Quercetin-Crosslinked Chitosan Films for Controlled Release of Antimicrobial Drugs
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
Natural polymer-based films, due to their favorable biological and mechanical properties, have demonstrated great potential as coatings for biomedical applications. Among them, chitosan films have been widely studied both as coating materials and as controlled drug release systems. Crosslinkers are often used to tune chitosan’s crosslinking degree and thus to control the drug release kinetics. For this purpose, quercetin, a plant-derived natural polyphenol, has gained attention as a crosslinker, mainly for its intrinsic anti-inflammatory, antioxidant, and antibacterial features. In this study, chitosan films crosslinked with three different concentrations of quercetin (10, 20, and 30% w/w) have been used as controlled release systems for the delivery of the antibacterial drug trimethoprim (TMP, 10% w/w). Physicochemical and antimicrobial properties were investigated. Surface wettability and composition of the films were assessed by contact angle measurements, X-ray photoelectron spectroscopy (XPS), and Fourier-transform infrared spectroscopy (FTIR), respectively. The release kinetic of TMP in phosphate-buffered saline (PBS) and 2-(N-morpholino) ethanesulfonic acid (MES) was studied over time. Finally, antibacterial properties were assessed on E. coli and S. aureus through Kirby–Bauer disc diffusion and micro-dilution broth assays. Results show that quercetin, at the tested concentrations, clearly increases the crosslinking degree in a dose-dependent manner, thus influencing the release kinetic of the loaded TMP while maintaining its bactericidal effects. In conclusion, this work demonstrates that quercetin-crosslinked chitosan films represent a promising strategy for the design of antibiotic-releasing coatings for biomedical applications.
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) | 0.001 | 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