<i>In Vitro</i> Biocompatibility Evaluation of Novel Urethane–Siloxane Co-Polymers Based on Poly( <i>ϵ</i> -Caprolactone)- <i>block</i> -Poly(Dimethylsiloxane)- <i>block</i> -Poly( <i>ϵ</i> -Caprolactone)
Bibliographic record
Abstract
Novel polyurethane co-polymers (TPUs), based on poly(ϵ-caprolactone)-block-poly(dimethylsiloxane)-block-poly(ϵ-caprolactone) (PCL-PDMS-PCL) as soft segment and 4,4'-methylenediphenyl diisocyanate (MDI) and 1,4-butanediol (BD) as hard segment, were synthesized and evaluated for biomedical applications. The content of hard segments (HS) in the polymer chains was varied from 9 to 63 wt%. The influence of the content and length of the HS on the thermal, surface, mechanical properties and biocompatibility was investigated. The structure, composition and HS length were examined using (1)H- and quantitative (13)C-NMR spectroscopy. DSC results implied that the synthesized TPUs were semicrystalline polymers in which both the hard MDI/BD and soft PCL-PDMS-PCL segments participated. It was found that an increase in the average HS length (from 1.2 to 14.4 MDI/BD units) was accompanied by an increase in the crystallinity of the hard segments, storage moduli, hydrophilicity and degree of microphase separation of the co-polymers. Depending on the HS content, a gradual variation in surface properties of co-polymers was revealed by FT-IR, AFM and static water contact angle measurements. The in vitro biocompatibility of co-polymers was evaluated using the endothelial EA.hy926 cell line and protein adsorption on the polyurethane films. All synthesized TPUs adsorbed more albumin than fibrinogen from multicomponent protein mixture, which may indicate biocompatibility. The polyurethane films with high HS content and/or high roughness coefficient exhibit good surface properties and biocompatible behavior, which was confirmed by non-toxic effects to cells and good cell adhesion. Therefore, the non-cytotoxic chemistry of the co-polymers makes them good candidates for further development as biomedical implants.
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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".