Developing Hybrid Polymer Scaffolds Using Peptide Modified Biopolymers for Cell Implantation
Bibliographic record
Abstract
Polymeric scaffolds containing biomimics offer exciting therapies with broad potential impact for cellular therapies and thereby potentially improve success rates. Here we report the designing and fabrication of a hybrid scaffold that can prevent a foreign body reaction and maintain cell viability. A biodegradable acrylic based cross-linkable polycaprolactone based polymer was developed and using a multihead electrospinning station to fabricate hybrid scaffolds. This consists of cell growth factor mimics and factors to prevent a foreign body reaction. Transplantation studies were performed subcutaneously and in epididymal fat pad of immuno-competent Balb/c mice and immuno-suppressed B6 Rag1 mice and we demonstrated extensive neo-vascularization and maintenance of islet cell viability in subcutaneously implanted neonatal porcine islet cells for up to 20 weeks of post-transplant. This novel approach for cell transplantation can improve the revascularization and allow the integration of bioactive molecules such as cell adhesion molecules, growth factors, etc.
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 | 0.000 |
| 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".