Abstract 14969: A Four Week Exercise Intervention in a Cohort of Young Army Recruits is Associated With Anti-inflammatory and Pro-antioxidant Responses
Bibliographic record
Abstract
Introduction: Regular physical activity is considered a cornerstone of cardiovascular disease prevention and is therefore strongly encouraged by most medical societies. Apart from its beneficial effects on classical cardiovascular risk factors, an anti-inflammatory effect is strongly implicated based on results from observational studies. Hypothesis: Data regarding the effect of an exercise intervention on healthy individuals are limited and contradictory. The present study aimed to investigate the effects of a physical activity intervention on the inflammatory marker S100A8/A9, the soluble form of the receptors for advanced glycation end products (sRAGE) and the anioxidant DJ-1. Methods: 332 young army recruits volunteered and 169 completed the study. The participants underwent the standard basic training of Greek army recruits which includes 2 hours of aerobic exercise, 5 times a week. Plasma S100A8/A9, sRAGE and DJ-1 were measured at the beginning and at the end of the training period. Results: At the end of the training period we observed a statistically significant reduction of S100A8/A9 (630.98 vs 472.12 ng/ml, p=0.001) and soluble RAGE (416.21 vs 225.19 pg/ml, p=0.001) while DJ-1 was significantly increased (62.48 vs 74.45 ng/ml, p<0.05). S100A8/A9 reduction was positively correlated with body weight (r=.238 [.106, .375], p=0.002), indicating that heavier individuals could benefit more from an exercise intervention. Conclusions: A 4 weeks military exercise training intervention resulted in a reduction of the pro-inflammatory S100A8/A9 complex as well as an increase of the anti-oxidant DJ- 1 protein, supporting the anti-inflammatory and anti-oxidant effects of physical activity. The observed reduction of sRAGEs was interpreted as a sign of diminished AGE-RAGE axis activation.
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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) | 0.003 | 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".