Comparison of Successful and Unsuccessful Islet/Sertoli Cell Cotransplant Grafts in Streptozotocin-Induced Diabetic Mice
Bibliographic record
Abstract
Sertoli cells (SC) protect islet allografts from immune destruction in diabetic rodents. In this study, we examined the difference between successful and rejected islet/SC cografts in order to further improve this procedure for optimal extension of islet allograft survival. We cotransplanted 500 BALB/c islets with 1-8 million BALB/c SC under the kidney capsule of diabetic BALB/c, C3H-HeJ, and C57BL/6 mice. Cotransplantation of islets with up to 8 million SC was not detrimental to long-term islet graft function in syngeneic mice. However, large numbers of SC were detrimental to islet graft survival in allogeneic mice with the optimal dose for cotransplantation of 4 or 1 million SC in C3H-HeJ or C57BL/6 mice, respectively. Examination of successful grafts, from euglycemic recipients, revealed the presence of SC arranged in tubule structures with islets surrounding these tubules. Cellular infiltrate in successful grafts revealed CD4 T cells and macrophages along the periphery and within the grafts, and very few CD8 T cells. Conversely, examination of unsuccessful grafts, harvested from hyperglycemic recipients at the time of rejection, revealed the presence of SC arranged randomly with islets adjacent to the Sertoli cells, when present, and massive CD4 and CD8 T cell as well as macrophage cell infiltration. Prolongation of islet allograft survival appeared to be a function of SC transplant mass and recipient genetic background. A consequence of long-term graft acceptance is the formation of SC tubule structures, which may be an additional requirement for optimal protection of islet allografts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".