Co electrospinning -poly (vinyl alcohol)-chitosan/gelatin-poly (<i>ϵ</i>-caprolacton) nanofibers for diabetic wound-healing application
Bibliographic record
Abstract
With the increasing prevalence of diabetes, the healing of diabetic wounds has become a significant challenge for both healthcare professionals and patients. Recognizing the urgent need for effective solutions, it is crucial to develop suitable scaffolds specifically tailored for diabetic wound healing. In line with this objective, we have developed novel hybrid nanofibrous scaffolds by combining polyvinyl alcohol/chitosan (PVA/CS) and gelatin/poly(ε-caprolactone) (Gel/PCL) polymers through a double-nozzle electrospinning technique. In this study, we investigated the influence of the Gel/PCL blend ratio on the properties of the resulting nanofibers. Three different hybrid scaffold structures were examined: Gel/PCL (80:20)-PVA/CS (80:20), Gel/PCL (50:50)-PVA/CS (80:20), and Gel/PVA (20:80)-PVA/CS (80:20). Our findings demonstrate that the electrospun nanofibers of PVA/CS (80:20)-Gel/PCL (80:20) exhibited optimal mechanical performance, with a contact angle of approximately 54° and a diameter of 183 nm. Considering the crucial role of inhibiting bacterial adhesion in the success of implanted materials, we evaluated the cytocompatibility of the hybrid electrospun nanofibers using mouse fibroblast cells (L-929 cells). The in vitro cytotoxicity results obtained from L-929 fibroblast cell culture on the hybrid scaffolds revealed enhanced cell proliferation and appropriate cell morphology on the PVA/CS (80:20)-Gel/PCL (80:20) sample, indicating its capability to support tissue cell integration. Based on the information obtained from this study, the fabricated hybrid scaffold holds great promise for diabetic ulcer healing. Its optimal mechanical properties, suitable contact angle, and favorable cytocompatibility highlight its potential as a valuable tool in the field of diabetic wound healing. The development of such hybrid scaffolds represents a significant step forward in addressing the challenges associated with diabetic wound care.
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".