Improved islet recovery and efficacy through co-culture and co-transplantation of islets with human adipose-derived mesenchymal stem cells
Bibliographic record
Abstract
Islet transplantation is an established clinical procedure for select patients with type 1 diabetes and severe hypoglycemia to stabilize glycemic control. Post-transplant, substantial beta cell mass is lost, necessitating multiple donors to maintain euglycemia. A potential strategy to augment islet engraftment is the co-transplantation of islets with multipotent mesenchymal stem cells to capitalize upon their pro-angiogenic and anti-inflammatory properties. Herein, we examine the in vitro and in vivo effect of co-culturing murine islets with human adipose-derived mesenchymal stem cells (Ad-MSCs). Islets co-cultured with Ad-MSCs for 48 hours had decreased cell death, superior viability as measured by membrane integrity, improved glucose stimulated insulin secretion and reduced apoptosis compared to control islets. These observations were recapitulated with human islets, albeit tested in a limited capacity. Recipients of marginal mouse islet mass grafts, co-transplanted with Ad-MSCs without a co-culture period, did not reverse to normoglycemia as efficiently as islets alone. However, utilizing a 48-hour co-culture period, marginal mouse islets grafts with Ad-MSCs achieved a superior percent euglycemia rate when compared to islets cultured and transplanted alone. A co-culture period of human islets with human Ad-MSCs may have a clinical benefit improving engraftment outcomes.
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 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 | 0.001 | 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".