Advertisement

Early Detection and Treatment of Patients with Alzheimer’s Disease: Future Perspectives

  • Francesca L. Guest
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1118)

Abstract

Alzheimer’s disease affects approximately 6% of people over the age of 65 years. It is characterized as chronic degeneration of cortical neurons, with loss of memory, cognition and executive functions. As the disease progresses, it is accompanied by accumulation of amyloid plaques and neurofibrillary tangles in key areas of the brain, leading to a loss of neurogenesis and synaptic plasticity in the hippocampus, along with changes in the levels of essential neurotransmitters such as acetylcholine and glutamate. Individuals with concomitant diseases such as depression, diabetes and cardiovascular disorders have a higher risk of developing Alzheimer’s disease, and those who have a healthier diet and partake in regular exercise and intellectual stimulation have a lower risk of developing the disorder. This chapter describes the advances made in early diagnosis of Alzheimer’s disease as this could help to improve outcomes for the patients by facilitating earlier treatment.

Keywords

Alzheimer’s disease Biomarkers Imaging Proteomics Metabolomics Lab-on-a-chip Smartphone monitoring 

References

  1. 1.
    Kalaria RN, Maestre GE, Arizaga R, Friedland RP, Galasko D, Hall K et al (2008) Alzheimer’s disease and vascular dementia in developing countries: prevalence, management, and risk factors. Lancet Neurol 7:812–826PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP (2013) The global prevalence of dementia: a systematic review and metaanalysis. Alzheimers Dement 9(1):63–75 e62. https://doi.org/10.1016/j.jalz.2012.11.007CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Perneczky R (ed) (2018) Biomarkers for preclinical Alzheimer’s disease (Neuromethods), 1st edn. Humana Press, Clifton. ISBN-10: 1493976737Google Scholar
  5. 5.
    Kazim SF, Iqbal K (2016) Neurotrophic factor small-molecule mimetics mediated neuroregeneration and synaptic repair: emerging therapeutic modality for Alzheimer’s disease. Mol Neurodegener 11(1):50. https://doi.org/10.1186/s13024-016-0119-y
  6. 6.
    Mu Y, Gage FH (2011) Adult hippocampal neurogenesis and its role in Alzheimer’s disease. Mol Neurodegener 6:85. https://doi.org/10.1186/1750-1326-6-85PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Battaglia F, Wang HY, Ghilardi MF, Gashi E, Quartarone A, Friedman E et al (2007) Cortical plasticity in Alzheimer’s disease in humans and rodents. Biol Psychiatry 62:1405–1412PubMedCrossRefGoogle Scholar
  8. 8.
    Davies P, Maloney AJ (1976) Selective loss of central cholinergic neurons in Alzheimer’s disease. Lancet 2(8000):1403CrossRefGoogle Scholar
  9. 9.
    Hung SY, Fu WM (2017) Drug candidates in clinical trials for Alzheimer’s disease. J Biomed Sci 24(1):47. https://doi.org/10.1186/s12929-017-0355-7
  10. 10.
    Larson EB, Shadlen MF, Wang L, McCormick WC, Bowen JD, Teri L et al (2004) Survival after initial diagnosis of Alzheimer disease. Ann Intern Med 140(7):501–509PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    Guest PC (2017) Biomarkers and mental illness: it’s not all in the mind, 1st edn. Copernicus, Göttingen. ISBN-10: 3319460870Google Scholar
  12. 12.
    Barron AM, Pike CJ (2012) Sex hormones, aging, and Alzheimer’s disease. Front Biosci (Elite Ed) 4:976–997Google Scholar
  13. 13.
    McGeer PL, McGeer EG (2001) Polymorphisms in inflammatory genes and the risk of Alzheimer disease. Arch Neurol 58(11):1790–1792PubMedCrossRefGoogle Scholar
  14. 14.
    van Exel E, Eikelenboom P, Comijs H, Frölich M, Smit JH, Stek ML et al (2009) Vascular factors and markers of inflammation in offspring with a parental history of late-onset Alzheimer disease. Arch Gen Psychiatry 66(11):1263–1270PubMedCrossRefGoogle Scholar
  15. 15.
    Moustafa AA, Hassan M, Hewedi DH, Hewedi I, Garami JK, Al Ashwal H et al (2018) Genetic underpinnings in Alzheimer’s disease—a review. Rev Neurosci 29(1):21–38PubMedCrossRefGoogle Scholar
  16. 16.
    Ford E, Greenslade N, Paudyal P, Bremner S, Smith HE, Banerjee S et al (2018) Predicting dementia from primary care records: a systematic review and meta-analysis. PLoS One 13(3):e0194735. https://doi.org/10.1371/journal.pone.0194735CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Friedman DB, Becofsky K, Anderson LA, Bryant LL, Hunter RH, Ivey SL et al (2015) Public perceptions about risk and protective factors for cognitive health and impairment: a review of the literature. Int Psychogeriatr 27(8):1263–1275PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    De-Paula VJ, Radanovic M, Diniz BS, Forlenza OV (2012) Alzheimer’s disease. Subcell Biochem 65:329–352PubMedCrossRefGoogle Scholar
  19. 19.
    Huse JT, Doms RW (2000) Closing in on the amyloid cascade: recent insights into the cell biology of Alzheimer’s disease. Mol Neurobiol 22(1–3):81–98PubMedGoogle Scholar
  20. 20.
    Rentz DM, Parra Rodriguez MA, Amariglio R, Stern Y, Sperling R, Ferris S (2013) Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer’s disease: a selective review. Alzheimers Res Ther 5:58. https://doi.org/10.1186/alzrt222 CrossRefGoogle Scholar
  21. 21.
    Rentz DM, Amariglio RE, Becker JA, Frey M, Olson LE, Frishe K et al (2011) Face-name associative memory performance is related to amyloid burden in normal elderly. Neuropsychologia 49(9):2776–2783PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Cecchini MA, Yassuda MS, Bahia VS, de Souza LC, Guimarães HC, Caramelli P et al (2017) Recalling feature bindings differentiates Alzheimer’s disease from frontotemporal dementia. J Neurol 264(10):2162–2169PubMedCrossRefGoogle Scholar
  23. 23.
