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Record W4402573466 · doi:10.1177/17455057241277072

Diet and the gut microbiota-immune axis in the context of perinatal mental health: Protocol for a prospective cohort study

2024· article· en· W4402573466 on OpenAlexafffundabout
Caroline Wallace, Marie‐Claude Audet

Bibliographic record

VenueWomen s Health · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsMedicineGut floraMental healthPsychosocialContext (archaeology)PregnancyProspective cohort studyPostpartum periodCohortPostpartum depressionCohort studyDepression (economics)ObstetricsInternal medicineImmunologyPsychiatryBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Physiological and psychosocial changes experienced by women during the perinatal period may put them at risk for postpartum mental health disturbances. Accumulating evidence suggests that dietary patterns may influence mental health through the modulation of the gut microbiota and its effects on host immune activity. Thus, targeting the gut microbiota via dietary intake could serve as both a preventative and therapeutic strategy in improving perinatal mental health. OBJECTIVES: Here, we present a protocol for a prospective cohort study that primarily aims to determine if diet quality during pregnancy is protective against postpartum depression severity. Secondary objectives will examine if microbiota- and blood-based inflammatory markers may be associated with the relationship between prenatal diet quality and postpartum depression severity, as well as with associations between additional dietary and mental health outcomes. METHODS AND ANALYSIS: Dietary patterns and mental health symptoms will be documented in 100 pregnant women at 4 time points during pregnancy and postpartum. Participants will also provide stool and blood samples at the same time points to determine microbiota composition and predicted function and inflammatory factors, respectively. Stool microbiota will be analyzed using 16S ribosomal RNA gene sequencing and bioinformatics tools (QIIME 2/PICRUSt2). Inflammatory factors will be determined using high-sensitivity antibody-based immunoassays. Statistical analyses will include linear mixed models and hierarchical linear mixed effect models. ETHICS: The study was approved by the Research Ethics Boards of the Royal Ottawa Health Care Group (#2022002) and of the University of Ottawa (#H-06-22-8013). Informed consent will be obtained from all participants before their enrollment. DISCUSSION: Findings from this study will help develop evidence-based dietary recommendations and potential interventions for women susceptible to or suffering from postpartum mental health issues that are accessible, noninvasive, and have potential to play a role in prevention and treatment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.030
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.020
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0300.009

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 head0.011
GPT teacher head0.330
Teacher spread0.319 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations1
Published2024
Admission routes3
Has abstractyes

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