Long-term function and optimization of mouse and human islet transplantation in the subcutaneous device-less site
Bibliographic record
Abstract
Clinical islet transplantation has routinely been demonstrated to be an efficacious means of restoring glycemic control in select patients with autoimmune diabetes. Notwithstanding marked progress and improvements, the broad-spectrum application of this treatment option is restricted by the complications associated with intrahepatic portal cellular infusion and the scarcity of human donor pancreata. Recent progress in stem cell biology has demonstrated that the potential to expand new β cells for clinical transplantation is now a reality. As such, research focus is being directed toward optimizing safe extrahepatic transplant sites to house future alternative β cell sources for clinical use. The present study expands on our previous development of a prevascularized subcutaneous device-less (DL) technique for cellular transplantation, by demonstrating long-term (>365 d) durable syngeneic murine islet graft function. Furthermore, histological analysis of tissue specimens collected immediately post-DL site creation and acutely post-human islet transplantation demonstrates that this technique results in close apposition of the neovascularized collagen to the transplanted cells without dead space, thereby avoiding hypoxic luminal dead-space. Murine islets transplanted into the DL site created by a larger luminal diameter (6-Fr.) (n = 11), reversed diabetes to the similar capacity as our standard DL method (5-Fr.)(n = 9). Furthermore, glucose tolerance testing did not differ between these 2 transplant groups (p > 0 .05). Taken together, this further refinement of the DL transplant approach facilitates a simplistic means of islet infusion, increases the transplant volume capacity and may provide an effective microenvironment to house future alternative β cell sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".