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Record W2064248930 · doi:10.1371/journal.ppat.1000934

Epithelial p38α Controls Immune Cell Recruitment in the Colonic Mucosa

2010· article· en· W2064248930 on OpenAlexaff
Young Jun Kang, Motoyuki Otsuka, Arjen van den Berg, Lixin Hong, Zhe Huang, Xiurong Wu, Duanwu Zhang, Bruce A. Vallance, Peter S. Tobias, Jiahuai Han

Bibliographic record

VenuePLoS Pathogens · 2010
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteNational Key Research and Development Program of ChinaHigher Education Discipline Innovation ProjectNational Natural Science Foundation of ChinaNational Institutes of HealthNational Science Foundation
KeywordsImmune systemCell biologyIntestinal mucosaChemistryBiologyMicrobiologyImmunologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Intestinal epithelial cells (IECs) compose the first barrier against microorganisms in the gastrointestinal tract. Although the NF-kappaB pathway in IECs was recently shown to be essential for epithelial integrity and intestinal immune homeostasis, the roles of other inflammatory signaling pathways in immune responses in IECs are still largely unknown. Here we show that p38alpha in IECs is critical for chemokine expression, subsequent immune cell recruitment into the intestinal mucosa, and clearance of the infected pathogen. Mice with p38alpha deletion in IECs suffer from a sustained bacterial burden after inoculation with Citrobacter rodentium. These animals are normal in epithelial integrity and immune cell function, but fail to recruit CD4(+) T cells into colonic mucosal lesions. The expression of chemokines in IECs is impaired, which appears to be responsible for the impaired T cell recruitment. Thus, p38alpha in IECs contributes to the host immune responses against enteric bacteria by the recruitment of immune 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.837
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.272
Teacher spread0.238 · 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.

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

Citations20
Published2010
Admission routes1
Has abstractyes

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