Grafting of a model protein on lactide and caprolactone based biodegradable films for biomedical applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thermoplastic biodegradable polymers displaying elastomeric behavior and mechanical consistency are greatly appreciated for the regeneration of soft tissues and for various medical devices. However, while the selection of a suitable base material is determined by mechanical and biodegradation considerations, it is the surface properties of the biomaterial that are responsible for the biological response. In order to improve the interaction with cells and modulate their behavior, biologically active molecules can be incorporated onto the surface of the material. With this aim, the surface of a lactide and caprolactone based biodegradable elastomeric terpolymer was modified in two stages. First, the biodegradable polymer surface was aminated by atmospheric pressure plasma treatment and second a crosslinker was grafted in order to covalently bind the biomolecule. In this study, albumin was used as a model protein. According to X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM), albumin was efficiently immobilized on the surface of the terpolymer, the degree of albumin surface coverage (ΓBSA) reached ~35%. Moreover, gel permeation chromatography (GPC) studies showed that the hydrolytic degradation kinetic of the synthesized polymer was slightly delayed when albumin was grafted. However, the degradation process in the bulk of the material was unaffected, as demonstrated by Fourier transform infrared (FTIR) analyses. Furthermore, XPS analyses showed that the protein was still present on the surface after 28 days of degradation, meaning that the surface modification was stable, and that there had been enough time for the biological environment to interact with the modified material.
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.
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 | 0.000 | 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 it