Isolation and characterization of epithelial cells and fibroblasts from the human penile urethra
Bibliographic record
Abstract
Introduction: Urethral strictures and hypospadias are common urological conditions for which autologous reconstruction remains challenging. Tissue engineering offers a promising alternative, yet current strategies often rely on heterotopic cell sources, potentially limiting functional integration. Here, we report the first isolation and characterization of epithelial and stromal cells from distinct regions of the human penile urethra: the spongy urethra and the proximal and distal fossa navicularis. Methods: Cells were isolated from the three regions of the penile urethra in 12 donors. Detailed characterization was performed for 3-4 donors, assessing yield, growth parameters, immunophenotype, and progenitor preservation. We evaluated 3-, 4-, and 6-mm biopsies to determine the minimal tissue size required for clinically relevant cell yields. Multiple enzymatic protocols were compared, using thermolysin or dispase II for epithelial-stromal separation, followed by collagenase ± elastase digestion for stromal cell recovery. Results: Cell extraction had a 100% success rate across all tested protocols. The combination of dispase and a 4-h collagenase/elastase digestion yielded the highest cell numbers and clonogenic potential. All biopsy sizes produced sufficient cells for tissue engineering. Discussion: These findings demonstrate the feasibility of harvesting high-quality, organ-specific autologous cells from minimal urethral biopsies. In addition to their clinical potential, these cells provide a foundation for preclinical disease modelling using patient-derived pathological cells, which are currently unavailable for in vitro studies of urethral disorders.
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 | 0.000 | 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) | 0.001 | 0.001 |
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".