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Record W2046897800 · doi:10.1097/mib.0000000000000343

Harnessing Regulatory T Cells for the Treatment of Inflammatory Bowel Disease

2015· review· en· W2046897800 on OpenAlexaff
Duke Geem, Akihito Harusato, Kyle L. Flannigan, Timothy L. Denning

Bibliographic record

VenueInflammatory Bowel Diseases · 2015
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitute of Infection and Immunity
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of General Medical SciencesNational Institutes of Health
KeywordsFOXP3ImmunologyInflammatory bowel diseaseImmune systemInflammationLamina propriaImmune toleranceRegulatory T cellAntigenBiologyMedicineDiseaseT cellIL-2 receptorPathologyEpithelium

Abstract

fetched live from OpenAlex

Regulatory CD4 T (Treg) cells are comprised of a heterogeneous population of cells that play a vital role in suppressing inflammation and maintaining immune tolerance. The immunoregulatory function of Treg cells is especially important in the intestine where the mucosa is exposed to a diverse array of foreign antigens-including those derived from food and commensal bacteria. Treg cells are enriched in the intestinal lamina propria and provide a crucial function in promoting tolerance to enteric antigens while modulating tissue inflammation. Correspondingly, Treg cell dysfunction is associated with a breakdown in intestinal tolerance and the induction of aberrant immune responses that may contribute to the pathogenesis of inflammatory bowel disease. This review will provide a brief overview of Treg cell biology with a focus on Foxp3 Treg and type 1 regulatory (Tr1) cells and summarize the evidence for defective Treg cells in experimental and human inflammatory bowel disease. The potential application of Treg cells as a treatment for inflammatory bowel disease will also be discussed in the context of Treg infusion therapy and the in vivo induction/expansion of intestinal Treg cells.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.283
Teacher spread0.255 · 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.

Study designNot applicable
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

Citations48
Published2015
Admission routes1
Has abstractyes

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