Carbohydrate Structure Dependent Hemocompatibility of Biomimetic Functional Polymer Brushes on Surfaces
Bibliographic record
Abstract
Glycocalyx mimicking glycopolymer brushes presenting mannose, galactose and glucose residues in the pyranose form, similar to those present on cell surfaces, were synthesized on planar substrates (Si wafer, gold chip) and monodispersed polystyrene (PS) particles, and the interaction of blood to these surfaces were studied using various methods with the goal of producing a hemocompatible surface. Surface plasmon resonance (SPR) spectroscopy and gel analyses showed that the total protein adsorption from plasma was greatly reduced, as low as 24.3 ng/cm(2) from undiluted plasma on the glucose carrying brush. The protein adsorption decreased with increasing grafting density of the brushes. It was also found that the protein adsorption varied with the anticoagulant used for blood collection; much higher amount of protein was adsorbed from heparinzied plasma than citrated plasma. Proteomics protein identification analysis revealed that protein adsorption from plasma depended on the type of sugar residue present on the surface as well as the type of anticoagulant. All the three types of glycopolymer brushes showed similar level of platelet activation as that of buffer control irrespective of the nature of carbohydrate residue. However, the number of adhered platelet and their morphology depended on the type of carbohydrate residue present on the brush. On glucose brush, the extent of platelet adhesion and spreading was significantly lowered compared to other brushes. All the glycopolymer brushes were neutral to blood coagulation as indicated by thromboelastography analysis. The glucose brush gave a slightly longer initial coagulation time suggesting that this surface may be more biocompatible. Our data demonstrate that the structure of carbohydrate residue is an important factor in the design of synthetic blood contacting surface based on glycopolymer.
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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 | 0.000 |
| 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) | 0.001 | 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".