An endothelialized urothelial cell-seeded tubular graft for urethral replacement
Bibliographic record
Abstract
INTRODUCTION: Many efforts are used to improve surgical techniques and graft materials for urethral reconstruction. We developed an endothelialized tubular structure for urethral reconstruction. METHODS: Two tubular models were created in vitro. Human fibroblasts were cultured for 4 weeks to form fibroblast sheets. Then, endothelial cells (ECs) were seeded on the fibroblast sheets and wrapped around a tubular support to form a cylinder for the endothelialized tubular urethral model (ET). No ECs were added in the standard tubular model (T). After 21 days of maturation, urothelial cells were seeded into the lumen of both models. Constructs were placed under perfusion in a bioreactor for 1 week. At several times, histology and immunohistochemistry were performed on grafted nude mice to evaluate the impact of ECs on vascularization. RESULTS: Both models produced an extracellular matrix, without exogenous material, and developed a pseudostratified urothelium. Seven days after the graft, mouse red blood cells were present only in the outer layers in T model, but in the full thickness of ET model. After 14 days, erythrocytes were present in both models, but in a greater proportion in ET model. At day 28, both models were well-vascularized, with capillary-like structures in the whole thickness of the tubes. CONCLUSION: Incorporating endothelial cells was associated with an earlier vascularization of the grafts, which could decrease the necrosis of the transplanted tissue. As those models can be elaborated with the patient's cells, this tubular urethral graft would be unique in its autologous property.
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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 | 0.001 | 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".