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Record W1971757865 · doi:10.2337/db14-1223

Reduced Expression of the MDA5 Gene <i>IFIH1</i> Prevents Autoimmune Diabetes

2015· article· en· W1971757865 on OpenAlexafffund
Pamela J. Lincez, Iryna Shanina, Marc S. Horwitz

Bibliographic record

VenueDiabetes · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of British Columbia
FundersCanadian Diabetes AssociationJuvenile Diabetes Research Foundation International
KeywordsAutoimmunityBiologyMDA5GeneInterferonLocus (genetics)VirologyImmunologyRNAImmune systemRNA interferenceGenetics

Abstract

fetched live from OpenAlex

Although it is widely accepted that type 1 diabetes (T1D) is the result of the autoimmune destruction of insulin-producing β-cells in the pancreas, little is known about the events leading to islet autoimmunity. Epidemiological and genetic data have associated virus infections and antiviral type I interferon (IFN-I) response genes with T1D. Genetic variants in the T1D risk locus interferon induced with helicase C domain 1 (IFIH1) have been identified by genome-wide association studies to confer resistance to T1D and result in the reduction in expression of the intracellular RNA virus sensor known as melanoma differentiation-associated protein 5 (MDA5). Here, we translate the reduction in IFIH1 gene expression that results in protection from T1D. Our functional studies demonstrate that mice heterozygous at the Ifih1 gene express less than half the level of MDA5 protein, which leads to a unique antiviral IFN-I signature and adaptive response after virus infection that protects from T1D. IFIH1 heterozygous mice have a regulatory rather than effector T-cell response at the site of autoimmunity, supporting IFIH1 expression as an essential regulator of the diabetogenic T-cell response and providing a potential mechanism for patients carrying IFIH1 protective polymorphisms.

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 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 score0.049
Threshold uncertainty score0.522

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)0.0000.000

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 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

Citations82
Published2015
Admission routes2
Has abstractyes

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