researchers (Sonveaux et al. 2008) determined the metabolic characteristics of two tumor lines via measurement of O2 consumption, glucose utilization, and La production. One line, SiHa human cervix squamous carcinoma cells, consumed O2 rapidly, used glucose more slowly, produced La more slowly, and oxidized La as readily as glucose. The second line, WiDr human colorectal adenocarcinoma cells behaved conversely to the SiHa cells in that they consumed O2 slowly, used glucose more rapidly, produced La more rapidly, and were much less effective at oxidizing La. In addition, the tumor lines differed in terms of MCT expression in that the SiHa cells preferentially expressed MCT1, whereas the WiDr cells expressed MCT4. Following up on these results in vitro, Sonveaux et al. (2008) obtained both SiHa and WiDr tumor biopsies from tumors grown in mice from the corresponding cancer cells injected intramuscularly in the rear leg. The SiHa tumors were particularly interesting. Within the SiHa tumors, two tumor cell subpopulations were documented; one group was located in a well-vascularized, well-oxygenated area of the tumor and the other was located in a poorly vascularized, hypoxic area. MCT1 was expressed in the oxygenated cells but not in the hypoxic cells. Again, following in the footsteps of exercise metabolism research, Sonveaux et al. viewed the whole of their results and hypothesized a La shuttle in which La is produced by the hypoxic tumor sites and oxidized as a fuel in the normoxic sites. In a commentary further detailing the potential facets of such a shuttle, Greg Semenza, himself the discoverer of HIF1-α (Semenza and Wang 1992), stated, “Was there any precedent that should have alerted us to the existence of this symbiotic relationship between aerobic and hypoxic cancer cells? Of course: the well-known recycling of lactate in exercising muscle” (Semenza 2008). This began the incorporation of knowledge gained from studying La metabolism in exercise physiology, particularly the work of G. A. Brooks, into tumor physiology.

The Warburg cancer cell profile is characterized by several features. First, there is an increase in glycolytic enzymes, sometimes by as much as 500-fold (Moreno-Sánchez et al. 2007; San-Millán and Brooks 2017). The ample carbohydrate fuel supply that is critical for Warburg cells is aided by an increased expression of glucose transporters, particularly GLUT1, a phenomenon that is associated with aggressive tumors and a poor prognosis [e.g., (Kunkel et al. 2003; San-Millán and Brooks 2017)]. Note that the basis for the whole-body non-invasive PET scan (18F-fluorodeoxygluscose positron emission tomography) technique for diagnosing and monitoring cancer progression is based on the high glucose uptake by tumor cells (Jadvar et al. 2009). Since La is the terminal end-product, it is not surprising that MCT1 and MCT4 transporters are often overexpressed in many types of cancers [e.g., (Kennedy and Dewhirst 2010; San-Millán and Brooks 2017)], and are in fact, correlated with a poor prognosis and high mortality (Pértega-Gomes et al. 2011). The underlying causes of these changes and of cancer itself, are numerous, complicated, and incompletely understood [e.g., (San-Millán and Brooks 2017)]. Intriguingly, Sán-Millan and Brooks (2017) have even proposed that the elevated La production and subsequent increased [La] (up to 40-fold) are central signaling players in the generation of the Warburg cell profile. The primary LDH isoform in Warburg cells is LDHA (Semenza et al. 1996; Vander Heiden et al. 2009; Granchi et al. 2010; San-Millán and Brooks 2017) which has been argued to promote La production [e.g., (Everse and Kaplan 1973; Granchi et al. 2010)] and to negatively impact prognosis [e.g., (Sheng et al. 2012; Shi et al. 2014; Huang et al. 2016)]. Knockdown of LDHA has been an experimental approach to cancer treatment and it has met with some success [e.g., (Fantin et al. 2006; Vander Heiden 2011; Wang et al. 2015)]. However, it is not clear that LDHA has been inhibited independently of total LDH activity. We have previously expressed our skepticism that LDH isoform profile is a determinative factor in net La production and accumulation (Rogatzki et al. 2015). This reprogramming of cell metabolism in many, perhaps most cancer cells, is so dramatic and widespread that it has been proposed as a new hallmark of cancer (Hanahan and Weinberg 2011).

One might ask why cancer cells would gorge on glucose and only partially realize its full energy potential by emphasizing La production rather than full oxidation. An older idea (Potter 1958) that has been re-derived (Vander Heiden et al. 2009; Hanahan and Weinberg 2011; Martinez-Outschoorn et al. 2017) is that this metabolic scheme provides building blocks for proliferation. Because the organism absorbs the burden of regulating blood glucose concentration, the tumor cells are awash in fuel, thus negating any substrate limitation. Subsequent to the rapid use of glucose, glycolytic intermediates are diverted into numerous biosynthetic pathways. Included in these proliferative pathways are the generation of nucleosides and amino acids, providing the foundational materials for macromolecules and organelles which can ultimately constitute new cells via rapid cell division. Faster conversion of fuel into biomass maximizes the rate of growth; proliferation rather than efficiency may be the “goal” of the cancer cell (Vander Heiden et al. 2009). An additional benefit of increased La production and efflux to the cancer cell might be the acidification of the extracellular milieu, which is believed to facilitate cell invasion of surrounding tissue and metastasis (Gatenby and Gillies 2004; Gillies and Gatenby 2007).

Given the Warburg cell’s dependence on glucose as a fuel, a clever notion is to deprive tumors of glucose and thereby either kill them, weaken them, or heighten their susceptibility to other treatments (Nijsten and van Dam 2009). It is well known that depriving cultured cancer cells of glucose is frequently detrimental to growth [e.g., (Aykin-Burns et al. 2009; Choo et al. 2010; Graham et al. 2012)]. However, how can the organism survive the glucose deprivation required to damage cancer cells? Nijsten and van Dam (Nijsten and van Dam 2009) proposed making patients severely hypoglycemic while using La as an alternative fuel; i.e., lactate-protected hypoglycemia (LPH) (Goodwin et al. 2015). As revealed in the cell-to-cell lactate shuttle, most normal cells (but not Warburg cells) can readily use La as a fuel. A particular concern, despite studies showing that the brain can oxidize La, is whether or not the brain can survive in the face of severe hypoglycemia (< 1 mM). A case study encouraged this idea. Oldenbeuving et al. (Oldenbeuving et al. 2014) reported the case of a patient arriving at the emergency room with what is usually considered nonsurvivable hypoglycemia (0.7 mM); however, his arterial [La] was 25 mM. The patient, suffering from paracetamol-induced acute liver failure, was ambulating and speaking, presumably due to the use of La as a fuel by his vital tissues, particularly the brain. Subsequently, Goodwin et al. (Goodwin ML, Rogatzki MJ, Sun Y, McDonald JR, Lee K, Oldenbeuving G, Nijsten MWN, Gladden LB, unpublished results) attempted LPH in an anesthetized canine model. As shown in Fig. 11, Panel A, three animals were made severely hypoglycemic via a combination of insulin, propranolol, and ethanol/phenformin; once severe hypoglycemia was reached, the anesthetized animals survived on the average about 30 min as indicated by isoelectricity on the electroencephalogram. In contrast, two animals were made hyperlactatemic ([La] = ≈ 10 mM; Fig. 11B) prior to initiating severe hypoglycemia. Those two animals survived at least 5 h before brain isoelectricity occurred. These results offer the tantalizing possibility that the brain can survive severe hypoglycemia for at least several hours in the presence of hyperlactatemia.

Fig. 11

Demonstration of lactate-protected hypoglycemia (LPH) in anesthetized dogs. A Experimental manipulation of [glucose] in anesthetized dogs (n = 3) as described in the text. Once blood [glucose] was reduced to < 1 mM, time to brain isoelectricity (death) was ~ 0.5 h. In B, the same protocol was repeated (n = 2) but with prior and continued infusion of exogenous La to almost ten times normal and clamped there (~ 10 mM). Subsequently, time to isoelectricity was increased 10-fold (> 5.5 h), substantiating for the first time in whole animals what had been suspected from clinical case reports (Oldenbeuving et al. 2014) and decades of data demonstrating La’s ability to be transported and utilized as a fuel throughout almost all tissues of the body (Gladden 2004b). This proposed LPH (Nijsten and van Dam 2009; Goodwin et al. 2015) might function for at least a period of hours. Note different scales on x- and y-axes in Panels A versus B. Data are from unpublished results of Goodwin ML, Rogatzki MJ, Sun Y, McDonald JR, Lee K, Oldenbeuving G, Nijsten MWN, Gladden LB

Unfortunately, it is possible, perhaps likely, that the idea of treating cancer with LPH is overly simplistic. Work from Lisanti’s lab (Pavlides et al. 2009; Gladden et al. 2011; Whitaker-Menezes et al. 2011) found that when MCF7 breast cancer cells were co-cultured with normal fibroblasts, the fibroblasts began to express MCT4, something they failed to do when cultured alone. Furthermore, the breast cancer cells in this co-culture demonstrated an upregulation of MCT1. This group (Pavlides et al. 2009; Whitaker-Menezes et al. 2011; Witkiewicz et al. 2012) has proposed that these results are part of a shuttle between stromal fibroblasts which display aerobic glycolysis, producing La, which is subsequently taken up by the neighboring cancer cells and oxidized as a fuel. The behavior of the cancer cells in this scenario was described as ‘Reverse Warburg’ (Pavlides et al. 2009). Overall, these results are a warning to remember that tumors are a heterogeneous collection of normal tissue cells, immune cells, blood vessels, and cancer cells, some of which may be of a Warburg phenotype, while others are of a Reverse-Warburg type (Hanahan and Weinberg 2011; Martinez-Outschoorn et al. 2017; Potter et al. 2016; Lytovchenko and Kunji 2017). Some areas of the tumor may be hypoxic, while others are amply supplied with O2. Still other areas are nutrient deficient or nutrient rich, and this landscape is likely to change as the tumor infiltrates and proliferates (Hanahan and Weinberg 2011; Martinez-Outschoorn et al. 2016; Potter et al. 2016; Lytovchenko and Kunji 2017).

As a result, it should be emphasized here that cell culture experiments in vitro can afford excellent control of the local environment, but also can be quite misleading, as so much of cancer cell behavior depends on a complex and poorly understood tumor microenvironment (Goodwin et al. 2015). In addition, an often-unrecognized shortcoming of cell studies in vitro is that the cells are typically exposed to ambient O2 levels; these levels are extremely hyperoxic in comparison with conditions observed in vivo. Accordingly, studies utilizing whole limbs or animals likely provide a more nuanced understanding of how the tumor interacts with its microenvironment, including its production and/or consumption of La. Sauer and Dauchy (1985) measured arteriovenous differences across tumors in their rat model and demonstrated that most tumors were net La producers when the arterial [La] was below 2.5 mM; they subsequently utilized La as a fuel when arterial [La] was above 2.5 mM (Sauer and Dauchy 1985). It is likely that the degree to which tumors globally utilize La as a fuel ultimately depends on cell type, available substrate, and specific microenvironment. Targeting this remarkably flexible metabolism as a means to combat cancer is a formidable challenge!

While targeting La metabolism per se may prove to be quite difficult, recent work suggests that La is also a potent signaling molecule (see above as well), driving HIF1-α, VEGF, and ultimately angiogenesis (Goodwin et al. 2014). Lactate’s role as a signaling molecule was first described as a glycolytic metabolite that could, independent of O2, induce angiogenesis (Murray and Wilson 2001); this has now expanded with both theoretical and experimental support into the cancer literature. A recent review (Goodwin et al. 2015) highlights this lactate-to-angiogenesis pathway. Briefly, LDH is near-equilibrium and any increase in glycolysis will increase both [La] and [pyruvate]. Increased [pyruvate] inhibits formation of 2-oxoglutarate, the molecule typically responsible for degradation of HIF1-α. Thus, increases in [La] and [pyruvate] independent of O2 tension, can drive stabilization of HIF1-α and lead to angiogenesis. This has been demonstrated in several experimental designs but is yet to be implemented clinically. Most recently, the Kevin B. Jones lab in Utah introduced a novel transgenic mouse sarcoma model which resulted in mouse tumors that were indistinguishable from the human tumor (Goodwin et al. 2014). These tumors formed in areas of high [La] and expressed large amounts of HIF1-α despite normoxic conditions. As further confirmation of La’s potent role as a signal, daily exogenous La administration led to dramatic upregulation in the vascularity of these already well-vascularized tumors.

Research in skeletal muscle provided the early framework from which clinical application has now begun in both the central nervous system and tumor research. While many active clinical areas are currently under investigation (see section “Lactate in clinical applications”), research extending what is known about La metabolism in muscle to now include the brain and tumors has raised as many questions as it has answered. Given La’s central role as the metabolite by which whole-body metabolism is coordinated (Gladden 2004b), opportunities for clinical application are numerous.

Lactate in clinical applications

Given the confusion surrounding lactate research over the last 100 years, it is not surprising that in many ways clinical application has lagged even further behind. Originally thought of as a “hypoxic waste product”, many clinicians still view La in this manner. [La] is most often used by hospitals today in the trauma setting as an indicator of “resuscitation.” While frank dysoxia will obligatorily engender an elevated [La], an elevated [La] clearly does not typically indicate clinical hypoxia or hypoperfusion, a point that continues to cloud clinical interpretation. To complicate matters, [La] during the first 48 h in the hospital has remained one of the best indicators of clinical outcomes, with persistently elevated [La] being a relatively good predictor of surgical complications and even mortality (Claridge et al. 2000). Although typically reported as “clearance” in multiple papers (and even in their titles!) (Odom et al. 2013), concentration and not clearance is almost exclusively what is actually measured in the trauma and critical care setting (Goodwin and Rothberg 2014).

Many large clinical trials have examined [La] and clinical outcomes in the trauma and critical care setting. However, careful review of the literature calls into question the rationale for La-guided treatment in clinical practice. Pölönen et al. (Pölönen et al. 2000) used goals of [La] < 2.0 mM and SvO2 > 70% in the 8 h postoperative window in 403 bypass patients, utilizing additional IV fluids and dobutamine in an attempt to reach these goals. While the treatment group had less organ dysfunction and shorter length of stay by 1 day, only 57% actually met the goals (versus 42% in the control group) and [La] was not different between groups at any sampling time, suggesting that under-resuscitation/hypoperfusion is likely not the reason for continued La elevation in this setting (Pölönen et al. 2000). This type of goal-driven therapy has been repeated in septic shock patients, indicating some improvements with the additional treatments, but little to no difference in [La] between groups (Rivers et al. 2001; ProCESS 2014). Perhaps the most often cited study is from the Netherlands (Jansen et al. 2010), in which 348 ICU patients underwent goal-directed therapy in a randomized controlled trial with a goal of decreasing [La] by 20% every 2 h for 8 h utilizing fluids and vasodilators. The treatment group did receive significantly more fluid and medication, with a slight change in adjusted in-hospital and ICU (but not 28-day) mortality. However, [La] was not significantly different between the two groups at any time. Despite these results, the authors conclude that “lactate monitoring during the first 8 h of ICU admission, aimed at reducing lactate levels by 20% per 2 h, significantly reduced ICU length of stay and also ICU and hospital mortality…” Despite no change in [La] between the groups, this study (Jansen et al. 2010) continues to be cited as a reason that La-guided treatment should be utilized.

The question looming over these trials is why [La] remains elevated despite interventions that increase cardiac index and/or perfusion, and thereby global O2 delivery. This has led many clinicians to use the phrase “occult hypoperfusion,” in reference to the noted elevated [La] in patients in whom no perfusion deficit can be found and attempts to increase perfusion do not alter [La]. Clinicians often cite visceral organs as being the site of ischemia, yet this has been difficult to demonstrate in normal trauma or critical care settings. For example, clamping off the superior mesenteric artery in animals, making much of the bowel ischemic, fails to induce enough La production to increase arterial [La] to a significantly different level (Heino et al. 1997; Tenhunen et al. 2001). Consistent with this, improving the microcirculation of critical organs in critically ill patients does not alter arterial [La] (Trzeciak et al. 2008).

We are intensely skeptical of “occult hypoperfusion” in these cases, and propose instead that the increased [La] is due to nonhypoxic mechanisms. Clinically, increases in blood [La] due to hypoxia is likely the exception rather than the rule. Dysoxia is difficult to evoke, even during intense exercise. Richardson et al. (1995), cited earlier, had subjects inspire 12% O2, yet muscle PiO2 remained above the level of O2-limited mitochondrial function. Furthermore, even in conditions of very high [La] after exercise or seizures, once the stimulus is removed, [La] rapidly returns to normal levels within a few hours. In the trauma setting, [La] may remain elevated for several days in patients who ultimately have poor clinical outcomes, suggesting some underlying metabolic derangement. While it is beyond the scope of this review, this persistent [La] elevation may be due to the underlying stress response of trauma or critical care, as catecholamines stimulate ß-adrenergic receptors on skeletal muscle, liberating skeletal muscle glycogen as La (Clutter et al. 1980; Stainsby et al. 1987). This response has previously been described in burn patients (Gore et al. 1991), and numerous lines of animal and human studies support this hypothesis as the mechanism for elevated La in many trauma and critical care patients (Irving 1968; Daniel et al. 1976a, b, 1978; Benedict and Grahame-Smith 1978; Liddell et al. 1979; James et al. 1996, 1999a, b; Luchette et al. 2002; Garcia-Alvarez et al. 2014).

