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Record W1983921084 · doi:10.4161/gmic.18604

The continuum of intestinal CD4<sup>+</sup>T cell adaptations in host-microbial mutualism

2011· article· en· W1983921084 on OpenAlexfundno aff
Markus B. Geuking, Kathy D. McCoy, Andrew J. Macpherson

Bibliographic record

VenueGut Microbes · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchCanada Research ChairsSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungInselspital, Universitätsspital Bern
KeywordsBiologyHomeostasisInflammationMutualism (biology)Cell biologyDysbiosisImmunologyT cellGut floraCellImmune systemMicrobiologyGeneticsEcology

Abstract

fetched live from OpenAlex

How a mutualistic relationship between the intestinal microbiota and intestinal T cell compartments is established is important, as a breakdown of intestinal T cell homeostasis may cause inflammatory bowel diseases. A number of studies have shown that different bacterial species modulate the intestinal CD4(+) T cell compartment in different ways. We performed mechanistic in vivo studies that demonstrated the crucial requirement for regulatory T cells (Treg) and interleukin-10 (IL-10) in the induction of intestinal T cell homeostasis even following colonization with a completely benign microbiota. In the absence of a functional Treg response or IL-10 receptor signaling, the same bacteria that induced a Treg response in wild-type animals now induced T helper type 17 responses, without intestinal inflammation. Therefore, Treg, IL-10 and Th17 are crucial regulatory mechanisms in the intestine not only for controlling inflammation, but also to establish a continuum of CD4(+) T cell homeostasis upon commensal colonization.

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 score0.001
Threshold uncertainty score0.004

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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