Bovine colostrum, training status, and gastrointestinal permeability during exercise in the heat: a placebo-controlled double-blind study
Bibliographic record
Abstract
Heat stress can increase gastrointestinal permeability, allowing ingress of gram-negative bacterial fragments and thus potentially inflammation and ultimately endotoxemia. Permeability may rise with intense exercise, yet some data indicate that endotoxemia may be mitigated with bovine colostrum supplementation. Using a double-blind, randomised, placebo-controlled crossover study, we tested whether bovine colostrum (COL; 1.7 g·kg(-1)·day(-1) for 7 days) would attenuate physiological strain and aid exercise capacity in the heat, especially in untrained individuals. Seven trained men (T; peak oxygen uptake 64 ± 4 mL·kg(-1)·min(-1)) and 8 untrained men (UT, peak oxygen uptake 46 ± 4 mL·kg(-1)·min(-1)) exercised for 90 min in 30 °C (50 % relative humidity) after COL or placebo (corn flour). Exercise consisted of 15-min cycling at 50 % heart rate reserve (HRR) before and after 60 min of running (30 min at 80 % HRR then 30-min distance trial). Heart rate, blood pressure (Finometer), esophageal, and skin temperatures were recorded continuously. Gastrointestinal permeability was assessed from urine (double-sugar model, using high-performance liquid chromatography) and blood (intestinal fatty acid-binding protein, I-FABP). The T group ran ∼2.4 km (35%) further than the UT group in the distance trial, and I-FABP increased more in the T group than in the UT group, but physiological and performance outcomes were unaffected by colostrum supplementation, irrespective of fitness. Circulating pro- and anti-inflammatory cytokine concentrations were higher following exercise, but were not modulated by fitness or COL. Despite substantial thermal and cardiovascular strain incurred in environmental conditions in which exertional endotoxemia may occur, bovine colostrum supplementation had no observable benefit on the physiology or performance of either highly trained endurance athletes or untrained individuals.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Placebo-controlled trial of bovine colostrum on gut permeability during exercise.
This randomized exercise study evaluates bovine colostrum effects rather than research practice.
Exercise-physiology RCT-style study of colostrum and GI permeability under heat stress.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".