    Holden HM, Hoebel C, Loftis K, Gilbert PE (2012) Spatial pattern separation in cognitively normal young and older adults. Hippocampus 22(9):1826–1832PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Counts SE, Ikonomovic MD, Mercado N, Vega IE, Mufson EJ (2017) Biomarkers for the early detection and progression of Alzheimer’s disease. Neurotherapeutics 14(1):35–53PubMedCrossRefGoogle Scholar
  25. 25.
    Villemagne VL, Rowe CC, Barnham KJ, Cherny R, Woodward M, Bozinosvski S et al (2017) A randomized, exploratory molecular imaging study targeting amyloid β with a novel 8-OH quinoline in Alzheimer’s disease: the PBT2-204 IMAGINE study. Alzheimers Dement (N Y) 3(4):622–635Google Scholar
  26. 26.
    Varma VR, Oommen AM, Varma S, Casanova R, An Y, Andrews RM et al (2018) Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: a targeted metabolomics study. PLoS Med 15(1):e1002482. https://doi.org/10.1371/journal.pmed.1002482PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Nabers A, Perna L, Lange J, Mons U, Schartner J, Güldenhaupt J et al (2018) Amyloid blood biomarker detects Alzheimer’s disease. EMBO Mol Med. 10(5). https://doi.org/10.15252/emmm.201708763PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Herman L, Atri A, Salloway S (2017) Alzheimer’s disease in primary care: the significance of early detection, diagnosis, and intervention. Am J Med 130(6):756. https://doi.org/10.1016/j.amjmed.2017.04.001PubMedCrossRefGoogle Scholar
  29. 29.
    Wattmo C, Wallin ÅK (2017) Early- versus late-onset Alzheimer’s disease in clinical practice: cognitive and global outcomes over 3 years. Alzheimers Res Ther 9(1):70. https://doi.org/10.1186/s13195-017-0294-2
  30. 30.
  31. 31.
    Manning FC (1994) Tacrine therapy for the dementia of Alzheimer’s disease. Am Fam Physician 50(4):819–826PubMedGoogle Scholar
  32. 32.
    Gauthier S, Panisset M, Nalbantoglu J, Poirier J (1997) Alzheimer’s disease: current knowledge, management and research. CMAJ 157(8):1047–1052PubMedPubMedCentralGoogle Scholar
  33. 33.
    Nordberg A, Svensson AL (1998) Cholinesterase inhibitors in the treatment of Alzheimer’s disease: a comparison of tolerability and pharmacology. Drug Saf 19(6):465–480PubMedCrossRefGoogle Scholar
  34. 34.
    Grutzendler J, Morris JC (2001) Cholinesterase inhibitors for Alzheimer’s disease. Drugs 61(1):41–52PubMedCrossRefGoogle Scholar
  35. 35.
    Doraiswamy PM (2002) Non-cholinergic strategies for treating and preventing Alzheimer’s disease. CNS Drugs 16(12):811–824PubMedCrossRefGoogle Scholar
  36. 36.
    Mezeiova E, Korabecny J, Sepsova V, Hrabinova M, Jost P, Muckova L et al (2017) Development of 2-methoxyhuprine as novel lead for Alzheimer’s disease therapy. Molecules 22(8). https://doi.org/10.3390/molecules22081265PubMedCentralCrossRefPubMedGoogle Scholar
  37. 37.
    Oset-Gasque MJ, Marco-Contelles J (2017) New tacrines as anti-Alzheimer’s disease agents. The (Benzo)Chromeno-PyranoTacrines. Curr Top Med Chem 17(31):3349–3360PubMedCrossRefGoogle Scholar
  38. 38.
    Doggrell S (2003) Is memantine a breakthrough in the treatment of moderate-to-severe Alzheimer’s disease? Expert Opin Pharmacother 4(10):1857–1860PubMedCrossRefGoogle Scholar
  39. 39.
    Modrego PJ (2010) Depression in Alzheimer’s disease. Pathophysiology, diagnosis, and treatment. J Alzheimers Dis 21(4):1077–1087PubMedCrossRefGoogle Scholar
  40. 40.
    El Haj M, Gallouj K, Antoine P (2017) Google calendar enhances prospective memory in Alzheimer’s disease: a case report. J Alzheimers Dis 57(1):285–291PubMedCrossRefGoogle Scholar
  41. 41.
    Brown EL, Ruggiano N, Li J, Clarke PJ, Kay ES, Hristidis V (2017) Smartphone-based health technologies for dementia care: opportunities, challenges, and current practices. J Appl Gerontol 1:733464817723088. https://doi.org/10.1177/0733464817723088PubMedCrossRefGoogle Scholar
  42. 42.
    Brown BM, Peiffer JJ, Sohrabi HR, Mondal A, Gupta VB, Rainey-Smith SR et al (2012) Intense physical activity is associated with cognitive performance in the elderly. Transl Psychiatry 2:e191. https://doi.org/10.1038/tp.2012.118PubMedPubMedCentralCrossRefGoogle Scholar
  43. 43.
    Huntley JD, Gould RL, Liu K, Smith M, Howard RJ (2015) Do cognitive interventions improve general cognition in dementia? A meta-analysis and meta-regression. BMJ Open 5(4):e005247. https://doi.org/10.1136/bmjopen-2014-005247PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Jhee S, Shiovitz T, Crawford AW, Cutler NR (2001) Beta-amyloid therapies in Alzheimer’s disease. Expert Opin Investig Drugs 10(4):593–605PubMedCrossRefGoogle Scholar
  45. 45.
    Pollack SJ, Lewis H (2005) Secretase inhibitors for Alzheimer’s disease: challenges of a promiscuous protease. Curr Opin Investig Drugs 6(1):35–47PubMedGoogle Scholar
  46. 46.
