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Record W2956063300 · doi:10.1002/1873-3468.13527

Compositional and functional features of the female premenopausal and postmenopausal gut microbiota

2019· article· en· W2956063300 on OpenAlexaff
Hui Zhao, Juanjuan Chen, Xiaoping Li, Qiang Sun, Panpan Qin, Qi Wang

Bibliographic record

VenueFEBS Letters · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Toronto
FundersScience, Technology and Innovation Commission of Shenzhen MunicipalityShenzhen Government
KeywordsGut floraPhysiologyPostmenopausal womenRoseburiaFirmicutesEstrogenMenopauseMicrobiomeMedicineBacteroidetesBiologyInternal medicineEndocrinologyBioinformaticsLactobacillusImmunologyBacteria

Abstract

fetched live from OpenAlex

Endogenous estrogen deficiency accelerates many diseases in postmenopausal women, and gut microbes contribute to estrogen level modulation. However, the compositional alterations and influences of the gut microbiota in postmenopausal women remain uncertain. A metagenome-wide association study was performed to compare the gut microbiota of 24 premenopausal and 24 postmenopausal women. Firmicutes and Roseburia spp. are depleted, while Bacteroidetes and the toluene-producing genus Tolumonas are overrepresented in fecal samples from postmenopausal women. The pentose phosphate pathway is enriched in premenopausal women. Homocysteine synthesis-related processes are enriched in postmenopausal women. The gut microbiomes of premenopausal and postmenopausal women differ and produce different metabolites. The gut microbiome may be a therapeutic target to reduce risks and improve the quality of life in postmenopausal women.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.206
Teacher spread0.201 · 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
GenreEmpirical

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

Citations139
Published2019
Admission routes1
Has abstractyes

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