Fluoxetine inhibits monocrotaline-induced pulmonary arterial remodeling involved in inhibition of RhoA–Rho kinase and Akt signalling pathways in rats
Bibliographic record
Abstract
Activation of the small GTPase Ras homolog gene family member A (RhoA) and Rho-associated kinase (ROCK) are important in the pathogenesis of pulmonary arterial hypertension (PAH). Selective serotonin reuptake inhibitors inhibit activation of RhoA and ROCK in vitro, and ameliorate PAH and pulmonary arterial remodeling in vivo. However, little is known about whether the RhoA-ROCK signalling pathway is involved in the treatment of PAH with fluoxetine in vivo. The aim of the present study was to investigate the involvement of the RhoA-ROCK signalling pathway in the protective effect of the selective serotonin reuptake inhibitor fluoxetine against monocrotaline (MCT)-induced pulmonary arterial remodeling. MCT was applied to establish PAH in male Wistar rats. Fluoxetine was administered by gastric gavage once a day for 21 d. The results showed that MCT induced pulmonary arterial remodeling, raised the serotonylation and membrane translocation of RhoA in the lungs, and increased serotonin transporter (5-HTT), RhoA, and ROCK2 expression, and extracellular signal-regulated kinase (ERK) and Akt phosphorylation in the pulmonary arteries and the lungs. Fluoxetine markedly inhibited these MCT-induced changes. The findings suggest that fluoxetine inhibits MCT-induced pulmonary arterial remodeling in rats by inhibition of the RhoA-ROCK and Akt signalling pathways.
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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) | 0.001 | 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) | 0.002 | 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".