    Chen GF, Xu TH, Yan Y, Zhou YR, Jiang Y, Melcher K (2017) Amyloid beta: structure, biology and structure-based therapeutic development. Acta Pharmacol Sin 38(9):1205–1235PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Nisha CM, Kumar A, Nair P, Gupta N, Silakari C, Tripathi T et al (2016) Molecular docking and in silico ADMET study reveals acylguanidine 7a as a potential inhibitor of β-secretase. Adv Bioinforma 2016:9258578. https://doi.org/10.1155/2016/9258578CrossRefGoogle Scholar
  48. 48.
    Galimberti D, Scarpini E (2017) Pioglitazone for the treatment of Alzheimer’s disease. Expert Opin Investig Drugs 26(1):97–101PubMedCrossRefGoogle Scholar
  49. 49.
    Correia SC, Santos RX, Perry G, Zhu X, Moreira PI, Smith MA (2011) Insulin-resistant brain state: the culprit in sporadic Alzheimer’s disease? Ageing Res Rev 10(2):264–273PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Sato T, Hanyu H, Hirao K, Kanetaka H, Sakurai H, Iwamoto T (2011) Efficacy of PPAR-γ agonist pioglitazone in mild Alzheimer disease. Neurobiol Aging 32(9):1626–1633PubMedCrossRefGoogle Scholar
  51. 51.
    Cheng H, Shang Y, Jiang L, Shi TL, Wang L (2016) The peroxisome proliferators activated receptor-gamma agonists as therapeutics for the treatment of Alzheimer’s disease and mild-to-moderate Alzheimer’s disease: a meta-analysis. Int J Neurosci 126(4):299–307PubMedCrossRefPubMedCentralGoogle Scholar
  52. 52.
    Wisniewski T, Drummond E (2016) Developing therapeutic vaccines against Alzheimer’s disease. Expert Rev Vaccines 15(3):401–415PubMedPubMedCentralGoogle Scholar
  53. 53.
    Grüninger F (2015) Invited review: drug development for tauopathies. Neuropathol Appl Neurobiol 41(1):81–96PubMedCrossRefPubMedCentralGoogle Scholar
  54. 54.
    Godyń J, Jończyk J, Panek D, Malawska B (2016) Therapeutic strategies for Alzheimer’s disease in clinical trials. Pharmacol Rep 68(1):127–138PubMedCrossRefPubMedCentralGoogle Scholar
  55. 55.
    Novak P, Schmidt R, Kontsekova E, Zilka N, Kovacech B, Skrabana R et al (2017) Safety and immunogenicity of the tau vaccine AADvac1 in patients with Alzheimer’s disease: a randomised, double-blind, placebo-controlled, phase 1 trial. Lancet Neurol 16(2):123–134PubMedCrossRefGoogle Scholar
  56. 56.
    Wang C, Shou Y, Pan J, Du Y, Liu C, Wang H (2018) The relationship between cholesterol level and Alzheimer’s disease-associated APP proteolysis/Aβ metabolism. Nutr Neurosci 11:1–11. https://doi.org/10.1080/1028415X.2017.1416942
  57. 57.
    Schultz BG, Patten DK, Berlau DJ (2018) The role of statins in both cognitive impairment and protection against dementia: a tale of two mechanisms. Transl Neurodegener 7:5. https://doi.org/10.1186/s40035-018-0110-3
  58. 58.
    Li HH, Lin CL, Huang CN (2018) Neuroprotective effects of statins against amyloid β-induced neurotoxicity. Neural Regen Res 13(2):198–206PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Chu CS, Tseng PT, Stubbs B, Chen TY, Tang CH, Li DJ et al (2018) Use of statins and the risk of dementia and mild cognitive impairment: a systematic review and meta-analysis. Sci Rep 8(1):5804. https://doi.org/10.1038/s41598-018-24248-8
  60. 60.
    Münch G, Schinzel R, Loske C, Wong A, Durany N, Li JJ et al (1998) Alzheimer’s disease—synergistic effects of glucose deficit, oxidative stress and advanced glycation endproducts. J Neural Transm 105:439–461PubMedCrossRefPubMedCentralGoogle Scholar
  61. 61.
    Wong A, Luth HJ, Deuther-Conrad W, Dukic-Stefanovic S, Gasic-Milenkovic J, Arendt T et al (2001) Advanced glycation endproducts co-localize with inducible nitric oxide synthase in Alzheimer’s disease. Brain Res 920:32–40PubMedCrossRefGoogle Scholar
  62. 62.
    Venigalla M, Sonego S, Gyengesi E, Sharman MJ, Münch G (2016) Novel promising therapeutics against chronic neuroinflammation and neurodegeneration in Alzheimer’s disease. Neurochem Int 95:63–74PubMedCrossRefGoogle Scholar
  63. 63.
    Figueiredo-Pereira ME, Corwin C, Babich J (2016) Prostaglandin J2: a potential target for halting inflammation-induced neurodegeneration. Ann N Y Acad Sci 1363:125–137PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Camargo CHF, Justus FF, Retzlaff G, Blood MRY, Schafranski MD (2015) Action of anti-TNF-α drugs on the progression of Alzheimer’s disease: a case report. Dement Neuropsychol 9(2):196–200PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Butchart J, Brook L, Hopkins V, Teeling J, Püntener U, Culliford D et al (2015) Etanercept in Alzheimer disease: a randomized, placebo-controlled, double-blind, phase 2 trial. Neurology 84(21):2161–2168PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Mazzanti G, Di Giacomo S (2016) Curcumin and resveratrol in the management of cognitive disorders: what is the clinical evidence?. Molecules 21(9). https://doi.org/10.3390/molecules21091243PubMedCentralCrossRefPubMedGoogle Scholar
  67. 67.
    Barbara R, Belletti D, Pederzoli F, Masoni M, Keller J, Ballestrazzi A et al (2017) Novel Curcumin loaded nanoparticles engineered for Blood-Brain Barrier crossing and able to disrupt Abeta aggregates. Int J Pharm 526(1–2):413–424PubMedCrossRefGoogle Scholar
  68. 68.
