On arginine‐based polyurethane‐blends specific to vascular prostheses
Bibliographic record
Abstract
Abstract Polymer blends based on Tecoflex™ and an experimental aliphatic polyurethane (HMDI‐PCL‐arginine stands for 4,4 (metylene‐biscyclohexyl) isocyanate ‐ poly (ε caprolactone) diol, SPUUR stands for segmented poly(urea)urethanes using amino acid of L‐Arginine as chain extender) were obtained by solvent casting, and further studied by fourier transform infrared (FTIR) and Raman spectroscopy, differential scanning calorimetry (DSC), thermogravimetric analysis, and X‐ray diffraction (XRD). Their biological performances were assessed in terms of hemocompatibility and Human umbilical vein endothelial cell (HUVEC) cytotoxicity. Tensile properties of dumbbell specimens were compared to longitudinal and circumferential tensile properties of tubular vascular graft. FTIR showed that as the SPUUR content increased in the blend, absorptions at 2860 cm−1 increased, carbonyl absorptions at 1724 cm−1 broaden and the small peak at 2796 cm−1, typical of Tecoflex™ disappeared. Raman spectroscopy showed that the low intensity carbonyl absorption at 1724 cm−1 also increased with SPUUR content. DSC allowed detection of PCL soft segment melting (Tm = 50°C) in agreement with X‐ray reflections at 21.3° and 23.6°, assigned to SPUUR. However, no improvements in thermal stability were detected by TGA by blending. The addition of SPUUR to Tecoflex™ improved hemocompatibility and HUVEC cytotoxicity. The vascular grafts performance showed that 40% SPUUR blends exhibited the highest force in the longitudinal test whereas 50% SPUUR blends showed the highest circumferential force. Pressure burst strength was higher than 1000 mmHg for all blends. Overall, these blends can be used for high caliber vascular grafts.
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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".