Correction of Significant Urethral Anomalies Using a Tissue-Engineered Human Urethral Substitute: Proof of Concept
Bibliographic record
Abstract
Urethral reconstruction remains a challenge. Indeed, the use of oral mucosa, the reference biomaterial for urethroplasty, is associated with two main drawbacks: the limited availability of autologous tissues and potential short- and long-term complications, especially for patients with recurrences or severe anomalies. Therefore, the development of alternative approaches, such as urethral tissue engineering, is necessary. A new type of human urethral substitute devoid of exogenous biomaterials has been reconstructed in vitro. It presented sufficient mechanical strength and had histological and functional properties comparable to native tissues. These reconstructed tissues were implanted in vivo to repair hypospadias induced in tacrolimus-immunosuppressed rabbits via a two-stage urethroplasty. In the first stage, the distal part of the native urethra was removed, and a flat graft was implanted, leaving the urethra open proximally. Twelve weeks later, the graft was tubularized to create a neourethra, reproducing the usual clinical scenario. The results obtained for the experimental group were less effective than for the control group, with a success rate of 50% after excluding the animal affected by unwanted events unrelated to urethroplasty, and it is possible that the animal model or surgical technique used was not suitable and should be modified. Nevertheless, half of the urethral substitutes grafted on rabbits showed successful integration. These self-assembled artificial tissues represent promising substitutes for urethroplasty.
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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 | 0.001 | 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 | 0.000 | 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".