Engineered Robust Hydrophobic/Hydrophilic Nanofibrous Scaffolds with Drug-Eluting, Antioxidant, and Antimicrobial Capacity
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
Multifunctional nanofibrous architectures have attracted extensive attention for biomedical applications due to their adjustable and versatile properties. Electrospun fabrics stand out as key building blocks for these structures, yet improving their mechanobiological and physicochemical performance is a challenge. Here, we introduce biodegradable engineered hydrophobic/hydrophilic scaffolds consisting of electrospun polylactide nanofibers coated with drug-eluting synthetic (poly(vinyl alcohol)) and natural (starch) polymers. The microstructure of these composite scaffolds was tailored for an increased hydrophilicity, optimized permeability, water retention capacity of up to 5.1 g/g, and enhanced mechanical properties under both dry and wet conditions. Regarding the latter, normalized tensile strengths of up to 32.4 MPa were achieved thanks to the improved fiber interactions and fiber-coating stress transfer. Curcumin was employed as a model drug, and its sustained release in a pure aqueous medium was investigated for 35 days. An in-depth study of the release kinetics revealed the outstanding water solubility and bioavailability of curcumin, owing to its complexation with the hydrophilic polymers and further delineated the role of the hydrophobic nanofibrous network in regulating its release rate. The modified curcumin endowed the composites with antioxidant activities up to 5.7 times higher than that of free curcumin as well as promising anti-inflammatory and bacteriostatic activities. The cytocompatibility and cell proliferation capability on human dermal fibroblasts also evidenced the safe use of the constructs. Finally, the fabrics present pH-responsive color-changing behavior easily distinguishable within the pH range of 5-9. Thus, these designs offer a facile and cost-effective roadmap for the fabrication of smart multifunctional biomaterials, especially for chronic wound healing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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