Given La’s now well-supported role as both fuel and signaling molecule, it is worth noting that its prolonged elevation with trauma or critical illness may simply represent the body in a state of prolonged stress, and the La elevation a result of prolonged catecholamine elevation in an effort to mount a “fight or flight” response. Nonetheless, prolonged elevated [La] remains a useful clinical marker across multiple disciplines, and it is always prudent to ensure adequate oxygenation. Venkatesan et al. (Venkatesan et al. 2015) demonstrated that hip fracture patients with [La] > 3.0 mM on arrival have four times the 30-day mortality as those with [La] < 3.0 mM on arrival. Claridge et al. (Claridge et al. 2000) followed [La] for 24 h after admission to the ICU for trauma; those who had [La] that remained > 2.5 mM at 12 h had six times the mortality and four times the infection rate of those who normalized before 12 h. Multiple examples of this are found in the clinical literature, and it remains a good predictor of how a patient might do, despite the gross mechanistic misinterpretation by many clinicians. Finally, studies that simply alter the [La] do not change the poor prognosis of these patients [e.g., with DCA to activate PDH complex and drive increased formation of acetyl CoA (Stacpoole et al. 1992)], further highlighting the indirect nature of the relationship between [La] and clinical outcomes. It is apparent that the mechanisms underlying an elevated [La] must be the problem.

In opposition to the negative consequences associated with elevated [La] in many critical care and trauma situations, there is growing evidence that deliberate induction of hyperlactatemia may be beneficial in some conditions. As summarized by Ichai et al. (2014), La infusion has elicited improved myocardial function in patients with septic shock, after cardiac surgery, and with acute heart failure (Nalos et al. 2014). Positive results have also been found for La infusion in traumatic brain injury (Ichai et al. 2013, 2014; Brooks and Martin 2014; Quintard et al. 2016). In addition, La has been proposed as a salvage fuel in the use of severe hypoglycemia as a potential therapy in the treatment of tumors exhibiting the Warburg effect (Nijsten and van Dam 2009) as discussed above.

Yes, Virginia, there is a lactic acidosis

While lactic acid has long been known as a strong biological acid (pKa = 3.86), hypotheses centering on its formation and effects in vivo seem to have clouded the picture. Following an earlier proposal by Hochachka and Mommsen (1983), Robergs et al. (2004, 2005, 2006; Robergs 2008) have asserted that there is no lactic acidosis during exercise (or any other condition perhaps). This assertion is proffered on the basis of a detailed accounting of the reactions of glycolysis, concluding that (1) La is the biochemical end-product of glycolysis, not HLa, (2) the LDH reaction from pyruvate to La “consumes protons” (H+), and (3) the acidosis typically seen in conjunction with increasing [La] is due to the hydrolysis of ATP that was not produced by oxidative phosphorylation inside mitochondria; i.e., non-mitochondrial ATP. However, disregarding the question of whether or not La is the only physicochemical contributor to the acidosis of exercise (it likely is not) (Böning and Maassen 2008a, b; Lindinger and Heigenhauser 2008a, b; Gladden 2008c), there are significant errors in Robergs’ claims. First, the argument that the major source of protons is the hydrolysis of non-mitochondrially produced (glycolytic) ATP hinges on a decreasing concentration of ATP. In fact, ATP concentration changes relatively little under most conditions. Studies of phosphagen concentration in skeletal muscle during exercise date back to those of Hultman and colleagues (Hultman et al. 1967; Gollnick and Hermansen 1973) who showed that while phosphocreatine concentration declined linearly with increases in exercise intensity, changes in [ATP] were comparatively minor. Second, even though it is agreed that La, not HLa, is produced by glycolysis (Jones 1980; Robergs et al. 2004), La cannot exist in isolation. La must immediately be in equilibrium with the same pH as all other acids in solution; this is the isohydric principle.

So, whether HLa is viewed as (1) a strong biological acid which is almost entirely dissociated at usual muscle and blood pH values, or (2) a significant contributor to the strong ion difference [SID; (Stewart 1981; Kellum and Elbers 2009)], both constructs entail an acidifying effect of La accumulation. Aside from basic principles, Marcinek et al. (2010) have found that there is close relationship between pH decline and La accumulation with constant [ATP] in direct experimental testing. Specifically, they (Marcinek et al. 2010) measured pH and [ATP] in ischemic mouse muscle using 31P-MRS, and intracellular [La] chemically. Even with no change in [ATP], their calculated H+ generation agreed closely with the increase in [La] over the course of the ischemic period.

Certainly one could argue that if pyruvate instead of La accumulated during exercise or some other glycolytic stimulus, then the [H+] would increase more, because pyruvic acid is a stronger acid than HLa. However, it is La rather than pyruvate that increases dramatically because of an equilibrium constant for the LDH reaction that is strongly in favor of La (Lambeth and Kushmerick 2002). In fact, the La to pyruvate ratio ranges from about 10:1 at rest to values as high as 159:1 in skeletal muscle immediately following exhaustive dynamic exercise (Sahlin et al. 1976; Rogatzki et al. 2015). In conclusion, increases in [La] do have an acidifying effect.


Prebble (2010) has documented that it was research focused on muscle metabolism by a group of biochemists that led to discovery of the glycolytic pathway while also laying the foundation for discovery of the origins of aerobic phosphorylation. Most of these biochemists had the common influence of the Otto Meyerhof laboratory (Prebble 2010). Of course, the quest for an understanding of La production and removal in muscle was an important linchpin of the glycolytic research. Allchin (2002) asserts, and we agree, that understanding cellular metabolism/bioenergetics is a great achievement of the twentieth century that has not been acclaimed to the same extent as advancements in evolution, genetics, and molecular biology (Prebble 2010), but should be. Within this wondrous web of cellular bioenergetics, Scheele’s little three carbon molecule seems to grow in importance. Should this be surprising? No. For most vertebrates, and certainly mammals, there are two ATP-generating systems, glycolysis and oxidative phosphorylation. Glycolysis does not require O2 and has La as its end-product, because the equilibrium of the LDH reaction is markedly in favor of La. La, then, is an immediate reservoir supplying pyruvate to mitochondria for complete oxidative combustion. Therefore, La stands at the intersection of anaerobic and aerobic metabolism of carbohydrate fuel. La may also coordinate cytosolic redox state among tissues throughout the body. It is of little wonder, then, that we find La involved throughout intermediary metabolism, including both global extraorgan exchange and intra-tissue exchange.


Compliance with ethical standards

Conflict of interest

There are no conflicts of interest.


