The influence of exercise intensity and exercise mode on gastrointestinal damage
Bibliographic record
Abstract
Strenuous exercise increases gastrointestinal damage, but the dose–response relationship is yet to be elucidated. It is also commonly believed that running causes greater gastrointestinal damage than cycling. Two randomised, crossover studies aimed to 1) quantify gastrointestinal damage with increasing exercise intensity, and 2) determine if running was associated with greater gastrointestinal damage than cycling. Following a maximal oxygen uptake (V̇O 2max ) test, participants completed 3 cycling trials at different intensities (60 min at 40%, 60% and 80% V̇O 2max ; n = 10 (5 female, 5 male)) (INTENSITY), or 1 running and 1 cycling trial (45 min at 70% V̇O 2max ; n = 11 (3 female, 8 male)) (MODE). Venous blood samples were collected pre- and post-exercise to measure gastrointestinal damage via intestinal fatty acid binding protein (I-FABP). In INTENSITY, I-FABP magnitude of change was greater at 80% V̇O 2max than 40% V̇O 2max (p < 0.01). In MODE, I-FABP magnitude of change was greater with cycling (mean (SD)) (84.7 (133.2)% d = 1.07) compared with running (19.3 (33.1)%, d = 0.65) with a moderate effect (d = 0.68, p = 0.024). Rating of perceived exertion (RPE) and heart rate (HR) were higher during cycling (RPE p < 0.0001; HR p < 0.0001) but rectal temperature was not different between modes (p = 0.94). While gastrointestinal damage increases with increasing exercise intensity, running was not associated with greater gastrointestinal damage than cycling. Novelty: A fraction of the anaerobic threshold, rather than a fraction of V̇O 2max , may be more predictive of intensity that results in exercise induced gastrointestinal damage. The mode of exercise may not be as important as intensity for inducing gastrointestinal damage. Improving anaerobic threshold may reduce susceptibility to gastrointestinal damage when exercising at high intensities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".