The Influence of Electrospinning Parameters and Drug Loading on Polyhydroxyalkanoate (PHA) Nanofibers for Drug Delivery
Bibliographic record
Abstract
The impact of polymer concentration and drug loading on nanofiber morphology and diameter were investigated during electrospinning of polyhydroxyalkanoate nanofibrous films. Low molecular weight poly(3hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-95 mol% 4HB)] required a 5-fold higher solution concentration than high molecular weight poly(3-hydroxybutyrate) [P(3HB)] to produce bead-free nanofibers. Loading the films with paclitaxel increased the initial polymer solution viscosity allowing larger diameter nanofibers to form. Furthermore, paclitaxel added at 1% (w/w) into 8 % (w/v) P(3HB-co-95 mol% 4HB) solution eliminated the formation of beads seen in solutions without the drug, at the same initial polymer solution concentration. In preliminary drug release studies, nanofiber mats consisting of large-diameter nanofibers with high drug loading released paclitaxel at a faster rate due to larger pore sizes. This was a consequence of the random packing of larger diameter nanofibers. However, the release pattern of nanofibers with low drug loading was much more consistent and controlled. Lastly, we have shown the potential applications of P(3HB-co-4HB) drug loaded nanofibers in the development of biocompatible drug eluting stents by directly coating a metal stent with a homogeneous layer of electrospun polymer.
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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 | 0.001 |
| Scholarly communication | 0.000 | 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".