Immune cell changes in response to a swimming training session during a 24-h recovery period
Bibliographic record
Abstract
Understanding the impact of training sessions on the immune response is crucial for the adequate periodization of training, to prevent both a negative influence on health and a performance impairment of the athlete. This study evaluated acute systemic immune cell changes in response to an actual swimming session, during a 24-h recovery period, controlling for sex, menstrual cycle phases, maturity, and age group. Competitive swimmers (30 females, 15 ± 1.3 years old; and 35 males, 16.5 ± 2.1 years old) performed a high-intensity training session. Blood samples were collected before, immediately after, 2 h after, and 24 h after exercise. Standard procedures for the assessment of leukogram by automated counting (Coulter LH 750, Beckman) and lymphocytes subsets by flow cytometry (FACS Calibur BD, Biosciences) were used. Subjects were grouped according to competitive age groups and pubertal Tanner stages. Menstrual cycle phase was monitored. The training session induced neutrophilia, lymphopenia, and a low eosinophil count, lasting for at least 2 h, independent of sex and maturity. At 24 h postexercise, the acquired immunity of juniors (15-17 years old), expressed by total lymphocytes and total T lymphocytes (CD3(+)), was not fully recovered. This should be accounted for when planning a weekly training program. The observed lymphopenia suggests a lower immune surveillance at the end of the session that may depress the immunity of athletes, highlighting the need for extra care when athletes are exposed to aggressive environmental agents such as swimming pools.
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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".