Fluorofenidone attenuates vascular remodeling in hypoxia-induced pulmonary hypertension of rats
Bibliographic record
Abstract
Fluorofenidone (AKF-PD) is a novel pyridone derivate that targets transforming growth factor-β1 (TGF-β1) signaling. Previous studies have proven that AKF-PD functions as an antifibrotic agent in pulmonary fibrosis and renal fibrosis models. Activated TGF-β1 signaling is thought to be a major feature of pulmonary hypertension (PH). TGF-β1 exerts powerful pro-proliferation effects on pulmonary arterial smooth muscle cells (PASMCs), and hence, prompts vascular remodeling. This study is designed to investigate the effect of AKF-PD on vascular remodeling in a rat model of hypoxia-induced PH. PH was induced in rats by 4 weeks of hypoxia. The expression of TGF-β1, collagen I, and collagen III was analyzed by ELISA, immunohistochemistry, real-time PCR, or Western blot. Proliferation of cultured PASMCs was determined by the BrdU incorporation method and flow cytometry. The results showed that AKF-PD treatment (0.5 or 1.0 g·(kg body mass)·d(-1)) for 4 weeks attenuated pulmonary vascular remodeling and improved homodynamic parameters. TGF-β1 level was significantly down-regulated by AKF-PD both in vivo and in vitro. Furthermore, hypoxia- and TGF-β1-induced PASMC proliferation and collagen expression were both significantly suppressed by AKF-PD. These results suggest that AKF-PD ameliorates the progression of PH induced by hypoxia in rats through its regulation of TGF-β1 expression, PASMC proliferation, and the extracellular matrix.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".