Convenient Fabrication of Electrospun Prolamin Protein Delivery System with Three-Dimensional Shapeability and Resistance to Fouling
Bibliographic record
Abstract
It has been newly discovered that by simply altering the applied voltage, the resultant electrospun prolamin protein fabrics can rapidly (within 30 s) form either flat sheets or self-rolled tubes when immersed in water. This phenomenon opens up many potential biomedical applications for drug delivery. The morphology and structure of both dry and wet fibers were characterized in detail. The hordein/zein fibers fabricated at relatively lower voltage were stabilized by the preaggregated nanoscale hydrophobic domains and exhibited restricted swelling while maintaining a flat sheet shape with minimal changes to secondary structure when immersed in water. By applying a higher voltage, we triggered a greater bending instability during the electrospinning process, and the hordein/zein network structure generated could rapidly relax in an aqueous environment. This increased mobility of molecular chains allowed the uneven aggregation of hydrophobic dopants, which catalyzed the self-rolling of the aligned fibers. Sessile drop measurements even showed a reduction in the contact angle from 106 to 39° for the fibers with 50% zein prepared at raised voltage, indicating the conversion of surface properties caused by the relaxation. All the fibers demonstrated low toxicity in human primary dermal fibroblast cell culture. Moreover, the electrospun fabrics exhibited a strong resistance to protein adsorption and cell attachment, and the release experiment indicated that both three-dimensional porous structures could serve as a carrier for controlled release of incorporated bioactive compounds into phosphate-buffered saline. Therefore, these electrospun prolamin protein fabrics represent an ideal and novel platform to develop nonadherent drug delivery systems for wound dressing and other biomedical applications.
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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 | 0.000 | 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 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".