Surface characterization, hemo- and cytocompatibility of segmented poly(dimethylsiloxane)-based polyurethanes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Segmented polyurethanes based on poly(dimethylsiloxane), currently used for biomedical applications, have sub-optimal biocompatibility which reduces their efficacy. Improving the endothelial cell attachment and blood-contacting properties of PDMS-based copolymers would substantially improve their clinical applications. We have studied the surface properties and in vitro biocompatibility of two series of segmented poly(urethane-dimethylsiloxane)s (SPU-PDMS) based on hydroxypropyl- and hydroxyethoxypropyl- terminated PDMS with potential applications in blood-contacting medical devices. SPU-PDMS copolymers were characterized by contact angle measurements, surface free energy determination (calculated using the van Oss-Chaudhury-Good and Owens-Wendt methods), and atomic force microscopy. The biocompatibility of copolymers was evaluated using an endothelial EA.hy926 cell line by direct contact assay, before and after pre-treatment of copolymers with multicomponent protein mixture, as well as by a competitive blood-protein adsorption assay. The obtained results suggested good blood compatibility of synthesized copolymers. All copolymers exhibited good resistance to fibrinogen adsorption and all favored albumin adsorption. Copolymers based on hydroxyethoxypropyl-PDMS had lower hydrophobicity, higher surface free energy, and better microphase separation in comparison with hydroxypropyl-PDMS-based copolymers, which promoted better endothelial cell attachment and growth on the surface of these polymers as compared to hydroxypropyl-PDMS-based copolymers. The results showed that SPU-PDMS copolymers display good surface properties, depending on the type of soft PDMS segments, which can be tailored for biomedical application requirements such as biomedical devices for short- and long-term uses.
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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 | 0.001 | 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 it