Heparin-modified dendrimer cross-linked collagen matrices for the delivery of basic fibroblast growth factor (FGF-2)
Bibliographic record
Abstract
Tissue integration between a tissue-engineered corneal equivalent and the host eye is of critical importance in ensuring long-term implant success. A novel dendrimer cross-linked collagen scaffold has previously shown good corneal epithelial cell compatibility in vitro particularly when the highly functional dendrimer cross-linkers were functionalized to introduce additional biological groups. Herein we investigated heparinization of these materials and their potential to facilitate the delivery of basic fibroblast growth factor (FGF-2) in an active form, ultimately for use as a corneal tissue scaffold. Collagen gels cross-linked with 1-ethyl-3-(3-dimethyl aminopropyl) carbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) chemistry, and varying amounts of polypropyleneimine octaamine generation 2 (G2) dendimer and heparin were synthesized. Swelling studies and differential scanning calorimetry characterization indicated higher gel stability with the introduction of dendrimer cross-linking, which was not compromised by heparin integration. Dendrimer cross-linked gels with or without heparin gave multiple denaturation peaks, as did the heparinized EDC gels. This is thought to be the result of the heterogeneous cross-linking possible between collagen, the dendrimer and heparin. Release of FGF-2 from collagen gels showed typical first-order kinetics, with an initial burst followed by a prolonged gradual release. Heparinized dendrimer cross-linked gels released approx. 40% of the growth factor over a 2-week period, with significance maintenance of growth factor activity. Incorporation of heparin resulted in somewhat prolonged release from these systems.
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) | 0.000 | 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".