Fibroblast Cell-Based Therapy for Experimental Autoimmune Diabetes
Bibliographic record
Abstract
Type 1 diabetes (T1D) results from autoimmune destruction of insulin producing β cells of the pancreatic islets. Curbing autoimmunity at the initiation of T1D can result in recovery of residual β cells and consequently remission of diabetes. Here we report a cell-based therapy for autoimmune diabetes in non-obese diabetic (NOD) mice using dermal fibroblasts. This was achieved by a single injection of fibroblasts, expressing the immunoregulatory molecule indoleamine 2,3 dioxygenase (IDO), into peritoneal cavity of NOD mice shortly after the onset of overt hyperglycemia. Mice were then monitored for reversal of hyperglycemia and changes in inflammatory/regulatory T cell profiles. Blood glucose levels dropped into the normal range in 82% of NOD mice after receiving IDO-expressing fibroblasts while all control mice remained diabetic. We found significantly reduced islet inflammation, increased regulatory T cells, and decreased T helper 17 cells and β cell specific autoreactive CD8+ T cells following IDO cell therapy. We further showed that some of intraperitoneal injected fibroblasts migrated to local lymph nodes and expressed co-inhibitory molecules. These findings suggest that IDO fibroblasts therapy can reinstate self-tolerance and alleviate β cell autoreactivity in NOD mice, resulting in remission of 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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".