Immunological Changes in Response to Exercise
Bibliographic record
Abstract
PURPOSE: This study tested the hypothesis that exercise-induced perturbation and recovery of the immune system would vary with age, puberty, and gender in healthy children and adolescents. METHODS: Twelve-year-old girls (YG; N = 14) and boys (YB; N = 20), and 14-yr-old girls (OG; N = 11) and boys (OB; N = 13) cycled for 60 min at 70% VO2max. Blood was collected before, at 30 and 60 min of exercise, and at 30 and 60 min of recovery to measure total leukocytes, leukocyte and lymphocyte subsets, and cytokines. Age and pubertal (Tanner stage) effects within genders and gender effects within age and pubertal groups were determined. RESULTS: Exercise-induced increases in lymphocytes, CD3-CD16+CD56+ counts, and IL-6 were approximately 83, 90, and 390% greater in OG versus YG (P < 0.05). Recovery leukocytosis and neutrophilia were approximately 56 and 35% greater in OB versus YB (P < 0.05). Pubertal stage did not have a statistically significant influence on responses in girls, but the lowest pubertal stage consistently showed smaller changes in lymphocytes and CD3-CD16+CD56+ counts. Recovery neutrophilia was approximately 120% greater in postpubertal boys versus prepubertal or pubertal boys (P < 0.05). Responses of lymphocytes and CD3-CD16+CD56+ counts, respectively, were approximately 120 and 82% greater in OG versus OB (P < 0.05), with no differences between YG and YB. Exercise-induced increases in total leukocytes, lymphocytes, and CD3-CD16+CD56+ counts were at least 35% greater in girls versus boys of similar pubertal status (P < 0.05). Regardless of age, puberty, or gender, IL-8 levels were significantly higher during recovery versus rest (P < 0.05). CONCLUSION: These results highlight the need to control for age, puberty, and gender when interpreting immunologic responses to exercise in a pediatric population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".