Development of Alcalase-Polyacrylonitrile Nanofibrous Biocatalytic Membranes for Protein Hydrolysis
Bibliographic record
Abstract
Biocatalytic membranes (BM) combine the benefits of enzymes and membranes and have found a wide variety of applications. This study focused on the development of BM by immobilizing alcalase onto electrospun polyacrylonitrile nanofibrous membranes (PANMs) modified with 1-ethyl-3-(3-dimethylamino-propyl) carbodiimide/ N -hydroxy succinimide through covalent bonding. Scanning electron microscopy and Fourier transform infrared spectroscopy were used to characterize the alcalase-functionalized PAN nanofibrous biocatalytic membrane (PAN-BM). The PAN-BM demonstrated enhanced pH and thermal stability compared to free alcalase. The BM retained 45% of its initial activity after 10 repeated uses under optimum conditions (i.e., 50 °C and pH 9.0). A BM reactor was successfully demonstrated for continuous hydrolysis of model substrate azo-casein (0.5% w/v), with its extent of hydrolysis significantly affected by both the number of layers of PAN-BM and the flux of feed. A five-layer PAN-BM was also successfully tested for continuous hydrolysis of the raw soy proteins (1.4% w/v) extracted from commercial soybean meals, showing a promising potential of application.
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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) | 0.001 | 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 | 0.001 | 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".