Autoantigen Recognition Is Required for Recruitment of IGRP206–214-Autoreactive CD8+ T Cells but Is Dispensable for Tolerance
Bibliographic record
Abstract
The progression of autoimmune responses is associated with an avidity maturation process driven by preferential expansion of high avidity clonotypes at the expense of their low avidity counterparts. Central and peripheral tolerance hinder the contribution of high-avidity clonotypes targeting residues 206-214 of islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP(206-214)) during the earliest stages of autoimmune diabetes. In this study, we probe the molecular determinants and biochemical consequences of IGRP(206-214)/K(d) recognition by high-, intermediate-, and low-avidity autoreactive CD8+ T cells, and we investigate the effects of genetic IGRP(206-214) silencing on their developmental biology. We find that differences in avidity for IGRP(206-214)/K(d) map to CDR1α and are associated with quantitative differences in CD3ε proline-rich sequence exposure and Nck recruitment. Unexpectedly, we find that tolerance of high-avidity CD8+ T cells, unlike their activation and recruitment into the pancreas, is dissociated from recognition of IGRP(206-214), particularly in adult mice. This finding challenges the view that tolerance of pathogenic autoreactive T cells is invariably triggered by recognition of the peptide-MHC complex that drives their activation in the periphery, indicating the existence of mechanisms of tolerance that are capable of sensing the avidity, hence pathogenicity of autoreactive T cells without the need to rely on local autoantigen availability.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".