Diabetes Is Reversed in a Murine Model by Marginal Mass Syngeneic Islet Transplantation Using a Subcutaneous Cell Pouch Device
Bibliographic record
Abstract
BACKGROUND: Islet transplantation is a successful β-cell replacement therapy for selected patients with type 1 diabetes mellitus. Although high rates of early insulin independence are achieved routinely, long-term function wanes over time. Intraportal transplantation is associated with procedural risks, requires multiple donors, and does not afford routine biopsy. Stem cell technologies may require potential for retrievability, and graft removal by hepatectomy is impractical. There is a clear clinical need for an alternative, optimized transplantation site. The subcutaneous space is a potential substitute, but transplantation of islets into this site has routinely failed to reverse diabetes. However, an implanted device, which becomes prevascularized before transplantation, may alter this equation. METHODS: Syngeneic mouse islets were transplanted subcutaneously within Sernova Corp's Cell Pouch (CP). All recipients were preimplanted with CPs 4 weeks before diabetes induction and transplantation. After transplantation, recipients were monitored for glycemic control and glucose tolerance. RESULTS: Mouse islets transplanted into the CP routinely restored glycemic control with modest delay and responded well to glucose challenge, comparable to renal subcapsular islet grafts, despite a marginal islet dose, and normoglycemia was maintained until graft explantation. In contrast, islets transplanted subcutaneously alone failed to engraft. Islets within CPs stained positively for insulin, glucagon, and microvessels. CONCLUSIONS: The CP is biocompatible, forms an environment suitable for islet engraftment, and offers a potential alternative to the intraportal site for islet and future stem cell therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".