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Record W2118871422 · doi:10.2337/diabetes.49.4.548

Co-expression of HLA DR3 and DQ8 results in the development of spontaneous insulitis and loss of tolerance to GAD65 in transgenic mice.

2000· article· en· W2118871422 on OpenAlexaff
Roshini S. Abraham, Yogish C. Kudva, S. Brian Wilson, J L Strominger, Chella S. David

Bibliographic record

VenueDiabetes · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsInstitute of Nutrition, Metabolism and Diabetes
FundersNational Institute of Allergy and Infectious Diseases
KeywordsInsulitisAlleleTransgeneGenetically modified mouseImmunologyBiologyAutoimmunityLinkage disequilibriumHuman leukocyte antigenImmune toleranceHLA-DQMajor histocompatibility complexHaplotypeHistocompatibilityGeneticsImmune systemGeneAntigen

Abstract

fetched live from OpenAlex

Specific HLA DQ and DR alleles have been associated with susceptibility to type 1 diabetes. HLA DQ8 and DQ2 have been shown to strongly predispose to disease and to be in linkage disequilibrium with at-risk DR4 and DR3 alleles, respectively. Inheritance of a mixed DR3/DR4 haplotype confers the greatest risk. A double transgenic mouse expressing both DR3 and DQ8 was generated to investigate potential major histocompatibility complex class II interactions. The DR3/DQ8 transgenic mice developed a spontaneous loss of tolerance to GAD65, in which the T-cell response to GAD65 was restricted by HLA DR. Although the mice also showed spontaneous insulitis, they did not progress to overt diabetes. Mice expressing either transgene (DQ8 or DR3) alone showed mild infiltration of their islets, which disappeared when DQ8 or DR3 was co-expressed with a resistant DR2 allele or the neutral DQ6 allele. Therefore, in a fashion analogous to human diabetes, the murine model demonstrated a requirement for a combination of at-risk DR and DQ allotypes for the initiation of spontaneous autoimmunity.

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 score0.140
Threshold uncertainty score0.259

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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations52
Published2000
Admission routes1
Has abstractyes

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