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Record W2056386675 · doi:10.1126/science.1233521

Sex Differences in the Gut Microbiome Drive Hormone-Dependent Regulation of Autoimmunity

2013· article· en· W2056386675 on OpenAlexafffund
Janet Markle, Daniel N. Frank, Steven Mortin-Toth, Charles E. Robertson, Leah M. Feazel, Ulrike Rolle‐Kampczyk, Martin von Bergen�, Kathy D. McCoy, Andrew J. Macpherson, Jayne S. Danska

Bibliographic record

VenueScience · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Human Genome Research InstituteCanadian Institutes of Health Research
KeywordsNodAutoimmunityMicrobiomeBiologyNOD miceHormoneAndrogenImmunologyTestosterone (patch)Sex hormone-binding globulinAndrogen receptorAutoimmune diseaseGut floraDiabetes mellitusAutoantibodyEndocrinologyImmune systemGeneticsCancerAntibodyProstate cancer

Abstract

fetched live from OpenAlex

Mighty Male Microbes Both genetic and environmental factors contribute to an individual's susceptibility to autoimmune disease, but the specific environmental influences are not well characterized. Markle et al. (p. 1084 , published online 17 January; see the Perspective by Flak et al. ) explored how microbial factors, in particular the gut microbiota, influence susceptibility to type 1 diabetes in mice. In the non-obese diabetic (NOD) mouse model of type 1 diabetes, female mice are significantly more susceptible to disease than males; however, this difference was not apparent under germ-free conditions. Transfer of cecal contents from male NOD mice to female NOD mice prior to disease onset protected against pancreatic islet inflammation, autoantibody production, and the development of diabetes and was associated with increased testosterone in female mice. Blocking androgen receptor activity abrogated protection. Thus, the microbiota may be able to regulate sex hormones and influence an individual's susceptibility to autoimmunity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.007
GPT teacher head0.217
Teacher spread0.211 · 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

Citations2,036
Published2013
Admission routes2
Has abstractyes

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