Stem cell therapies for Type 1 diabetes: current status and proposed road map to guide successful clinical trials
Bibliographic record
Abstract
Many people with Type 1 diabetes struggle with the burden of self-management and are unable to achieve optimal glycaemic control without risk of hypoglycaemia. Future therapies with the potential to reduce the risk for short- and long-term complications while simultaneously reducing the burden of diabetes are therefore attractive. β-cell replacement is one strategy which might achieve this. Islet transplantation is limited by organ supply and the risks of long-term immunosuppression. Encapsulated stem-cell-derived β cells have the potential to address both of these issues and phase I/II clinical trials of encapsulated pancreatic progenitors have begun. A significant risk associated with the translation of stem-cell science to the clinical management of Type 1 diabetes is an underestimation of the complexity of the process and a mismatch between the hype and the expectations of both people with Type 1 diabetes and the public. We provide an update on progress in clinical trials of encapsulated stem-cell-derived β cells and propose a road map for the design and conduct of future trials to facilitate the translation of this exciting science to clinical care.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".