The influence of isocyanurate content on the bioperformance of hydrocarbon-based polyurethanes
Bibliographic record
Abstract
Bulk, surface and bioactivity of newly synthesized hydroxy telechelic polyisoprene-based (H-HTPI) polyurethane were investigated by means of ATR-FT-IR, contact-angle measurements, cell viability, calcification, and platelet and fibrinogen quantification. The influence of isophorone diisocyanates isocyanurate (I-IPDI) content on these properties was determined. Results generally showed a non-significant difference in these properties when they were compared with a commercially available biomedical polyurethane (PU), such as Tecoflex. Unexpectedly, where the increase of isocyanate content for commercial diisocyanate-based biocompatible PU significantly increases the surface contact angle, the new hydroxy telechelic polyisoprene-based PU showed a decrease of water contact angle with increasing I-IPDI content in the polymer. Nevertheless, the overall surface exhibited hydrophobic properties, i.e., theta > 85. Polymer cytotoxicity, assessed with L929 cell line in direct contact with the surface of the samples, showed no toxic effects on the cells. Interestingly, regardless of the I-IPDI content, platelet adhesion and fibrinogen adsorption, as well as the mineral deposition were fairly similar for all synthesized PUs. Our findings revealed that replacing diisocyanates by their isocyanurate homologues is a very relevant approach for preparation of polyurethanes with different mechanical properties while maintaining similar surface properties.
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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".