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Record W2946806251 · doi:10.1101/646620

Age-dependent sexual dimorphism in the adult human gut microbiota

2019· preprint· en· W2946806251 on OpenAlexfundno aff
Xiuying Zhang, Huanzi Zhong, Yufeng Li, Zhun Shi, Zhe Zhang, Xianghai Zhou, Huahui Ren, Shanmei Tang, Xueyao Han, Yuxiang Lin, Dan Wang, Fangming Yang, Chao Fang, Zuodi Fu, Lianying Wang, Shida Zhu, Yong Hou, Xun Xu, Huanming Yang, Jian Wang, Karsten Kristiansen, Junhua Li, Linong Ji

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaPeking UniversityUniversity of TorontoPeking University People's HospitalGovernment of Jiangxi ProvinceBroad Institute
KeywordsSexual dimorphismGut floraBiologyMicrobiomePopulationDemographyGut microbiomeSex characteristicsPhysiologyZoologyImmunologyBioinformaticsGenetics

Abstract

fetched live from OpenAlex

Abstract A decade of studies has established the importance of the gut microbiome in human health. In spite of sex differences in the physiology, lifespan, and prevalence of many age-associated diseases, sex and age disparities in the gut microbiota have been little studied. Here we show age-related sex differences in the adult gut microbial composition and functionality in two community-based cohorts from Northern China and the Netherlands. Consistently, women harbour a more diverse and stable microbial community across broad age ranges, whereas men exhibit a more variable gut microbiota strongly correlated with age. Reflecting the sex-biased age-gut microbiota interaction patterns, sex differences observed in younger adults are considerably reduced in the elderly population. Our findings highlight the age- and sex-biased differences in the adult gut microbiota across two ethnic population and emphasize the need for considering age and sex in studies of the human gut microbiota.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

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