Induction of autoimmune diabetes in non-obese diabetic mice requires interleukin-21-dependent activation of autoreactive CD8+ T cells
Bibliographic record
Abstract
Non-obese diabetic (NOD) mice lacking interleukin (IL)-21 or IL-21 receptor do not develop autoimmune type 1 diabetes (T1D). We have shown recently that IL-21 may promote activation of autoreactive CD8(+) T cells by increasing their antigen responsiveness. To investigate the role of IL-21 in activating diabetogenic CD8(+) T cells in the NOD mouse, we generated IL-21-deficient NOD mice expressing the highly pathogenic major histocompatibility complex (MHC) class-I-restricted 8.3 transgenic T cell receptor (TCR). IL-21 deficiency protected 8.3-NOD mice completely from T1D. CD8(+) T cells from the 8.3-NOD.Il21(-/-) mice showed decreased antigen-induced proliferation but displayed robust antigen-specific cytolytic activity and production of effector cytokines. IL-21-deficient 8.3 T cells underwent efficient homeostatic proliferation, and previous antigen stimulation enabled these cells to cause diabetes in NOD.Scid recipients. The 8.3 T cells that developed in an IL-21-deficient environment showed impaired antigen-specific proliferation in vivo even in IL-21-sufficient mice. These cells also showed impaired IL-2 production and Il2 gene transcription following antigen stimulation. However, IL-2 addition failed to reverse their impaired proliferation completely. These findings indicate that IL-21 is required for efficient initial activation of autoreactive CD8(+) T cells but is dispensable for the activated cells to develop effector functions and cause disease. Hence, therapeutic targeting of IL-21 in T1D may inhibit activation of naive autoreactive CD8(+) T cells, but may have to be combined with other strategies to inhibit already activated cells.
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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 | 0.001 |
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".