Decreased Survival of Islet Allografts in Rats with Advanced Chronic Complications of Diabetes
Bibliographic record
Abstract
Successful islet transplantation has been possible in experimental animals in contrast to humans. One difference between animal models of diabetes and human islet transplantation is the presence of advanced chronic complications in humans. Even longer-term follow-up of islet transplantation in humans according to the Edmonton protocol suggests that advanced chronic complications may adversely affect allograft survival with the glucocorticoid-free immunosuppressive regimen as well. We developed a rat model of chronic complications of diabetes and compared islet allograft survival in rats with advanced chronic complications to age-matched control rats with acute onset diabetes. Islets were transplanted at either the renal supcapsular, intrahepatic, or intramuscular location. The survival of islet allografts in rats with chronic complications was decreased at all sites compared with the age-matched controls. The best survival in the rats with advanced chronic complications occurred at the renal subcapsular site. Blood sugar measurements indicated impaired glucose tolerance in most of the rats with chronic complications and surviving renal subcapsular islet allograft. Histological and gross examination of the surviving renal subcapsular islet allografts indicated disordered angiogenesis in the rats with chronic complications. Rats with successful intrahepatic islet allografts and the respective age-matched controls had comparable blood sugars. Survival of islet allografts at the intramuscular site was poor in rats with chronic complications or acute onset diabetes. We conclude that the structural or metabolic abnormalities associated with chronic poor control of diabetes impair islet allograft survival and function. This should be considered as a possible explanation for failure of islet allograft survival in human islet transplantation.
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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) | 0.001 | 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".