Physiology of Erectile Function
Bibliographic record
Abstract
INTRODUCTION: There are numerous investigations concerning the balance and interactions between relaxant and contractile factors regulating penile smooth muscle (arterial and trabecular) tone, the determinant of penile flaccidity or erection. Enhanced knowledge of erectile physiology may improve management of men with erectile dysfunction. Aim. To provide state-of-the-art knowledge on the physiology of erectile function. METHODS: An international consultation in collaboration with the major urology and sexual medicine associations assembled over 200 multidisciplinary experts from 60 countries into 17 committees. Committee members established specific objectives and scopes for various male and female sexual medicine topics. The recommendations concerning state-of-the-art knowledge in the respective sexual medicine topic represent the opinion of experts from five continents developed in a process over a two-year period. Concerning the physiology of erectile function and pathophysiology of erectile dysfunction committee, there were seven experts from five countries. MAIN OUTCOME MEASURE: Expert opinion was based on the grading of evidence-based medical literature, widespread internal committee discussion, public presentation, and debate. RESULTS: Key roles in the mechanism determining the tone of penile smooth muscle are played by the rise of the intracellular concentration of free calcium and the sensitivity of the contractile machinery to calcium, endothelial health, endothelium-derived nitric oxide, endothelium-derived hyperpolarizing factor (EDHF), neuronal nitric oxide, cyclic guanosine monophosphate-dependent protein kinase and phosphodiesterase type 5. CONCLUSIONS: A number of new mechanisms have been identified for the local regulation of penile smooth muscle contractility and therefore penile erection. Molecules participating in these pathways can be considered targets for the development of new treatments to treat 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".