Type I Diabetes and Multiple Sclerosis Patients Target Islet Plus Central Nervous System Autoantigens; Nonimmunized Nonobese Diabetic Mice Can Develop Autoimmune Encephalitis
Bibliographic record
Abstract
Type I diabetes and multiple sclerosis (MS) are distinct autoimmune diseases where T cells target either islet or CNS self-proteins. Unexpectedly, we found that autoreactive T cells in diabetic patients, relatives with high diabetes risk, nonobese diabetic (NOD) mice, and MS patients routinely target classical islet as well as CNS autoantigens. The pathogenic potential of CNS autoreactivity was testable in NOD mice. Pertussis holotoxin, without additional Ags or adjuvants, allowed development of an NOD mouse-specific, autoimmune encephalitis with variable primary-progressive, monophasic, and relapsing-remitting courses. T cells from diabetic donors transferred CNS disease to pertussis toxin-pretreated NOD.scid mice, with accumulation of CD3/IFN-gamma transcripts in the brain. Diabetes and MS appear more closely related than previously perceived. NOD mouse-specific, autoimmune encephalitis provides a new MS model to identify factors that determine alternative disease outcomes in hosts with similar autoreactive T cell repertoires.
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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) | 0.002 | 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".