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Record W4386607312 · doi:10.1002/dev.22424

Exploring the effect of prenatal maternal stress on the microbiomes of mothers and infants: A systematic review

2023· review· en· W4386607312 on OpenAlexafffund
Jennifer Mepham, Taylor Nelles‐McGee, Krysta Andrews, Andrea González

Bibliographic record

VenueDevelopmental Psychobiology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcMaster University
FundersCanada Research Chairs
KeywordsMicrobiomePsychological interventionPsycINFOMEDLINEAnxietyMedicinePsychologyClinical psychologyBiologyBioinformaticsPsychiatry

Abstract

fetched live from OpenAlex

Prenatal maternal stress (PNMS)-characterized by exposure to stress, anxiety, depression, or intimate partner violence-has been linked to biological alterations in infants, including disruptions to their intestinal microbiota, which have long-term implications for children's developmental outcomes. Significant research has been done examining the effects of PNMS on the microbiome in animals, but less is known about these effects in human research. The current systematic review aimed to synthesize current findings on the association between PNMS and mother and infant microbiomes. Medline, Embase, PsycInfo, Web of Science, and Eric databases were searched through to February 2022. A total of eight studies (n = 2219 infants, 2202 mothers) were included in the qualitative synthesis. Findings provided promising evidence of the role that PNMS plays in altering the microbial composition, diversity, and gut immunity in mothers and infants. Notably, majority of included studies found that higher PNMS was linked to increases in genera from the phylum Proteobacteria. The factors influencing these effects are explored including nutrition, birth mode, and parenting behaviors. Potential interventions to mitigate the adverse effects of PNMS are discussed, along with recommendations for future studies with longitudinal designs to better understand the appropriate type and timing of interventions needed to promote "healthy" maternal and infant microbial functioning.

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)0.001
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.052
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.056
GPT teacher head0.330
Teacher spread0.274 · 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 designSystematic review
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

Citations18
Published2023
Admission routes2
Has abstractyes

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