Preclinical Investigation of Trifluoperazine as a Novel Therapeutic Agent for the Treatment of Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Trifluoperazine (TFP), an antipsychotic drug approved by the Food and Drug Administration, has been show to exhibit anti-cancer effects. Pulmonary arterial hypertension (PAH) is a devastating disease characterized by a progressive obliteration of small pulmonary arteries (PAs) due to exaggerated proliferation and resistance to apoptosis of PA smooth muscle cells (PASMCs). However, the therapeutic potential of TFP for correcting the cancer-like phenotype of PAH-PASMCs and improving PAH in animal models remains unknown. PASMCs isolated from PAH patients were exposed to different concentrations of TFP before assessments of cell proliferation and apoptosis. The in vivo therapeutic potential of TFP was tested in two preclinical models with established PAH, namely the monocrotaline and sugen/hypoxia-induced rat models. Assessments of hemodynamics by right heart catheterization and histopathology were conducted. TFP showed strong anti-survival and anti-proliferative effects on cultured PAH-PASMCs. Exposure to TFP was associated with downregulation of AKT activity and nuclear translocation of forkhead box protein O3 (FOXO3). In both preclinical models, TFP significantly lowered the right ventricular systolic pressure and total pulmonary resistance and improved cardiac function. Consistently, TFP reduced the medial wall thickness of distal PAs. Overall, our data indicate that TFP could have beneficial effects in PAH and support the view that seeking new uses for old drugs may represent a fruitful approach.
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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 | 0.001 |
| 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".