Granulocyte-Macrophage Colony-Stimulating Factor Prevents Diabetes Development in NOD Mice by Inducing Tolerogenic Dendritic Cells that Sustain the Suppressive Function of CD4+CD25+ Regulatory T Cells
Bibliographic record
Abstract
Autoimmune diabetes results from a breakdown of self-tolerance that leads to T cell-mediated beta-cell destruction. Abnormal maturation and other defects of dendritic cells (DCs) have been associated with the development of diabetes. Evidence is accumulating that self-tolerance can be restored and maintained by semimature DCs induced by GM-CSF. We have investigated whether GM-CSF is a valuable strategy to induce semimature DCs, thereby restoring and sustaining tolerance in NOD mice. We found that treatment of prediabetic NOD mice with GM-CSF provided protection against diabetes. The protection was associated with a marked increase in the number of tolerogenic immature splenic DCs and in the number of Foxp3+CD4+CD25+ regulatory T cells (Tregs). Activated DCs from GM-CSF-protected mice expressed lower levels of MHC class II and CD80/CD86 molecules, produced more IL-10 and were less effective in stimulating diabetogenic CD8+ T cells than DCs of PBS-treated NOD mice. Adoptive transfer experiments showed that splenocytes of GM-CSF-protected mice did not transfer diabetes into NOD.SCID recipients. Depletion of CD11c+ DCs before transfer released diabetogenic T cells from the suppressive effect of CD4+CD25+ Tregs, thereby promoting the development of diabetes. These results indicated that semimature DCs were required for the sustained suppressive function of CD4+CD25+ Tregs that were responsible for maintaining tolerance of diabetogenic T cells in NOD mice.
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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 | 0.000 |
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".