Characterization and Hemocompatibility of α, β, and γ Cyclodextrin-Modified Magnetic Nano-Adsorbents
Bibliographic record
Abstract
Kidney dysfunction leads to the retention of metabolites within the blood that are not effectively cleared with conventional hemodialysis. Magnetic nanoparticle (MNP)-based absorbents have inherent properties that make them amenable to capturing toxins in the blood, notably a large surface area that can be chemically modified to enhance toxin capture and the ability to be easily collected from the blood using an external magnetic field. Cyclodextrins (CDs) present a chemical structure that facilitates the binding of small molecules. However, the hemocompatibility of MNPs modified with films composed of different native types of CDs (α, β, or γ) has not yet been investigated, which is information crucial to the potential clinical application of MNPs to supplement hemodialysis. To this end, films of α-, β-, or γ-CDs were formed on MNPs and characterized. The impact of these films on the adsorbed protein structure, composition of key adsorbed proteins, and clotting kinetics were evaluated. It was found that modified MNPs did not significantly affect the secondary structure of some proteins (albumin, lysozyme, α-lactalbumin). The adsorbed proteome from platelet-poor human plasma was evaluated as a function of film properties. Compared to non-modified nanoparticles, CD-modified MNPs exhibited a significant decrease in the adsorbed protein per surface area of MNPs. The immunoblot results showed variations in the adsorption levels of C3, fibrinogen, antithrombin, Factor XI, and plasminogen across CD-modified MNPs. The hemocompatibility experiments showed that CD-modified MNPs are compatible with human whole blood, with no significant impact on platelet activation, hemolysis, or hemostasis.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 teacher head, 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".