Lipoprotein interactions with a polyurethane and a polyethylene oxide-modified polyurethane at the plasma–material interface
Bibliographic record
Abstract
Lipoproteins [high density lipoprotein (HDL), low density lipoprotein (LDL), and very low density lipoprotein (VLDL)] are present in blood in relatively high concentrations, and, given their importance in cardiovascular disease, the interactions of these species with blood contacting biomaterials and their possible role in thrombogenesis is of interest. In the present communication, quantitative data on the adsorption of apolipoprotein AI, apolipoprotein AII (the main protein components of HDL), and apolipoprotein B (the main protein component of LDL and VLDL), as well as the lipoproteins themselves from plasma to a biomedical grade polyurethane (PU) with and without a copolymer additive that contains polyethylene oxide (PEO) segments, were investigated. Adsorption from some binary solutions was also studied. Significant quantities of the apolipoproteins were found to adsorb from plasma to the PU, while adsorption to the PEO material was more than 90% lower, demonstrating strong protein resistance of the latter material. In contrast, significant quantities of the lipoproteins were found to adsorb to the PEO as well as to the PU material. From these and previously published results, it is concluded that the protein layer formed on the PU surface from plasma (and by extension from blood) contains apolipoproteins and lipoproteins in addition to other plasma proteins; the layer formed on the PEO surface, however, appears to contain minimal quantities of plasma proteins (including free apolipoproteins) but significant quantities of lipoproteins.
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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 | 0.000 | 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) | 0.001 | 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".