  1. Abbrescia DI, La Piana G, Lofrumento NE (2012) Malate-aspartate shuttle and exogenous NADH/cytochrome c electron transport pathway as two independent cytosolic reducing equivalent transfer systems. Arch Biochem Biophys 518(2):157–163. PubMedCrossRefGoogle Scholar
  2. Agnati LF, Zoli M, Strömberg I, Fuxe K (1995) Intercellular communication in the brain: wiring versus volume transmission. Neurosci 69(3):711–726CrossRefGoogle Scholar
  3. Ahlborg G, Wahren J (1972) Brain substrate utilization during prolonged exercise. Scand J Clin Lab Invest 29(4):397–402PubMedCrossRefGoogle Scholar
  4. Ahmed K, Tunaru S, Tang C, Müller M, Gille A, Sassmann A, Hanson J, Offermanns S (2010) An autocrine lactate loop mediates insulin-dependent inhibition of lipolysis through GPR81. Cell Metab 11(4):311–319. PubMedCrossRefGoogle Scholar
  5. Akerboom TPM, Tager JM, Van der Meer R (1979) Techniques for the investigation of intracellular compartmentation. In: Komberg H, Metcalfe J, Northcote D (eds) In: Techniques in the life sciences. Biochemistry, techniques in metabolic research. Elsevier (North-Holland), AmsterdamGoogle Scholar
  6. Allchin D (2002) To Err and Win a Nobel Prize: Paul Boyer, ATP synthase and the emergence of bioenergetics. J Hist Biol 35(1):149–172PubMedCrossRefGoogle Scholar
  7. Allen DG, Lamb GD, Westerblad H (2008) Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 88(1):287–332PubMedCrossRefGoogle Scholar
  8. Andrews MA, Godt RE, Nosek TM (1996) Influence of physiological L (+)-lactate concentrations on contractility of skinned striated muscle fibers of rabbit. J Appl Physiol 80(6):2060–2065PubMedCrossRefGoogle Scholar
  9. Armstrong RB (1988) Muscle fiber recruitment patterns and their metabolic correlates. In: Horton E, Terjung R (eds) Exercise, nutrition and energy metabolism. MacMillan Publishing Co., New York, pp 9–26Google Scholar
  10. Ashford CA, Holmes EG (1929) Contributions to the study of brain metabolism. V. Role of phosphates in lactic acid production. Biochem J 23:748–759PubMedPubMedCentralCrossRefGoogle Scholar
  11. Atlante A, Gagliardi S, Marra E, Calissano P, Passarella S (1999) Glutamate neurotoxicity in rat cerebellar granule cells involves cytochrome c release from mitochondria and mitochondrial shuttle impairment. J Neurochem 73(1):237–246. PubMedCrossRefGoogle Scholar
  12. Atlante A, de Bari L, Bobba A, Marra E, Passarella S (2007) Transport and metabolism of l-lactate occur in mitochondria from cerebellar granule cells and are modified in cells undergoing low potassium dependent apoptosis. Biochim Biophys Acta Bioenerg 1767(11):1285–1299. CrossRefGoogle Scholar
  13. Attwell D (2000) Brain uptake of glutamate: food for thought. J Nutr 130(4):1023S-1025SCrossRefGoogle Scholar
  14. Aykin-Burns N, Ahmad Iman M, Zhu Y, Oberley Larry W, Spitz Douglas R (2009) Increased levels of superoxide and H2O2 mediate the differential susceptibility of cancer cells versus normal cells to glucose deprivation. Biochem J 418(1):29–37PubMedPubMedCentralCrossRefGoogle Scholar
  15. Baba N, Sharma HM (1971) Histochemistry of lactic dehydrogenase in heart and pectoralis muscles of rat. J Cell Biol 51(3):621–635PubMedPubMedCentralCrossRefGoogle Scholar
  16. Bagger JP, Thomassen A, Nielsen TT (2000) Cardiac energy metabolism in patients with chest pain and normal coronary angiograms. Am J Cardiol 85(3):315–320PubMedCrossRefGoogle Scholar
  17. Bangsbo J, Juel C (2006) Counterpoint: Lactic acid accumulation is a disadvantage during muscle activity. J Appl Physiol 100(4):1410–1414CrossRefGoogle Scholar
  18. Barnard RJ, Holloszy JO (2003) The metabolic systems: aerobic metabolism and substrate utilization in Exercising skeletal muscle. In: Tipton CM (ed) Exercise physiology: people and ideas. Springer, New York, pp 292–321.
  19. Barnett JA (2003) A history of research on yeasts 5: the fermentation pathway. Yeast 20(6):509–543PubMedCrossRefGoogle Scholar
  20. Barnett JA, Entian KD (2005) A history of research on yeasts 9: regulation of sugar metabolism. Yeast 22(11):835–894PubMedCrossRefGoogle Scholar
  21. Beaver WL, Wasserman K, Whipp BJ (1986) A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol 60(6):2020–2027PubMedCrossRefGoogle Scholar
  22. Bélanger M, Allaman I, Magistretti PJ (2011) Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation. Cell Metab 14(6):724–738PubMedCrossRefGoogle Scholar
  23. Benedict CR, Grahame-Smith DG (1978) Plasma noradrenaline and adrenaline concentrations and dopamine-β-hydroxylase activity in patients with shock due to septicaemia, trauma and haemorrhage. QJM: Int J Med 47(1):1–20. Google Scholar
  24. Beneke R, von Duvillard SP (1996) Determination of maximal lactate steady state response in selected sports events. Med Sci Sports Exerc 28(2):241–246PubMedCrossRefGoogle Scholar
  25. Benninga H (1990) A history of lactic acid making: a chapter in the history of biotechnology, vol 11. Kluwer Academic Publishers, BostonGoogle Scholar
  26. Bergersen LH (2007) Is lactate food for neurons? Comparison of monocarboxylate transporter subtypes in brain and muscle. Neuroscience 145(1):11–19PubMedCrossRefGoogle Scholar
  27. Bergersen LH, Gjedde A (2012) Is lactate a volume transmitter of metabolic states of the brain? Front Neuroenergetics 4(5).
  28. Bergersen LH, Johannsson E, Veruki ML, Nagelhus EA, Halestrap A, Sejersted OM, Ottersen OP (1999) Cellular and subcellular expression of monocarboxylate transporters in the pigment epithelium and retina of the rat. Neuroscience 90(1):319–331PubMedCrossRefGoogle Scholar
  29. Bergman BC, Wolfel EE, Butterfield GE, Lopaschuk GD, Casazza GA, Horning MA, Brooks GA (1999) Active muscle and whole body lactate kinetics after endurance training in men. J Appl Physiol 87(5):1684–1696PubMedCrossRefGoogle Scholar
  30. Bergman BC, Horning MA, Casazza GA, Wolfel EE, Butterfield GE, Brooks GA (2000) Endurance training increases gluconeogenesis during rest and exercise in men. Am J Physiol Endocrinol Metab 278(2):E244–E251PubMedCrossRefGoogle Scholar
  31. Berlinerblau M (1887) Über das Vorkommen der Milchsäure im Blute und ihre Entstehung im Organismus. Naunyn-Schmiedeberg’s Arch Pharmacol 23(5):333–346CrossRefGoogle Scholar
  32. Bernard C (1855) Lecons de physiologie experimentale appliquee a la medecine, faites au College de France par M. Claude Bernard: Cours du semestre d’hiver 1854–1855, vol 1. Baillière, ParisCrossRefGoogle Scholar
  33. Bernard C (1877) De la matière glycogène considerée comme condition de developpement de certains tissus, chez le foetus, avant l’apparition de la function glycogénique du foie: In Leçons sur le diabète. Extrait de Compt rend des séances de l’Acad des Sci 48, 1859. Baillière, ParisGoogle Scholar
  34. Bernardi P, Azzone GF (1981) Cytochrome c as an electron shuttle between the outer and inner mitochondrial membranes. J Biol Chem 256(14):7187–7192PubMedGoogle Scholar
  35. Berzelius JJ (1848) Jahres-bericht über die fortschritte der chemie und mineralogie, vol 3. Laupp’ sche Buchhandlung, TübingenGoogle Scholar
  36. Bickham DC, Bentley DJ, Le Rossignol PF, Cameron-Smith D (2006) The effects of short-term sprint training on MCT expression in moderately endurance-trained runners. Eur J Appl Physiol 96(6):636–643PubMedCrossRefGoogle Scholar
  37. Billat VL, Richard R, Binsse VM, Koralsztein JP, Haouzi P (1998) The V̇O2 slow component for severe exercise depends on type of exercise and is not correlated with time to fatigue. J Appl Physiol 85(6):2118–2124PubMedCrossRefGoogle Scholar
  38. Bishop DJ, Jenkins DG, Mackinnon LT (1998) The relationship between plasma lactate parameters, Wpeak and 1-h cycling performance in women. Med Sci Sports Exerc 30(8):1270–1275PubMedCrossRefGoogle Scholar
  39. Bishop DJ, Edge J, Thomas C, Mercier J (2007) High-intensity exercise acutely decreases the membrane content of MCT1 and MCT4 and buffer capacity in human skeletal muscle. J Appl Physiol 102(2):616–621PubMedCrossRefGoogle Scholar
  40. Bittar PG, Charnay Y, Pellerin L, Bouras C, Magistretti PJ (1996) Selective distribution of lactate dehydrogenase isoenzymes in neurons and astrocytes of human brain. J Cereb Blood Flow Metab 16(6):1079–1089PubMedCrossRefGoogle Scholar
  41. Bodrova ME, Dedukhova VI, Mokhova EN, Skulachev VP (1998) Membrane potential generation coupled to oxidation of external NADH in liver mitochondria. FEBS Lett 435(2–3):269–274PubMedCrossRefGoogle Scholar
  42. Bonen A (2001) The expression of lactate transporters (MCT1 and MCT4) in heart and muscle. Eur J Appl Physiol 86(1):6–11PubMedCrossRefGoogle Scholar
  43. Böning D, Maassen N (2008a) Point: counterpoint: lactic acid is/is not the only physicochemical contributor to the acidosis of exercise. J Appl Physiol 105(1):358–359PubMedCrossRefGoogle Scholar
  44. Böning D, Maassen N (2008b) Point: lactic acid is the only physiochemical contributor to the acidosis of exercise. Rebuttal J Appl Physiol 105(1):368CrossRefGoogle Scholar
  45. Boumezbeur F, Petersen KF, Cline GW, Mason GF, Behar KL, Shulman GI, Rothman DL (2010) The contribution of blood lactate to brain energy metabolism in humans measured by dynamic 13C nuclear magnetic resonance spectroscopy. J Neurosci 30(42):13983–13991PubMedPubMedCentralCrossRefGoogle Scholar
  46. Brandt RB, Laux JE, Spainhour SE, Kline ES (1987) Lactate dehydrogenase in rat mitochondria. Arch Biochem Biophys 259(2):412–422. PubMedCrossRefGoogle Scholar
  47. Bransford DR, Howley ET (1977) Oxygen cost of running in trained and untrained men and women. Med Sci Sports 9(1):41–44PubMedGoogle Scholar
  48. Brin M (1965) The synthesis and metabolism of lactic acid isomers. Ann N Y Acad Sci 119(1):942–956Google Scholar
  49. Bröer S, Schneider H-P, Bröer A, Rahman B, Hamprecht B, Deitmer JW (1998) Characterization of the monocarboxylate transporter 1 expressed in Xenopus laevis oocytes by changes in cytosolic pH. Biochem J 333(1):167–174PubMedPubMedCentralCrossRefGoogle Scholar
  50. Brooks GA (1985a) Anaerobic threshold: review of the concept and directions for future research. Med Sci Sports Exerc 17(1):22–34PubMedGoogle Scholar
  51. Brooks GA (1985b) Lactate: Glycolytic end-product and oxidative substrate during sustained exercise in mammals—the “Lactate Shuttle”. In: Gilles R (ed) Circulation, respiration, and metabolism: current comparative approaches. Springer, Berlin, pp 208–218.
  52. Brooks GA (1998) Mammalian fuel utilization during sustained exercise. Comp Biochem Physiol B Biochem Mol Biol 120(1):89–107PubMedCrossRefGoogle Scholar
  53. Brooks GA (2000) Intra-and extra-cellular lactate shuttles. Med Sci Sports Exerc 32(4):790–799PubMedCrossRefGoogle Scholar
  54. Brooks GA (2002) Lactate shuttles in nature. Biochem Soc Trans 30(2):258–264PubMedCrossRefGoogle Scholar
  55. Brooks GA (2007) Lactate: link between glycolytic and oxidative metabolism. Sports Med 37(4–5):341–343PubMedCrossRefGoogle Scholar
  56. Brooks GA (2009) Cell–cell and intracellular lactate shuttles. J Physiol 587(23):5591–5600PubMedPubMedCentralCrossRefGoogle Scholar
  57. Brooks GA (2012) Bioenergetics of exercising humans. Compr Physiol (2):537–562Google Scholar
  58. Brooks GA (2016) Energy flux, lactate shuttling, mitochondrial dynamics, and hypoxia. In: Roach RC, Hackett PH, Wagner PD (eds) Hypoxia: translation in progress. Springer US, Boston, pp 439–455.
  59. Brooks GA, Gladden LB (2003) The metabolic systems: anaerobic metabolism (glycolytic and phosphagen). In: Tipton CE (ed) Exercise physiology. people and ideas. Oxford University Press, New York, pp 322–360CrossRefGoogle Scholar
  60. Brooks GA, Martin NA (2014) Cerebral metabolism following traumatic brain injury: new discoveries with implications for treatment. Front Neurosci 8:408. PubMedGoogle Scholar
  61. Brooks GA, Brown MA, Butz C, Sicurello JP, Dubouchaud H (1999a) Cardiac and skeletal muscle mitochondria have a monocarboxylate transporter MCT1. J Appl Physiol 87(5):1713–1718PubMedCrossRefGoogle Scholar
  62. Brooks GA, Dubouchaud H, Brown M, Sicurello JP, Butz CE (1999b) Role of mitochondrial lactate dehydrogenase and lactate oxidation in the intracellular lactate shuttle. Proc Natl Acad Sci USA 96(3):1129–1134. PubMedPubMedCentralCrossRefGoogle Scholar
  63. Bruton JD, Lännergren J, Westerblad H (1998) Effects of CO2-induced acidification on the fatigue resistance of single mouse muscle fibers at 28 C. J Appl Physiol 85(2):478–483PubMedCrossRefGoogle Scholar
  64. Cahn RS, Ingold CK, Prelog V (1956) The specification of asymmetric configuration in organic chemistry. Experientia 12(3):81–94CrossRefGoogle Scholar
  65. Cai TQ, Ren N, Jin L, Cheng K, Kash S, Chen R, Wright SD, Taggart AKP, Waters MG (2008) Role of GPR81 in lactate-mediated reduction of adipose lipolysis. Biochem Biophys Res Commun 377(3):987–991. PubMedCrossRefGoogle Scholar
  66. Caiozzo VJ, Davis JA, Ellis JF, Azus JL, Vandagriff R, Prietto CA, McMaster WC (1982) A comparison of gas exchange indices used to detect the anaerobic threshold. J Appl Physiol 53(5):1184–1189PubMedCrossRefGoogle Scholar
  67. Cairns SP, Lindinger MI (2008) Do multiple ionic interactions contribute to skeletal muscle fatigue? J Physiol 586(17):4039–4054PubMedPubMedCentralCrossRefGoogle Scholar
  68. Camici P, Marraccini P, Marzilli M, Lorenzoni R, Buzzigoli G, Puntoni R, Boni C, Bellina CR, Klassen GA, L’Abbate A (1989) Coronary hemodynamics and myocardial metabolism during and after pacing stress in normal humans. Am J Physiol Endocrinol Metab 257(3):E309–E317CrossRefGoogle Scholar
  69. Caplice E, Fitzgerald GF (1999) Food fermentations: role of microorganisms in food production and preservation. Int J Food Microbiol 50(1):131–149PubMedCrossRefGoogle Scholar
  70. Chance B, Williams GR (1956) The respiratory chain and oxidative phosphorylation. Adv Enzymol Relat Areas Mol Biol 17:65–134Google Scholar
  71. Chatham JC, Des Rosiers C, Forder JR (2001) Evidence of separate pathways for lactate uptake and release by the perfused rat heart. Am J Physiol Endocrinol Metab 281(4):E794–E802PubMedCrossRefGoogle Scholar
  72. Chen Y Jr, Mahieu NG, Huang X, Singh M, Crawford PA, Johnson SL, Gross RW, Schaefer J, Patti GJ (2016) Lactate metabolism is associated with mammalian mitochondria. Nat Chem Biol 12(11):937–943. PubMedPubMedCentralCrossRefGoogle Scholar
  73. Chen C, Pore N, Behrooz A, Ismail-Beigi F, Maity A (2001) Regulation of glut1 mRNA by hypoxia-inducible factor-1 Interaction between H-ras and hypoxia. J Biol Chem 276(12):9519–9525PubMedCrossRefGoogle Scholar
  74. Chen C-M, Chen S-M, Chien P-J, Yu H-Y (2015) Development of an enzymatic assay system of d-lactate using d-lactate dehydrogenase and a UV-LED fluorescent spectrometer. J Pharm Biomed Anal 116:150–155PubMedCrossRefGoogle Scholar
  75. Cheng B, Kuipers H, Snyder AC, Keizer HA, Jeukendrup A, Hesselink M (1992) A new approach for the determination of ventilatory and lactate thresholds. Int J Sports Med 13(07):518–522PubMedCrossRefGoogle Scholar
  76. Chih C-P, Roberts EL Jr (2003) Energy substrates for neurons during neural activity: a critical review of the astrocyte-neuron lactate shuttle hypothesis. J Cereb Blood Flow Metab 23(11):1263–1281PubMedCrossRefGoogle Scholar
  77. Chih C-P, Lipton P, Roberts EL (2001) Do active cerebral neurons really use lactate rather than glucose? Trends Neurosci 24(10):573–578PubMedCrossRefGoogle Scholar
  78. Choo AY, Kim SG, Vander Heiden MG, Mahoney SJ, Vu H, Yoon S-O, Cantley LC, Blenis J (2010) Glucose addiction of TSC null cells is caused by failed mTORC1-dependent balancing of metabolic demand with supply. Mol Cell 38(4):487–499. PubMedPubMedCentralCrossRefGoogle Scholar
  79. Chung Y, Molé PA, Sailasuta N, Tran TK, Hurd R, Jue T (2005) Control of respiration and bioenergetics during muscle contraction. Am J Physiol Cell Physiol 288(3):C730–C738. CrossRefGoogle Scholar
  80. Clanton T, Hogan M, Gladden L (2013) Regulation of cellular gas exchange, oxygen sensing, and metabolic control. Compr Physiol 3(3):1135–1190PubMedGoogle Scholar
