Canagliflozin alleviates pulmonary hypertension by activating PPARγ and inhibiting its S225 phosphorylation.

Pulmonary hypertension (PH) is a progressive fatal disease with no cure. Canagliflozin (CANA), a novel medication for diabetes, has been found to have remarkable cardiovascular benefits. However, few studies have addressed the effect and pharmacological mechanism of CANA in the treatment of PH. Therefore, our study aimed to investigate the effect and pharmacological mechanism of CANA in treating PH. First, CANA suppressed increased pulmonary artery pressure, right ventricular hypertrophy, and vascular remodeling in both mouse and rat PH models. Network pharmacology, transcriptomics, and biological results suggested that CANA could ameliorate PH by suppressing excessive oxidative stress and pulmonary artery smooth muscle cell proliferation partially through the activation of PPARγ. Further studies demonstrated that CANA inhibited phosphorylation of PPARγ at Ser225 (a novel serine phosphorylation site in PPARγ), thereby promoting the nuclear translocation of PPARγ and increasing its ability to resist oxidative stress and proliferation. Taken together, our study not only highlighted the potential pharmacological effect of CANA on PH but also revealed that CANA-induced inhibition of PPARγ Ser225 phosphorylation increases its capacity to counteract oxidative stress and inhibits proliferation. These findings may stimulate further research and encourage future clinical trials exploring the therapeutic potential of CANA in PH treatment.

Icariside II alleviates lipopolysaccharide-induced acute lung injury by inhibiting lung epithelial inflammatory and immune responses mediated by neutrophil extracellular traps.

AIMS: Acute lung injury (ALI) is a life-threatening lung disease characterized by inflammatory cell infiltration and lung epithelial injury. Icariside II (ICS II), one of the main active ingredients of Herba Epimedii, exhibits anti-inflammatory and immunomodulatory effects. However, the effect and mechanism of ICS II in ALI remain unclear. The purpose of the current study was to investigate the pharmacological effect and underlying mechanism of ICS II in ALI. MAIN METHODS: Models of neutrophil-like cells, human peripheral blood neutrophils, and lipopolysaccharide (LPS)-induced ALI mouse model were utilized. RT-qPCR and Western blotting determined the gene and protein expression levels. Protein distribution and quantification were analyzed by immunofluorescence. KEY FINDINGS: ICS II significantly reduced lung histopathological damage, edema, and inflammatory cell infiltration, and it reduced pro-inflammatory cytokines in ALI. There is an excessive activation of neutrophils leading to a significant production of NETs in ALI mice, a process mitigated by the administration of ICS II. In vivo and in vitro studies found that ICS II could decrease NET formation by targeting neutrophil C-X-C chemokine receptor type 4 (CXCR4). Further data showed that ICS II reduces the overproduction of dsDNA, a NETs-related component, thereby suppressing cGAS/STING/NF-κB signalling pathway activation and inflammatory mediators release in lung epithelial cells. SIGNIFICANCE: This study suggested that ICS II may alleviate LPS-induced ALI by modulating the inflammatory response, indicating its potential as a therapeutic agent for ALI treatment.

Long non-coding RNA and Evolving drug resistance in lung cancer.

Non-small cell lung cancer (NSCLC) is one of the most devastating cancers with a high incidence and mortality rates of all cancers. Locally advanced or metastatic NSCLC patients can benefit from platinum-based chemotherapy and targeted therapy drugs. Nevertheless, primary or acquired drug resistance will result in ineffective treatment, leading to tumor progression. The detailed mechanism underlying drug resistance to NSCLC are complicated and result from various factor. Among them, long noncoding RNAs (lncRNAs) have been found to be critically involved in NSCLC development and play a vital role in mediating therapy resistance. In this review, we attempt to systematically summarize the mechanisms underlying the lncRNA-mediated resistance to chemotherapy agents and targeted therapy drugs against lung cancer.

An optimized machine learning method for predicting wogonin therapy for the treatment of pulmonary hypertension.

Human health is at risk from pulmonary hypertension (PH), characterized by decreased pulmonary vascular resistance and constriction of the pulmonary vessels, resulting in right heart failure and dysfunction. Thus, preventing PH and monitoring its progression before treating it is vital. Wogonin, derived from the leaves of Scutellaria baicalensis Georgi, exhibits remarkable pharmacological activity. In this study, we examined the effectiveness of wogonin in mitigating the progression of PH in mice using right heart catheterization and hematoxylin-eosin (HE) staining. As an alternative to minimize the possibility of harming small animals, we present a scientifically effective feature selection method (BSCDWOA-KELM) that will allow us to develop a novel simpler noninvasive prediction method for wogonin in treating PH. In this method, we use the proposed enhanced whale optimizer (SCDWOA) in conjunction with the kernel extreme learning machine (KELM). Initially, we let SCDWOA perform global optimization experiments on the IEEE CEC2014 benchmark function set to verify its core advantages. Lastly, 12 public and PH datasets are examined for feature selection experiments using BSCDWOA-KELM. As shown in the experimental results for global optimization, the proposed SCDWOA has better convergence performance. Meanwhile, the proposed binary SCDWOA (BSCDWOA) significantly improves the ability of KELM to classify data. By utilizing the BSCDWOA-KELM, key indicators such as the Red blood cell (RBC), the Haemoglobin (HGB), the Lymphocyte percentage (LYM%), the Hematocrit (HCT), and the Red blood cell distribution width-size distribution (RDW-SD) can be efficiently screened in the Pulmonary hypertension dataset, and one of its most essential points is its accuracy of greater than 0.98. Consequently, the BSCDWOA-KELM introduced in this study can be used to predict wogonin therapy for treating pulmonary hypertension in a simple and noninvasive manner.