MétaCan
Menu
Back to cohort
Record W2052169601 · doi:10.1155/2012/560817

New Insights into the Immunological Changes in IL-10-Deficient Mice during the Course of Spontaneous Inflammation in the Gut Mucosa

2012· article· en· W2052169601 on OpenAlexaff
Ana Cristina Gomes-Santos, Thaís G. Moreira, Antônio Barros de Castro, Bernardo Coelho Horta, Luísa Lemos, Déborah Nogueira Cruz, Mauro Andrade Freitas Guimarães, Denise Carmona Cara, Donna‐Marie McCafferty, Ana Maria Caetano Faria

Bibliographic record

VenueClinical and Developmental Immunology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsUniversity of Calgary
FundersFundação de Amparo à Pesquisa do Estado de Minas GeraisConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsInflammationImmunologyIntestinal mucosaBiologyPathologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

IL-10 is a regulatory cytokine that plays a major role in the homeostasis of the gut and this is illustrated by the fact that IL-10(-/-) mice develop spontaneous colitis. In this study, IL-10(-/-) mice were analyzed for immunological changes during colitis development. We found a reduced frequency of regulatory T cells CD4(+)CD25(+)Foxp3(+) and higher frequency of activated T cells in the colon that precedes the macroscopic signs of the disease. Production of IL-17 and IFN-γ was higher in the colon. Colitis progression culminates with the reduction of CD4(+)LAP(+) regulatory T cells in the intestine. Frequency of B1 cells and the secretory IgA production were both elevated. Despite these alterations, 16-week-old IL-10(-/-) mice could be rendered tolerant by a continuous feeding protocol. Our study provides detailed analysis of changes that precede colitis and it also suggests that oral tolerance could be used to design novel alternative therapies for the 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 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: Bench or experimental · Consensus signal: Bench or experimental
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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.273
Teacher spread0.254 · 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 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

Citations87
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueClinical and Developmental ImmunologySame topicImmune Response and InflammationFrench-language works237,207