  81. Claridge JA, Crabtree TD, Pelletier SJ, Butler K, Sawyer RG, Young JS (2000) Persistent occult hypoperfusion is associated with a significant increase in infection rate and mortality in major trauma patients. J Trauma Acute Care Surg 48(1):8–14CrossRefGoogle Scholar
  82. Clutter WE, Bier DM, Shah SD, Cryer PE (1980) Epinephrine plasma metabolic clearance rates and physiologic thresholds for metabolic and hemodynamic actions in man. J Clin Invest 66(1):94PubMedPubMedCentralCrossRefGoogle Scholar
  83. Colcombe SJ, Erickson KI, Raz N, Webb AG, Cohen NJ, McAuley E, Kramer AF (2003) Aerobic fitness reduces brain tissue loss in aging humans. J Gerentol A Biol Sci Med Sci 58(2):M176–M180Google Scholar
  84. Coles L, Litt J, Hatta H, Bonen A (2004) Exercise rapidly increases expression of the monocarboxylate transporters MCT1 and MCT4 in rat muscle. J Physiol 561(1):253–261PubMedPubMedCentralCrossRefGoogle Scholar
  85. Connett RJ, Gayeski TEJ, Honig CR (1983) Lactate production in a pure red muscle in absence of anoxia mechanisms and significance. In: Bicher HI, Bruley DF (eds) Oxygen transport to tissue—IV. Advances in experimental medicine and biology, vol 159. Springer, Boston, MA, pp 327–335CrossRefGoogle Scholar
  86. Connett RJ, Gayeski TEJ, Honig CR (1984) Lactate accumulation in fully aerobic, working, dog gracilis muscle. Am J Physiol Heart Circ Physiol 246(1):H120–H128CrossRefGoogle Scholar
  87. Connett RJ, Gayeski TEJ, Honig CR (1986) Lactate efflux is unrelated to intracellular PO2 in a working red muscle in situ. J Appl Physiol 61(2):402–408PubMedCrossRefGoogle Scholar
  88. Connett RJ, Honig CR, Gayeski TEJ, Brooks GA (1990) Defining hypoxia: a systems view of V̇O2, glycolysis, energetics, and intracellular PO2. J Appl Physiol 68(3):833–842PubMedCrossRefGoogle Scholar
  89. Connor H, Woods HF (1982) Quantitative aspects of L (+)-lactate metabolism in human beings. In: Porter R, Lawrenson G (eds) Metabolic acidosis (Ciba Foundation Symposium 87). Pitman Books Ltd, London, pp 214–234Google Scholar
  90. Cori CF, Cori GT (1925) The carbohydrate metabolism of tumors II. Changes in the sugar, lactic acid, and CO2—combining Power of Blood Passing through a tumor. J Biol Chem 65(2):397–405Google Scholar
  91. Dalsgaard MK, Quistorff B, Danielsen ER, Selmer C, Vogelsang T, Secher NH (2004) A reduced cerebral metabolic ratio in exercise reflects metabolism and not accumulation of lactate within the human brain. J Physiol 554(2):571–578PubMedCrossRefGoogle Scholar
  92. Daniel AM, Pierce CH, MacLean LD, Shizgal HM (1976a) Lactate metabolism in the dog during shock from hemorrhage, cardiac tamponade or endotoxin. Surg Gynecol Obstet 143(4):581–586PubMedGoogle Scholar
  93. Daniel AM, Shizgal HM, MacLean LD (1976b) Endogenous fuels in experimental shock. Surg Forum 27(62):32–33PubMedGoogle Scholar
  94. Daniel AM, Shizgal HM, MacLean LD (1978) The anatomic and metabolic source of lactate in shock. Surg Gynecol Obstet 147(5):697–700PubMedGoogle Scholar
  95. Davis JA, Caiozzo VJ, Lamarra N, Ellis JF, Vandagriff R, Prietto CA, McMaster WC (1983) Does the gas exchange anaerobic threshold occur at a fixed blood lactate concentration of 2 or 4 mM? Int J Sports Med 4(2):89–93PubMedCrossRefGoogle Scholar
  96. De Bari L, Atlante A, Valenti D, Passarella S (2004) Partial reconstruction of in vitro gluconeogenesis arising from mitochondrial l-lactate uptake/metabolism and oxaloacetate export via novel l-lactate translocators. Biochem J 380(1):231–242. PubMedPubMedCentralCrossRefGoogle Scholar
  97. De Paoli FV, Overgaard K, Pedersen TH, Nielsen OB (2007) Additive protective effects of the addition of lactic acid and adrenaline on excitability and force in isolated rat skeletal muscle depressed by elevated extracellular K+. J Physiol 581(2):829–839PubMedPubMedCentralCrossRefGoogle Scholar
  98. De Bari L, Chieppa G, Marra E, Passarella S (2010) l-lactate metabolism can occur in normal and cancer prostate cells via the novel mitochondrial l-lactate dehydrogenase. Int J Oncol 37(6):1607–1620. PubMedGoogle Scholar
  99. Debold EP, Fitts RH, Sundberg C, Nosek TM (2016) Muscle fatigue from the perspective of a single crossbridge. Med Sci Sports Exerc 48(11):2270–2280PubMedCrossRefGoogle Scholar
  100. Degroot M, Massie BM, Boska M, Gober J, Miller RG, Weiner MW (1993) Dissociation of [H+] from fatigue in human muscle detected by high time resolution 31P-NMR. Muscle Nerve 16(1):91–98PubMedCrossRefGoogle Scholar
  101. Deuticke B (1982) Monocarboxylate transport in erythrocytes. J Membr Biol 70(2):89–103PubMedCrossRefGoogle Scholar
  102. Elustondo PA, White AE, Hughes ME, Brebner K, Pavlov E, Kane DA (2013) Physical and functional association of lactate dehydrogenase (LDH) with skeletal muscle mitochondria. J Biol Chem 288(35):25309–25317PubMedPubMedCentralCrossRefGoogle Scholar
  103. Engelhardt H (1848) Ueber die Verschiedenheit der durch Gährung aus dem Zucker erzeugten und der in der Fleischflüssigkeit enthaltenen Milchsäure. Eur J Org Chem 65(3):359–367Google Scholar
  104. Everse J, Kaplan NO (1973) Lactate dehydrogenases: structure and function. Adv Enzymol Relat Areas Mol Biol 37:61–133PubMedGoogle Scholar
  105. Fantin VR, St-Pierre J, Leder P (2006) Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance. Cancer Cell 9(6):425–434PubMedCrossRefGoogle Scholar
  106. Faude O, Kindermann W, Meyer T (2009) Lactate threshold concepts. Sports Med 39(6):469–490PubMedCrossRefGoogle Scholar
  107. Favero TG, Zable AC, Bowman MB, Thompson A, Abramson JJ (1995) Metabolic end products inhibit sarcoplasmic reticulum Ca2+ release and [3H] ryanodine binding. J Appl Physiol 78(5):1665–1672PubMedCrossRefGoogle Scholar
  108. Filiz AI, Aladag H, Akin ML, Sucullu I, Kurt Y, Yucel E, Uluutku AH (2010) The role of d-lactate in differential diagnosis of acute appendicitis. J Invest Surg 23(4):218–223PubMedCrossRefGoogle Scholar
  109. Fitts RH (1994) Cellular mechanisms of muscle fatigue. Physiol Rev 74(1):49–94PubMedCrossRefGoogle Scholar
  110. Fitts RH (2016) The role of acidosis in fatigue: pro perspective. Med Sci Sports Exerc 48(11):2335–2338PubMedCrossRefGoogle Scholar
  111. Fletcher WM, Hopkins FG (1907) Lactic acid in amphibian muscle. J Physiol 35(4):247–309PubMedPubMedCentralCrossRefGoogle Scholar
  112. Folwarczny C (1863) Handbuch der physiologischen Chemie mit Rücksicht auf pathologische Chemie und analytische Methoden: Mit vier Tabellen. Exemplar anf holland. Papier. Sallmayr and Comp, ViennaGoogle Scholar
  113. Fortney SM, Nadel ER, Wenger CB, Bove JR (1981) Effect of blood volume on sweating rate and body fluids in exercising humans. J Appl Physiol 51(6):1594–1600PubMedCrossRefGoogle Scholar
  114. Fuxe K, Dahlström AB, Jonsson G, Marcellino D, Guescini M, Dam M, Manger P, Agnati L (2010) The discovery of central monoamine neurons gave volume transmission to the wired brain. Prog Neurobiol 90(2):82–100PubMedCrossRefGoogle Scholar
  115. Gaesser GA, Brooks GA (1975) Muscular efficiency during steady-rate exercise: effects of speed and work rate. J Appl Physiol 38(6):1132–1139PubMedCrossRefGoogle Scholar
  116. Gaesser GA, Poole DC (1996) The slow component of oxygen uptake kinetics in humans. Exerc Sport Sci Rev 24(1):35–70PubMedGoogle Scholar
  117. Gaglio G (1866) Die Milchsäure des Blutes und ihre Ursprungsstatten. Arch Anat Physiol Abt 10:400–414Google Scholar
  118. Gallagher CN, Carpenter KLH, Grice P, Howe DJ, Mason A, Timofeev I, Menon DK, Kirkpatrick PJ, Pickard JD, Sutherland GR, Hutchinson PJ (2009) The human brain utilizes lactate via the tricarboxylic acid cycle: A 13C-labelled microdialysis and high-resolution nuclear magnetic resonance study. Brain 132(10):2839–2849. PubMedCrossRefGoogle Scholar
  119. Garcia-Alvarez M, Marik P, Bellomo R (2014) Stress hyperlactataemia: present understanding and controversy. Lancet Diabetes Endocrinol 2(4):339–347. PubMedCrossRefGoogle Scholar
  120. Gatenby RA, Gillies RJ (2004) Why do cancers have high aerobic glycolysis? Nat Rev Cancer 4(11):891–899PubMedCrossRefGoogle Scholar
  121. Ge H, Weiszmann J, Reagan JD, Gupte J, Baribault H, Gyuris T, Chen J-l, Tian H, Li Y (2008) Elucidation of signaling and functional activities of an orphan GPCR, GPR81. J Lipid Res 49(4):797–803. PubMedCrossRefGoogle Scholar
  122. Gertz EW, Wisneski JA, Stanley WC, Neese RA (1988) Myocardial substrate utilization during exercise in humans. Dual carbon-labeled carbohydrate isotope experiments. J Clin Invest 82(6):2017–2025PubMedPubMedCentralCrossRefGoogle Scholar
  123. Gillies RJ, Gatenby RA (2007) Adaptive landscapes and emergent phenotypes: why do cancers have high glycolysis? J Bioenerg Biomembr 39(3):251–257PubMedCrossRefGoogle Scholar
  124. Gjedde A, Léger GC, Cumming P, Yasuhara Y, Evans AC, Guttman M, Kuwabara H (1993) Striatal l-DOPA decarboxylase activity in Parkinson’s disease in vivo: implications for the regulation of dopamine synthesis. J Neurochem 61(4):1538–1541PubMedCrossRefGoogle Scholar
  125. Gladden LB (1989) Lactate uptake by skeletal muscle. Exerc Sport Sci Rev 17:115–155PubMedGoogle Scholar
  126. Gladden LB (1991) Net lactate uptake during progressive steady-level contractions in canine skeletal muscle. J Appl Physiol 71(2):514–520PubMedCrossRefGoogle Scholar
  127. Gladden LB (1996) Lactate transport and exchange during exercise. In: Rowell LB, Shepherd JT (eds) Handbook of physiology, Section 12—Exercise: regulation and integration of multiple systems. Oxford University Press, New York, pp 614–648Google Scholar
  128. Gladden LB (2004a) Lactate metabolism during exercise. In: Poortmans JR (ed) Principles of exercise biochemistry, vol 46. Karger Publishers, Basel, pp 152–196CrossRefGoogle Scholar
  129. Gladden LB (2004b) Lactate metabolism: a new paradigm for the third millennium. J Physiol 558(1):5–30PubMedPubMedCentralCrossRefGoogle Scholar
  130. Gladden LB (2008a) 200th anniversary of lactate research in muscle. Exerc Sport Sci Rev 36(3):109–115PubMedCrossRefGoogle Scholar
  131. Gladden LB (2008b) A lactatic perspective on metabolism. Med Sci Sports Exerc 40(3):477–485PubMedCrossRefGoogle Scholar
  132. Gladden LB (2008c) Cause and effect? J Appl Physiol 105(1):364PubMedGoogle Scholar
  133. Gladden LB (2016) The basic science of exercise fatigue. Med Sci Sports Exerc 48(11):2222–2223PubMedCrossRefGoogle Scholar
  134. Gladden L, Hogan M (2006) Point: counterpoint: commentaries on ‘Lactic acid accumulation is an advantage/disadvantage during muscle activity’. J Appl Physiol 100(4):2100–2101PubMedGoogle Scholar
  135. Gladden LB, Welch HG (1978) Efficiency of anaerobic work. J Appl Physiol 44(4):564–570PubMedCrossRefGoogle Scholar
  136. Gladden LB, Yates JW (1983) Lactic acid infusion in dogs: effects of varying infusate pH. J Appl Physiol 54(5):1254–1260PubMedCrossRefGoogle Scholar
  137. Gladden LB, Yates JW, Stremel RW, Stamford BA (1985) Gas exchange and lactate anaerobic thresholds: inter-and intraevaluator agreement. J Appl Physiol 58(6):2082–2089PubMedCrossRefGoogle Scholar
  138. Gladden LB, Crawford RE, Webster MJ (1992) Effect of blood flow on net lactate uptake during steady-level contractions in canine skeletal muscle. J Appl Physiol 72(5):1826–1830PubMedCrossRefGoogle Scholar
  139. Gladden LB, Crawford RE, Webster MJ (1994) Effect of lactate concentration and metabolic rate on net lactate uptake by canine skeletal muscle. Am J Physiol Regul Integr Comp Physiol 266(4):R1095–R1101CrossRefGoogle Scholar
  140. Gladden LB, Goodwin ML, McDonald JR, Nijsten MWN (2011) Fuel for cancer cells? Cell Cycle 10(15):2422–2422. CrossRefGoogle Scholar
  141. Glancy B, Hartnell LM, Malide D, Yu Z-X, Combs CA, Connelly PS, Subramaniam S, Balaban RS (2015) Mitochondrial reticulum for cellular energy distribution in muscle. Nature 523(7562):617PubMedCrossRefGoogle Scholar
  142. Gnaiger E (2001) Bioenergetics at low oxygen: dependence of respiration and phosphorylation on oxygen and adenosine diphosphate supply. Respir Physiol 128(3):277–297PubMedCrossRefGoogle Scholar
  143. Gnaiger E, Kuznetsov AV (2002) Mitochondrial respiration at low levels of oxygen and cytochrome c. Biochem Soc Trans 30(2):252–258PubMedCrossRefGoogle Scholar
  144. Gnaiger E, Steinlechner-Maran R, Méndez G, Eberl T, Margreiter R (1995) Control of mitochondrial and cellular respiration by oxygen. J Bioenerg Biomembr 27(6):583–596PubMedCrossRefGoogle Scholar
  145. Gold M, Miller HI, Issekutz B, Spitzer JJ (1963) Effect of exercise and lactic acid infusion on individual free fatty acids of plasma. Am J Physiol 205(5):902–904PubMedGoogle Scholar
  146. Gollnick PD, Hermansen L (1973) Biochemical adaptations to exercise anaerobic metabolism. Exerc Sport Sci Rev 1(1):1–44PubMedCrossRefGoogle Scholar
  147. Gollnick PD, Bayly WM, Hodgson DR (1986) Exercise intensity, training, diet, and lactate concentration in muscle and blood. Med Sci Sports Exerc 18(3):334–340PubMedCrossRefGoogle Scholar
  148. Goodwin ML, Rothberg DL (2014) Lactate metabolism in trauma. J Trauma Acute Care Surg 77(1):182–183PubMedCrossRefGoogle Scholar
  149. Goodwin ML, Jin H, Straessler K, Smith-Fry K, Zhu J, Monument MJ, Grossmann AH, Randall RL, Capecchi MR, Jones KB (2014) Modeling alveolar soft part sarcomagenesis in the mouse: A role for lactate in the tumor microenvironment. Cancer Cell 26(6):851–862PubMedPubMedCentralCrossRefGoogle Scholar
  150. Goodwin ML, Gladden LB, Nijsten, MWN, Jones KB (2015) Lactate and Cancer: Revisiting the Warburg Effect in an Era of Lactate Shuttling. Front Nutr 1:27. PubMedPubMedCentralCrossRefGoogle Scholar
  151. Gore DC, Honeycutt D, Jahoor F, Barrow RE, Wolfe RR, Herndon DN (1991) Propranolol diminishes extremity blood flow in burned patients. Ann Surg 213(6):568–574PubMedPubMedCentralCrossRefGoogle Scholar
  152. Graham NA, Tahmasian M, Kohli B, Komisopoulou E, Zhu M, Vivanco I, Teitell MA, Wu H, Ribas A, Lo RS, Mellinghoff IK, Mischel PS, Graeber TG (2012) Glucose deprivation activates a metabolic and signaling amplification loop leading to cell death. Mol Syst Biol 8:589. PubMedPubMedCentralCrossRefGoogle Scholar
  153. Granchi C, Bertini S, Macchia M, Minutolo F (2010) Inhibitors of lactate dehydrogenase isoforms and their therapeutic potentials. Curr Med Chem 17(7):672–697PubMedCrossRefGoogle Scholar
  154. Green HJ, Hughson RL, Orr GW, Ranney DA (1983) Anaerobic threshold, blood lactate, and muscle metabolites in progressive exercise. J Appl Physiol 54(4):1032–1038PubMedCrossRefGoogle Scholar
  155. Green HJ, Halestrap A, Mockett C, O’Toole D, Grant S, Ouyang J (2002) Increases in muscle MCT are associated with reductions in muscle lactate after a single exercise session in humans. Am J Physiol Endocrinol Metab 282(1):E154–E160PubMedCrossRefGoogle Scholar
  156. Green HJ, Duhamel TA, Holloway GP, Moule JW, Ranney DW, Tupling AR, Ouyang J (2008) Rapid upregulation of GLUT-4 and MCT-4 expression during 16 h of heavy intermittent cycle exercise. Am J Physiol Regul Integr Comp Physiol 294(2):R594–R600CrossRefGoogle Scholar
  157. Grimaux E (1890) Une lettre inédite de Scheele à Lavoisier [An unpublished letter from Scheele to Lavoisier]. Revue générale des sciences pures et appliqués, vol 1, pp 1–2Google Scholar
  158. Halestrap AP (1976) Transport of pyruvate and lactate into human erythrocytes. Evidence for the involvement of the chloride carrier and a chloride-independent carrier. Biochem J 156(2):193–207PubMedPubMedCentralCrossRefGoogle Scholar
  159. Halestrap AP (2012) The monocarboxylate transporter family—structure and functional characterization. IUBMB Life 64(1):1–9PubMedCrossRefGoogle Scholar
  160. Halestrap AP (2013) Monocarboxylic acid transport. Compr Physiol 3:1611–1643PubMedCrossRefGoogle Scholar
  161. Halestrap AP, Denton RM (1974) Specific inhibition of pyruvate transport in rat liver mitochondria and human erythrocytes by α-cyano-4-hydroxycinnamate. Biochem J 138(2):313–316PubMedPubMedCentralCrossRefGoogle Scholar
