Priming and effector dependence on insulin B:9–23 peptide in NOD islet autoimmunity
Bibliographic record
Abstract
NOD mice with knockout of both native insulin genes and a mutated proinsulin transgene, alanine at position B16 in preproinsulin (B16:A-dKO mice), do not develop diabetes. Transplantation of NOD islets, but not bone marrow, expressing native insulin sequences (tyrosine at position B16) into B16:A-dKO mice rapidly restored development of insulin autoantibodies (IAAs) and insulitis, despite the recipients' pancreatic islets lacking native insulin sequences. Splenocytes from B16:A-dKO mice that received native insulin-positive islets induced diabetes when transferred into wild-type NOD/SCID or B16:A-dKO NOD/SCID mice. Splenocytes from mice immunized with native insulin B chain amino acids 9-23 (insulin B:9-23) peptide in CFA induced rapid diabetes upon transfer only in recipients expressing the native insulin B:9-23 sequence in their pancreata. Additionally, CD4(+) T cells from B16:A-dKO mice immunized with native insulin B:9-23 peptide promoted IAAs in NOD/SCID mice. These results indicate that the provision of native insulin B:9-23 sequences is sufficient to prime anti-insulin autoimmunity and that subsequent transfer of diabetes following peptide immunization requires native insulin B:9-23 expression in islets. Our findings demonstrate dependence on B16 alanine versus tyrosine of insulin B:9-23 for both the initial priming and the effector phase of NOD anti-islet autoimmunity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".