Transit Time Affects the Community Stability of<i>Lactobacillus</i>and<i>Bifidobacterium</i>Species in an<i>In Vitro</i>Model of Human Colonic Microbiotia
Bibliographic record
Abstract
Retention time, which is analogous to transit time, is an index for bacterial stability in the intestine. Its consideration is of particular importance to optimize the delivery of probiotic bacteria in order to improve treatment efficacy. This study aims to investigate the effect of retention time on Lactobacilli and Bifidobacteria stability using an established in vitro human colon model. Three retention times were used: 72, 96, and 144 h. The effect of retention time on cell viability of different bacterial populations was analyzed with bacterial plate counts and PCR. The proportions of intestinal Bifidobacteria, Lactobacilli, Enterococci, Staphylococci and Clostridia populations, analyzed by plate counts, were found to be the same as that in human colonic microbiota. Retention time in the human colon affected the stability of Lactobacilli and Bifidobacteria communities, with maximum stability observed at 144 h. Therefore, retention time is an important parameter that influences bacterial stability in the colonic microbiota. Future clinical studies on probiotic bacteria formulations should take into consideration gastrointestinal transit parameters to improve treatment efficacy.
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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) | 0.000 | 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".