  162. Halestrap AP, Meredith D (2004) The SLC16 gene family—from monocarboxylate transporters (MCTs) to aromatic amino acid transporters and beyond. Pflügers Archiv 447(5):619–628PubMedCrossRefGoogle Scholar
  163. Halestrap AP, Wilson MC (2012) The monocarboxylate transporter family—role and regulation. IUBMB Life 64(2):101–109CrossRefGoogle Scholar
  164. Hamann JJ, Kelley KM, Gladden LB (2001) Effect of epinephrine on net lactate uptake by contracting skeletal muscle. J Appl Physiol 91(6):2635–2641PubMedCrossRefGoogle Scholar
  165. Hamann S, Kiilgaard JF, la Cour M, Prause JU, Zeuthen T (2003) Cotransport of H+, lactate, and H2O in porcine retinal pigment epithelial cells. Exp Eye Res 76(4):493–504PubMedCrossRefGoogle Scholar
  166. Hanahan D, Weinberg Robert A (2011) Hallmarks of cancer: the next generation. Cell 144(5):646–674. PubMedCrossRefGoogle Scholar
  167. Harrison TR, Pilcher C (1930a) Studies in congestive heart failure: I. The effect of edema on oxygen utilization. J Clin Invest 8(2):259–290PubMedPubMedCentralCrossRefGoogle Scholar
  168. Harrison TR, Pilcher C (1930b) Studies in congestive heart failure: II. The respiratory exchange during and after exercise. J Clin Invest 8(3):291–315PubMedPubMedCentralCrossRefGoogle Scholar
  169. Hasegawa H, Fukushima T, Lee J-A, Tsukamoto K, Moriya K, Ono Y, Imai K (2003) Determination of serum d-lactic and l-lactic acids in normal subjects and diabetic patients by column-switching HPLC with pre-column fluorescence derivatization. Anal Bioanal Chem 377(5):886–891PubMedCrossRefGoogle Scholar
  170. Haseler LJ, Richardson RS, Videen JS, Hogan MC (1998) Phosphocreatine hydrolysis during submaximal exercise: the effect of FIO2. J Appl Physiol 85(4):1457–1463PubMedCrossRefGoogle Scholar
  171. Hashimoto T, Brooks GA (2008) Mitochondrial lactate oxidation complex and an adaptive role for lactate production. Med Sci Sports Exerc 40(3):486–494PubMedCrossRefGoogle Scholar
  172. Hashimoto T, Hussien R, Brooks G (2006) Colocalization of MCT1, CD147, and LDH in mitochondrial inner membrane of L6 muscle cells: evidence of a mitochondrial lactate oxidation complex. Am J Physiol Endocrinol Metab 290(6):E1237–E1244. PubMedCrossRefGoogle Scholar
  173. Hashimoto T, Hussien R, Oommen S, Gohil K, Brooks GA (2007) Lactate sensitive transcription factor network in L6 cells: activation of MCT1 and mitochondrial biogenesis. FASEB J 21(10):2602–2612PubMedCrossRefGoogle Scholar
  174. Hashimoto T, Hussien R, Cho H-S, Kaufer D, Brooks GA (2008) Evidence for the mitochondrial lactate oxidation complex in rat neurons: demonstration of an essential component of brain lactate shuttles. PLoS One 3(8):e2915PubMedPubMedCentralCrossRefGoogle Scholar
  175. Hashimoto T, Tsukamoto H, Takenaka S, Olesen ND, Petersen LG, Sørensen H, Nielsen HB, Secher NH, Ogoh S (2017) Maintained exercise-enhanced brain executive function related to cerebral lactate metabolism in men. FASEB J. Google Scholar
  176. Heck H, Mader A, Hess G, Mücke S, Müller R, Hollmann W (1985) Justification of the 4-mmol/l lactate threshold. Int J Sports Med 6(3):117–130PubMedCrossRefGoogle Scholar
  177. Heino A, Hartikainen J, Merasto ME, Koski EMJ, Alhava E, Takala J (1997) Systemic and regional effects of experimental gradual splanchnic ischemia. J Crit Care 12(2):92–98PubMedCrossRefGoogle Scholar
  178. Helmholtz HV (1845) Ueber den Stoffverbrauch bei der Muskelaktion. Arch Anat Physiol (72):72–83Google Scholar
  179. Herbst E, George M, Brebner K, Holloway G, Kane D (2017) Lactate is oxidized outside of the mitochondrial matrix in rodent brain. Appl Physiol Nutr Metab. PubMedGoogle Scholar
  180. Hill AV, Kupalov P (1929) Anaerobic and aerobic activity in isolated muscle. Proc Roy Soc London Series B 105(737):313–322CrossRefGoogle Scholar
  181. Hill AV, Long CNH, Lupton H (1924) Muscular exercise, lactic acid, and the supply and utilisation of oxygen. Proc R Soc Lond Series B, Contain Papers Biol Character 97(681):84–138CrossRefGoogle Scholar
  182. Hochachka PW, Mommsen TP (1983) Protons and anaerobiosis. Science 219(4591):1391–1397PubMedCrossRefGoogle Scholar
  183. Hogan MC, Cox RH, Welch HG (1983) Lactate accumulation during incremental exercise with varied inspired oxygen fractions. J Appl Physiol 55(4):1134–1140PubMedCrossRefGoogle Scholar
  184. Hogan MC, Arthur PG, Bebout DE, Hochachka PW, Wagner PD (1992a) Role of O2 in regulating tissue respiration in dog muscle working in situ. J Appl Physiol 73(2):728–736PubMedCrossRefGoogle Scholar
  185. Hogan MC, Nioka S, Brechue WF, Chance B (1992b) A 31P-NMR study of tissue respiration in working dog muscle during reduced O2 delivery conditions. J Appl Physiol 73(4):1662–1670PubMedCrossRefGoogle Scholar
  186. Hogan MC, Gladden LB, Kurdak SS, Poole DC (1995) Increased [lactate] in working dog muscle reduces tension development independent of pH. Med Sci Sports Exerc 27(3):371–377PubMedCrossRefGoogle Scholar
  187. Hollmann W (1985) Historical remarks on the development of the aerobic-anaerobic threshold up to 1966. Int J Sports Med 6(03):109–116PubMedCrossRefGoogle Scholar
  188. Holmes EG (1930) Oxidations in central and peripheral nervous tissue. Biochem J 24:914–925PubMedPubMedCentralCrossRefGoogle Scholar
  189. Holmes BE, Holmes EG (1925a) Contributions to the study of brain metabolism. I. Carbohydrate metabolism. Preliminary paper. Biochem J 19:492–499PubMedPubMedCentralCrossRefGoogle Scholar
  190. Holmes EG, Holmes BE (1925b) Contributions to the study of brain metabolism. II. Carbohydrate metabolism. Biochem J 19:836–839PubMedPubMedCentralCrossRefGoogle Scholar
  191. Holmes EG, Holmes BE (1926) Contributions to the study of brain metabolism. III. Carbohydrate metabolism relationship of glycogen and lactic acid. Biochem J 20:1196–1203PubMedPubMedCentralCrossRefGoogle Scholar
  192. Holmes EG, Holmes BE (1927) Contributions to the study of brain metabolism. IV. Carbohydrate metabolism of the brain tissue of depancreatized cats. Biochem J 21:412–418PubMedPubMedCentralCrossRefGoogle Scholar
  193. Hoshino D, Hanawa T, TakAhashi Y, Masuda H, Kato M, Hatta H (2014) Chronic post-exercise lactate administration with endurance training increases glycogen concentration and monocarboxylate transporter 1 protein in mouse white muscle. J Nutr Sci Vitaminol 60(6):413–419PubMedCrossRefGoogle Scholar
  194. Huang X, Li X, Xie X, Ye F, Chen B, Song C, Tang H, Xie X (2016) High expressions of LDHA and AMPK as prognostic biomarkers for breast cancer. Breast 30:39–46. PubMedCrossRefGoogle Scholar
  195. Huckabee WE, Judson WE (1958) The role of anaerobic metabolism in the performance of mild muscular work. I. Relationship to oxygen consumption and cardiac output, and the effect of congestive heart failure. J Clin Invest 37(11):1577–1592PubMedPubMedCentralCrossRefGoogle Scholar
  196. Hui S, Ghergurovich JM, Morscher RJ, Jang C, Teng X, Lu W, Esparza LA, Reya T, Yanxiang GJ, White E (2017) Glucose feeds the TCA cycle via circulating lactate. Nature 551(7678):115–118PubMedCrossRefGoogle Scholar
  197. Hultman E, Bergström J, Anderson NM (1967) Breakdown and resynthesis of phosphorylcreatine and adenosine triphosphate in connection with muscular work in man. Scand J Clin Lab Invest 19(1):56–66PubMedCrossRefGoogle Scholar
  198. Ichai C, Payen JF, Orban JC, Quintard H, Roth H, Legrand R, Francony G, Leverve X (2013) Half-molar sodium lactate to prevent intracranial hypertensive episodes in severe traumatic brain-injured patients: a randomized controlled trial. Intensive Care Med 39(8):1413–1422. PubMedCrossRefGoogle Scholar
  199. Ichai C, Orban J-C, Fontaine E (2014) Sodium lactate for fluid resuscitation: the preferred solution for the coming decades? Crit Care 18(4):163. PubMedPubMedCentralCrossRefGoogle Scholar
  200. Ide K, Secher NH (2000) Cerebral blood flow and metabolism during exercise. Prog Neurobiol 61(4):397–414PubMedCrossRefGoogle Scholar
  201. Ide K, Horn A, Secher NH (1999) Cerebral metabolic response to submaximal exercise. J Appl Physiol 87(5):1604–1608PubMedCrossRefGoogle Scholar
  202. Ide K, Schmalbruch IK, Quistorff B, Horn A, Secher NH (2000) Lactate, glucose and O2 uptake in human brain during recovery from maximal exercise. J Physiol 522(1):159–164PubMedPubMedCentralCrossRefGoogle Scholar
  203. Irving MH (1968) The sympatho-adrenal factor in haemorrhagic shock. Ann R Coll Surg Engl 42(6):367–386PubMedPubMedCentralGoogle Scholar
  204. Ivy JL, Withers RT, Van Handel PJ, Elger DH, Costill DL (1980) Muscle respiratory capacity and fiber type as determinants of the lactate threshold. J Appl Physiol 48(3):523–527PubMedCrossRefGoogle Scholar
  205. Jacobs RA, Meinild A-K, Nordsborg NB, Lundby C (2013) Lactate oxidation in human skeletal muscle mitochondria. Am J Physiol Endocrinol Metab 304(7):E686–E694. PubMedCrossRefGoogle Scholar
  206. Jadvar H, Alavi A, Gambhir SS (2009) 18F-FDG uptake in lung, breast, and colon cancers: molecular biology correlates and disease characterization. J Nucl Med 50(11):1820–1827PubMedPubMedCentralCrossRefGoogle Scholar
  207. James JH, Fang C-H, Schrantz SJ, Hasselgren P-O, Paul RJ, Fischer JE (1996) Linkage of aerobic glycolysis to sodium-potassium transport in rat skeletal muscle. Implications for increased muscle lactate production in sepsis. J Clin Invest 98(10):2388–2397PubMedPubMedCentralCrossRefGoogle Scholar
  208. James JH, Luchette FA, McCarter FD, Fischer JE (1999a) Lactate is an unreliable indicator of tissue hypoxia in injury or sepsis. Lancet 354(9177):505–508PubMedCrossRefGoogle Scholar
  209. James JH, Wagner KR, King J-K, Leffler RE, Upputuri RK, Balasubramaniam A, Friend LA, Shelly DA, Paul RJ, Fischer JE (1999b) Stimulation of both aerobic glycolysis and Na+-K+-ATPase activity in skeletal muscle by epinephrine or amylin. Am J Physiol Endocrinol Metab 277(1):E176–E186CrossRefGoogle Scholar
  210. Jansen TC, van Bommel J, Schoonderbeek FJ, Sleeswijk Visser SJ, van der Klooster JM, Lima AP, Willemsen SP, Bakker J (2010) Early lactate-guided therapy in intensive care unit patients: a multicenter, open-label, randomized controlled trial. Am J Respir Crit Care Med 182(6):752–761PubMedCrossRefGoogle Scholar
  211. Jervell O (1928) Investigation of the concentration of lactic acid in blood and urine under physiologic and pathologic conditions. Acta Med Scand Suppl XXIV:1–135Google Scholar
  212. Jöbsis FF, Stainsby WN (1968) Oxidation of NADH during contractions of circulated mammalian skeletal muscle. Respir Physiol 4(3):292–300PubMedCrossRefGoogle Scholar
  213. Jones NL (1980) Hydrogen ion balance during exercise. Clin Sci 59(2):85–91PubMedCrossRefGoogle Scholar
  214. Jones AM, Doust JH (1998) The validity of the lactate minimum test for determination of the maximal lactate steady state. Med Sci Sports Exerc 30(8):1304–1313PubMedCrossRefGoogle Scholar
  215. Jones RS, Morris ME (2016) Monocarboxylate Transporters: Therapeutic targets and prognostic factors in disease. Clin Pharmacol Ther 100(5):454–463PubMedPubMedCentralCrossRefGoogle Scholar
  216. Jones DP, Sies H (2015) The redox code. Antiox Redox Signal 23(9):734–746CrossRefGoogle Scholar
  217. Jørgensen BM, Rasmussen HN, Rasmussen UF (1985) Ubiquinone reduction pattern in pigeon heart mitochondria. Identification of three distinct ubiquinone pools. Biochem J 229(3):621–629. PubMedPubMedCentralCrossRefGoogle Scholar
  218. Juel C (2001) Current aspects of lactate exchange: lactate/H+ transport in human skeletal muscle. Eur J Appl Physiol 86(1):12–16PubMedCrossRefGoogle Scholar
  219. Juel C, Halestrap AP (1999) Lactate transport in skeletal muscle—role and regulation of the monocarboxylate transporter. J Physiol 517(3):633–642PubMedPubMedCentralCrossRefGoogle Scholar
  220. Juel C, Honig A, Pilegaard H (1991) Muscle lactate transport studied in sarcolemmal giant vesicles: dependence on fibre type and age. Acta Physiol 143(4):361–366CrossRefGoogle Scholar
  221. Kane DA (2014) Lactate oxidation at the mitochondria: a lactate-malate-aspartate shuttle at work. Front Neurosci 8:366. PubMedPubMedCentralCrossRefGoogle Scholar
  222. Karlsson J, Bonde-Petersen F, Henriksson J, Knuttgen HG (1975) Effects of previous exercise with arms or legs on metabolism and performance in exhaustive exercise. J Appl Physiol 38(5):763–767PubMedCrossRefGoogle Scholar
  223. Katz A, Sahlin K (1988) Regulation of lactic acid production during exercise. J Appl Physiol 65(2):509–518PubMedCrossRefGoogle Scholar
  224. Keir DA, Fontana FY, Robertson TC, Murias JM, Paterson DH, Kowalchuk JM, Pogliaghi S (2015) Exercise intensity thresholds: identifying the boundaries of sustainable performance. Med Sci Sports Exerc 47(9):1932–1940PubMedCrossRefGoogle Scholar
  225. Kelley KM, Hamann JJ, Navarre C, Gladden LB (2002) Lactate metabolism in resting and contracting canine skeletal muscle with elevated lactate concentration. J Appl Physiol 93(3):865–872PubMedCrossRefGoogle Scholar
  226. Kellum JA, Elbers PWG (eds) (2009) Stewart’s textbook of acid-base., AmsterdamGoogle Scholar
  227. Kennedy KM, Dewhirst MW (2010) Tumor metabolism of lactate: the influence and therapeutic potential for MCT and CD147 regulation. Future Oncol 6(1):127–148PubMedPubMedCentralCrossRefGoogle Scholar
  228. Kim J-W, Tchernyshyov I, Semenza GL, Dang CV (2006) HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab 3(3):177–185PubMedCrossRefGoogle Scholar
  229. Kindermann W, Simon G, Keul J (1979) The significance of the aerobic-anaerobic transition for the determination of work load intensities during endurance training. Eur J Appl Physiol Occup Physiol 42(1):25–34PubMedCrossRefGoogle Scholar
  230. Kitaoka Y, Takeda K, Tamura Y, Hatta H (2016) Lactate administration increases mRNA expression of PGC-1α and UCP3 in mouse skeletal muscle. Appl Physiol Nutr Metab 41(6):695–698PubMedCrossRefGoogle Scholar
  231. Klausen K, Knuttgen HG, Forster HV (1972) Effect of pre-existing high blood lactate concentration on maximal exercise performance. Scand J Clin Lab Invest 30(4):415–419PubMedCrossRefGoogle Scholar
  232. Kline JA, Thornton LR, Lopaschuk GD, Barbee WR, Watts JA (2000) Lactate improves cardiac efficiency after hemorrhagic shock. Shock 14(2):215–221PubMedCrossRefGoogle Scholar
  233. Knuth ST, Dave H, Peters JR, Fitts RH (2006) Low cell pH depresses peak power in rat skeletal muscle fibres at both 30 C and 15 C: implications for muscle fatigue. J Physiol 575(3):887–899PubMedPubMedCentralCrossRefGoogle Scholar
  234. Kompanje E, Jansen T, van der Hoven B, Bakker J (2007) The first demonstration of lactic acid in human blood in shock by Johann Joseph Scherer (1814–1869) in January 1843. Intensive Care Med 33(11):1967–1971PubMedPubMedCentralCrossRefGoogle Scholar
  235. Krebs HA (1972) The Pasteur effect and the relations between respiration and fermentation. Essays Biochem 8:1–34PubMedGoogle Scholar
  236. Kuei C, Yu J, Zhu J, Wu J, Zhang L, Shih A, Mirzadegan T, Lovenberg T, Liu C (2011) Study of GPR81, the lactate receptor, from distant species identifies residues and motifs critical for GPR81 functions. Mol Pharmacol 80(5):848–858PubMedCrossRefGoogle Scholar
  237. Kunkel M, Reichert TE, Benz P, Lehr HA, Jeong JH, Wieand S, Bartenstein P, Wagner W, Whiteside TL (2003) Overexpression of Glut-1 and increased glucose metabolism in tumors are associated with a poor prognosis in patients with oral squamous cell carcinoma. Cancer 97(4):1015–1024PubMedCrossRefGoogle Scholar
  238. Kushmerick J (1983) Energetics of muscle contraction. In: Peachey LD (ed) Handbook of physiology, skeletal muscle. American Physiological Society, Bethesda, MD, pp 189–236Google Scholar
  239. Lamb GD, Stephenson DG (2006) Point: Lactic acid accumulation is an advantage during muscle activity. J Appl Physiol 100(4):1410–1412PubMedCrossRefGoogle Scholar
  240. Lambeth MJ, Kushmerick MJ (2002) A computational model for glycogenolysis in skeletal muscle. Ann Biomed Eng 30(6):808–827PubMedCrossRefGoogle Scholar
