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Record W3010781360 · doi:10.1111/imm.13191

Immunological roles of intestinal mesenchymal cells

2020· review· en· W3010781360 on OpenAlexafffund
Carolyn A. Thomson, Robert J. B. Nibbs, Kathy D. McCoy, Allan McI. Mowat

Bibliographic record

VenueImmunology · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsUniversity of Calgary
FundersMedical Research CouncilCanadian Institutes of Health ResearchJuvenile Diabetes Research Foundation United Kingdom
KeywordsMesenchymal stem cellBiologyImmunologyCell biology

Abstract

fetched live from OpenAlex

The intestine is continuously exposed to an enormous variety and quantity of antigens and innate immune stimuli derived from both pathogens and harmless materials, such as food and commensal bacteria. Accordingly, the intestinal immune system is uniquely adapted to ensure appropriate responses to the different kinds of challenge; maintaining tolerance to harmless antigens in the steady-state, whilst remaining poised to deal with potential pathogens. To accomplish this, leucocytes of the intestinal immune system have to adapt to a constantly changing environment and interact with many different non-leucocytic intestinal cell types, including epithelial and endothelial cells, neurons, and a heterogenous network of intestinal mesenchymal cells (iMC). These interactions are intricately involved in the generation of protective immunity, the elaboration of inflammatory responses, and the development of inflammatory conditions, such as inflammatory bowel diseases. Here we discuss recent insights into the immunological functions of iMC under homeostatic and inflammatory conditions, focusing particularly on iMC in the mucosa and submucosa, and highlighting how an appreciation of the immunology of iMC may help understand the pathogenesis and treatment of disease.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.006

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 head0.038
GPT teacher head0.282
Teacher spread0.244 · 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; both teacher heads agree on what is shown here.

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

Citations28
Published2020
Admission routes2
Has abstractyes

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