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Record W2895738698 · doi:10.1139/cjpp-2018-0467

Inhibition of microRNA-155 attenuates concanavalin-A-induced autoimmune hepatitis by regulating Treg/Th17 cell differentiation

2018· article· en· W2895738698 on OpenAlexvenueno aff
Guangtao Xia, Sensen Wu, Xia Wang, Min Fu

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
FundersNatural Science Foundation of Shandong Province
KeywordsAntagomirmiR-155Concanavalin AAutoimmune hepatitisImmunologyMedicineInflammationHepatitisInterleukin 17Autoimmune diseasemicroRNACancer researchBiologyAntibody

Abstract

fetched live from OpenAlex

Autoimmune hepatitis (AIH) is a chronic progressive autoimmune disease characterized by hepatic inflammation. This study aimed to investigate the effect of antagomir-155 on concanavalin A (ConA)-induced AIH, and its possible mechanisms. According to the results, the expression of miR-155 was raised in liver tissues after 48 h exposure to ConA. Treatment with antagomir-155 attenuated ConA-induced liver injury in mice by reducing serum alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase levels. In addition, antagomir-155 significantly alleviated the differentiation of Treg/Th17 cells in the livers of AIH mice, and suppressed Th17-cells-mediated production of pro-inflammatory cytokines IL-17A, IL-23, but not Treg-cells-mediated production of anti-inflammatory cytokine IL-10. Finally, the beneficial effect of antagomir-155 on ConA-induced AIH was abolished by administration of recombinant IL-17A. Our data demonstrated that antagomir-155 treatment could prevent AIH via regulating the differentiation of Treg and Th17 cells, suggesting that microRNA-155 may be an intriguing therapeutic target of AIH.

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 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 score0.197
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)0.0010.000

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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 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

Citations44
Published2018
Admission routes1
Has abstractyes

Explore more

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