Effect of exercise-induced dehydration on circulatory markers of oxidative damage and antioxidant capacity
Bibliographic record
Abstract
Dehydration is a common event associated with exercise. However, few studies have examined the effects of dehydration on plasma redox status in humans. Eighty-two athletes were recruited and baseline anthropometrics and blood samples were obtained. Athletes then engaged in a dehydration protocol, training until 3% of preweight body mass was lost. Athletes returned to the lab and had postdehydration blood collected. Athletes then consumed an isotonic drink until pre-exercise body weight was reestablished. Blood was then recollected (1 h post full rehydration (PFR)). Samples were centrifuged and the plasma snap frozen in liquid nitrogen and stored at −80 °C. Lipid and protein oxidative stress was determined by measuring F2-isoprostanes and protein carbonyls (PC), respectively. Antioxidant capacity was determined by the ferric reducing ability of plasma (FRAP) and trolox equivalent antioxidant capacity (TEAC) assays. Plasma osmolality was determined using an osmometer. Statistical analysis utilized a 1-way ANOVA with posthoc testing. Values are reported as mean ± SD. Plasma osmolality was significantly elevated immediately postdehydration (p ≤ 0.001) but decreased to baseline at PFR. Plasma TEAC increased immediately postdehydration and at PFR (p ≤ 0.001). FRAP increased immediately postdehydration (p ≤ 0.001) and decreased to below baseline at PFR (p ≤ 0.05). Conversely, F2-isoprostanes declined significantly from baseline to immediately postdehydration and then significantly rose at PFR (p ≤ 0.001), whereas PC declined at PFR (p ≤ 0.01). This study indicates that dehydration and exercise cause a significant increase in plasma osmolality and antioxidant potential immediately postexercise. We propose dehydration significantly elevates antioxidant concentration which suppresses F2-isoprostanes and PC.
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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".