Synergistic Reversal of Type 1 Diabetes in NOD Mice With Anti-CD3 and Interleukin-1 Blockade
Bibliographic record
Abstract
Inflammatory cytokines are involved in autoimmune diabetes: among the most prominent is interleukin (IL)-1β. We postulated that blockade of IL-1β would modulate the effects of anti-CD3 monoclonal antibody (mAb) in treating diabetes in NOD mice. To test this, we treated hyperglycemic NOD mice with F(ab')(2) fragments of anti-CD3 mAb with or without IL-1 receptor antagonist (IL-1RA), or anti-IL-1β mAb. We studied the reversal of diabetes and effects of treatment on the immune system. Mice that received a combination of anti-CD3 mAb with IL-1RA showed a more rapid rate of remission of diabetes than mice treated with anti-CD3 mAb or IL-1RA alone. Combination-treated mice had increased IL-5, IL-4, and interferon (IFN)-γ levels in circulation. There were reduced pathogenic NOD-relevant V7 peptide-V7(+) T cells in the pancreatic lymph nodes. Their splenocytes secreted more IL-10, had increased arginase expression in macrophages and dendritic cells, and had delayed adoptive transfer of diabetes. After 1 month, there were increased concentrations of IgG1 isotype antibodies and reduced intrapancreatic expression of IFN-γ, IL-6, and IL-17 despite normal splenocyte cytokine secretion. These studies indicate that the combination of anti-CD3 mAb with IL-1RA is synergistic in reversal of diabetes through a combination of mechanisms. The combination causes persistent remission from islet inflammation.
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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".