    Liu QP, Wu YF, Cheng HY, Xia T, Ding H, Wang H et al (2016) Habitual coffee consumption and risk of cognitive decline/dementia: a systematic review and meta-analysis of prospective cohort studies. Nutrition 32:628–636PubMedCrossRefPubMedCentralGoogle Scholar
  69. 69.
    Wu L, Sun D, He Y (2017) Coffee intake and the incident risk of cognitive disorders: a dose-response meta-analysis of nine prospective cohort studies. Clin Nutr 36(3):730–736PubMedCrossRefGoogle Scholar
  70. 70.
    Camandola S, Plick N, Mattson MP (2018) Impact of coffee and cacao purine metabolites on neuroplasticity and neurodegenerative disease. Neurochem Res. https://doi.org/10.1007/s11064-018-2492-0PubMedCrossRefGoogle Scholar
  71. 71.
    Thaipisuttikul P, Galvin JE (2012) Use of medical foods and nutritional approaches in the treatment of Alzheimer’s disease. Clin Pract (Lond) 9:199–209CrossRefGoogle Scholar
  72. 72.
    Farina N, Rusted J, Tabet N (2014) The effect of exercise interventions on cognitive outcome in Alzheimer’s disease: a systematic review. Int Psychogeriatr 26:9–18PubMedPubMedCentralGoogle Scholar
  73. 73.
    Bertram S, Brixius K, Brinkmann C (2016) Exercise for the diabetic brain: how physical training may help prevent dementia and Alzheimer’s disease in T2DM patients. Endocrine 53(2):350–363PubMedCrossRefPubMedCentralGoogle Scholar
  74. 74.
    Shankle WR, Hara J, Barrentine LW, Curole MV (2016) CerefolinNAC therapy of hyperhomocysteinemia delays cortical and white matter atrophy in Alzheimer’s disease and cerebrovascular disease. J Alzheimers Dis 54(3):1073–1084PubMedCrossRefPubMedCentralGoogle Scholar
  75. 75.
    Ohnuma T, Toda A, Kimoto A, Takebayashi Y, Higashiyama R, Tagata Y et al (2016) Benefits of use, and tolerance of, medium-chain triglyceride medical food in the management of Japanese patients with Alzheimer’s disease: a prospective, open-label pilot study. Clin Interv Aging 11:29–36PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Berti V, Walters M, Sterling J, Quinn CG, Logue M, Andrews R et al (2018) Mediterranean diet and 3-year Alzheimer brain biomarker changes in middle-aged adults. Neurology 90(20):e1789–e1798. https://doi.org/10.1212/WNL.0000000000005527PubMedCrossRefPubMedCentralGoogle Scholar
  77. 77.
    Pedersen BK (2017) Anti-inflammatory effects of exercise: role in diabetes and cardiovascular disease. Eur J Clin Investig 47(8):600–611CrossRefGoogle Scholar
  78. 78.
    Zanuso S, Sacchetti M, Sundberg CJ, Orlando G, Benvenuti P, Balducci S (2017) Exercise in type 2 diabetes: genetic, metabolic and neuromuscular adaptations. A review of the evidence. Br J Sports Med 51(21):1533–1538PubMedCrossRefPubMedCentralGoogle Scholar
  79. 79.
    Rendeiro C, Rhodes JS (2018) A new perspective of the hippocampus in the origin of exercise-brain interactions. Brain Struct Funct 223(6):2527–2545. https://doi.org/10.1007/s00429-018-1665-6PubMedCrossRefPubMedCentralGoogle Scholar
  80. 80.
    Devenney KE, Sanders ML, Lawlor B, Olde Rikkert MGM, Schneider S, NeuroExercise Study Group (2017) The effects of an extensive exercise programme on the progression of Mild Cognitive Impairment (MCI): study protocol for a randomised controlled trial. BMC Geriatr 17(1):75. https://doi.org/10.1186/s12877-017-0457-9
  81. 81.
    Karssemeijer EG, Bossers WJ, Aaronson JA, Kessels RP, Olde Rikkert MG (2017) The effect of an interactive cycling training on cognitive functioning in older adults with mild dementia: study protocol for a randomized controlled trial. BMC Geriatr 17(1):73. https://doi.org/10.1186/s12877-017-0464-x
  82. 82.
    Jensen CS, Portelius E, Høgh P, Wermuth L, Blennow K, Zetterberg H et al (2017) Effect of physical exercise on markers of neuronal dysfunction in cerebrospinal fluid in patients with Alzheimer’s disease. Alzheimers Dement (N Y) 3(2):284–290Google Scholar
  83. 83.
    Barreto PS, Demougeot L, Vellas B, Rolland Y (2017) Exercise training for preventing dementia, mild cognitive impairment, and clinically meaningful cognitive decline: a systematic review and meta-analysis. J Gerontol A Biol Sci Med Sci 73(11):1504–1511. https://doi.org/10.1093/gerona/glx234CrossRefGoogle Scholar
  84. 84.
    Cavedo E, Lista S, Khachaturian Z, Aisen P, Amouyel P, Herholz K et al (2014) The road ahead to cure Alzheimer’s disease: development of biological markers and neuroimaging methods for prevention trials across all stages and target populations. J Prev Alzheimers Dis 1(3):181–202PubMedPubMedCentralGoogle Scholar
  85. 85.
    Baldeiras I, Santana I, Leitão MJ, Gens H, Pascoal R, Tábuas-Pereira M et al (2018) Addition of the Aβ42/40 ratio to the cerebrospinal fluid biomarker profile increases the predictive value for underlying Alzheimer’s disease dementia in mild cognitive impairment. Alzheimers Res Ther 10(1):33. https://doi.org/10.1186/s13195-018-0362-2
  86. 86.
    Tang X, Cai F, Ding DX, Zhang LL, Cai XY, Fang Q (2018) Magnetic resonance imaging relaxation time in Alzheimer’s disease. Brain Res Bull 140:176–189. https://doi.org/10.1016/j.brainresbull.2018.05.004PubMedCrossRefGoogle Scholar
  87. 87.
    Matsuda H (2016) MRI morphometry in Alzheimer’s disease. Ageing Res Rev 30:17–24PubMedCrossRefGoogle Scholar
  88. 88.
