Impact of probiotic supplementation on exercise endurance among nonelite athletes: a randomized, placebo-controlled, double-blind, clinical trial
Bibliographic record
Abstract
This randomized, placebo-controlled, double-blind, parallel trial investigated whether generally healthy adult, nonelite runners would have a greater time-to-exhaustion during submaximal treadmill running with probiotic versus placebo supplementation. It was hypothesized that the probiotic would impact training progression by reducing gastrointestinal (GI) and cold/flu symptoms. Participants who typically ran ≥24 km/week, ran or cross-trained 3–5 days per week, and had a maximal oxygen intake (V̇O 2 max) in the 60–85th percentile were enrolled. V̇O 2 max was used to establish individualized workload settings (85% of V̇O 2 max) for the submaximal endurance tests at baseline and following 6 weeks of supplementation with a probiotic ( Lactobacillus helveticus Lafti L10, 5×10 9 CFU/capsule/day) or placebo. Participants self-reported GI and cold/flu symptoms and physical activity via daily and weekly questionnaires. Outcomes were tested using a linear model to determine if mean response values adjusted for baseline differed between groups. Twenty-eight participants ( n = 14/group), aged 25 ± 5 years (mean ± SD) with a body mass index of 23 ± 3 kg/m 2 , completed the study. At the final visit the probiotic group had a lower time-to-exhaustion versus the placebo group ( P = 0.01) due to an increase in time-to-exhaustion with the placebo (1344 ± 188 to 1565 ± 219 s, P = 0.01) with no change with the probiotic (1655 ± 230 to 1547 ± 215 s, P = 0.23). During the intervention, the probiotic group completed fewer aerobic training sessions per week ( P = 0.02) and trained at a lower intensity ( P = 0.007) versus the placebo group. Few GI and cold/flu symptoms were reported with no differences between groups. Time-to-exhaustion increased in the placebo group, possibly due to differences in training habits.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 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".