Bioavailability of immobilized epidermal growth factor: Covalent versus noncovalent grafting
Bibliographic record
Abstract
In an effort to rationalize and optimize an antiapoptotic coating combining chondroitin sulfate (CS) and epidermal growth factor (EGF) for vascular applications, the authors here report the comparison of two grafting strategies aiming to display EGF in an oriented fashion on CS. For that purpose, the authors produced, purified, and characterized a chimeric protein corresponding to EGF that was N-terminally fused to a cysteine and a coil peptide. The chimera was covalently immobilized via its free thiol group or captured via coiled-coil interactions at the surface of a biosensor or on a chondroitin sulfate coating in multiwell plates, mimicking the coating that was previously developed by them for stent-graft surfaces. The interactions of grafted EGF with the soluble domain of its receptor or the impact of grafted EGF upon vascular smooth muscle survival in proapoptotic conditions indicated that the coiled-coil based tethering was the best approach to display EGF. These results, combined to direct enzyme-linked immunosorbent assay measurements, indicated that the coiled-coil tethering approach allowed increasing the amount of bioavailable EGF when compared to covalent coupling, rather than the total amount of grafted EGF, while using much lower concentrations of tagged EGF during incubation.
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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 | 0.000 | 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".