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Record W4288074569 · doi:10.3389/fimmu.2022.924311

Structural plasticity in I-Ag7 links autoreactivity to hybrid insulin peptides in type I diabetes

2022· article· en· W4288074569 on OpenAlexafffund
Elena Erausquin, Pau Serra, Daniel Parras, Pere Santamaría, Jacinto López‐Sagaseta

Bibliographic record

VenueFrontiers in Immunology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Calgary
FundersInstituto de Salud Carlos IIICanadian Institutes of Health ResearchGeneralitat de CatalunyaMinisterio de Ciencia e InnovaciónCentres de Recerca de Catalunya
KeywordsType 1 diabetesInsulinType 2 diabetesMedicineDiabetes mellitusImmunologyEndocrinology

Abstract

fetched live from OpenAlex

We recently provided evidence for promiscuous recognition of several different hybrid insulin peptides (HIPs) by the highly diabetogenic, I-Ag7-restricted 4.1-T cell receptor (TCR). To understand the structural determinants of this phenomenon, we solved the structure of an agonistic HIP/I-Ag7complex, both in isolation as well as bound to the 4.1-TCR. We find that HIP promiscuity of the 4.1-TCR is dictated, on the one hand, by an amino acid sequence pattern that ensures I-Ag7binding and, on the other hand, by the presence of three acidic residues at positions P5, P7 and P8 that favor an optimal engagement by the 4.1-TCR’s complementary determining regions. Surprisingly, comparison of the TCR-bound and unbound HIP/I-Ag7structures reveals that 4.1-TCR binding triggers several novel and unique structural motions in both the I-Ag7molecule and the peptide that are essential for docking. This observation indicates that the type 1 diabetes-associated I-Ag7molecule is structurally malleable and that this plasticity allows the recognition of multiple peptides by individual TCRs that would otherwise be unable to do so.

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 score0.002

Distilled classifier scores by category (both heads)

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 head0.004
GPT teacher head0.205
Teacher spread0.200 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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