Depression induced by chronic stress leads to penile cavernosal dysfunction: protective effect of anti-TNF-α treatment
Bibliographic record
Abstract
Psychological stress may lead to erectile dysfunction (ED), and inflammation has been evaluated as a major contributing factor. The goal of this study was to investigate the effects of etanercept (ETN), an anti-tumor necrosis factor α (TNF-α) protein, on cavernosal function in the unpredictable chronic mild stress (UCMS) rat model of depression. Animals were divided into 4 groups: animals not exposed to UCMS, animals not exposed to UCMS and treated with ETN, animals exposed to UCMS, and animals treated with ETN while exposed to UCMS. UCMS significantly impaired the neurogenic and endothelium-dependent relaxation responses; reduced cavernosal endothelial nitric oxide (NO) synthase (eNOS) and neuronal NO synthase (nNOS) expressions; decreased testosterone levels; enhanced systemic levels of corticosterone, TNF-α, interleukin 1β (IL-1β), interleukin 6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and intercellular adhesion molecule 1 (ICAM-1); and also increased cavernosal levels of TNF-α, IL-1β, and IL-6 in rats. ETN administration restored NO-mediated neurogenic and endothelium-dependent relaxation responses of the corpus cavernosum, increased cavernosal eNOS and nNOS expressions, enhanced testosterone levels, and decreased corticosterone levels in UCMS-exposed rats. Also, systemic inflammatory markers and cavernosal proinflammatory cytokine levels were reduced by ETN. Our results demonstrate the role of TNF-α-mediated inflammation in the development of depression and ED in rats exposed to chronic stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".