Integration of nondegradable polystyrene and degradable gelatin in a core–sheath nanofibrous patch for pelvic reconstruction
Bibliographic record
Abstract
Pelvic organ prolapse (POP) is a serious health issue affecting many adult women. Complications of POP include pelvic pressure, pelvic pain, and problems in emptying their bowels or bladder. Sometimes, POP may even cause urinary outflow obstruction and lead to bladder or kidney infections. Currently, synthetic and naturally derived materials have been chosen for treatment of POP to reduce the high recurrence rates after surgical interventions. However, existing materials for POP treatment cannot meet the clinical requirements in terms of biocompatibility, mechanics, and minimal risk of rejection. Especially, erosion in synthetic polymers and rapid degradation in natural polymers limit their further applications in clinics. To address these concerns, we report a novel POP replacement using core-sheath polystyrene/gelatin electrospun nanofiber mesh. The outside gelatin sheath provides a hydrophilic surface and implantable integrity between host and guest, while the inner PS core offers the necessary mechanical support. The composite mesh shows graft accommodation in pelvic submucosa after implantation in vivo, as shown in hematoxylin-eosin staining and T helper cell phenotype and macrophage phenotype stainings. Qualitative analysis of inducible nitric oxide synthase, arginase, interferon-γ, and interleukin-10 gene expressions also indicates that the implanted composite mesh switches to accommodation mode 2 weeks postimplantation. Thus, these novel core-sheath polystyrene/gelatin nanofibrous membranes are promising in pelvic reconstruction.
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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".