Fluoxetine protects against monocrotaline-induced pulmonary arterial remodeling by inhibition of hypoxia-inducible factor-1α and vascular endothelial growth factor
Bibliographic record
Abstract
The selective serotonin re-uptake inhibitor fluoxetine has been shown to protect against monocrotaline (MCT)-induced pulmonary hypertension in rats. To investigate the possible role of hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) in mediating this protective effect, MCT-treated rats were administered fluoxetine by gavage, at doses of 2 mg/kg body mass or 10 mg/kg once daily for 3 weeks. Changes in pulmonary hemodynamic parameters, pulmonary artery morphologies, and expressions of HIF-1α and VEGF were assessed. Fluoxetine at the 10 mg/kg dose, but not at the 2 mg/kg dose, attenuated the effects of MCT on pulmonary artery pressure, right ventricle index, and medial wall thickness. In addition, 10 mg/kg fluoxetine mitigated the MCT-induced up-regulation of HIF-1α and VEGF protein and reactive oxygen species (ROS) in the lungs. This dosage also decreased pERK1/2 levels and inhibited proliferation of pulmonary arterial smooth muscle cells in MCT-treated rats. In conclusion, fluoxetine can protect against MCT-induced pulmonary arterial remodeling, which linked to reduced ROS generation and decreased HIF-1α and VEGF protein levels via the ERK1/2 phosphorylation pathway.
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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".