    Tae WS, Ham BJ, Pyun SB, Kang SH, Kim BJ (2018) Current clinical applications of diffusion-tensor imaging in neurological disorders. J Clin Neurol 14(2):129–140PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    Hua J, Liu P, Kim T, Donahue M, Rane S, Chen JJ et al (2018) MRI techniques to measure arterial and venous cerebral blood volume. Neuroimage. pii: S1053-8119(18)30115-0. https://doi.org/10.1016/j.neuroimage.2018.02.027
  90. 90.
    Schilling LP, Zimmer ER, Shin M, Leuzy A, Pascoal TA, Benedet AL et al (2016) Imaging Alzheimer’s disease pathophysiology with PET. Dement Neuropsychol 10(2):79–90PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP et al (2004) Imaging brain amyloid in Alzheimer’s disease with Pittsburgh compound-B. Ann Neurol 55(3):306–319PubMedCrossRefGoogle Scholar
  92. 92.
    Vandenberghe R, Van Laere K, Ivanoiu A, Salmon E, Bastin C, Triau E et al (2010) 18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial. Ann Neurol 68(3):319–329PubMedCrossRefGoogle Scholar
  93. 93.
    Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, Någren K et al (2009) Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 73(10):754–760PubMedPubMedCentralCrossRefGoogle Scholar
  94. 94.
    Rosenberg PB, Wong DF, Edell SL, Ross JS, Joshi AD, Brašić JR et al (2013) Cognition and amyloid load in Alzheimer disease imaged with florbetapir F 18(AV-45) positron emission tomography. Am J Geriatr Psychiatry 21(3):272–278PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Fischer FU, Wolf D, Scheurich A, Fellgiebel A (2015) Alzheimer’s disease neuroimaging I. Altered whole-brain white matter networks in preclinical Alzheimer’s disease. Neuroimage Clin 8:660–666PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Thal DR, Beach TG, Zanette M, Heurling K, Chakrabarty A, Ismail A et al (2015) [(18)F]flutemetamol amyloid positron emission tomography in preclinical and symptomatic Alzheimer’s disease: specific detection of advanced phases of amyloid-beta pathology. Alzheimers Dement 11(8):975–985PubMedCrossRefGoogle Scholar
  97. 97.
    Chiaravalloti A, Castellano AE, Ricci M, Barbagallo G, Sannino P, Ursini F et al (2018) Coupled imaging with [18F]FBB and [18F]FDG in AD subjects show a selective association between amyloid burden and cortical dysfunction in the brain. Mol Imaging Biol 20(4):659–666PubMedCrossRefGoogle Scholar
  98. 98.
    Akiyama H, Barger S, Barnum S, Bradt B, Bauer J, Cole GM et al (2000) Inflammation and Alzheimer’s disease. Neurol Aging 21(3):383–421CrossRefGoogle Scholar
  99. 99.
    Cagnin A, Brooks DJ, Kennedy AM, Gunn RN, Myers R, Turkheimer FE et al (2001) In-vivo measurement of activated microglia in dementia. Lancet 358(9280):461–457PubMedCrossRefGoogle Scholar
  100. 100.
    Carter SF, Scholl M, Almkvist O, Wall A, Engler H, Långström B et al (2012) Evidence for astrocytosis in prodromal Alzheimer disease provided by 11C-deuterium-L-deprenyl: a multitracer PET paradigm combining 11C-Pittsburgh compound B and 18F-FDG. J Nuclear Med 53(1):37–46CrossRefGoogle Scholar
  101. 101.
    Rodriguez-Vieitez E, Nordberg A (2018) Imaging neuroinflammation: quantification of astrocytosis in a multitracer PET approach. Methods Mol Biol 1750:231–251PubMedCrossRefGoogle Scholar
  102. 102.
    Sebastián-Serrano Á, de Diego-García L, Díaz-Hernández M (2018) The neurotoxic role of extracellular Tau protein. Int J Mol Sci 19(4). https://doi.org/10.3390/ijms19040998PubMedCentralCrossRefPubMedGoogle Scholar
  103. 103.
    Zimmer ER, Leuzy A, Gauthier S, Rosa-Neto P (2014) Developments in Tau PET imaging. Can J Neurol Sci 41(5):547–553PubMedCrossRefGoogle Scholar
  104. 104.
    Shimada H, Kitamura S, Shinotoh H, Endo H, Niwa F, Hirano S et al (2016) Association between Aβ and tau accumulations and their influence on clinical features in aging and Alzheimer’s disease spectrum brains: a [<sup>11</sup>C]PBB3-PET study. Alzheimers Dement (Amst) 6:11–20Google Scholar
  105. 105.
    Ishiki A, Okamura N, Furukawa K, Furumoto S, Harada R, Tomita N et al (2015) Longitudinal assessment of Tau pathology in patients with Alzheimer’s disease using [18F]THK-5117 positron emission tomography. PLoS One 10(10):e0140311. https://doi.org/10.1371/journal.pone.0140311PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Schaffer C, Sarad N, DeCrumpe A, Goswami D, Herrmann S, Morales J et al (2015) Biomarkers in the diagnosis and prognosis of Alzheimer’s disease. J Lab Autom 20(5):589–600PubMedPubMedCentralCrossRefGoogle Scholar
  107. 107.
    Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE (1997) Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 42(1):85–94PubMedCrossRefGoogle Scholar
  108. 108.
    Silverman DH, Small GW, Chang CY, Lu CS, Kung De Aburto MA et al (2001) Positron emission tomography in evaluation of dementia: regional brain metabolism and longterm outcome. JAMA 286(17):2120–2127PubMedCrossRefGoogle Scholar
  109. 109.
    Mosconi L (2005) Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging 32(4):486–510PubMedCrossRefGoogle Scholar
  110. 110.
    Scholl M, Damian A, Engler H (2014) Fluorodeoxyglucose PET in neurology and psychiatry. PET Clin 9(4):371–390CrossRefGoogle Scholar
  111. 111.
