Sulfonate Groups and Saccharides as Essential Structural Elements in Heparin-Mimicking Polymers Used as Surface Modifiers: Optimization of Relative Contents for Antithrombogenic Properties
Bibliographic record
Abstract
Blood compatibility is a long sought-after goal in biomaterials research, but remains an elusive one, and in spite of extensive work in this area, there is still no definitive information on the relationship between material properties and blood responses such as coagulation and thrombus formation. Materials modified with heparin-mimicking polymers have shown promise and indeed may be seen as comparable to materials modified with heparin itself. In this work, heparin was conceptualized as consisting of two major structural elements: saccharide- and sulfonate-containing units, and polymers based on this concept were developed. Copolymers of 2-methacrylamido glucopyranose, containing saccharide groups, and sodium 4-vinylbenzenesulfonate, containing sulfonate groups, were graft-polymerized on vinyl-functionalized polyurethane (PU) surfaces by free radical polymerization. This graft polymerization method is simple, and the saccharide and sulfonate contents are tunable by regulating the feed ratio of the monomers. Homopolymer-grafted materials, containing only sulfonate or saccharide groups, showed different effects on cell-surface interactions including platelet adhesion, adhesion and proliferation of vascular endothelial cells, and adhesion and proliferation of smooth muscle cells. The copolymer-grafted materials showed effects due to both sulfonate and saccharide elements with respect to blood responses, and the optimum composition was obtained at a 2:1 ratio of sulfonate to saccharide units (material designated as PU-PS1M1). In cell adhesion experiments, this material showed the lowest platelet and human umbilical vein smooth muscle cell density and the highest human umbilical vein endothelial cell density. Among the materials investigated, PU-PS1M1 also had the longest plasma clotting time. This material was thus shown to be multifunctional with a combination of properties, suggesting thromboresistant behavior in blood contact.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 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".