Different Effects of FK506, Rapamycin, and Mycophenolate Mofetil on Glucose-Stimulated Insulin Release and Apoptosis in Human Islets
Bibliographic record
Abstract
Pancreatic islet transplantation has the potential to be an effective treatment for type 1 diabetes mellitus. While recent improvements have improved 1-year outcomes, follow-up studies show a persistent loss of graft function/survival over 5 years. One possible cause of islet transplant failure is the immunosuppressant regimen required to prevent alloimmune graft rejection. Although there is evidence from separate studies, mostly in rodents and cell lines, that FK506 (tacrolimus), rapamycin (sirolimus), and mycophenolate mofetil (MMF; CellCept) can damage pancreatic beta-cells, there have been few side-by-side, multiparameter comparisons of the effects of these drugs on human islets. In the present study, we show that 24-h exposure to FK506 or MMF impairs glucose-stimulated insulin secretion in human islets. FK506 had acute and direct effects on insulin exocytosis, whereas MMF did not. FK506, but not MMF, impaired human islet graft function in diabetic NOD*scid mice. All of the immunosuppressants tested in vitro increased caspase-3 cleavage and caspase-3 activity, whereas MMF induced ER-stress to the greatest degree. Treating human islets with the GLP-1 agonist exenatide ameliorated the immunosuppressant-induced defects in glucose-stimulated insulin release. Together, our results demonstrate that immunosuppressants impair human beta-cell function and survival, and that these defects can be circumvented to a certain extent with exenatide treatment.
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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 | 0.000 |
| 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".