    Mosconi L, Mistur R, Switalski R, Tsui WH, Glodzik L, Li Y et al (2009) FDG-PET changes in brain glucose metabolism from normal cognition to pathologically verified Alzheimer’s disease. Eur J Nucl Med Mol Imaging 36(5):811–822PubMedPubMedCentralCrossRefGoogle Scholar
  112. 112.
    Hansson O, Zetterberg H, Buchhave P, Londos E, Blennow K, Minthon L (2006) Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 5:228–234PubMedCrossRefGoogle Scholar
  113. 113.
    Hansson O, Zetterberg H, Buchhave P, Andreasson U, Londos E, Minthon L et al (2007) Prediction of Alzheimer’s disease using the CSF Abeta42/Abeta40 ratio in patients with mild cognitive impairment. Dement Geriatr Cogn Disord 23:316–320PubMedCrossRefPubMedCentralGoogle Scholar
  114. 114.
    Wiltfang J, Esselmann H, Bibl M, Hull M, Hampel H, Kessler H et al (2007) Amyloid beta peptide ratio 42/40 but not A beta 42 correlates with phospho-Tau in patients with low- and high-CSF A beta 40 load. J Neurochem 101:1053–1059PubMedCrossRefPubMedCentralGoogle Scholar
  115. 115.
    Lewczuk P, Matzen A, Blennow K, Parnetti L, Molinuevo JL, Eusebi P et al (2017) Cerebrospinal fluid Abeta42/40 corresponds better than Abeta42 to amyloid PET in Alzheimer’s disease. J Alzheimers Dis 55:813–822PubMedPubMedCentralCrossRefGoogle Scholar
  116. 116.
    Dumurgier J, Schraen S, Gabelle A, Vercruysse O, Bombois S, Laplanche JL et al (2015) Cerebrospinal fluid amyloid-β 42/40 ratio in clinical setting of memory centers: a multicentric study. Alzheimers Res Ther 7(1):30. https://doi.org/10.1186/s13195-015-0114-5
  117. 117.
    De Roeck EE, Engelborghs S, Dierckx E (2016) Next generation brain health depends on early Alzheimer disease diagnosis: from a timely diagnosis to future population screening. J Am Med Dir Assoc 17(5):452–453PubMedCrossRefPubMedCentralGoogle Scholar
  118. 118.
    Vos SJB, Verhey F, Frolich L, Kornhuber J, Wiltfang J, Maier W et al (2015) Prevalence and prognosis of Alzheimer’s disease at the mild cognitive impairment stage. Brain 138:1327–1338PubMedPubMedCentralCrossRefGoogle Scholar
  119. 119.
    Bjerke M, Zetterberg H, Edman Å, Blennow K, Wallin A, Andreasson U (2011) Cerebrospinal fluid matrix metalloproteinases and tissue inhibitor of metalloproteinases in combination with subcortical and cortical biomarkers in vascular dementia and Alzheimer’s disease. J Alzheimers Dis 27(3):665–676PubMedCrossRefGoogle Scholar
  120. 120.
    Slaets S, Le Bastard N, Martin JJ, Sleegers K, Van Broeckhoven C, De Deyn PP et al (2013) Cerebrospinal fluid Aβ1-40 improves differential dementia diagnosis in patients with intermediate P-tau181P levels. J Alzheimers Dis 36(4):759–767PubMedCrossRefGoogle Scholar
  121. 121.
    Llorens F, Schmitz M, Ferrer I, Zerr I (2016) CSF biomarkers in neurodegenerative and vascular dementias. Prog Neurobiol 138-140:36–53PubMedCrossRefGoogle Scholar
  122. 122.
    Blennow K, Zetterberg H (2018) The past and the future of Alzheimer’s disease fluid biomarkers. J Alzheimers Dis 62(3):1125–1140PubMedPubMedCentralCrossRefGoogle Scholar
  123. 123.
    Brinkmalm A, Brinkmalm G, Honer WG, Frolich L, Hausner L, Minthon L et al (2014) SNAP-25 is a promising novel cerebrospinal fluid biomarker for synapse degeneration in Alzheimer’s disease. Mol Neurodegener 9:53. https://doi.org/10.1186/1750-1326-9-53PubMedPubMedCentralCrossRefGoogle Scholar
  124. 124.
    Ohrfelt A, Brinkmalm A, Dumurgier J, Brinkmalm G, Hansson O, Zetterberg H et al (2016) The pre-synaptic vesicle protein synaptotagmin is a novel biomarker for Alzheimer’s disease. Alzheimers Res Ther 8:41. https://doi.org/10.1186/s13195-016-0208-8
  125. 125.
    Blennow K (2017) A review of fluid biomarkers for Alzheimer’s disease: moving from CSF to blood. Neurol Ther 6(Suppl 1):15–24PubMedPubMedCentralCrossRefGoogle Scholar
  126. 126.
    Soares HD, Chen Y, Sabbagh M, Roher A, Schrijvers E, Breteler M (2009) Identifying early markers of Alzheimer’s disease using quantitative multiplex proteomic immunoassay panels. Ann N Y Acad Sci 1180:56–67PubMedCrossRefGoogle Scholar
  127. 127.
    Perneczky R, Guo LH (2016) Plasma proteomics biomarkers in Alzheimer’s disease: latest advances and challenges. Methods Mol Biol 1303:521–529CrossRefGoogle Scholar
  128. 128.
    Le Bastard N, Aerts L, Leurs J, Blomme W, De Deyn PP, Engelborghs S (2009) No correlation between time-linked plasma and CSF Abeta levels. Neurochem Int 55(8):820–825PubMedCrossRefGoogle Scholar
  129. 129.
    Vogelgsang J, Shahpasand-Kroner H, Vogelgsang R, Streit F, Vukovich R, Wiltfang J (2018) Multiplex immunoassay measurement of amyloid-β<sub>42</sub> to amyloid-β<sub>40</sub> ratio in plasma discriminates between dementia due to Alzheimer’s disease and dementia not due to Alzheimer’s disease. Exp Brain Res 236(5):1241–1250PubMedCrossRefGoogle Scholar
  130. 130.
