Exercise and the Immune System: Regulation, Integration, and Adaptation
Bibliographic record
Abstract
Stress-induced immunological reactions to exercise have stimulated much research into stress immunology and neuroimmunology. It is suggested that exercise can be employed as a model of temporary immunosuppression that occurs after severe physical stress. The exercise-stress model can be easily manipulated experimentally and allows for the study of interactions between the nervous, the endocrine, and the immune systems. This review focuses on mechanisms underlying exercise-induced immune changes such as neuroendocrinological factors including catecholamines, growth hormone, cortisol, beta-endorphin, and sex steroids. The contribution of a metabolic link between skeletal muscles and the lymphoid system is also reviewed. The mechanisms of exercise-associated muscle damage and the initiation of the inflammatory cytokine cascade are discussed. Given that exercise modulates the immune system in healthy individuals, considerations of the clinical ramifications of exercise in the prevention of diseases for which the immune system has a role is of importance. Accordingly, drawing on the experimental, clinical, and epidemiological literature, we address the interactions between exercise and infectious diseases as well as exercise and neoplasia within the context of both aging and nutrition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".