Defining conditions for covalent immobilization of angiogenic growth factors onto scaffolds for tissue engineering
Bibliographic record
Abstract
Rapid vascularization of engineered tissues in vitro and in vivo remains one of the key limitations in tissue engineering. We propose that angiogenic growth factors covalently immobilized on scaffolds for tissue engineering can be used to accomplish this goal. The main objectives of this work were: (a) to derive desirable experimental conditions for the covalent immobilization of vascular endothelial growth factor (VEGF) and angiopoietin-1 (Ang1) on porous collagen scaffolds; and (b) to determine whether primary endothelial cells respond to these scaffolds with covalently immobilized angiogenic factors. VEGF and Ang1 were covalently immobilized onto porous collagen scaffolds, using 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) chemistry. To improve covalent immobilization conditions: (a) different reaction buffers [phosphate-buffered saline (PBS), distilled water, or 2-(N-morpholino)ethanesulphonic acid (MES)] were used; and (b) step immobilization was compared to bulk immobilization. In step immobilization, growth factors are applied after EDC activation of the scaffold, while in bulk immobilization, reagents are simultaneously applied to the scaffold. PBS as the reaction buffer resulted in higher amounts of VEGF and Ang1 immobilized (ELISA), higher cell proliferation rates (XTT) and increased lactate metabolism compared to water and MES as the reaction buffers. Step immobilization in PBS buffer was also more effective than bulk immobilization. Immobilized growth factors resulted in higher cell proliferation and lactate metabolism compared to soluble growth factors used at comparable concentrations. Tube formation by CD31-positive cells was also observed in collagen scaffolds with immobilized VEGF or Ang1 using H5V and primary rat aortic endothelial cells but not on control scaffolds.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 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".