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Record W4405632833 · doi:10.1016/j.yfrne.2024.101173

Gut feeling: Exploring the intertwined trilateral nexus of gut microbiota, sex hormones, and mental health

2024· review· en· W4405632833 on OpenAlexafffund
Luana Lemos Leão, Saba Miri, Riadh Hammami

Bibliographic record

VenueFrontiers in Neuroendocrinology · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsNexus (standard)FeelingGut floraHormoneMental healthBiologyGut–brain axisPsychologySocial psychologyImmunologyEndocrinologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

• Gut microbiota and sex hormones are intertwined and interconnected, impacting mental health and well-being. • Early development of the gut microbiome has profound long-term effects on mental health. • This review builds a synthesized overview from published research to connect these intertwined concepts. The complex interplay between the gut microbiota, sex hormones, and mental health is emerging as a pivotal factor in understanding and managing psychiatric disorders. Beyond their traditional roles, sex hormones exert profound effects on various physiological systems including the gut microbiota. Fluctuations in sex hormone levels, notably during the menstrual cycle, influence gut physiology and barrier function, shaping gut microbiota composition and immune responses. Conversely, the gut microbiota actively modulates sex hormone levels via enzymatic processes. This bidirectional relationship underscores the significance of the gut-brain axis in maintaining mental well-being. This review explores the multifaceted interactions between sex hormones, the gut microbiota, and mental health outcomes. We highlight the potential of personalized interventions in treating psychiatric disorders, particularly in vulnerable populations such as premenopausal women and individuals with depressive disorders. By elucidating these complex interactions, we aim to provide insights for future research into targeted interventions, enhancing mental health outcomes.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.310
Teacher spread0.273 · 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.

Study designNot applicable
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

Citations24
Published2024
Admission routes2
Has abstractyes

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