    Mielke MM, Hagen CE, Xu J, Chai X, Vemuri P, Lowe VJ et al (2018) Plasma phospho-tau181 increases with Alzheimer’s disease clinical severity and is associated with tau- and amyloid-positron emission tomography. Alzheimers Dement. pii: S1552-5260(18)30067-0. https://doi.org/10.1016/j.jalz.2018.02.013CrossRefGoogle Scholar
  131. 131.
    Neergaard JS, Dragsbæk K, Christiansen C, Karsdal MA, Brix S, Henriksen K (2018) Two novel blood-based biomarker candidates measuring degradation of tau are associated with dementia: a prospective study. PLoS One 13(4):e0194802. https://doi.org/10.1371/journal.pone.0194802PubMedPubMedCentralCrossRefGoogle Scholar
  132. 132.
    O’Bryant SE, Xiao G, Barber R, Reisch J, Hall J, Cullum CM et al (2011) A blood-based algorithm for the detection of Alzheimer’s disease. Dement Geriatr Cogn Disord 32(1):55–62PubMedPubMedCentralCrossRefGoogle Scholar
  133. 133.
    Hye A, Riddoch-Contreras J, Baird AL, Ashton NJ, Bazenet C, Leung R et al (2014) Plasma proteins predict conversion to dementia from prodromal disease. Alzheimers Dement 10(6):799–807PubMedPubMedCentralCrossRefGoogle Scholar
  134. 134.
    Choi HJ, Byun MS, Yi D, Sohn BK, Lee JH, Lee JY et al (2017) Associations of thyroid hormone serum levels with in-vivo Alzheimer’s disease pathologies. Alzheimers Res Ther 9(1):64. https://doi.org/10.1186/s13195-017-0291-5
  135. 135.
    Weston PSJ, Poole T, Ryan NS, Nair A, Liang Y, Macpherson K et al (2017) Serum neurofilament light in familial Alzheimer disease: a marker of early neurodegeneration. Neurology 89(21):2167–2175PubMedPubMedCentralCrossRefGoogle Scholar
  136. 136.
    Cao X, Zhu M, He Y, Chu W, Du Y, Du H (2018) Increased serum acylated ghrelin levels in patients with mild cognitive impairment. J Alzheimers Dis 61(2):545–552PubMedPubMedCentralCrossRefGoogle Scholar
  137. 137.
    Ouma S, Suenaga M, Bölükbaşı Hatip FF, Hatip-Al-Khatib I, Tsuboi Y et al (2018) Serum vitamin D in patients with mild cognitive impairment and Alzheimer’s disease. Brain Behav 8(3):e00936. https://doi.org/10.1002/brb3.936PubMedPubMedCentralCrossRefGoogle Scholar
  138. 138.
    Guo R, Fan G, Zhang J, Wu C, Du Y, Ye H et al (2017) A 9-microRNA signature in serum serves as a noninvasive biomarker in early diagnosis of Alzheimer’s disease. J Alzheimers Dis 60(4):1365–1377PubMedCrossRefPubMedCentralGoogle Scholar
  139. 139.
    Wei H, Xu Y, Xu W, Zhou Q, Chen Q, Yang M et al (2018) Serum exosomal miR-223 serves as a potential diagnostic and prognostic biomarker for dementia. Neuroscience 379:167–176PubMedCrossRefPubMedCentralGoogle Scholar
  140. 140.
    Yang TT, Liu CG, Gao SC, Zhang Y, Wang PC (2018) The serum exosome derived MicroRNA-135a, -193b, and -384 were potential Alzheimer’s disease biomarkers. Biomed Environ Sci 31(2):87–89PubMedGoogle Scholar
  141. 141.
    Denk J, Oberhauser F, Kornhuber J, Wiltfang J, Fassbender K, Schroeter ML et al (2018) Specific serum and CSF microRNA profiles distinguish sporadic behavioural variant of frontotemporal dementia compared with Alzheimer patients and cognitively healthy controls. PLoS One 13(5):e0197329. https://doi.org/10.1371/journal.pone.0197329PubMedPubMedCentralCrossRefGoogle Scholar
  142. 142.
    Wu Y, Xu J, Xu J, Cheng J, Jiao D, Zhou C et al (2017) Lower serum levels of miR-29c-3p and miR-19b-3p as biomarkers for Alzheimer’s disease. Tohoku J Exp Med 242(2):129–136PubMedCrossRefPubMedCentralGoogle Scholar
  143. 143.
    Magalhães TNC, Weiler M, Teixeira CVL, Hayata T, Moraes AS, Boldrini VO et al (2017) Systemic inflammation and multimodal biomarkers in amnestic mild cognitive impairment and Alzheimer’s disease. Mol Neurobiol 55(7):5689–5697. https://doi.org/10.1007/s12035-017-0795-9PubMedCrossRefPubMedCentralGoogle Scholar
  144. 144.
    Lai KSP, Liu CS, Rau A, Lanctôt KL, Köhler CA, Pakosh M et al (2017) Peripheral inflammatory markers in Alzheimer’s disease: a systematic review and meta-analysis of 175 studies. J Neurol Neurosurg Psychiatry 88(10):876–882PubMedCrossRefGoogle Scholar
  145. 145.
    Chen A, Oakley AE, Monteiro M, Tuomela K, Allan LM, Mukaetova-Ladinska EB et al (2016) Multiplex analyte assays to characterize different dementias: brain inflammatory cytokines in poststroke and other dementias. Neurobiol Aging 38:56–67. https://doi.org/10.1016/j.neurobiolaging.2015.10.021PubMedPubMedCentralCrossRefGoogle Scholar
  146. 146.
    Choi C, Jeong JH, Jang JS, Choi K, Lee J, Kwon J et al (2008) Multiplex analysis of cytokines in the serum and cerebrospinal fluid of patients with Alzheimer’s disease by color-coded bead technology. J Clin Neurol 4(2):84–88. https://doi.org/10.3988/jcn.2008.4.2.84PubMedCrossRefGoogle Scholar
  147. 147.
