Human neural crest stem cells transplanted in rat penile corpus cavernosum to repair erectile dysfunction
Bibliographic record
Abstract
OBJECTIVE: To investigate the feasibility of applying neural crest stem cells (NCSCs), with multipotent capacity, to repair injury in the penile cavernosum, the HNC10.K10 (K10) immortalized NCSC line was transplanted into the penile cavernosum of adult rats, as one of the causes of erectile dysfunction is damaged penile cavernous smooth muscle cells and sinus endothelial cells. MATERIALS AND METHODS: The K10 human NCSC line was generated via transfection of primary cultured NCSC with a retroviral vector encoding v-myc. K10 NCSCs were transplanted into the cavernosum of adult rats. The expression of cell type-specific markers for endothelial cells (CD31 and von Willebrand factor), and specific markers for smooth muscle cells (smooth muscle cell actin, calponin, and desmin) was determined immunohistochemically in the penile cavernosum of rats 2 weeks after transplantation. RESULTS: In the rat cavernosum, transplanted K10 NCSCs identified by human nuclear antigen labelling expressed cell type-specific markers for endothelial cells (CD31 and von Willebrand factor), and specific markers for smooth muscle cells (smooth muscle cell actin, calponin, and desmin) 2 weeks after transplantation. Human NCSCs transplanted into the rat penile corpus cavernosum differentiated into endothelial cells or smooth muscle cells, as shown by their expression of cell type-specific markers for the cell types. CONCLUSION: It appears that NCSCs are an ideal cell source for reconstructing endothelial and smooth muscle cells in the corpus cavernosum in cell therapy for patients with erectile dysfunction.
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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) | 0.002 | 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".