Improvement of erectile dysfunction using endothelial progenitor cells from fetal cerebral vasculature in the cavernous nerve injury of rats
Bibliographic record
Abstract
BACKGROUND: Because of limited differentiation to endothelium from mesenchymal stem cells, it has been strongly recommended to use endothelial progenitor cells for the regeneration of the damaged endothelium of corpora cavernosa. This study was performed to investigate the immortalized human cerebral endothelial cells and their capability for repairing erectile dysfunction in a rat model of cavernous nerve injury. Circulating endothelial progenitor cells were isolated from human fetal brain vasculature at the periventricular region of telencephalic tissues. Over 95% of CD 31-positive cells were sorted and cultured for 10 days. Human cerebral endothelial progenitor cells were injected into the cavernosa of rats with cavernous nerve injury. Erectile response was then assessed. In in vivo assays, rats were divided into three groups: group 1, sham operation: group 2, bilateral cavernous nerve injury: and group 3, treatment with human cerebral endothelial cells after cavernous nerve injury. RESULTS: Established immortalized circulating endothelial progenitor cells showed expression of human telomerase reverse transcriptase transcript by RT-PCR. They also showed the expression of vascular endothelial growth factor, von Willebrand factor, vascular endothelial growth factor receptor, and CD31, cell type-specific markers for endothelial cells by RT-PCR. In in vitro angiogenesis assays, they demonstrated tube formation that suggested morphological properties of endothelial progenitor cells. In in vivo assays, impaired erectile function of rat with cavernous nerve injury recovered at 2, 4, and 12 weeks after transplantation of human cerebral endothelial cells into the cavernosa. CONCLUSIONS: Telomerase reverse transcriptase-circulating endothelial progenitor cells from fetal brain vasculature could repair erectile dysfunction of rats with cavernous nerve injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".