  241. Lauritzen KH, Morland C, Puchades M, Holm-Hansen S, Hagelin EM, Lauritzen F, Attramadal H, Storm-Mathisen J, Gjedde A, Bergersen LH (2013) Lactate receptor sites link neurotransmission, neurovascular coupling, and brain energy metabolism. Cereb Cortex 24(10):2784–2795PubMedCrossRefGoogle Scholar
  242. Lauritzen KH, Morland C, Puchades M, Holm-Hansen S, Hagelin EM, Lauritzen F, Attramadal H, Storm-Mathisen J, Gjedde A, Bergersen LH (2014) Lactate receptor sites link neurotransmission, neurovascular coupling, and brain energy metabolism. Cereb Cortex 24(10):2784–2795. PubMedCrossRefGoogle Scholar
  243. Lavoisier A-L (1789) Traité élémentaire de chimie. Chez Cuchet, ParisGoogle Scholar
  244. Lehninger AL (1951) Phosphorylation coupled to oxidation of dihydrodiphosphopyridine nucleotide. J Biol Chem 190(1):345–359PubMedGoogle Scholar
  245. Leite TC, Da Silva D, Coelho RG, Zancan P, Sola-Penna M (2007) Lactate favours the dissociation of skeletal muscle 6-phosphofructo-1-kinase tetramers down-regulating the enzyme and muscle glycolysis. Biochem J 408(1):123–130CrossRefGoogle Scholar
  246. Leite TC, Coelho RG, Da Silva D, Coelho WS, Marinho-Carvalho MM, Sola-Penna M (2011) Lactate downregulates the glycolytic enzymes hexokinase and phosphofructokinase in diverse tissues from mice. FEBS Lett 585(1):92–98PubMedCrossRefGoogle Scholar
  247. Lemire J, Mailloux RJ, Appanna VD (2008) Mitochondrial lactate dehydrogenase is involved in oxidative-energy metabolism in human astrocytoma cells (CCF-STTG1). PLoS ONE, 3(2):e1550. PubMedPubMedCentralCrossRefGoogle Scholar
  248. Levinovitz AW, Ringertz N (2001) The nobel prize: the first 100 Years. Imperial College Press, LondonCrossRefGoogle Scholar
  249. Li S, Kim E, Bonanno JA (2016) Fluid transport by the cornea endothelium is dependent on buffering lactic acid efflux. Am J Physiol Cell Physiol 311(1):C116–C126CrossRefGoogle Scholar
  250. Liang X, Liu L, Fu T, Zhou Q, Zhou D, Xiao L, Liu J, Kong Y, Xie H, Yi F (2016) Exercise inducible lactate dehydrogenase B regulates mitochondrial function in skeletal muscle. J Biol Chem 291(49):25306–25318PubMedPubMedCentralCrossRefGoogle Scholar
  251. Liddell MJ, Daniel AM, MacLean LD, Shizgal HM (1979) The role of stress hormones in the catabolic metabolism of shock. Surg Gynecol Obstet 149(6):822–830PubMedGoogle Scholar
  252. Lindinger MI, Spriet LL, Hultman E, Putman T, McKelvie RS, Lands LC, Jones NL, Heigenhauser GJ (1994) Plasma volume and ion regulation during exercise after low- and high-carbohydrate diets. Am J Physiol 266(6 Pt 2):R1896–R1906PubMedGoogle Scholar
  253. Lindinger M, Heigenhauser G (2008a) Counterpoint: lactic acid is not the only physicochemical contributor to the acidosis of exercise-Rebuttal. J Appl Physiol 105(1):359–361PubMedCrossRefGoogle Scholar
  254. Lindinger M, Heigenhauser G (2008b) Counterpoint: lactic acid is not the only physicochemical contributor to the acidosis of exercise. Rebuttal J Appl Physiol 105(1):361–362Google Scholar
  255. Lindinger MI, Leung M, Trajcevski KE, Hawke TJ (2011) Volume regulation in mammalian skeletal muscle: the role of sodium-potassium-chloride cotransporters during exposure to hypertonic solutions. J Physiol 589(Pt 11):2887–2899PubMedPubMedCentralCrossRefGoogle Scholar
  256. Lindinger MI, Leung MJ, Hawke TJ (2013) Inward flux of lactate- through monocarboxylate transporters contributes to regulatory volume increase in mouse muscle fibers. PLoS ONE 8(12):e84451. PubMedPubMedCentralCrossRefGoogle Scholar
  257. Liu C, Wu J, Zhu J, Kuei C, Yu J, Shelton J, Sutton SW, Li X, Su JY, Mirzadegan T, Mazur C, Kamme F, Lovenberg TW (2009) Lactate inhibits lipolysis in fat cells through activation of an orphan G-protein-coupled receptor, GPR81. J Biol Chem 284(5):2811–2822. PubMedCrossRefGoogle Scholar
  258. Lockwood LB, Yoder DE, Zienty M (1965) Lactic acid. Ann N Y Acad Sci 119(1):854–867PubMedGoogle Scholar
  259. Lopaschuk GD, Ussher JR, Folmes CDL, Jaswal JS, Stanley WC (2010) Myocardial fatty acid metabolism in health and disease. Physiol Rev 90(1):207–258PubMedCrossRefGoogle Scholar
  260. Luchette FA, Jenkins WA, Friend LA, Su C, Fischer JE, James JH (2002) Hypoxia is not the sole cause of lactate production during shock. J Trauma Acute Care Surg 52(3):415–419CrossRefGoogle Scholar
  261. Lundberg GD (2011) Medical Publishing for an N of One-New technologies and mind-sets required for information delivery in the age of genomics. Scientist 25(4):31Google Scholar
  262. Lundgren A (2014) Carl Wilhelm Scheele. Encyclopaedia Britannica, Inc. Accessed 2 Aug 2017
  263. Lundin G, Ström G (1947) The concentration of blood lactic acid in man during muscular work in relation to the partial pressure of oxygen of the inspired air. Acta Physiol 13(3):253–266CrossRefGoogle Scholar
  264. Lunt SY, Vander Heiden MG (2011) Aerobic glycolysis: meeting the metabolic requirements of cell proliferation. Annu Rev Cell Dev Biol 27(1):441–464. PubMedCrossRefGoogle Scholar
  265. Lytovchenko O, Kunji ERS (2017) Expression and putative role of mitochondrial transport proteins in cancer. Biochim Biophys Acta Bioenerg 1858(8):641–654. CrossRefGoogle Scholar
  266. Mack GW (2012) The body fluid and hemopoietic systems. In: Farrell PA, Joyner MJ, Caiozzo VJ (eds) ACSM’s advanced exercise physiology, 2nd edition. Lippincott Williams & Wilkins, New York, pp 535–536Google Scholar
  267. Magistretti PJ, Pellerin L (1996) Cellular bases of brain energy metabolism and their relevance to functional brain imaging: evidence for a prominent role of astrocytes. Cereb Cortex 6(1):50–61PubMedCrossRefGoogle Scholar
  268. Marcinek DJ, Kushmerick MJ, Conley KE (2010) Lactic acidosis in vivo: testing the link between lactate generation and H + accumulation in ischemic mouse muscle. J Appl Physiol 108(6):1479–1486PubMedPubMedCentralCrossRefGoogle Scholar
  269. Martinez-Outschoorn UE, Peiris-Pages M, Pestell RG, Sotgia F, Lisanti MP (2017) Cancer metabolism: a therapeutic perspective. Nat Rev Clin Oncol 14(1):11–31. PubMedCrossRefGoogle Scholar
  270. Martin-Requero A, Ayuso MS, Parilla R (1986) Rate-limiting steps for hepatic gluconeogenesis. Mechanisms of oxamate inhibition of mitochondrial pyruvate metabolism. J Biol Chem 261(30):13973–13978PubMedGoogle Scholar
  271. Mason S (2017) Lactate shuttles in neuroenergetics—homeostasis, allostasis and beyond. Front Neurosci 11:43PubMedPubMedCentralGoogle Scholar
  272. Mazzeo RS, Reeves JT (2003) Adrenergic contribution during acclimatization to high altitude: perspectives from Pikes Peak. Exerc Sport Sci Rev 31(1):13–18PubMedCrossRefGoogle Scholar
  273. Mazzeo RS, Brooks GA, Schoeller DA, Budinger TF (1986) Disposal of blood [1–13C] lactate in humans during rest and exercise. J Appl Physiol 60(1):232–241PubMedCrossRefGoogle Scholar
  274. Mazzeo RS, Bender PR, Brooks GA, Butterfield GE, Groves BM, Sutton JR, Wolfel EE, Reeves JT (1991) Arterial catecholamine responses during exercise with acute and chronic high-altitude exposure. Am J Physiol Endocrinol Metab 261(4):E419–E424CrossRefGoogle Scholar
  275. Merezhinskaya N, Fishbein WN (2009) Monocarboxylate transporters: Past, present, and future. Histol Histopathol 24(2):243–264PubMedGoogle Scholar
  276. Meyerhof O (1930a) Die chemischen Vorgänge im Zusammenhang mit der Wärmebildung. Die chemischen Vorgänge im Muskel und ihr Zusammenhang mit Arbeitsleistung und Wärmebildung. Springer, Berlin, HeidelbergCrossRefGoogle Scholar
  277. Meyerhof O (1930b) The chemistry of muscular contraction. Lancet 216(5600):1415–1422CrossRefGoogle Scholar
  278. Meyerhof O (1942) Intermediary carbohydrate metabolism. In: A symposium on respiratory enzymes. The University of Wisconsin Press, Madison, pp 3–15Google Scholar
  279. Miller BF, Fattor Ja J, Ka H, Ma Navazio F, Lindinger MI, Brooks Ga (2002a) Lactate and glucose interactions during rest and exercise in men: effect of exogenous lactate infusion. J Physiol 544 (3):963–975. PubMedPubMedCentralCrossRefGoogle Scholar
  280. Miller BF, Fattor JA, Jacobs KA, Horning MA, Suh S-H, Navazio F, Brooks GA (2002b) Metabolic and cardiorespiratory responses to “the lactate clamp”. Am J Physiol Endocrinol Metab 283(5):E889–E898PubMedCrossRefGoogle Scholar
  281. Mobasheri A, Richardson S, Mobasheri R, Shakibaei M, Hoyland JA (2005) Hypoxia inducible factor-1 and facilitative glucose transporters GLUT1 and GLUT3: putative molecular components of the oxygen and glucose sensing apparatus in articular chondrocytes. Histol Histopathol 20(4):1327–1338PubMedGoogle Scholar
  282. Molé PA, Chung Y, Tran TK, Sailasuta N, Hurd R, Jue T (1999) Myoglobin desaturation with exercise intensity in human gastrocnemius muscle. Am J Physiol Regul Integr Comp Physiol 277(1):R173–R180CrossRefGoogle Scholar
  283. Moreno-Sánchez R, Rodríguez-Enríquez S, Marín-Hernández A, Saavedra E (2007) Energy metabolism in tumor cells. FEBS J 274(6):1393–1418PubMedCrossRefGoogle Scholar
  284. Morland C, Lauritzen KH, Puchades M, Holm-Hansen S, Andersson K, Gjedde A, Attramadal H, Storm-Mathisen J, Bergersen LH (2015) The lactate receptor, G-protein-coupled receptor 81/hydroxycarboxylic acid receptor 1: Expression and action in brain. J Neurosci Res 93(7):1045–1055PubMedCrossRefGoogle Scholar
  285. Mosler F, Körner W (1862) Zur Blut- und Harnanalyse bei Leukämie. Virchows Arch 25(1):142–150. CrossRefGoogle Scholar
  286. Murray B, Wilson DJ (2001) A study of metabolites as intermediate effectors in angiogenesis. Angiogenesis 4(1):71–77PubMedCrossRefGoogle Scholar
  287. Nalbandian M, Takeda M (2016) Lactate as a signaling molecule that regulates exercise-induced adaptations. Biology 5(4):38. PubMedCentralCrossRefGoogle Scholar
  288. Nalos M, Leverve XM, Huang SJ, Weisbrodt L, Parkin R, Seppelt IM, Ting I, McLean AS (2014) Half-molar sodium lactate infusion improves cardiac performance in acute heart failure: a pilot randomised controlled clinical trial. Crit Care 18(2):R48. PubMedPubMedCentralCrossRefGoogle Scholar
  289. Nasse OJF (1877) Bemerkungen zur Physiologie der Kohlehydrate. Pflügers Archiv Euro J Physiol 14(1):473–484CrossRefGoogle Scholar
  290. Nasse OJF (1879) Chemie und Stoffwechsel der Muskeln, vol 1. In: [Hermann’s] Handbuch der Physiologie. Der Bewegungsapparate, FCW Vogel, LeipzigGoogle Scholar
  291. Needham DM (1971) Machina carnis: the biochemistry of muscular contraction in its historical development. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  292. Nelson CR, Debold EP, Fitts RH (2014) Phosphate and acidosis act synergistically to depress peak power in rat muscle fibers. Am J Physiol Cell Physiol 307(10):C939–C950CrossRefGoogle Scholar
  293. Nichol AD, Egi M, Pettila V, Bellomo R, French C, Hart G, Davies A, Stachowski E, Reade MC, Bailey M (2010) Relative hyperlactatemia and hospital mortality in critically ill patients: a retrospective multi-centre study. Crit Care 14(1):R25. PubMedPubMedCentralCrossRefGoogle Scholar
  294. Nicholls DG, Ferguson SJ (2013) Bioenergetics. 4th edn. Academic Press, LondonGoogle Scholar
  295. Nicholson RM, Sleivert GG (2001) Indices of lactate threshold and their relationship with 10-km running velocity. Med Sci Sports Exerc 33(2):339–342PubMedCrossRefGoogle Scholar
  296. Nielsen OB, Paoli F, Overgaard K (2001) Protective effects of lactic acid on force production in rat skeletal muscle. J Physiol 536(1):161–166PubMedPubMedCentralCrossRefGoogle Scholar
  297. Nielsen HB, Clemmesen JO, Skak C, Ott P, Secher NH (2002) Attenuated hepatosplanchnic uptake of lactate during intense exercise in humans. J Appl Physiol 92(4):1677–1683PubMedCrossRefGoogle Scholar
  298. Nijsten MWN, van Dam GM (2009) Hypothesis: using the Warburg effect against cancer by reducing glucose and providing lactate. Med Hypotheses 73(1):48–51PubMedCrossRefGoogle Scholar
  299. Nohl H (1987) Demonstration of the existence of an organo-specific NADH dehydrogenase in heart mitochondria. Eur J Biochem 169(3):585–591. PubMedCrossRefGoogle Scholar
  300. Odom SR, Howell MD, Silva GS, Nielsen VM, Gupta A, Shapiro NI, Talmor D (2013) Lactate clearance as a predictor of mortality in trauma patients. J Trauma Acute Care Surg 74(4):999–1004PubMedCrossRefGoogle Scholar
  301. Okubo Y, Iino M (2011) Visualization of glutamate as a volume transmitter. J Physiol 589(3):481–488PubMedCrossRefGoogle Scholar
  302. Oldenbeuving G, McDonald JR, Goodwin ML, Sayilir R, Reijngoud DJ, Gladden LB, Nijsten MWN (2014) A patient with acute liver failure and extreme hypoglycaemia with lactic acidosis who was not in coma: causes and consequences of lactate-protected hypoglycaemia. Anaesth Intensive Care 42(4):507–511PubMedGoogle Scholar
  303. Otto AM (2016) Warburg effect(s)—a biographical sketch of Otto Warburg and his impacts on tumor metabolism. Cancer Metab 4(1):5. PubMedPubMedCentralCrossRefGoogle Scholar
  304. Owles WH (1930) Alterations in the lactic acid content of the blood as a result of light exercise and associated changes in the CO2-combining power of the blood and in the alveolar CO2 pressure. J Physiol 69(2):214–237PubMedPubMedCentralCrossRefGoogle Scholar
  305. Paddle BM (1985) A cytoplasmic component of pyridine nucleotide fluorescence in rat diaphragm: evidence from comparisons with flavoprotein fluorescence. Pflügers Archiv 404(4):326–331PubMedCrossRefGoogle Scholar
  306. Pagliassotti MJ, Donovan CM (1990) Role of cell type in net lactate removal by skeletal muscle. Am J Physiol Endocrinol Metab 258(4):E635–E642CrossRefGoogle Scholar
  307. Parolin ML, Chesley A, Matsos MP, Spriet LL, Jones NL, Heigenhauser GJF (1999) Regulation of skeletal muscle glycogen phosphorylase and PDH during maximal intermittent exercise. Am J Physiol Endocrinol Metab 277(5):E890–E900CrossRefGoogle Scholar
  308. Parsikia A, Bones K, Kaplan M, Strain J, Leung PS, Ortiz J, Joshi ART (2014) The predictive value of initial serum lactate in trauma patients. Shock 42(3):199–204PubMedCrossRefGoogle Scholar
  309. Passarella S, de Bari L, Valenti D, Pizzuto R, Paventi G, Atlante A (2008) Mitochondria and l-lactate metabolism. FEBS Lett 582(25–26):3569–3576. PubMedCrossRefGoogle Scholar
  310. Passarella S, Paventi G, Pizzuto R (2014) The mitochondrial l-lactate dehydrogenase affair. Front Neurosci 8:407. PubMedPubMedCentralCrossRefGoogle Scholar
  311. Pasteur L (1861) Expériences et vues nouvelles sur la nature des fermentations. Comptes Rendus Hebdomadaires des Séances de l’Académie des Sciences, Paris 53:1260–1264Google Scholar
  312. Paventi G, Pizzuto R, Passarella S (2017) The occurance of l-lactate dehydrogenase in the inner mitochondrial compartment of pig liver. Biochem Biophys Res Commun 489:255–261PubMedCrossRefGoogle Scholar
  313. Pavlides S, Whitaker-Menezes D, Castello-Cros R, Flomenberg N, Witkiewicz AK, Frank PG, Casimiro MC, Wang C, Fortina P, Addya S, Pestell RG, Martinez-Outschoorn UE, Sotgia F, Lisanti MP (2009) The reverse Warburg effect: Aerobic glycolysis in cancer associated fibroblasts and the tumor stroma. Cell Cycle 8(23):3984–4001. PubMedCrossRefGoogle Scholar
  314. Pedersen PK, Sj G, Juel C (2001) Plasma acid-base status and hyperventilation during cycling at MAXLASS in low and high lactate responders. Med Sci Sports Exerc 33(5):S314CrossRefGoogle Scholar
  315. Pedersen TH, Nielsen OB, Lamb GD, Stephenson DG (2004) Intracellular acidosis enhances the excitability of working muscle. Science 305(5687):1144–1147PubMedCrossRefGoogle Scholar
  316. Pellerin L (2003) Lactate as a pivotal element in neuron–glia metabolic cooperation. Neurochem 43(4):331–338CrossRefGoogle Scholar
  317. Pellerin L (2010) Food for thought: the importance of glucose and other energy substrates for sustaining brain function under varying levels of activity. Diabetes Metab 36:S59–S63CrossRefGoogle Scholar
  318. Pellerin L, Magistretti PJ (1994) Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization. Proc Natl Acad Sci 91(22):10625–10629PubMedPubMedCentralCrossRefGoogle Scholar
