Tolerance to Proinsulin-2 Is Due to Radioresistant Thymic Cells
Bibliographic record
Abstract
Proinsulin is a key Ag in type 1 diabetes, but the mechanisms regulating proinsulin immune tolerance are unknown. We have shown that preproinsulin-2 gene-deficient mice (proins-2(-/-)) are intolerant to proinsulin-2. In this study, we analyzed the mechanisms underlying T cell-mediated tolerance to proinsulin-2 in 129/Sv nonautoimmune mice. The expression of one proinsulin-2 allele, whatever its parental origin, was sufficient to maintain tolerance. The site of proinsulin-2 expression relevant to tolerance was evaluated in thymus and bone marrow chimeras. CD4+ T cell reactivity to proinsulin-2 was independent of proinsulin-2 expression in radiation-sensitive bone marrow-derived cells. A wt thymus restored tolerance in proins-2(-/-) mice. Conversely, the absence of the preproinsulin-2 gene in radioresistant thymic cells was sufficient to break tolerance. Although chimeric animals had proinsulin-2-reactive CD4+ T cells in their peripheral repertoire, they displayed no insulitis or insulin Abs, suggesting additional protective mechanisms. In a model involving transfer to immunodeficient (CD3epsilon(-/-)) mice, naive and proinsulin-2-primed CD4+ T cells were not activated, but could be activated by immunization regardless of whether the recipient mice expressed proinsulin-2. Furthermore, we could not identify a role for putative specific T cells regulating proinsulin-2-reactive CD4+ T in transfer experiments. Thus, proinsulin-2 gene expression by radioresistant thymic epithelial cells is involved in the induction of self-tolerance, and additional factors are required to induce islet abnormalities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".