CD28 co-stimulation restores T cell responsiveness in NOD mice by overcoming deficiencies in Rac-1/p38 mitogen-activated protein kinase signaling and IL-2 and IL-4 gene transcription
Bibliographic record
Abstract
Previously, we reported that T cell hyporesponsiveness induced by TCR ligation is causal to autoimmune diabetes in NOD mice. Neonatal CD28 co-stimulation reverses T cell hyporesponsiveness and protects NOD mice from diabetes by an IL-4-mediated mechanism, indicating that a deficiency in TCR signaling may be overcome by CD28/B7-2 co-stimulation in NOD T cells. To investigate which co-stimulation-induced signaling events mediate this protection, we analyzed the activity of Ras, Rac-1, mitogen-activated protein kinases (MAPK) and several transcription factors in TCR-activated NOD T cells in the presence or absence of CD28 co-stimulation. We show that CD28 co-stimulation restores normal TCR-induced activation of Rac-1 and p38 MAPK in NOD T cells. Deficiencies in TCR-induced nuclear expression of activating protein (AP)-1 binding proteins as well as activation of AP-1 and NF-AT in the IL-2 and IL-4 P1 promoters are also corrected by CD28 co-stimulation. Thus, CD28 co-stimulation reverses NOD T cell hyporesponsiveness by restoring TCR signaling leading to the activation of AP-1 and NF-AT during IL-2 and IL-4 gene transcription. Our findings provide additional evidence that CD28 co-stimulation amplifies signals delivered by the TCR and further explain the mechanism by which CD28 co-stimulation may protect against autoimmune diabetes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".