Enhancing the hemocompatibility of polyethersulfone (PES) hemodialysis membranes using synthesized pseudo zwittronic polymers with various orientations
Why this work is in the frame
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Bibliographic record
Abstract
The incompatibility of membrane materials with blood in the dialysis process has resulted in extensive number of side effects as well as undesired mortality rates for end-stage renal disease (ESRD) patients. Recent attention has been directed at enhancing the hemocompatibility of dialysis membranes. This study synthesized polyether sulfone (PES) mixed matrix membranes (MMMs) containing modified silica nanoparticles (SiO2 NPs) using the phase inversion technique. SiO2 NPs were modified with pseudo-zwitterionic (pZW) coatings of different structures. The modification of SiO2 NPs and their presence in casted MMMs were confirmed using Fourier-transform infrared (FTIR) spectroscopy. Molecular dynamics (MD) simulations were used to compute the quantity and energy of hydrogen bonds, which serve as a metric of hemocompatibility. Surface charge measurements were used to confirm the neutralization of the modified membrane surface charge. Atomic force microscopy (AFM) analysis revealed the influence of the structure of the SiO2 NPs on casted MMM surface roughness. The influence of the pZW coating structure on MMM hemocompatibility was examined in vitro using patient serum to investigate the inflammatory biomarkers released (C5a, IL-1α, IL-1β, IL-6, properdin, C5b-9). The clinicalex-vivo studies showed improvement of hemocompatibility in terms of IL-1α, IL-1β, Properdin, and C59-9. 5 % lower secretion of complement factor and interleukins reflected an improvement of hemocompatibility. Comparing MMM-1 to the other samples, the hemocompatibility profile was better. MD results were in agreement with the clinical outcomes as MMM-1 had the highest number of hydrogen bonds (8) and hydrogen bonding energy value (0.72 kcal/mol), indicating greater water interaction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it