Dysregulated mitogen-activated protein kinase and matrix metalloproteinase in ethanol-induced cavernosal dysfunction
Bibliographic record
Abstract
We evaluated the effects of ethanol consumption on the mitogen-activated protein kinases (MAPK) and metalloproteinases (MMP) pathways in the rat cavernosal smooth muscle (CSM). Male Wistar rats were treated with ethanol (20% v/v) for 6 weeks. Quantitative real-time polymerase chain reaction experiments showed that ethanol consumption did not alter mRNA levels of p38MAPK, SAPK/JNK, ERK1/2, MMP-2, or MMP-9 in the rat CSM. Western immunoblotting experiments revealed decreased protein expression of p38MAPK and phosphorylation of SAPK/JNK in the CSM from ethanol-treated rats. Additionally, ethanol consumption decreased the expression of MMP-2. Functional assays showed that SP600125, an inhibitor of SAPK/JNK, prevented the increase in endothelin (ET)-1-induced contraction in the CSM from ethanol-treated rats. Treatment with ethanol decreased MMP-2 activity, but did not change net MMP activity in the rat CSM. Ethanol consumption increased the circulating levels of MMP-2, MMP-9, and TIMP-2 as well as the MMP-9/TIMP-1 ratio. The major finding of our study is that ethanol consumption down-regulates both MAPK and MMP pathways in the rat CSM, whereas it increases the circulating levels of MMP-9. Additionally, we found that SAPK/JNK plays a role in ethanol-induced increase on ET-1 contraction in the isolated rat CSM.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".