Are the relationships between early activation of lymphocytes and cortisol or testosterone influenced by intensified cycling training in men?
Bibliographic record
Abstract
The effects of exercise training on lymphocyte responses, as well as changes in circulating endocrine parameters at rest, were investigated. Seven male cyclists participated in a 4 week high-intensity (HI) cycling training intervention. Training improved performance significantly (peak power output (PPO): 1.4%, p < 0.05; 5 km time trial: 3.8%, p < 0.01; 40 km time trial: 0.4%, p < 0.05). Resting hormone concentrations (testosterone, sex hormone binding globulin (SHBG), cortisol, corticosteroid-binding globulin (CBG), and dehydroepiandrosterone-sulphate (DHEA-S)) were unchanged, with the exception of a 20% decrease in testosterone post-HI training (p < 0.067). Subjects' CD3(+) cell counts decreased by 15% (p < 0.05), owing to significantly decreased CD4(+) cell counts and slightly lower CD8(+) and natural killer (NK) cell counts. Spontaneous in vitro CD69 expression increased in CD4(+) cells (mean +/- SD, pre: 12 +/- 6 cells x microL(-1); post: 35 +/- 37 cells x microL(-1); p < 0.05), but not in CD8(+) cells (pre: 20 +/- 29 cells x microL(-1); post: 33 +/- 16 cells x microL(-1)). Mitogen-induced CD69 expression decreased in both CD4+ (pre: 1570 +/- 1258 cells x microL(-1); post: 596 +/- 597 cells x microL(-1); p < 0.05) and CD8(+) lymphocytes (pre: 676 +/- 434 cells x microL(-1); post: 412 +/- 235 cells x microL(-1); p < 0.05). Testosterone correlated positively with several immune parameters at baseline, whereas cortisol correlated negatively with parameters of the innate immune system post-HI training. We conclude that the stress of unaccustomed exercise is evident in resting lymphocytes, but not in resting endocrine parameters. However, correlations between testosterone and cortisol and immune parameters suggest that these 2 hormones play a role in modulating immune status. Our results indicate the importance of assessing both spontaneous and mitogen-induced aspects of immune-cell activation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".