Testicular sertoli cells protect islet beta-cells from autoimmune destruction in NOD mice by a transforming growth factor-beta1-dependent mechanism.
Bibliographic record
Abstract
Testicular Sertoli cells protect pancreatic islet grafts from allo- and autoimmune destruction; however, the mechanism(s) of protection is unclear. The aim of this study was to determine whether Fas ligand (FasL) and/or transforming growth factor (TGF)-beta, immunoregulatory proteins produced by Sertoli cells, might mediate the protective effects of these cells against autoimmune destruction of islet beta-cells. Sertoli cells were purified from testes of NOD mice and implanted under the right renal capsule of diabetic NOD mice, whereas NOD islets were implanted under the left renal capsule. Of the mice that received islet and Sertoli cells grafts, 64% (9 of 14) remained normoglycemic at 60 days posttransplantation compared with 0% (0 of 6) of the mice that received islet grafts alone. Immunohistochemical examination of Sertoli cell grafts in normoglycemic mice revealed that TGF-beta1 expression by Sertoli cells remained high, whereas FasL expression by Sertoli cells decreased progressively posttransplantation. Also, plasma levels of TGF-beta1 were significantly elevated in mice that received Sertoli cells and islet grafts, and anti-TGF-beta1 antibody administration completely abrogated the protective effect of Sertoli cells on islet graft survival, whereas anti-FasL antibody did not. Islet graft destruction in anti-TGF-beta1-treated mice was associated with increases in interferon (IFN)-gamma-producing cells and decreases in interleukin (IL)-4-producing cells in the islet grafts. We conclude that 1) Sertoli cell production of TGF-beta1, not FasL, protects islet beta-cells from autoimmune destruction and 2) TGF-beta1 diverts islet-infiltrating cells from a beta-cell-destructive (IFN-gamma+) phenotype to a nondestructive (IL-4+) phenotype.
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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) | 0.001 | 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) | 0.002 | 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 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".