  319. Pellerin L, Magistretti PJ (2003) How to balance the brain energy budget while spending glucose differently. J Physiol 546(2):325–325PubMedPubMedCentralCrossRefGoogle Scholar
  320. Pellerin L, Magistretti PJ (2011) Sweet sixteen for ANLS. J Cereb Blood Flow Metab 32(7):1152–1166PubMedPubMedCentralCrossRefGoogle Scholar
  321. Pellerin L, Pellegri G, Bittar PG, Charnay Y, Bouras C, Martin JL, Stella N, Magistretti PJ (1998) Evidence supporting the existence of an activity-dependent astrocyte-neuron lactate shuttle. Dev Neurosci 20(4–5):291–299PubMedCrossRefGoogle Scholar
  322. Pértega-Gomes N, Vizcaíno JR, Miranda-Gonçalves V, Pinheiro C, Silva J, Pereira H, Monteiro P, Henrique RM, Reis RM, Lopes C, Baltazar F (2011) Monocarboxylate transporter 4 (MCT4) and CD147 overexpression is associated with poor prognosis in prostate cancer. BMC Cancer 11(1):312. PubMedPubMedCentralCrossRefGoogle Scholar
  323. Philp NJ, Yoon H, Lombardi L (2001) Mouse MCT3 gene is expressed preferentially in retinal pigment and choroid plexus epithelia. Am J Physiol Cell Physiol 280(5):C1319–C1326CrossRefGoogle Scholar
  324. Pizzuto R, Paventi G, Porcile C, Sarnataro D, Daniele A, Passarella S (2012) l-Lactate metabolism in HEP G2 cell mitochondria due to the l-lactate dehydrogenase determines the occurrence of the lactate/pyruvate shuttle and the appearance of oxaloacetate, malate and citrate outside mitochondria. Biochim Biophys Acta Bioenerg 1817(9):1679–1690CrossRefGoogle Scholar
  325. Plato PA, McNulty M, Crunk SM, Ergun AT (2008) Predicting lactate threshold using ventilatory threshold. Int J Sports Med 29(09):732–737PubMedCrossRefGoogle Scholar
  326. Pölönen P, Ruokonen E, Hippeläinen M, Pöyhönen M, Takala J (2000) A prospective, randomized study of goal-oriented hemodynamic therapy in cardiac surgical patients. Anesth Analg 90(5):1052–1059PubMedCrossRefGoogle Scholar
  327. Ponsot E, Zoll J, N’Guessan B, Ribera F, Lampert E, Richard R, Veksler V, Ventura-Clapier R, Mettauer B (2005) Mitochondrial tissue specificity of substrates utilization in rat cardiac and skeletal muscles. J Cell Physiol 203(3):479–486. PubMedCrossRefGoogle Scholar
  328. Poole RC, Halestrap AP (1992) Identification and partial purification of the erythrocyte l-lactate transporter. Biochem J 283(3):855–862PubMedPubMedCentralCrossRefGoogle Scholar
  329. Poole RC, Halestrap AP (1993) Transport of lactate and other monocarboxylates across mammalian plasma membranes. Am J Physiol Cell Physiol 264(4):C761–C782CrossRefGoogle Scholar
  330. Poole DC, Gladden LB, Kurdak S, Hogan MC (1994) l-(+)-lactate infusion into working dog gastrocnemius: no evidence lactate per se mediates V̇O2 slow component. J Appl Physiol 76(2):787–792PubMedCrossRefGoogle Scholar
  331. Posterino GS, Dutka TL, Lamb GD (2001) L (+)-lactate does not affect twitch and tetanic responses in mechanically skinned mammalian muscle fibres. Pflügers Arch 442(2):197–203PubMedCrossRefGoogle Scholar
  332. Potter VR (1958) The biochemical approach to the cancer problem. Fed Proc 17(2):691–697PubMedGoogle Scholar
  333. Potter M, Newport E, Morten KJ (2016) The Warburg effect: 80 years on. Biochem Soc Trans 44(5):1499–1505PubMedPubMedCentralCrossRefGoogle Scholar
  334. Prebble JN (2010) The discovery of oxidative phosphorylation: a conceptual off-shoot from the study of glycolysis. Stud Hist Philos Biol Biomed Sci 41(3):253–262PubMedCrossRefGoogle Scholar
  335. Pringle JS, Jones AM (2002) Maximal lactate steady state, critical power and EMG during cycling. Eur J Appl Physiol 88(3):214–226. PubMedCrossRefGoogle Scholar
  336. ProCESS (2014) A randomized trial of protocol-based care for early septic shock. N Engl J Med 2014(370):1683–1693Google Scholar
  337. Proia P, Di Liegro CM, Schiera G, Fricano A, Di Liegro I (2016) Lactate as a Metabolite and a Regulator in the Central Nervous System. Int J Mol Sci 17(9):1450–1470PubMedCentralCrossRefGoogle Scholar
  338. Quintard H, Patet C, Zerlauth J-B, Suys T, Bouzat P, Pellerin L, Meuli R, Magistretti PJ, Oddo M (2016) Improvement of neuroenergetics by hypertonic lactate therapy in patients with traumatic brain injury is dependent on baseline cerebral lactate/pyruvate ratio. J Neurotrauma 33(7):681–687PubMedPubMedCentralCrossRefGoogle Scholar
  339. Quistorff B, Secher NH, Van Lieshout JJ (2008) Lactate fuels the human brain during exercise. FASEB J 22(10):3443–3449PubMedCrossRefGoogle Scholar
  340. Racker E (1972) Bioenergetics and the problem of tumor growth: an understanding of the mechanism of the generation and control of biological energy may shed light on the problem of tumor growth. Am Sci 60(1):56–63PubMedGoogle Scholar
  341. Racker E (1974) History of the Pasteur effect and its pathobiology. Mol Cell Biochem 5(1–2):17–23PubMedCrossRefGoogle Scholar
  342. Rasmussen UF (1969) The oxidation of added NADH by intact heart mitochondria. FEBS Lett 2(3):157–162PubMedCrossRefGoogle Scholar
  343. Rasmussen UF, Rasmussen HN (1985) The NADH oxidase system (external) of muscle mitochondria and its role in the oxidation of cytoplasmic NADH. Biochem J 229(3):631–641PubMedPubMedCentralCrossRefGoogle Scholar
  344. Rasmussen UF, Krustrup P, Bangsbo J, Rasmussen HN (2001) The effect of high-intensity exhaustive exercise studied in isolated mitochondria from human skeletal muscle. Pflügers Archiv 443(2):180–187. PubMedCrossRefGoogle Scholar
  345. Rasmussen HN, van Hall G, Rasmussen UF (2002) Lactate dehydrogenase is not a mitochondrial enzyme in human and mouse vastus lateralis muscle. J Physiol 541(2):575–580. PubMedPubMedCentralCrossRefGoogle Scholar
  346. Rasmussen UF, Krustrup P, Kjaer M, Rasmussen HN (2003a) Human skeletal muscle mitochondrial metabolism in youth and senescence: no signs of functional changes in ATP formation and mitochondrial oxidative capacity. Pflügers Archiv 446:270–278PubMedCrossRefGoogle Scholar
  347. Rasmussen UF, Krustrup P, Kjær M, Rasmussen HN (2003b) Experimental evidence against the mitochondrial theory of aging. A study of isolated human skeletal muscle mitochondria. Exp Gerontol 38(8):877–886. PubMedCrossRefGoogle Scholar
  348. Rej R (1979) Measurement of aspartate aminotransferase activity: Effects of oxamate. Clin Chem 25(4):555–559PubMedGoogle Scholar
  349. Richardson R, Noyszewski E, Kendrick K, Leigh J, Wagner P (1995) Myoglobin O2 desaturation during exercise. Evidence of limited O2 transport. J Clin Invest 96(4):1916–1926PubMedPubMedCentralCrossRefGoogle Scholar
  350. Richardson RS, Noyszewski EA, Leigh JS, Wagner PD (1998) Lactate efflux from exercising human skeletal muscle: role of intracellular PO2. J Appl Physiol 85(2):627–634PubMedCrossRefGoogle Scholar
  351. Richardson RS, Leigh JS, Wagner PD, Noyszewski EA (1999) Cellular PO2 as a determinant of maximal mitochondrial O2 consumption in trained human skeletal muscle. J Appl Physiol 87(1):325–331PubMedCrossRefGoogle Scholar
  352. Richardson RS, Newcomer SC, Noyszewski EA (2001) Skeletal muscle intracellular PO2 assessed by myoglobin desaturation: response to graded exercise. J Appl Physiol 91(6):2679–2685PubMedCrossRefGoogle Scholar
  353. Richardson RS, Noyszewski EA, Saltin B, Gonzalez-Alonso J (2002) Effect of mild carboxy-hemoglobin on exercising skeletal muscle: intravascular and intracellular evidence. Am J Physiol Regul Integr Comp Physiol 283(5):R1131–R1139CrossRefGoogle Scholar
  354. Richardson RS, Duteil S, Wary C, Wray DW, Hoff J, Carlier PG (2006) Human skeletal muscle intracellular oxygenation: the impact of ambient oxygen availability. J Physiol 571(2):415–424PubMedPubMedCentralCrossRefGoogle Scholar
  355. Richter EA, Kiens B, Saltin B, Christensen NJ, Savard G (1988) Skeletal muscle glucose uptake during dynamic exercise in humans: role of muscle mass. Am J Physiol Endocrinol Metab 254(5):E555–E561CrossRefGoogle Scholar
  356. Rivers E, Nguyen B, Havstad S, Ressler J, Muzzin A, Knoblich B, Peterson E, Tomlanovich M (2001) Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med 345(19):1368–1377PubMedCrossRefGoogle Scholar
  357. Robergs RA (2008) Science vs. personal bias in acid-base physiology. J Appl Physiol 105(1):363PubMedCrossRefGoogle Scholar
  358. Robergs RA, Ghiasvand F, Parker D (2004) Biochemistry of exercise-induced metabolic acidosis. Am J Physiol Regul Integr Comp Physiol 287(3):R502–R516CrossRefGoogle Scholar
  359. Robergs RA, Ghiasvand F, Parker D (2005) Lingering construct of lactic acidosis. Am J Physiol Regul Integr Comp Physiol 289(3):R904–R910CrossRefGoogle Scholar
  360. Robergs RA, Ghiasvand F, Parker D (2006) Reply: the wandering argument favoring a lactic acidosis. Am J Physiol Regul Integr Comp Physiol 291(1):R238–R239CrossRefGoogle Scholar
  361. Roef MJ, De Meer K, Kalhan SC, Straver H, Berger R, Reijngoud D-J (2003) Gluconeogenesis in humans with induced hyperlactatemia during low-intensity exercise. Am J Physiol Endocrinol Metab 284(6):E1162–E1171PubMedCrossRefGoogle Scholar
  362. Rogatzki MJ, Ferguson BS, Goodwin ML, Gladden LB (2015) Lactate is always the end product of glycolysis. Front Neurosci 9:22. PubMedPubMedCentralCrossRefGoogle Scholar
  363. Rooney K, Trayhurn P (2011) Lactate and the GPR81 receptor in metabolic regulation: implications for adipose tissue function and fatty acid utilisation by muscle during exercise. Br J Nutr 106(9):1310–1316. PubMedCrossRefGoogle Scholar
  364. Roos A (1975) Intracellular pH and distribution of weak acids across cell membranes. A study of d-and l-lactate and of DMO in rat diaphragm. J Physiol 249(1):1–25PubMedPubMedCentralCrossRefGoogle Scholar
  365. Roth DA, Brooks GA (1990a) Lactate and pyruvate transport is dominated by a pH gradient-sensitive carrier in rat skeletal muscle sarcolemmal vesicles. Arch Biochem Biophys 279(2):386–394. PubMedCrossRefGoogle Scholar
  366. Roth DA, Brooks GA (1990b) Lactate transport is mediated by a membrane-bound carrier in rat skeletal muscle sarcolemmal vesicles. Arch Biochem Biophys 279(2):377–385PubMedCrossRefGoogle Scholar
  367. Sahlin K, Ren JM (1989) Relationship of contraction capacity to metabolic changes during recovery from a fatiguing contraction. J Appl Physiol 67(2):648–654PubMedCrossRefGoogle Scholar
  368. Sahlin K, Harris R, Nylind B, Hultman E (1976) Lactate content and pH in muscle samples obtained after dynamic exercise. Pflügers Archiv 367(2):143–149PubMedCrossRefGoogle Scholar
  369. Sahlin K, Fernström M, Svensson M, Tonkonogi M (2002) No evidence of an intracellular lactate shuttle in rat skeletal muscle. J Physiol 541(2):569–574. PubMedPubMedCentralCrossRefGoogle Scholar
  370. Sakagami H, Makino Y, Mizumoto K, Isoe T, Takeda Y, Watanabe J, Fujita Y, Takiyama Y, Abiko A, Haneda M (2014) Loss of HIF-1α impairs GLUT4 translocation and glucose uptake by the skeletal muscle cells. Am J Physiol Endocrinol Metab 306(9):E1065–E1076PubMedCrossRefGoogle Scholar
  371. Samaja M, Allibardi S, Milano G, Neri G, Grassi B, Gladden LB, Hogan MC (1999) Differential depression of myocardial function and metabolism by lactate and H+. Am J Physiol Heart Circ Physiol 276(1):H3–H8CrossRefGoogle Scholar
  372. San-Millán I, Brooks GA (2017) Reexamining cancer metabolism: Lactate production for carcinogenesis could be the purpose and explanation of the Warburg Effect. Carcinogenesis 38(2):119–133. PubMedGoogle Scholar
  373. Sauer LA, Dauchy RT (1985) Regulation of lactate production and utilization in rat tumors in vivo. J Biol Chem 260(12):7496–7501PubMedGoogle Scholar
  374. Scandurra FM, Gnaiger E (2010) Cell respiration under hypoxia: facts and artefacts in mitochondrial oxygen kinetics. In: Takahashi E, Bruley DF (eds) Oxygen Transport to Tissue XXXI, Adv Exp Med Biol, vol 662. Springer US, Boston, pp 7–25.
  375. Scheele CW, Bergman T (1777) Chemische Abhandlung von der Luft und dem Feuer: nebst einem Vorbericht. Verlegt von Magnus Swederus. SL Crusius, Upsalla, LeipzigGoogle Scholar
  376. Scheele CW, Forster JR, Priestley J, Kirwan R, Bergman T (1780) Chemical Observations and Experiments on Air and Fire, translated by Forster JR. Johnson, LondonGoogle Scholar
  377. Scherer JJ (1843) Chemische und mikroskopische Untersuchungen zur Pathologie: angestellt an den Kliniken des Julius-Hospitales zu Würzburg. Kessinger Legacy Reprints Publishing, WhitefishGoogle Scholar
  378. Scherer JJ (1851) Eine Untersuchung des Blutes bei Leukämie. Verhandlungen der Physikalisch-Medicinischen Gesellschaft im Würzburg 2:321–325Google Scholar
  379. Schurr A (2006) Lactate: the ultimate cerebral oxidative energy substrate? J Cereb Blood Flow Metab 26(1):142–152PubMedCrossRefGoogle Scholar
  380. Schurr A (2014) Cerebral glycolysis: a century of persistent misunderstanding and misconception. Front Neurosci 8 (360).
  381. Schurr A (2017) Lactate, Not Pyruvate, Is the End Product of Glucose Metabolism via Glycolysis. In: Caliskan M, Kavakli HI, Oz GC (eds) Biochem Genet Mol Biol. InTech, Rijeka, p 2.
  382. Schurr A, Payne RS (2007) Lactate, not pyruvate, is neuronal aerobic glycolysis end product: An in vitro electrophysiological study. Neuroscience 147(3):613–619. PubMedCrossRefGoogle Scholar
  383. Schurr A, West CA, Rigor BM (1988) Lactate-supported synaptic function in the rat hippocampal slice preparation. Science 240(4857):1326–1328PubMedCrossRefGoogle Scholar
  384. Schurr A, Payne RS, Miller JJ, Rigor BM (1997a) Brain lactate is an obligatory aerobic energy substrate for functional recovery after hypoxia: further in vitro validation. J Neurochem 69(1):423–426PubMedCrossRefGoogle Scholar
  385. Schurr A, Payne RS, Miller JJ, Rigor BM (1997b) Brain lactate, not glucose, fuels the recovery of synaptic function from hypoxia upon reoxygenation: an in vitro study. Brain Res 744(1):105–111PubMedCrossRefGoogle Scholar
  386. Schurr A, Payne RS, Miller JJ, Rigor BM (1997c) Glia are the main source of lactate utilized by neurons for recovery of function posthypoxia. Brain Res 774(1):221–224PubMedCrossRefGoogle Scholar
  387. Semenza GL (2001) HIF-1, O2, and the 3 PHDs: how animal cells signal hypoxia to the nucleus. Cell 107(1):1–3PubMedCrossRefGoogle Scholar
  388. Semenza GL (2004) Hydroxylation of HIF-1: oxygen sensing at the molecular level. Physiol 19(4):176–182CrossRefGoogle Scholar
  389. Semenza GL (2008) Tumor metabolism: cancer cells give and take lactate. J Clin Invest 118(12):3835–3837PubMedPubMedCentralGoogle Scholar
  390. Semenza GL, Wang GL (1992) A nuclear factor induced by hypoxia via de novo protein synthesis binds to the human erythropoietin gene enhancer at a site required for transcriptional activation. Mol Cell Biol 12(12):5447–5454PubMedPubMedCentralCrossRefGoogle Scholar
  391. Semenza GL, Jiang B-H, Leung SW, Passantino R, Concordet J-P, Maire P, Giallongo A (1996) Hypoxia response elements in the aldolase A, enolase 1, and lactate dehydrogenase A gene promoters contain essential binding sites for hypoxia-inducible factor 1. J Biol Chem 271(51):32529–32537PubMedCrossRefGoogle Scholar
  392. Severinghaus JW (2006) The breathless quest for the gas supporting combustion. Phys Today 59(8):51. CrossRefGoogle Scholar
  393. Severinghaus JW (2016) Eight sages over five centuries share oxygens discovery. Adv Physiol Edu 40(3):370–376CrossRefGoogle Scholar
  394. Sheng SL, Liu JJ, Dai YH, Sun XG, Xiong XP, Huang G (2012) Knockdown of lactate dehydrogenase A suppresses tumor growth and metastasis of human hepatocellular carcinoma. FEBS J 279(20):3898–3910PubMedCrossRefGoogle Scholar
  395. Shi M, Cui J, Du J, Wei D, Jia Z, Zhang J, Zhu Z, Gao Y, Xie K (2014) A novel KLF4/LDHA signaling pathway regulates aerobic glycolysis in and progression of pancreatic cancer. Clin Cancer Res 20(16):4370–4380PubMedPubMedCentralCrossRefGoogle Scholar
  396. Siegler JC, Marshall PWM, Bishop D, Shaw G, Green S (2016) Mechanistic insights into the efficacy of sodium bicarbonate supplementation to improve athletic performance. Sports Med Open 2(1):41PubMedPubMedCentralCrossRefGoogle Scholar
