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Record W4389099748 · doi:10.3390/ijms242316870

Major Depressive Disorder and Gut Microbiota: Role of Physical Exercise

2023· review· en· W4389099748 on OpenAlexaff
Pedro Borges de Souza, Laura A. Borba, Louise Castro de Jesus, Ana Paula Valverde, Joana Gil‐Mohapel, Ana Lúcia S. Rodrigues

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsGut floraMedicinePsychologyImmunology

Abstract

fetched live from OpenAlex

Major depressive disorder (MDD) has a high prevalence and is a major contributor to the global burden of disease. This psychiatric disorder results from a complex interaction between environmental and genetic factors. In recent years, the role of the gut microbiota in brain health has received particular attention, and compelling evidence has shown that patients suffering from depression have gut dysbiosis. Several studies have reported that gut dysbiosis-induced inflammation may cause and/or contribute to the development of depression through dysregulation of the gut-brain axis. Indeed, as a consequence of gut dysbiosis, neuroinflammatory alterations caused by microglial activation together with impairments in neuroplasticity may contribute to the development of depressive symptoms. The modulation of the gut microbiota has been recognized as a potential therapeutic strategy for the management of MMD. In this regard, physical exercise has been shown to positively change microbiota composition and diversity, and this can underlie, at least in part, its antidepressant effects. Given this, the present review will explore the relationship between physical exercise, gut microbiota and depression, with an emphasis on the potential of physical exercise as a non-invasive strategy for modulating the gut microbiota and, through this, regulating the gut-brain axis and alleviating MDD-related symptoms.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.355
Teacher spread0.332 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations48
Published2023
Admission routes1
Has abstractyes

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