Psychobiotics and the Microbiota–Gut–Brain Axis: Where Do We Go from Here?
Bibliographic record
Abstract
The bidirectional relationship between the gut microbiota and the nervous system is known as the microbiota-gut-brain axis (MGBA). The MGBA controls the complex interactions between the brain, the enteric nervous system, the gut-associated immune system, and the enteric neuroendocrine systems, regulating key physiological functions such as the immune response, sleep, emotions and mood, food intake, and intestinal functions. Psychobiotics are considered tools with the potential to modulate the MGBA through preventive, adjunctive, or curative approaches, but their specific mechanisms of action on many aspects of health are yet to be characterized. This narrative review and perspectives article highlights the key paradigms needing attention as the scope of potential probiotics applications in human health increases, with a growing body of evidence supporting their systemic beneficial effects. However, there are many limitations to overcome before establishing the extent to which we can incorporate probiotics in the management of neuropsychiatric disorders. Although this article uses the term probiotics in a general manner, it remains important to study probiotics at the strain level in most cases.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".