A Fermented Milk Product with B. lactis CNCM I-2494 and Lactic Acid Bacteria Improves Gastrointestinal Comfort in Response to a Challenge Diet Rich in Fermentable Residues in Healthy Subjects
Bibliographic record
Abstract
Background: Healthy plant-based diets rich in fermentable residues may induce gas-related symptoms. Our aim was to determine the potential of a fermented milk product with probiotics in improving digestive comfort with such diets. Methods: In an open design, a 3-day high-residue diet was administered to healthy subjects (n = 74 included, n = 63 completed) before and following 28 days consumption of a fermented milk product (FMP) containing Bifidobacterium animalis subsp. lactis CNCM I-2494 and lactic acid bacteria. Main outcomes: digestive sensations, number of daytime anal gas evacuations, and gas volume evacuated during 4 h after a probe meal. Results: As compared to the habitual diet, the high-residue diet induced gas-related symptoms (flatulence score 4.9 vs. 1.2; p ≤ 0.0001), increased the daily number of anal gas evacuations (20.7 vs. 8.7; p < 0.0001), and impaired digestive well-being (1.0 vs. 3.4; p < 0.05). FMP consumption reduced flatulence sensation (by −1.7 [−1.9; −1.6]; p < 0.0001), reduced the number of daily evacuations (by −5.8 [−6.5; −5.1]; p < 0.0001), and improved digestive well-being (by +0.6 [+0.4; +0.7]; p < 0.05). FMP consumption did not affect the gas volume evacuated after a probe meal. Conclusion: In healthy subjects, consumption of a FMP containing B. lactis CNCM I-2494 and lactic acid bacteria improves the tolerance of a flatulogenic diet by subjective and objective criteria (sensations and number of anal gas evacuations, respectively).
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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) | 0.001 | 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) | 0.001 | 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".