Performance Evaluation of a Dialyzer Equipped with a Hydrophilic Fiber Spacer to Enhance Internal Filtration
Bibliographic record
Abstract
Dialyzers equipped with a hydrophilic fiber spacer have been newly introduced in order to enhance internal filtration. The spacer is composed of a dialysis membrane bundle with several turns of the fibers wounding around it. Swelling of the spacer by absorption of water reduces the cross-sectional area of the dialysate stream and increases the pressure drop (ΔPD) on the dialysate side of the dialyzer. In addition to diffusive transport, the internal filtration induced by increasing ΔPD enhanced convective transport of the solute through the dialysis membrane, especially of relatively large molecular weight substances. We examined the performance of the newly introduced dialyzer in an experimental study using an aqueous solution of myoglobin and assessed the solute removal characteristics of the dialyzer with an analytical model. Three dialyzers with the spacer at different positions were used. The 40 mm wide spacer was inserted at the inlet (40 mm inlet), the center (40 mm central), and the outlet (40 mm outlet) of the dialyzer. The results of the experimental study showed that all dialyzers containing the spacer had a higher ΔPD than the control dialyzer (FB-150UH, Nipro Corp.). On the other hand, the 40 mm central dialyzer yielded higher myoglobin clearance than the 40-mm-inlet and the 40-mm-outlet dialyzers. The 40 mm central dialyzer had a higher average transmembrane pressure (TMP), because it had enough length before and after the spacer.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".