Differential Regulation of Circulating Soluble Receptor for Advanced Glycation End Products (sRAGEs) and Its Ligands S100A8/A9 Four Weeks Post an Exercise Intervention in a Cohort of Young Army Recruits
Bibliographic record
Abstract
Apart from its beneficial effects on cardiovascular risk factors, an anti-inflammatory effect of exercise is strongly implicated. Yet, 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 soluble form of the receptor for advanced glycation end products (sRAGEs) and its ligands S100A8/A9. A total of 332 young army recruits volunteered and 169 completed the study. The participants underwent the standard basic training of Greek army recruits. IL-6, IL-1β, S100A8/A9, and sRAGEs were measured at the beginning and at the end of the training period. Primary rodent adult aortic smooth muscle cells (ASMCs) were analyzed for responsiveness to direct stimulation with S100A8/A9 alone or in combination with sRAGEs. At the end of the training period, we observed a statistically significant reduction in S100A8/A9 (630.98 vs. 472.12 ng/mL, p = 0.001), IL-1β (9.39 [3.8, 44.14] vs. 5.03 [2.44, 27.3] vs. pg/mL, p = 0.001), and sRAGEs (398.38 vs. 220.1 pg/mL, p = 0.001). IL-6 values did not change significantly after exercise. S100A8/A9 reduction was positively correlated with body weight (r = 0.236 [0.095, 0.370], p = 0.002) and BMI (r = 0.221 [0.092, 0.346], p = 0.004). Direct stimulation of ASMCs with S100A8/A9 increased the expression of IL-6, IL-1β, and TNF-α and, in the presence of sRAGEs, demonstrated a dose-dependent inhibition. A 4-week military training resulted in significant reduction in the pro-inflammatory cytokines IL-1β and S100A8/A9 complex. The observed reduction in sRAGEs may possibly reflect diminished RAGE axis activation. Altogether, our findings support the anti-inflammatory properties of physical activity.
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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".