TCR transgenic mice reveal the impact of type 1 diabetes loci on early and late disease checkpoints
Bibliographic record
Abstract
Linkage analysis studies for autoimmune diabetes have revealed multiple non-major histocompatibility complex (MHC) chromosomal regions linked to disease susceptibility. To date, more than 20 insulin-dependent diabetes (Idd) loci linked to diabetes susceptibility have been identified in NOD mice and validated via congenic breeding. Importantly, evidence suggests that Idd loci may regulate at least two pathological steps during autoimmune diabetes development, namely the onset of insulitis and the transition from insulitis to overt diabetes. Here we assess the role of various non-MHC Idd diabetes-resistance loci, which have been validated in the non-transgenic setting, on autoimmune diabetes progression in the transgenic setting. Specifically, we generated multiple Idd congenic strains in the 3A9-TCR:insHEL NOD.H2(k) transgenic model and monitored their diabetes incidence. We show that 3A9-TCR:insHEL NOD.H2(k) mice congenic for Idd3 or Idd5 display a reduction in diabetes development, whereas mice congenic for Idd9 or Idd13 exhibit an increase, in comparison with 3A9-TCR:insHEL NOD.H2(k) mice. These results suggest that the presence of the 3A9-TCR and hen egg lysosyme transgenes can offset the regulatory function of certain diabetes-resistance genetic variants contained within the Idd loci, including Idd9 and Idd13. We propose the antigen-specific 3A9-TCR:insHEL transgenic model as a useful tool for the study of the genetics of autoimmune diabetes development.
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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 | 0.000 | 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 | 0.000 |
| 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".