Fibrin, a Scaffold Material for Islet Transplantation and Pancreatic Endocrine Tissue Engineering
Bibliographic record
Abstract
Fibrin is derived from fibrinogen during injury to produce a blood clot and thus promote wound repair. Composed of different domains, including Arg-Gly-Asp amino acid motifs, fibrin is used extensively as a hydrogel and sealant in the clinic. By binding to cell surface receptors like integrins and acting as a supportive 3D scaffold, fibrin has been useful in promoting cell differentiation, proliferation, function, and survival. In particular, fibrin has been able to maintain islet cell architecture, promote beta cell insulin secretion, and islet angiogenesis, as well as inducing a protective effect against cell death. During islet transplantation, fibrin improved neovascularization and islet function. These improvements resulted in reduced number of transplanted islets necessary to reverse diabetes. Therefore, fibrin, as a biocompatible and biodegradable scaffold, should be considered during subcutaneous islet transplantation and beta cell expansion in vitro to ensure maintenance of islet cell function, proliferation, and survival to develop effective cell-based therapies for the treatment of diabetes.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".