Electrospinning of soy protein isolate and poly(lactic acid) ultrafine fibers for controlled release of allyl isothiocyanate
Bibliographic record
Abstract
In this project, electrospinning technique was investigated to produce ultrafine soy protein isolate (SPI) and poly(lactic acid) (PLA) fibers. SPI fibers (~200 nm) were produced by electrospinning denatured protein (10-15% wt/wt) in aqueous solution (pH 12, 60 °C) in the presence of poly(ethylene oxide) (0.6-0.8% wt/wt) and Triton X-100 (0.5-1% wt/wt). In contrast, PLA fibers (~4 [mu]m) were spun from polymer (10% wt/wt) dissolved in a mixture of chloroform and dimethylformamide DMF (90:10). Fiber morphology can be manipulated readily by changing the fiber-forming formulation. An antimicrobial agent, allyl isothiocyanate (AITC), was incorporated in SPI and PLA electrospun fibers by direct addition of the antimicrobial into the fiber-forming solution. AITC concentration significantly affected the fiber morphology. AITC loss was reduced when cyclodextrins were used as a secondary carrier. Exposing these fibers to elevated humidity (>50% RH) triggered the release of AITC, with concomitant change in visual appearance and fiber micro-morphology. Preliminary studies showed that electrospun SPI fibers with AITC prevented mold growth on bread, indicating promising active and smart packaging applications.
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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) | 0.000 | 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 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".