High-fat feeding, but not strenuous exercise, increases blood oxidative stress in trained men
Bibliographic record
Abstract
Two prevalent origins of oxidative stress in Western society are the ingestion of high-fat meals and the performance of strenuous exercise. The purpose of this investigation was to compare the magnitude of increase in blood oxidative stress following acute feeding and acute exercise. Twelve exercise-trained men consumed a high-fat meal or performed 1 of 3 exercise bouts (steady-state aerobic; high-intensity, moderate-duration interval sprints; maximal intensity, short-duration interval sprints) in a random order, crossover design. Blood was collected before and at times following feeding and exercise. Samples were analyzed for trigylcerides, malondialdehyde (MDA), hydrogen peroxide (H(2)O(2)), advanced oxidation protein products (AOPP), nitrate/nitrite (NOx), trolox-equivalent antioxidant capacity (TEAC), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx). A significant condition effect was noted for MDA (p = 0.01), H(2)O(2) (p < 0.0001), and AOPP (p = 0.0006), with values highest for the meal condition. An increase of 88%, 247%, and 96% was noted from pre- to post-feeding for MDA, H(2)O(2), and AOPP, respectively. A condition effect was also noted for TEAC (p = 0.04) and CAT (p = 0.05), with values lowest for the meal condition (TEAC) and the meal and aerobic exercise condition (CAT). NOx, SOD, and GPx were relatively unaffected by feeding and exercise, while MDA, H(2)O(2), and AOPP experienced little change from pre- to postexercise (p > 0.05). These results illustrate that the magnitude of blood oxidative stress following a high-fat meal is significantly greater than that elicited by either aerobic or anaerobic exercise in a sample of exercise-trained men.
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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) | 0.000 | 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".