  397. Simon J, Young JL, Gutin B, Blood DK, Case RB (1983) Lactate accumulation relative to the anaerobic and respiratory compensation thresholds. J Appl Physiol 54(1):13–17PubMedCrossRefGoogle Scholar
  398. Siskind SJ, Sonnenblick EH, Forman R, Scheuer J, Lejemtel TH (1981) Acute substantial benefit of inotropic therapy with amrinone on exercise hemodynamics and metabolism in severe congestive heart failure. Circulation 64(5):966–973PubMedCrossRefGoogle Scholar
  399. Skelton MS, Kremer DE, Smith EW, Gladden LB (1995) Lactate influx into red blood cells of athletic and nonathletic species. Am J Physiol Regul Integr Comp Physiol 268(5):R1121–R1128CrossRefGoogle Scholar
  400. Skelton MS, Kremer DE, Smith EW, Gladden LB (1998) Lactate influx into red blood cells from trained and untrained human subjects. Med Sci Sports Exerc 30(4):536–542PubMedCrossRefGoogle Scholar
  401. Smith D, Pernet A, Hallett WA, Bingham E, Marsden PK, Amiel SA (2003) Lactate: a preferred fuel for human brain metabolism in vivo. J Cereb Blood Flow Metab 23(6):658–664PubMedCrossRefGoogle Scholar
  402. Sokoloff L (1989) Circulation and energy metabolism of the brain. Basic Neurochem 2:338–413Google Scholar
  403. Sonveaux P, Végran F, Schroeder T, Wergin MC, Verrax J, Rabbani ZN, De Saedeleer CJ, Kennedy KM, Diepart C, Jordan BF (2008) Targeting lactate-fueled respiration selectively kills hypoxic tumor cells in mice. J Clin Invest 118(12):3930–3942PubMedPubMedCentralGoogle Scholar
  404. Spangenburg EE, Ward CW, Williams JH (1998) Effects of lactate on force production by mouse EDL muscle: implications for the development of fatigue. Can J Physiol Pharmacol 76(6):642–648PubMedCrossRefGoogle Scholar
  405. Stacpoole PW, Wright EC, Baumgartner TG, Bersin RM, Buchalter S, Curry SH, Duncan CA, Harman EM, Henderson GN, Jenkinson S, Lachin JM, Lorenz A, Schneider SH, Siegel JH, Summer WR, Thompson D, Wolfe CL, Zorovich B (1992) A controlled clinical trial of dichloroacetate for treatment of lactic acidosis in adults. N Engl J Med 327(22):1564–1569. PubMedCrossRefGoogle Scholar
  406. Stainsby WN, Brooks GA (1990) Control of lactic acid metabolism in contracting muscles and during exercise. Exerc Sport Sci Rev 18(1):29–64PubMedCrossRefGoogle Scholar
  407. Stainsby WN, Welch HG (1966) Lactate metabolism of contracting dog skeletal muscle in situ. Am J Physiol 211(1):177–183PubMedGoogle Scholar
  408. Stainsby WN, Sumners C, Eitzman PD (1987) Effects of adrenergic agonists and antagonists on muscle O2 uptake and lactate metabolism. J Appl Physiol 62(5):1845–1851PubMedCrossRefGoogle Scholar
  409. Stanley WC (1991) Myocardial lactate metabolism during exercise. Med Sci Sports Exerc 23(8):920–924PubMedCrossRefGoogle Scholar
  410. Stanley WC, Gertz EW, Wisneski JA, Neese RA, Morris DL, Brooks GA (1986) Lactate extraction during net lactate release in legs of humans during exercise. J Appl Physiol 60(4):1116–1120PubMedCrossRefGoogle Scholar
  411. Stegmann H, Kindermann W, Schnabel A (1981) Lactate kinetics and individual anaerobic threshold. Int J Sports Med 2(3):160–165PubMedCrossRefGoogle Scholar
  412. Stewart PA (1981) How to understand acid-base: a quantitative acid-base primer for biology and medicine. Elsevier, New YorkGoogle Scholar
  413. Stickland MK, Lindinger MI, Olfert IM, Heigenhauser GJF, Hopkins SR (2013) Pulmonary gas exchange and acid-base balance during exercise. Compr Physiol (3):693–739Google Scholar
  414. Szczesna-Kaczmarek A, Litwinska D, Popinigis J (1984) Oxidation of NADH via an “external” pathway in skeletal -muscle mitochondria and its possible role in the repayment of lactacid oxygen debt. Int J Biochem 16(12):1231–1235PubMedCrossRefGoogle Scholar
  415. Tang F, Lane S, Korsak A, Paton JFR, Gourine AV, Kasparov S, Teschemacher AG (2014) Lactate-mediated glia-neuronal signalling in the mammalian brain. Nat Commun 5:3284. PubMedPubMedCentralGoogle Scholar
  416. Taylor EB (2017) Functional properties of the mitochondrial carrier system. Trends Cell Biol 27(9):633–644PubMedCrossRefGoogle Scholar
  417. Tenhunen JJ, Jakob SM, Takala JA (2001) Gut luminal lactate release during gradual intestinal ischemia. Intensive Care Med 27(12):1916–1922PubMedCrossRefGoogle Scholar
  418. The History of Cancer (2002) Accessed 9 Jan 2018
  419. Thomas C, Bishop DJ, Lambert K, Mercier J, Brooks GA (2012) Effects of acute and chronic exercise on sarcolemmal MCT1 and MCT4 contents in human skeletal muscles: current status. Am J Physiol Integr Comp Physiol 302(1):R1–R14CrossRefGoogle Scholar
  420. Thornburg JM, Nelson KK, Clem BF, Lane AN, Arumugam S, Simmons A, Eaton JW, Telang S, Chesney J (2008) Targeting aspartate aminotransferase in breast cancer. Breast Cancer Res 10(5):R84–R84. CrossRefGoogle Scholar
  421. Tonouchi M, Hatta H, Bonen A (2002) Muscle contraction increases lactate transport while reducing sarcolemmal MCT4, but not MCT1. Am J Physiol Endocrinol Metab 282(5):E1062–E1069PubMedCrossRefGoogle Scholar
  422. Trzeciak S, McCoy JV, Dellinger RP, Arnold RC, Rizzuto M, Abate NL, Shapiro NI, Parrillo JE, Hollenberg SM (2008) Early increases in microcirculatory perfusion during protocol-directed resuscitation are associated with reduced multi-organ failure at 24 h in patients with sepsis. Intensive Care Med 34(12):2210–2217PubMedPubMedCentralCrossRefGoogle Scholar
  423. Tsacopoulos M (2002) Metabolic signaling between neurons and glial cells: a short review. J Physiol (Paris) 96(3):283–288CrossRefGoogle Scholar
  424. Tsai S-F, Chen P-C, Calkins MJ, Wu S-Y, Kuo Y-M (2016) Exercise counteracts aging-related memory impairment: a potential role for the astrocytic metabolic shuttle. Front Aging Neurosci 8:57. PubMedPubMedCentralCrossRefGoogle Scholar
  425. Twentyman OP, Disley A, Gribbin HR, Alberti KG, Tattersfield AE (1981) Effect of beta-adrenergic blockade on respiratory and metabolic responses to exercise. J Appl Physiol 51(4):788–793PubMedCrossRefGoogle Scholar
  426. Ugrumov MV (2009) Non-dopaminergic neurons partly expressing dopaminergic phenotype: distribution in the brain, development and functional significance. J Chem Neuroanat 38(4):241–256PubMedCrossRefGoogle Scholar
  427. Ullah MS, Davies AJ, Halestrap AP (2006) The plasma membrane lactate transporter MCT4, but not MCT1, is up-regulated by hypoxia through a HIF-1 α -dependent mechanism. J Biol Chem 281(14):9030–9037. PubMedCrossRefGoogle Scholar
  428. Unkefer CJ, Blazer RM, London RE (1983) In vivo determination of the pyridine nucleotide reduction charge by carbon-13 nuclear magnetic resonance spectroscopy. Science 222(4619):62–65PubMedCrossRefGoogle Scholar
  429. Valenti D, di Bari L, Atlante A, Passarella S (2002) l-Lactate transport into rat heart mitochondria and reconstruction of the l-lactate/pyruvate shuttle. Biochem J 364(1):101–104PubMedPubMedCentralCrossRefGoogle Scholar
  430. Van Hall G (2000) Lactate as a fuel for mitochondrial respiration. Acta Physiol Scand 168(4):643–656PubMedCrossRefGoogle Scholar
  431. Van Hall G, Jensen-Urstad M, Rosdahl H, Holmberg HC, Saltin B, Calbet JAL (2003) Leg and arm lactate and substrate kinetics during exercise. Am J Physiol Endocrinol Metab 284(1):E193–E205PubMedCrossRefGoogle Scholar
  432. Vander Heiden MG (2011) Targeting cancer metabolism: a therapeutic window opens. Nat Rev Drug Discov 10(9):671–684PubMedCrossRefGoogle Scholar
  433. Vander Heiden MG, Cantley LC, Thompson CB (2009) Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science 324(5930):1029–1033PubMedPubMedCentralCrossRefGoogle Scholar
  434. Vanderthommen M, Duteil S, Wary C, Raynaud J-S, Leroy-Willig A, Crielaard J-M, Carlier PG (2003) A comparison of voluntary and electrically induced contractions by interleaved 1H- and 31P-NMRS in humans. J Appl Physiol 94(3):1012–1024PubMedCrossRefGoogle Scholar
  435. Venkatesan M, Smith RP, Balasubramanian S, Khan A, Uzoigwe CE, Coats TJ, Godsiff S (2015) Serum lactate as a marker of mortality in patients with hip fracture: a prospective study. Injury 46(11):2201–2205PubMedCrossRefGoogle Scholar
  436. Vogel JA, Gleser MA (1972) Effect of carbon monoxide on oxygen transport during exercise. J Appl Physiol 32(2):234–239PubMedCrossRefGoogle Scholar
  437. von Liebig J (1847) Recherches de chimie animale. CR Hebdom Seances Acad Sci 24:69–73Google Scholar
  438. von Muralt A (1950) The development of muscle-chemistry, a lesson in neurophysiology. Biochim Biophys Acta 4:126–129CrossRefGoogle Scholar
  439. von Euler H, Myrbäck K, Karlsson S (1925) Enzymatischer Abbau und Aufbau der Kohlehydrate. I. Phosphatumsatz und Glykogenspaltung in Muskel und Hefe. Hoppe-Seyler´s Zeitschrift für physiologische Chemie 143(4–6):243–264CrossRefGoogle Scholar
  440. Voter WA, Gayeski TE (1995) Determination of myoglobin saturation of frozen specimens using a reflecting cryospectrophotometer. Am J Physiol Heart Circ Physiol 269(4):H1328–H1341CrossRefGoogle Scholar
  441. Wang J, Wang H, Liu A, Fang C, Hao J, Wang Z (2015) Lactate dehydrogenase A negatively regulated by miRNAs promotes aerobic glycolysis and is increased in colorectal cancer. Oncotarget 6(23):19456–19468PubMedPubMedCentralGoogle Scholar
  442. Warburg O (1926) Über den Stoffwechsel der Tumoren. Arbeiten aus dem Kaiser Wilhelm-Institut für Biologie - Berlin-Dahlem Julius Springer, BerlinGoogle Scholar
  443. Warburg O, Minami S (1923) Versuche an überlebendem carcinomgewebe. Klin Wochenschr 2(17):776–777. Google Scholar
  444. Warburg O, Wind F, Negelein E (1927) The metabolism of tumors in the body. J Gen Physiol 8(6):519–530PubMedPubMedCentralCrossRefGoogle Scholar
  445. Wasserman K (1984) The anaerobic threshold measurement to evaluate exercise performance. Am Rev Respir Dis 129(2P2):S35–S40Google Scholar
  446. Wasserman K, Koike A (1992) Is the anaerobic threshold truly anaerobic? Chest 101(5):211S–218S. CrossRefGoogle Scholar
  447. Wasserman K, McIlroy MB (1964) Detecting the threshold of anaerobic metabolism in cardiac patients during exercise. Am J Cardiol 14(6):844–852PubMedCrossRefGoogle Scholar
  448. Wasserman K, Van Kessel AL, Burton GG (1967) Interaction of physiological mechanisms during exercise. J Appl Physiol 22(1):71–85PubMedCrossRefGoogle Scholar
  449. Wasserman K, Whipp BJ, Koyl SN, Beaver WL (1973) Anaerobic threshold and respiratory gas exchange during exercise. J Appl Physiol 35(2):236–243PubMedCrossRefGoogle Scholar
  450. Wasserman K, Beaver WL, Whipp BJ (1986) Mechanisms and patterns of blood lactate increase during exercise in man. Med Sci Sports Exerc 18(3):344–352PubMedCrossRefGoogle Scholar
  451. Welch HG, Stainsby WN (1967) Oxygen debt in contracting dog skeletal muscle in situ. Respir Physiol 3(2):229–242. PubMedCrossRefGoogle Scholar
  452. West JB (2014) Carl Wilhelm Scheele, the discoverer of oxygen, and a very productive chemist. Am J Physiol Lung Cell Mol Physiol 307(11):L811–L816CrossRefGoogle Scholar
  453. Westerblad H (2016) Acidosis is not a significant cause of skeletal muscle fatigue. Med Sci Sports Exerc 48(11):2339–2342PubMedCrossRefGoogle Scholar
  454. Westerblad H, Allen DG (1992) Changes of intracellular pH due to repetitive stimulation of single fibres from mouse skeletal muscle. J Physiol 449(1):49–71PubMedPubMedCentralCrossRefGoogle Scholar
  455. Whitaker-Menezes D, Martinez-Outschoorn UE, Lin Z, Ertel A, Flomenberg N, Witkiewicz AK, Birbe R, Howell A, Pavlides S, Gandara R, Pestell RG, Sotgia F, Philp NJ, Lisanti MP (2011) Evidence for a stromal-epithelial “lactate shuttle” in human tumors. Cell Cycle 10(11):1772–1783. PubMedPubMedCentralCrossRefGoogle Scholar
  456. Williams TI, Moyer AE (1982) A biographical dictionary of scientists, 3rd edn, vol 2. Wiley, New YorkGoogle Scholar
  457. Williamson DH, Lund P, Krebs Ha (1967) The redox state of free nicotinamide-adenine dinucleotide in the cytoplasm and mitochondria of rat liver. Biochem J 103(2):514–527. PubMedPubMedCentralCrossRefGoogle Scholar
  458. Wilson DF (1994) Factors affecting the rate and energetics of mitochondrial oxidative phosphorylation. Med Sci Sports Exerc 26(1):37–43PubMedCrossRefGoogle Scholar
  459. Wilson DF, Owen CS, Erecińska M (1979) Quantitative dependence of mitochondrial oxidative phosphorylation on oxygen concentration: a mathematical model. Arch Biochem Biophys 195(2):494–504. PubMedCrossRefGoogle Scholar
  460. Wilson DF, Rumsey WL, Green TJ, Vanderkooi JM (1988) The oxygen dependence of mitochondrial oxidative phosphorylation measured by a new optical method for measuring oxygen concentration. J Biol Chem 263(6):2712–2718PubMedGoogle Scholar
  461. Wislicenus J (1873) Ueber die optisch-active Milchsäure der Fleischflussigkeit, die Paramilchsäure. Justus Liebigs Ann Chem 167:302–346CrossRefGoogle Scholar
  462. Witkiewicz AK, Whitaker-Menezes D, Dasgupta A, Philp NJ, Lin Z, Gandara R, Sneddon S, Martinez-Outschoorn UE, Sotgia F, Lisanti MP (2012) Using the “reverse Warburg effect” to identify high-risk breast cancer patients: stromal MCT4 predicts poor clinical outcome in triple-negative breast cancers. Cell cycle 11(6):1108–1117PubMedPubMedCentralCrossRefGoogle Scholar
  463. Wood SM, Wiesener MS, Yeates KM, Okada N, Pugh CW, Maxwell PH, Ratcliffe PJ (1998) Selection and analysis of a mutant cell line defective in the hypoxia-inducible factor-1 α-subunit (HIF-1α) characterization of HIF-1α-dependent and independent hypoxia inducible gene expression. J Biol Chem 273(14):8360–8368PubMedCrossRefGoogle Scholar
  464. Woodson RD, Wills RE, Lenfant C (1978) Effect of acute and established anemia on O2 transport at rest, submaximal and maximal work. J Appl Physiol 44(1):36–43PubMedCrossRefGoogle Scholar
  465. Wyatt HL, Da Luz PL, Waters DD, Swan HJ, Forrester JS (1977) Contrasting influences of alterations in ventricular preload and afterload upon systemic hemodynamics, function, and metabolism of ischemic myocardium. Circulation 55(2):318–324PubMedCrossRefGoogle Scholar
  466. Yates JW, Gladden LB, Cresanta MK (1983) Effects of prior dynamic leg exercise on static effort of the elbow flexors. J Appl Physiol 55(3):891–896PubMedCrossRefGoogle Scholar
  467. Yeh MP, Gardner RM, Adams TD, Yanowitz FG, Crapo RO (1983) “Anaerobic threshold”:problems of determination and validation. J Appl Physiol 55(4):1178–1186PubMedCrossRefGoogle Scholar
  468. Ying W (2008) NAD+/NADH and NADP+/NADPH in cellular functions and cell Death: regulation and biological consequences. Antioxid Redox Signal 10(2):179–206. PubMedCrossRefGoogle Scholar
  469. Yoshida Y, Holloway GP, Ljubicic V, Hatta H, Spriet LL, Hood DA, Bonen A (2007) Negligible direct lactate oxidation in subsarcolemmal and intermyofibrillar mitochondria obtained from red and white rat skeletal muscle. J Physiol 582(Pt 3):1317–1335. PubMedPubMedCentralCrossRefGoogle Scholar
  470. Zeuthen T, Hamann S, la Cour M (1996) Cotransport of H+, lactate and H2O by membrane proteins in retinal pigment epithelium of bullfrog. J Physiol 497(1):3–17PubMedPubMedCentralCrossRefGoogle Scholar
  471. Zoli M, Agnati LF (1996) Wiring and volume transmission in the central nervous system: the concept of closed and open synapses. Prog Neurobiol 49(4):363–380PubMedCrossRefGoogle Scholar
  472. Zuntz VN (1911) Umsatz der nahrstoffe. XI. Betrachtungen uber die beziehungen zwischen nahrstoffen und leistungen des korpers. In: Oppenheimer K (ed) Handbuch der Biochemie des Menschen und der Tiere. pp 826–855Google Scholar

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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Applied Health SciencesUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Department of Health and Exercise ScienceAppalachian State UniversityBooneUSA
  3. 3.Department of OrthopaedicsUniversity of UtahSalt Lake CityUSA
  4. 4.Huntsman Cancer InstituteSalt Lake CityUSA
  5. 5.Department of Human KineticsSt. Francis Xavier UniversityAntigonishCanada
  6. 6.School of KinesiologyAuburn UniversityAuburnUSA

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