    Delaby C, Gabelle A, Blum D, Schraen-Maschke S, Moulinier A, Boulanghien J et al (2015) Central nervous system and peripheral inflammatory processes in Alzheimer’s disease: biomarker profiling approach. Front Neurol 6:181. https://doi.org/10.3389/fneur.2015.00181
  148. 148.
    Hochstrasser T, Marksteiner J, Defrancesco M, Deisenhammer EA, Kemmler G, Humpel C (2011) Two blood monocytic biomarkers (CCL15 and p21) combined with the mini-mental state examination discriminate Alzheimer’s disease patients from healthy subjects. Dement Geriatr Cogn Dis Extra 1(1):297–309PubMedPubMedCentralCrossRefGoogle Scholar
  149. 149.
    Doustar J, Torbati T, Black KL, Koronyo Y, Koronyo-Hamaoui M (2017) Optical coherence tomography in Alzheimer’s disease and other neurodegenerative diseases. Front Neurol 8:701. https://doi.org/10.3389/fneur.2017.00701CrossRefPubMedPubMedCentralGoogle Scholar
  150. 150.
    Hart NJ, Koronyo Y, Black KL, Koronyo-Hamaoui M (2016) Ocular indicators of Alzheimer’s: exploring disease in the retina. Acta Neuropathol 132:767–787PubMedPubMedCentralCrossRefGoogle Scholar
  151. 151.
    Coppola G, Di Renzo A, Ziccardi L, Martelli F, Fadda A, Manni G et al (2015) Optical coherence tomography in Alzheimer’s disease: a meta-analysis. PLoS One 10:e0134750. https://doi.org/10.1371/journal.pone.0134750PubMedPubMedCentralCrossRefGoogle Scholar
  152. 152.
    Schumacher S, Nestler J, Otto T, Wegener M, Ehrentreich-Förster E, Michel D et al (2012) Highly-integrated lab-on-chip system for point-of-care multiparameter analysis. Lab Chip 12:464–473PubMedCrossRefPubMedCentralGoogle Scholar
  153. 153.
    Peter H, Wienke J, Bier FF (2017) Lab-on-a-Chip multiplex assays. Methods Mol Biol 1546:283–294PubMedCrossRefGoogle Scholar
  154. 154.
    Peter H, Wienke J, Guest PC, Bistolas N, Bier FF (2017) Lab-on-a-Chip proteomic assays for psychiatric disorders. Adv Exp Med Biol 974:339–349PubMedCrossRefGoogle Scholar
  155. 155.
    Peter H, Bistolas N, Schumacher S, Laurisch C, Guest PC, Höller U et al (2018) Lab-on-a-Chip device for rapid measurement of vitamin D levels. Methods Mol Biol 1735:477–486PubMedCrossRefGoogle Scholar
  156. 156.
    Yetisen AK, Martinez-Hurtado JL, da Cruz VF, Simsekler MC, Akram MS, Lowe CR (2014) The regulation of mobile medical applications. Lab Chip 14:833–840PubMedCrossRefGoogle Scholar
  157. 157.
    Martinez-Hurtado JL, Yetisen AK, Yun SH (2017) Multiplex smartphone diagnostics. Methods Mol Biol 1546:295–302PubMedCrossRefGoogle Scholar
  158. 158.
    Matías-García PR, Martinez-Hurtado JL (2018) Kidney smartphone diagnostics. Methods Mol Biol 1735:487–498PubMedCrossRefGoogle Scholar
  159. 159.
    Vegt J, Guest PC (2018) A user-friendly app for blood coagulation disorders. Methods Mol Biol 1735:499–504PubMedCrossRefGoogle Scholar
  160. 160.
    Matías-García PR, Martinez-Hurtado JL, Beckley A, Schmidmayr M, Seifert-Klauss V (2018) Hormonal smartphone diagnostics. Methods Mol Biol 1735:505–515PubMedCrossRefGoogle Scholar
  161. 161.
    Hartin PJ, Nugent CD, McClean SI, Cleland I, Tschanz JT, Clark CJ et al (2016) The empowering role of mobile apps in behavior change interventions: the gray matters randomized controlled trial. JMIR Mhealth Uhealth 4(3):e93. https://doi.org/10.2196/mhealth.4878PubMedPubMedCentralCrossRefGoogle Scholar
  162. 162.
    Bonn SE, Alexandrou C, Hjörleifsdottir Steiner K, Wiklander K, Östenson CG, Löf M (2018) App-technology to increase physical activity among patients with diabetes type 2—the DiaCert-study, a randomized controlled trial. BMC Public Health 18(1):119. https://doi.org/10.1186/s12889-018-5026-4
  163. 163.
    Krishna S, Boren SA, Balas EA (2009) Healthcare via cell phones: a systematic review. Telemed J E Health 15:231–240PubMedPubMedCentralCrossRefGoogle Scholar
  164. 164.
    Guo T, Patnaik R, Kuhlmann K, Rai AJ, Sia SK (2015) Smartphone dongle for simultaneous measurement of hemoglobin concentration and detection of HIV antibodies. Lab Chip 15:3514–3520PubMedCrossRefGoogle Scholar
  165. 165.
    Barbosa AI, Gehlot P, Sidapra K, Edwards AD, Reis NM (2015) Portable smartphone quantitation of prostate specific antigen (PSA) in a fluoropolymer microfluidic device. Biosens Bioelectron 70:5–14PubMedCrossRefGoogle Scholar
  166. 166.
    Liao SC, Peng J, Mauk MG, Awasthi S, Song J, Friedman H (2016) Smart cup: a minimally-instrumented, smartphone-based point-of-care molecular diagnostic device. Sens Actuators B Chem 229:232–238PubMedPubMedCentralCrossRefGoogle Scholar
  167. 167.
    Yeo SJ, Choi K, Cuc BT, Hong NN, Bao DT, Ngoc NM et al (2016) Smartphone-based fluorescent diagnostic system for highly pathogenic H5N1 viruses. Theranostics 6:231–242PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Francesca L. Guest
    • 1
  1. 1.Taunton and Somerset NHS Trust, Musgrove Park HospitalTauntonUK

Personalised recommendations