Long‐Term Prevention of Diabetes and Marked Suppression of Insulin Autoantibodies and Insulitis in Mice Lacking Native Insulin B9–23 Sequence
Bibliographic record
Abstract
We analyzed double native insulin gene knockout NOD mice with a mutated (B16:alanine) proinsulin transgene at multiple ages for the development of insulin autoantibodies, insulitis, and diabetes. In contrast to mice with at least one copy of a native insulin gene that expressed insulin antibodies, only 2 out of 21 (10%) double native insulin gene knockout mice with a mutated insulin transgene developed insulin autoantibodies. Of 21 double insulin knockout mice sacrificed between 10 to 48 weeks of age, only 5 showed minimal insulitis versus 100% of wild-type NOD and more than 90% of insulin 1 knockout mice. Consistent with robust suppression of insulin autoantibodies and insulitis, no double insulin knockout mice developed diabetes. In that the B9-23 peptide with B16A is an altered peptide ligand inducing Th2 responses, we analyzed transfer of splenocytes into NOD.SCID mice. There was no evidence for regulatory T cells able to inhibit transfer of diabetes by diabetogenic NOD splenocytes. Insulin peptide B9-23 is likely a crucial target for initiation of islet autoimmunity and further mutation of the sequence will be tested to attempt to eliminate all anti-islet autoimmunity.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".