Unraveling Mechanisms of Action of Probiotics
Bibliographic record
Abstract
Probiotics are defined as living organisms that, when administered in sufficient numbers, are of benefit to the host. Current evidence indicates that varying probiotic strains mediate their effects by a variety of different effects that are dependent on the dosage employed as well as the route and frequency of delivery. Some probiotics act in the lumen of the gut by elaborating antibacterial molecules such as bacteriocins; others enhance the mucosal barrier by increasing the production of innate immune molecules, including goblet cell-derived mucins and trefoil factors and defensins produced by intestinal Paneth cells; and other probiotics mediate their beneficial effects by promoting adaptive immune responses (secretory immune globulin A, regulatory T cells, interleukin-10). Some probiotics have the capacity to activate receptors in the enteric nervous system, which could be used to promote pain relief in the setting of visceral hyperalgesia. Future development of the effective use of probiotics in treating various gastroenterological disorders in human participants should take advantage of this new knowledge. The creation of novel formulations of probiotics could be directed to effectively target certain mechanisms of actions that are altered in specific disease states.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".