Bone marrow mesenchymal stromal cell therapy for external urethral sphincter restoration in a rat model of stress urinary incontinence
Bibliographic record
Abstract
OBJECTIVE: To assess the effect of intra-sphincteric injections of bone marrow mesenchymal stromal cells (MSCs) on Valsalva leak point pressure (VLPP) changes in an animal model of stress urinary incontinence (SUI). MATERIALS AND METHODS: Twenty-four female Sprague-Dawley rats underwent bilateral pudendal nerve section to induce SUI. Six rats were SUI controls, 6 received periurethral injection of Plasma-Lyte (SUI placebo control) and 12 were given periurethral injection of PKH26-labeled MSCs. Four weeks after injection, conscious cystometry was undertaken in animals and VLPP recorded. All groups were sacrificed, and frozen urethra sections were submitted to pathology and immunohistochemistry assessment. RESULTS: Rat MSCs were positive for the cell surface antigens CD44, CD73, CD90, and RT1A, and negative for CD31, CD45, and RT1B, confirming their stem cell phenotype. In vitro, differentiated MSCs expressed α-smooth muscle actin (SMA) and desmin, markers of smooth and striated muscles in vivo. Immunohistochemistry of rat urethras revealed PKH26-labeled MSCs in situ and at the injection site. LPP was significantly improved in animals injected with MSCs. Mean LPP was 24.28 ± 1.47 cmH(2) O in rats implanted with MSCs and 16.21 ± 1.26 cmH(2) O in SUI controls (P<0.001). Atrophic urethras with implanted MSCs were positively stained for myosin heavy chain and desmin. CONCLUSION: Rat MSCs have the ability to differentiate and skew their phenotype towards smooth and striated muscles, as demonstrated by SMA up-regulation and desmin expression. Periurethral injection of MSCs in an animal model of SUI restored the damaged external urethral sphincter and significantly improved VLPP.
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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) | 0.001 | 0.001 |
| 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".