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Record W2138120955 · doi:10.1093/intimm/dxv004

Negative regulation of DSS-induced experimental colitis by PILRα

2015· article· en· W2138120955 on OpenAlexaff
Kazuki Kishida, Masako Kohyama, Yosuke Kurashima, Yuta Kogure, Jing Wang, Kouyuki Hirayasu, Tadahiro Suenaga, Hiroshi Kiyono, Jun Kunisawa, Hisashi Arase

Bibliographic record

VenueInternational Immunology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColitisInflammatory bowel diseaseInflammationImmunologyBiologyMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

Inflammatory bowel disease is thought to be a complex multifactorial disease, in which an increased inflammatory response plays an important role. Paired immunoglobulin-like type 2 receptor α (PILRα), well conserved in almost all mammals, is an inhibitory receptor containing immunoreceptor tyrosine-based inhibitory motifs in the cytoplasmic domain. PILRα is mainly expressed on myeloid cells and plays an important role in the regulation of inflammation. In the present study, we investigated the function of PILRα in inflammatory bowel disease using PILRα-deficient mice. When mice were orally administered dextran sulfate sodium (DSS), colonic mucosal injury and inflammation were significantly exacerbated in DSS-treated PILRα-deficient mice compared with wild-type (WT) mice. Flow cytometric analysis revealed that neutrophil and macrophage cell numbers were higher in the colons of DSS-treated PILRα-deficient mice than in those of WT mice. Blockade of CXCR2 expressed on neutrophils using a CXCR2 inhibitor decreased the severity of colitis observed in PILRα-deficient mice. These results suggest that PILRα negatively regulates inflammatory colitis by regulating the infiltration of inflammatory cells such as neutrophils and macrophages.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0040.001

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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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 designBench or experimental
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

Citations18
Published2015
Admission routes1
Has abstractyes

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