Transparent and Mechanically Robust Janus Nanofiber Membranes for Open Wound Healing and Monitoring
Bibliographic record
Abstract
The electrospun nanofiber membrane has demonstrated great potential for wound management due to its porous structure, large surface area, mechanical strength, and barrier properties. However, there is a need to develop transparent bioactive nanofibers with strong mechanical properties to facilitate the monitoring of the healing process. In this study, we present an electrospinning-based method for creating transparent (∼80–90%), strong (∼11–13 MPa), and Janus nanofiber membranes. The innovative square pattern architecture of the membrane includes a thin hydrophobic polycaprolactone layer on top of a layer of hydrophilic ethylene-vinyl alcohol nanofiber, which enables the absorption of excess biofluid from the wound and exhibits Janus wettability for water. Furthermore, incorporating 5% chitosan into the composition of the nanofibers accelerates the healing process through its antioxidant properties and antimicrobial activity against various bacteria, including drug-resistant strains. The developed membrane also demonstrates skin-repairing function, quick blood clotting (around 145 ± 12 s), and biocompatibility with keratinocyte (≥90%), as well as in vitro quick cell migration (∼24 h). With a tensile strength of 11–13 MPa, the membrane effectively adheres to the knee joint even after running 4 km. These optimal properties of the electrospun nanofiber membrane make it suitable for effective wound management and inspection of the healing process, without the need for frequent dressing changes.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Open science | 0.001 | 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 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".