MétaCan
Menu
Back to cohort
Record W1595069543 · doi:10.4049/jimmunol.180.7.4458

Autoimmunity to Both Proinsulin and IGRP Is Required for Diabetes in Nonobese Diabetic 8.3 TCR Transgenic Mice

2008· article· en· W1595069543 on OpenAlexaff
Balasubramanian Krishnamurthy, Lina Mariana, Shane A. Gellert, Peter G. Colman, Leonard C. Harrison, Andrew M. Lew, Pere Santamaría, Helen E. Thomas, Thomas W. H. Kay

Bibliographic record

VenueThe Journal of Immunology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProinsulinNOD miceBiologyCD8ImmunologyIsletNodImmune systemT cellCytotoxic T cellAutoimmunityDiabetes mellitusEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

T cells specific for proinsulin and islet-specific glucose-6-phosphatase catalytic subunit related protein (IGRP) induce diabetes in nonobese diabetic (NOD) mice. TCR transgenic mice with CD8(+) T cells specific for IGRP(206-214) (NOD8.3 mice) develop accelerated diabetes that requires CD4(+) T cell help. We previously showed that immune responses against proinsulin are necessary for IGRP(206-214)-specific CD8(+) T cells to expand. In this study, we show that diabetes development is dramatically reduced in NOD8.3 mice crossed to NOD mice tolerant to proinsulin (NOD-PI mice). This indicates that immunity to proinsulin is even required in the great majority of NOD8.3 mice that have a pre-existing repertoire of IGRP(206-214)-specific cells. However, protection from diabetes could be overcome by inducing islet inflammation either by a single dose of streptozotocin or anti-CD40 agonist Ab treatment. This suggests that islet inflammation can substitute for proinsulin-specific CD4(+) T cell help to activate IGRP(206-214)-specific T 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 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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

Citations56
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of ImmunologySame topicDiabetes and associated disordersFrench-language works237,207