ABSTRACT
OBJECTIVES: Celastrol has widespread therapeutic applications in various pathological conditions, including chronic inflammation. Previous studies have demonstrated the potent cardioprotective effects of celastrol. Nevertheless, limited attention has been given to its potential in reducing ventricular arrhythmias (VAs) following myocardial infarction (MI). Hence, this study aimed to elucidate the potential mechanisms underlying the regulatory effects of celastrol on VAs and cardiac electrophysiological parameters in rats after MI. METHODS: Sprague-Dawley rats were divided at random: the sham, MI, and MI + celastrol groups. The left coronary artery was occluded in the MI and MI + Cel groups. Electrocardiogram, heart rate variability (HRV), ventricular electrophysiological parameters analysis, histology staining of ventricles, Enzyme-linked immunosorbent assay (ELISA), western blotting and Quantitative real-time polymerase chain reaction (qRT-PCR) were performed to elucidate the underlying mechanism of celastrol. Besides, H9c2 cells were subjected to hypoxic conditions to create an in vitro model of MI and then treated with celastrol for 24â¯hours. Nigericin was used to activate the NLRP3 inflammasome. RESULTS: Compared with that MI group, cardiac electrophysiology instability was significantly alleviated in the MI + celastrol group. Additionally, celastrol improved HRV, upregulated the levels of Cx43, Kv.4.2, Kv4.3 and Cav1.2, mitigated myocardial fibrosis, and inhibited the NLRP3 inflammasome pathway. In vitro conditions also supported the regulatory effects of celastrol on the NLRP3 inflammasome pathway. CONCLUSIONS: Celastrol could alleviate the adverse effects of VAs after MI partially by promoting autonomic nerve remodeling, ventricular electrical reconstruction and ion channel remodeling, and alleviating ventricular fibrosis and inflammatory responses partly by through inhibiting the NLRP3/Caspase-1/IL-1ß pathway.
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INTRODUCTION: Obesity and imbalance in lipid homeostasis contribute greatly to heart failure with preserved ejection fraction (HFpEF), the dominant form of heart failure. Few effective therapies exist to control metabolic alterations and lipid homeostasis. OBJECTIVES: We aimed to investigate the cardioprotective roles of AdipoRon, the adiponectin receptor agonist, in regulating lipid accumulation in the two-hit HFpEF model. METHODS: HFpEF mouse model was induced using 60 % high-fat diet plus L-NAME drinking water. Then, AdipoRon (50 mg/kg) or vehicle were administered by gavage to the two-hit HFpEF mouse model once daily for 4 weeks. Cardiac function was evaluated using echocardiography, and Postmortem analysis included RNA-sequencing, untargeted metabolomics, transmission electron microscopy and molecular biology methods. RESULTS: Our study presents the pioneering evidence that AdipoR was downregulated and impaired fatty acid oxidation in the myocardia of HFpEF mice, which was associated with lipid metabolism as indicated by untargeted metabolomics. AdipoRon, orally active synthetic adiponectin receptor agonist, could upregulate AdipoR1/2 (independently of adiponectin) and reduce lipid droplet accumulation, and alleviate fibrosis to restore HFpEF phenotypes. Finally, AdipoRon primarily exerted its effects through restoring the balance of myocardial fatty acid intake, transport, and oxidation via the downstream AMPKα or PPARα signaling pathways. The protective effects of AdipoRon in HFpEF mice were reversed by compound C and GW6471, inhibitors of AMPKα and PPARα, respectively. CONCLUSIONS: AdipoRon ameliorated the HFpEF phenotype by promoting myocardial fatty acid oxidation, decreasing fatty acid transport, and inhibiting fibrosis via the upregulation of AdipoR and the activation of AdipoR1/AMPKα and AdipoR2/PPARα-related downstream pathways. These findings underscore the therapeutic potential of AdipoRon in HFpEF. Importantly, all these parameters get restored in the context of continued mechanical and metabolic stressors associated with HFpEF.
ABSTRACT
BACKGROUND: This study aimed to develop and validate a nomogram to predict probability of in-stent restenosis (ISR) in patients undergoing percutaneous coronary intervention (PCI). METHODS: Patients undergoing PCI with drug-eluting stents between July 2009 and August 2011 were retrieved from a cohort study in a high-volume PCI center, and further randomly assigned to training and validation sets. The least absolute shrinkage and selection operator (LASSO) regression model was used to screen out significant features for construction of nomogram. Multivariable logistic regression analysis was applied to build a nomogram-based predicting model incorporating the variables selected in the LASSO regression model. The area under the curve (AUC) of the receiver operating characteristics (ROC), calibration plot and decision curve analysis (DCA) were performed to estimate the discrimination, calibration and utility of the nomogram model respectively. RESULTS: A total of 463 patients with DES implantation were enrolled and randomized in the development and validation sets. The predication nomogram was constructed with five risk factors including prior PCI, hyperglycemia, stents in left anterior descending artery (LAD), stent type, and absence of clopidogrel, which proved reliable for quantifying risks of ISR for patients with stent implantation. The AUC of development and validation set were 0.706 and 0.662, respectively, indicating that the prediction model displayed moderate discrimination capacity to predict restenosis. The high quality of calibration plots in both datasets demonstrated strong concordance performance of the nomogram model. Moreover, DCA showed that the nomogram was clinically useful when intervention was decided at the possibility threshold of 9%, indicating good utility for clinical decision-making. CONCLUSIONS: The individualized prediction nomogram incorporating 5 commonly clinical and angiographic characteristics for patients undergoing PCI can be conveniently used to facilitate early identification and improved screening of patients at higher risk of ISR.
