Advertisement

Characterizing Blood Cells by Biophysical Measurements in Flow

  • W. Groner
  • D. Tycko
Conference paper

Abstract

One effect of automation in the hematology laboratory has been to introduce new characterizations of blood cells. Resistive pulse sensing (Coulter) and light scatter measurements in flow provide rapid and reproducible cell counts. They also provide information about red cell size, shape, and deformability. Thus, they have provided new characterization of these cells in terms of their biophysical properties. Leukocytes have been classified by optical scatter and absorption measurements in flow after being stained cytochemically. This provides rapid and precise WBC differential counts. However, here again, additional information about relative cell-enzyme content or activity is also accessible to provide a new characterization of the leukocytes. The ultimate range of utility of this expanding technology in the automated hematology laboratory of the future will, of course, depend upon establishing relations between the biophysical parameters and the functions of the cells. This, in turn, must depend upon the use of the technology by researchers and clinicians in studying cell function and the aberrations of these functions which define disease.

Key Words

Blood cells Hematology Flow cytometry Light scattering Leukocytes. 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    BESSMAN, J. D.: Erythropoiesis during recovery from iron deficiency: Normocytes and macrocytes. Blood 50, 987, 1977 PubMedGoogle Scholar
  2. 2.
    BESSMAN, J. D., FEINSTEIN, D. I.: Quantitative anisocytosis as a discriminant between iron deficiency and thalassemia minor. Blood 53, 288–293 1979 PubMedGoogle Scholar
  3. 3.
    BESSIS, M., MEL, H.: Hematology without the microscope. Blood Cells 1, 401–403, 1975 Google Scholar
  4. 4.
    BESSIS, M., MOHANDAS, N.: A diffractometric method for the measurement of cellular deformability. Blood Cells 1, 307–313, 1975 Google Scholar
  5. 5.
    BØYUM, A.: Isolation of mononuclear cells and granulocytes from human blood. Scand. J. Clin. Lab. Invest. 21 [Suppl. 97], 77, 1968 Google Scholar
  6. 6.
    COOKE, W. E.: Clinical Interpretation of Aids to Diagnosis. London, The Lancet J. 1930, p. 81Google Scholar
  7. 7.
    DAVE, J. V.: Subroutines for computing the parameters of electro-magnetic radiation scattered by a sphere. IBM Palo Alto Scientific Center Report No. 320–327, May 1968 Google Scholar
  8. 8.
    EINSTEIN, A.: J. Ann. Physik 33, 1275, 1910 CrossRefGoogle Scholar
  9. 9.
    KERKER, M.: The Scattering of Light and Other Electromagnetic Radiation. New York, Academic 1969 Google Scholar
  10. 10.
    KUBITSCHEK, H. E.: Electronic measurement of particle size. Res. Appl. Ind. 13, 1960 Google Scholar
  11. 11.
    LEWIS, S. M., BENTLEY, S. A.: Haemocytometry by laser-beam optics: Evaluation of the Hemac 630L. J. Clin. Pathol. 30, 54, 1977 PubMedCrossRefGoogle Scholar
  12. 12.
    MAXWELL, J. C.: A Treatise on Electricity and Magnetism, Vol. I, 3rd edn. Oxford, Clarendon, 1904, p. 440Google Scholar
  13. 13.
    MEL, H. C., YEE, J. P.: Erythrocyte size and deformability studies by resistive pulse spectroscopy. Blood Cells 1, 391–399, 1975 Google Scholar
  14. 14.
    O’BRIEN, R., CARDENOSA, G., SAMBUCETTI, L., PODOLAK, P.: Spectral characteristics of human leukocytes and their relevance to automated cell identification, III. Eosinophils, neutrophils and lymphocytes. Acta Cytol. 23, 231–236, 1979 PubMedGoogle Scholar
  15. 15.
    ORNSTEIN, L., ANSLEY, H., SAUNDERS, A.: Improving manual differential white cell counts with cytochemistry. Blood Cells 2, 557–585, 1976Google Scholar
  16. 16.
    PANGLAIS, G. A., WALDMAN, S. R., RAPPAPORT, H.: Cytochemical Findings in Human Nonneoplastic Blood and Tonsillar B and T Lymphocytes. Dept. Anatomic Pathology, City of Hope, Natl. Med. Center, Duarte, CA, 1977 Google Scholar
  17. 17.
    PIERRE, R. V., O’SULLIVAN, M. B.: Evaluation of the Hemalog D automated differential counter. Mayo Clin. Proc. 49, 870, 1974 PubMedGoogle Scholar
  18. 18.
    PONDER, E.: Hemolysis and Related Phenomena. New York, Grune and Stratton, 1948 Google Scholar
  19. 19.
    SCHILLING, V.: The Blood Picture (Translation). St. Louis, C.V. Mosby, 1929 Google Scholar
  20. 20.
    SIMMONS, A., LEAVERTON, P., ELBERT, G.: Normal laboratory values for differential white cell counts established by manual and automated cytochemical methods (Hemalog D™). J. Clin. Pathol. 27, 55–58, 1974 PubMedCrossRefGoogle Scholar
  21. STENGLE, J.M., STRUMA, M.M., LIDDY, T.J., BRECHER, G.: Mean corpuscular haemoglobin concentration and mean corpuscular volume as biologic constants. In: DE BOROVICZENY, C.G., ed., Standardization, Documentation and Normal Values in Hematology. Bibl. Haematol. (Basel) 21, 4, 1965Google Scholar
  22. KOERPER, M.A., MENTZER, W.C., BRECHER, G., DALLMAN, P.R. : Developmental changes in the red blood cell volume. Implications for screening infants and children for iron deficiency and thalassemia trait. J. Pediatr. 80, 580, 1976 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1981

Authors and Affiliations

  • W. Groner
    • 1
  • D. Tycko
    • 2
  1. 1.Technicon Instruments CorporationTarrytownUSA
  2. 2.State University of New York (SUNY)Stony BrookUSA

Personalised recommendations