Effects of Ovariectomy and Dehydroepiandrosterone (DHEA) on Vaginal Wall Thickness and Innervation
Bibliographic record
Abstract
INTRODUCTION: One mechanism by which low sexual steroid activity observed after menopause could cause sexual dysfunction is by deficient vaginal innervation. Recently, it has been shown that intravaginal administration of dehydroepiandrosterone (DHEA) could produce beneficial effects on sexual dysfunction in postmenopausal women. AIM: The goal of this study was to determine if DHEA could modify innervation in the rat vagina. MAIN OUTCOME MEASURES: The area occupied by the nerve fibers immunoreactive for protein gene product 9.5 (PGP 9.5), a panneuronal marker or tyrosine hydroxylase (TH), a sympathetic nerve fiber marker, in the lamina propria and muscular layers, respectively, as well as the total area of each of these 2 layers were measured by stereological analysis. METHODS: The innervation of the rat vagina was examined 9 months after ovariectomy (OVX) compared to intact animals and treatment of OVX animals with DHEA (80 mg/kg). Four sections from each vagina (5 animals/groups) were immunostained. RESULTS: In OVX animals, the lamina propria area was decreased to 44%, an effect which was reversed by DHEA to 69% of the intact value. OVX also caused a 59% decrease in the area of PGP 9.5 fibers, an effect which was prevented by DHEA, thus showing a 68% stimulatory effect of DHEA on the density of PGP 9.5 fibers in the lamina propria compared to OVX animals. Following OVX, the muscular layer area was decreased by 61%. DHEA treatment induced 118% and 71% increases in TH fiber area compared to OVX and intact animals, respectively. The density of TH fibers was 182% increased over intact controls by DHEA treatment of OVX animals. CONCLUSIONS: The relatively potent stimulatory effect of DHEA on intravaginal nerve fiber density provides a possible explanation for the beneficial effects of intravaginal DHEA on sexual dysfunction observed in postmenopausal women.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".