Proteins Linked to a Protein Transduction Domain Efficiently Transduce Pancreatic Islets
Bibliographic record
Abstract
The resounding success of a new immunosuppressive regimen known as the Edmonton protocol demonstrates that islet cell transplantation is becoming a therapeutic reality for diabetes. However, under the Edmonton protocol, a single donor does not provide enough islets to attain the insulin independence of a transplant recipient. This limitation is mainly caused by islet apoptosis triggered during isolation. In this study, we describe a highly efficient system of transiently transferring anti-apoptotic proteins into pancreatic islets, thus opening an exciting new therapeutic opportunity to improve the viability of transplantable islets. We fused beta-galactosidase to the 11-amino acid residues that constitute the protein transduction domain (PTD) of the HIV/TAT protein and transduced pancreatic islets ex vivo with this fusion protein in a dose-dependent manner with >80% efficiency. We observed that transduction of the anti-apoptotic proteins Bcl-X(L) and PEA-15 fused to TAT/PTD prevented apoptosis induced by tumor necrosis factor-alpha in a pancreatic beta-cell line, indicating that TAT/PTD anti-apoptotic proteins retained their biological activity. Finally, we demonstrated that TAT-fusion proteins did not affect the insulin secretion capability of islets, as determined by glucose static incubation and by reversion of hyperglycemia in diabetic immunodeficient mice.
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 | 0.000 | 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".