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Psychobiotics and the Microbiota–Gut–Brain Axis: Where Do We Go from Here?

2024· review· en· W4393081473 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicroorganisms · 2024
Typereview
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversité de MontréalUniversity of OttawaDalhousie UniversityLallemand (Canada)
Fundersnot available
KeywordsGut–brain axisGut floraBiologyImmunology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.019
GPT teacher head0.303
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it