Water‐soluble astaxanthin and silver enriched poly(vinyl alcohol)/silk fibroin crosslinking electrospun nanofiber for wound dressing
Bibliographic record
Abstract
Abstract The aim of this work is to fabricate a novel electrospun poly(vinyl alcohol) (PVA)/silk fibroin (SF) nanofibrous membrane containing astaxanthin (ASTA) and silver (Ag) nanoparticles as potential wound dressing. Since ASTA is typically liposoluble, the bioavailability could be greatly enhanced by improving its hydrophilicity. The antioxidant performance of eletrospun membrane is verified by ABTS radical scavenging assays. The beadless fibers could be fabricated at 16 kV when PVA (12, wt%) is blended with SF (6, wt%). In addition, the membrane is carefully chemically crosslinked by comparing the efforts (i.e., mechanical strength and water resistance) of glutaraldehyde dipping and vapor treatment. The morphology of the electrospun membrane is observed by scanning electron microscopy and optical microscope. The formation of Ag nanoparticles, which provides the membranes antibacterial properties, is also confirmed by energy dispersive spectroscopy and inhibition zone test. Meanwhile, the PVA/SF/ASTA/Ag compound membrane is characterized by Fourier transform infrared spectroscopy, x‐ray diffraction, thermo gravimetric analysis, differential thermal analysis, and water contact angle. The releasing of ASTA is also measured, and kinetic data are adjusted by Higuchi models. Finally, the biocompatibility is confirmed by in vitro cell staining experiments and in vivo rat models.
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.
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".