Defining optimal immunosuppression for islet transplantation based on reduced diabetogenicity in canine islet autografts
Bibliographic record
Abstract
BACKGROUND: The recent results of clinical islet transplantation have improved substantially with the introduction of a more potent but less diabetogenic immunosuppressant protocol. The successful development of this protocol was based in part on the outcomes of studies reported herein, addressing the diabetogenic potential of a series of immunosuppressant agents used alone or in combination in a canine islet autograft model. Although it is recognized that failure to achieve long-term insulin independence in human islet allotransplantation has been multifactorial, with low engraftment mass, acute or chronic rejection, autoimmune recurrence, loss of islet-acinar integrity, heterotopic site, denervation, and insulin resistance all being implicated to varying degrees, avoidance of diabetogenic immunosuppression has been pivotal to the enhanced outcomes of clinical islet transplantation. We here explore the effects of clinically relevant doses of cyclosporine or tacrolimus when given alone or in combination with glucocorticoids on long-term canine islet autograft function. METHOD: Dogs (n=8) underwent total pancreatectomy, islet isolation, and intrasplenic autotransplantation and were normoglycemic with stable long-term graft function 3 months to 8 years posttransplant. The frequently sampled intravenous glucose tolerance test (FSIGT) was performed predrug (baseline), at 1 month of therapy (on drug), and again 1 month after withdrawal of therapy (postdrug). RESULTS: Monotherapy treatments with low- or high-dose prednisone, Neoral, or tacrolimus had minimal impact on islet autograft function. The combination of Neoral and prednisone led to a marked impairment in glucose decay (25% decline from 1.77+/-0.2 to 1.24+/-0.2, P<0.05), without significant change in insulin responsiveness or glucose effectiveness. However, insulin sensitivity was markedly impaired while on therapy (7.10+/-1.2 to 3.10+/-0.5, P<0.01). Importantly, glucose decay and insulin sensitivity failed to return to baseline after withdrawal of therapy. The combination of tacrolimus and glucocorticoids led to permanent and irreversible diabetes in all recipients (n=6, P<0.001). Similar treatment of healthy control dogs led to a 44% decrease in glucose decay (P<0.01). CONCLUSIONS: Immunosuppression must be specifically tailored for islet transplantation and be glucocorticoid free if insulin independence is to be sustained clinically.
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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) | 0.000 | 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) | 0.000 | 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".