Aligned nanofibrous collagen membranes from fish swim bladder as a tough and acid-resistant suture for pH-regulated stomach perforation and tendon rupture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Wound closure in the complex body environment places higher requirements on suture's mechanical and biological performance. In the scenario of frequent mechanical gastric motility and extremely low pH, single functional sutures have limitations in dealing with stomach bleeding trauma where the normal healing will get deteriorated in acid. It necessitates to advance suture, which can regulate wounds, resist acid and intelligently sense stomach pH. METHODS: Based on fish swim bladder, a double-stranded drug-loaded suture was fabricated. Its cytotoxicity, histocompatibility, mechanical properties, acid resistance and multiple functions were verified. Also, suture's performance suturing gastric wounds and Achilles tendon was verified in an in vivo model. RESULTS: By investigating the swim bladder's multi-scale structure, the aligned tough collagen fibrous membrane can resist high hydrostatic pressure. We report that the multi-functional sutures on the twisted and aligned collagen fibers have acid resistance and low tissue reaction. Working with an implantable "capsule robot", the smart suture can inhibit gastric acid secretion, curb the prolonged stomach bleeding and monitor real-time pH changes in rabbits and pigs. The suture can promote stomach healing and is strong enough to stitch the fractured Achilles tendon. CONCLUSIONS: As a drug-loaded absorbable suture, the suture shows excellent performance and good application prospect in clinical work.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 it