Impact of Membrane Modification and Surface Immobilization Techniques on the Hemocompatibility of Hemodialysis Membranes: A Critical Review
Bibliographic record
Abstract
Despite significant research efforts, hemodialysis patients have poor survival rates and low quality of life. Ultrafiltration (UF) membranes are the core of hemodialysis treatment, acting as a barrier for metabolic waste removal and supplying vital nutrients. So, developing a durable and suitable membrane that may be employed for therapeutic purposes is crucial. Surface modificationis a useful solution to boostmembrane characteristics like roughness, charge neutrality, wettability, hemocompatibility, and functionality, which are important in dialysis efficiency. The modification techniques can be classified as follows: (i) physical modification techniques (thermal treatment, polishing and grinding, blending, and coating), (ii) chemical modification (chemical methods, ozone treatment, ultraviolet-induced grafting, plasma treatment, high energy radiation, and enzymatic treatment); and (iii) combination methods (physicochemical). Despite the fact that each strategy has its own set of benefits and drawbacks, all of these methods yielded noteworthy outcomes, even if quantifying the enhanced performance is difficult. A hemodialysis membrane with outstanding hydrophilicity and hemocompatibility can be achieved by employing the right surface modification and immobilization technique. Modified membranes pave the way for more advancement in hemodialysis membrane hemocompatibility. Therefore, this critical review focused on the impact of the modification method used on the hemocompatibility of dialysis membranes while covering some possible modifications and basic research beyond clinical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".