Novel perspectives on therapeutic modulation of the gut microbiota
Bibliographic record
Abstract
The gut microbiota contributes to the maintenance of health and, when disrupted, may drive gastrointestinal and extragastrointestinal disease. This can occur through direct pathways such as interaction with the epithelial barrier and mucosal immune system or indirectly via production of metabolites. There is no current curative therapy for chronic inflammatory conditions such as inflammatory bowel disease, which are complex multifactorial disorders involving genetic predisposition, and environmental triggers. Therapies are directed to suppress inflammation rather than the driver, and these approaches are not devoid of adverse effects. Therefore, there is great interest in modulation of the gut microbiota to provide protection from disease. Interventions that modulate the microbiota include diet, probiotics and more recently the emergence of experimental therapies such as fecal microbiota transplant or phage therapy. Emerging data indicate that certain bacteria can induce protective immune responses and enhance intestinal barrier function, which could be potential therapeutic targets. However, mechanistic links and specific therapeutic recommendations are still lacking. Here we provide a pathophysiological overview of potential therapeutic applications of the gut microbiota.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".