Evaluation of solute penetration across the polysulfone membrane with vitamin <scp>E</scp> coating
Bibliographic record
Abstract
Vitamin E (vit E) is coated on polysulfone (PS) dialysis membrane for antioxidative purpose. The membrane, however, has not yet been evaluated from the mass transfer point of view. We investigated this PS membrane with and without vit E coating in vitro ultrafiltration experiments to identify whether or not the coating influences the mass transfer. Dialyzers that included PS membrane with and without vit E coating were investigated. Aqueous test solution of various solutes including vitamin B12 (VB12 , MW1355), chymotrypsin (chymo, MW25000), and albumin (alb, MW66000) was prepared, and normal ultrafiltration experiments were performed at 310 K. Reverse ultrafiltration experiments in which test solution was filtered from outside to inside the hollow fiber were also performed. Sieving coefficients (SC) were computed for evaluation. SC for VB12 was the same regardless of vit E coating; however, chymo was 0.82 ± 0.01 and 0.86 ± 0.01, respectively, for the membrane with and without vit E. Thus, it would be understood that vit E coating reduces the pore size of the membrane, resulting the reduced transport of larger solutes. Like other PS membrane, SC for alb was decreased over time regardless of vit E coating. More importantly, although the steady-state SC for alb was almost identical in two membranes, PS without vit E showed much greater decrease for the first 2 h, while that with vit E showed very little decrease over time, which suggested the reduced fouling effect due to vit E coating. All the SC values found in reverse ultrafiltration were higher than those found in normal ultrafiltration; moreover, the degree of increase with chymo was approximately 5%, whereas that with alb was approximately 430%, which may be explained by a new model in which wedge effect is taken into consideration for the membrane transport. Vit E coating not only has antioxidative effect but also reduces the fouling that is usually caused by various proteins.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".