Vitamin C Supplementation and Salivary Immune Function Following Exercise-Heat Stress
Bibliographic record
Abstract
PURPOSE: Prolonged physical exertion and environmental heat stress may elicit postexercise depression of immune cell function, increasing upper respiratory tract infection (URTI) susceptibility. We investigated the effects of acute and short-term vitamin C (VC) compared with placebo (PL) supplementation on URTI susceptibility, salivary immunoglobulin A (s-IgA), and cortisol responses in healthy individuals following prolonged exercise-heat stress. METHODS: Twelve participants were randomized into the VC or PL group in a double-blind design. For 12 days, participants consumed 3x500 mg tablets of VC or PL per day, with testing completed at baseline, then following acute (1 d) and short-term (8 d) supplementation. Participants performed 120.1+/-49.6 min of cycling at 54+/-6% VO2max in a hot (34.8+/-1.0 degrees C and 13+/-3% relative humidity) environment, with saliva samples collected at pre-, post-, and 72 h postexercise. Health logs specifying URTI symptoms were completed for 7 days postexercise. RESULTS: A 2x3x3 mixed ANOVA with a post hoc Bonferroni correction factor revealed a significant linear trend in postexercise cortisol attenuation in the VC group, 21.7+/-15.1 nmol/L (mean+/-SD) at baseline, to 13.5+/-10.0 at acute, to 7.6+/-4.2 after short term (P=.032). No differences were detected in ratio of s-IgA to protein or URTI symptoms between groups. CONCLUSIONS: These data suggest that vitamin C supplementation can decrease postexercise cortisol in individuals performing exercise similar to that of a half-marathon or marathon in hot conditions. However, no changes in s-IgA and URTI were evident, possibly due to previous moderate training and reduced physical and psychological stress compared with athletes participating in ultramarathons.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".