In vitro degradation and erosion of degradable, segmented polyurethanes containing an amino acid-based chain extender
Bibliographic record
Abstract
In vitro degradation and erosion of novel, degradable segmented polyurethanes containing a phenylalanine diester chain extender were investigated by exposing the polymers to buffer. chymotrypsin, and trypsin solutions for up to 28 days. Polyurethane degradation and erosion were monitored by gravimetry, scanning electron microscopy (SEM), and gel permeation chromatography (GPC) and compared to a control polyurethane. Polyurethanes were synthesized using two different soft segments (polycaprolactone diol and polyethylene oxide) of variable molecular weight. Inclusion of the phenylalanine-based chain extender resulted in an increased susceptibility to enzyme-mediated, but not buffer-mediated, erosion in comparison to the control polyurethane. SEM analysis indicated that enzyme-mediated erosion proceeded via a surface-limited mechanism resulting in a progressive removal of material from the surface inwards with time. The magnitude of degradation and erosion was highly variable and was dependent on soft segment type and molecular weight. The range of degradation rates, as well as physicochemical properties, makes these polyurethanes potentially useful for a wide range of biomedical applications.
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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) | 0.000 | 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".