Surface immobilization of elastin‐like polypeptides using fluorinated surface modifying additives
Bibliographic record
Abstract
Elastin-like polypeptide (ELP) surface modification represents a valuable approach for the development of biomaterials in a wide range of medical applications. In this study, ELP surface modification has been achieved through the use of elastin cross-linking peptide (ECP) bioactive fluorinated surface modifiers (ECP-BFSMs). The synthesis of low molecular weight fluorinated additives was described and their subsequent blending with a base polycarbonate urethane (PCNU) was shown to successfully enrich the surface to allow for ELP surface cross-linking via lysine moieties on the peptide segments of the ECP-BFSMs. The kinetics for the surface migration of fluorescent ECP-BFSMs was studied over a 2-week period by two-photon confocal microscopy. A decrease in advancing contact angle from 87.9° to 75.3° was observed for ECP-BFSM modified PCNU and was associated with the presence of ECP peptides on the surface. X-ray photoelectron spectroscopy demonstrated an increase in surface atomic percent of fluorine (from 0.2 to 7.2%) and nitrogen (from 1.0 to 3.0%) associated with the surface localization of fluoro groups and amide groups associated with the peptides in the ECP-BFSMs. A further increase in surface atomic percent of nitrogen (from 3.0 to 8.3%) was observed after ELP surface cross-linking. These ELP-modified surfaces were shown to promote increased smooth muscle cell adhesion, spreading and retention over a 7-day culture period relative to their non-ELP4 analogs. This novel surface modifying additive approach may be used for various biomimetic applications since it generates a stable ECM-like surface retained onto a relatively inert fluorinated background.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| 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 | 0.001 |
| 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 teacher head, 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".