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Cell Biochemistry Martinsried |
1. Introduction: The overtraining syndrome as a consequence of prolonged physical exercise leads to reversible episodes of substantially lowered physical strength in combination with an increased susceptibility to opportunistic infections which may lead to life threatening disease. There are no early indicators of a beginning overtraining syndrome.
2. Goal: Early identification of endurance athletes in danger of overtraining syndrome by flow cytometric immunophenotyping of peripheral blood lymphocytes.
3. CLASSIF1
Data Pattern Classification:
A database was calculated from the CD45RO/CD4, CD45RO/CD8,
CD3/HLA-DR, CD3/CD16, CD19/blank two colour
assays in conjunction with simultaneous forward(FSC) and
sideward (SSC) light scatter analysis for a total of 72
normal/overtrained competition cyclists.
- Since no significant changes of the usual % frequency values of the
various lymphocyte populations were observed, an exhaustive analysis
of the flow cytometric list mode files was performed with 5x34=170
database columns instead of only 5x4=20 database columns on
% cell frequency analysis alone.
- Standardized and automated
data classification with the
CLASSIF1
multiparameter data classification program permitted the
>95% single case recognition of overtrained cyclists. The development
of the overtraining syndrome was paralleled by a reversible increase of
CD45RO antigen expression on the lymphocyte surface. Monitoring
this increase with time may be a means to avoid the occurrence of
overtraining syndromes in endurance athletes.
4. Conclusion: The determination of lymphocyte CD45RO antigen expression (antigen surface density) provides the >95% correct identification of an imminent overtraining syndrome by clinical cytomics. The relative frequency of the various lymphocyte populations, in contrast, is non informative.
Literature References:
L1
H Gabriel, A Urhausen, G Valet, U Heidelbach, W Kindermann: (1998)
Overtraining and immune system: A prospective longitudinal study in
endurance athletes. Med.Sci.Sports Exerc. 30:1151-1157
L2
G Valet, M Valet, D Tschöpe, H Gabriel, G Rothe,
W Kellermann, H Kahle: (1993) White cell and thrombocyte disorders:
Standardized, self-learning flow cytometric list mode data classification
with the CLASSIF1 program system. Ann.NY Acad.Sci. 677:233-251
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