In vitro Clearance and Hemocompatibility Assessment of Ultrathin Nanoporous Silicon Membranes for Hemodialysis Applications Using Human Whole Blood
Bibliographic record
Abstract
BACKGROUND/AIMS: Recent advances in nanotechnology have made it possible to mass-produce ultrathin silicon membranes with pore sizes in the range of nanometers. In this study, we investigate the possibility of employing ultrathin nanoporous silicon membranes with pore diameters of 5 and 20 nm for dialysis of human whole blood by performing in vitro clearance and hemocompatibility assessments. METHODS: A mini blood dialyzer is fabricated by mounting nanoporous silicon membranes on a Teflon structure. Clearance is calculated based on the concentration of sodium, chloride, ionized calcium, total CO2, glucose, creatinine and hematocrit measured before and after dialysis. Blood activation is assessed by flow cytometry. RESULTS: Blood contact with the nanoporous membranes induces considerable leukocyte activation. Coating of the membranes with polyethylene glycol significantly improves hemocompatibility without blocking the nanopores. CONCLUSION: Silicon nanoporous membranes are potential candidates for fabrication of miniaturized blood dialyzers. Their mechanical strength and hemocompatibility can be further improved.
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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) | 0.000 | 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".