Preparing and characterizing biodegradable materials for ureteral stents
Bibliographic record
Abstract
Abstract The development and application of biodegradable ureteral stents is of clinical significance for patients with ureteral stenosis and obstruction. We prepared five types of degradable monofilament, namely poly‐L‐lactide, poly(L‐lactide‐co‐ glycolide) (85% L‐lactide, 15% glycolide), poly(L‐lactide‐co‐glycolide‐co‐ε‐ caprolactone) (89% L‐lactide, 8% glycolide, and 3% ε‐caprolactone), poly(L‐lactide‐ co‐D,L‐lactide) (95% L‐lactide, 5% D,L‐lactide), and poly(lactide‐co‐ε‐caprolactone) (95% L‐lactide, 5% ε‐caprolactone), by melt extrusion and secondary drawing processes, after which degradation experiments were carried out in simulated urine at 37°C for 2 months. Because residues in the urinary systems of patients can cause complications, it is important that biodegradable ureteral stents are completely degraded after 6 weeks. Poly‐L‐lactide did not completely degrade under the abovementioned conditions and its molecular weight changed little. On the other hand, the poly(L‐lactide‐co‐glycolide) monofilament degraded slightly faster than that prepared from poly‐L‐lactide; however it maintained a certain mechanical strength after 8 weeks, which is not ideal for a woven ureteral stent. The poly(L‐lactide‐co‐D,L‐lactide), poly(L‐lactide‐co‐glycolide‐co‐ε‐caprolactone), and poly(lactide‐co‐ε‐caprolactone) monofilaments exhibited good tensile strengths and elongations at break in the first four weeks, which were reduced to almost zero in the eighth week. Ureteral stents made of these polymers can open narrow urethras at early stages and degrade completely at later stages. Based on its degradation rate, we conclude that the poly(lactide‐co‐ε‐caprolactone) monofilament is the best material for the preparation of ureteral stents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".