Cynaropicrin, a sesquiterpene lactone found in artichoke leaves exerts diverse pharmacological effects. This study investigated whether cynaropicrin has a paraptosis-like cell death effect in human hepatocellular carcinoma Hep3B cells in addition to the apoptotic effects reported in several cancer cell lines. Cynaropicrin-induced cytotoxicity and cytoplasmic vacuolation, a key characteristic of paraptosis, were not ameliorated by inhibitors of necroptosis, autophagy, or pan caspase inhibitors in Hep3B cells. Our study showed that cynaropicrin-induced cytotoxicity was accompanied by mitochondrial dysfunction and endoplasmic reticulum stress along with increased cellular calcium ion levels. These effects were significantly mitigated by endoplasmic reticulum stress inhibitor or protein synthesis inhibitor. Moreover, cynaropicrin treatment in Hep3B cells increased reactive oxygen species generation and downregulated apoptosis-linked gene 2-interacting protein X (Alix), a protein that inhibits paraptosis. The addition of the reactive oxygen species scavenger N-acetyl-L-cysteine (NAC) neutralized cynaropicrin-induced changes in Alix expression and endoplasmic reticulum stress marker proteins counteracting endoplasmic reticulum stress and mitochondrial impairment. This demonstrates a close relationship between endoplasmic reticulum stress and reactive oxygen species generation. Additionally, cynaropicrin activated p38 mitogen activated protein kinase and a selective p38 mitogen activated protein kinase blocker alleviated the biological phenomena induced by cynaropicrin. NAC pretreatment showed the best reversal of cynaropicrin induced vacuolation and cellular inactivity. Our findings suggest that cynaropicrin induced oxidative stress in Hep3B cells contributes to paraptotic events including endoplasmic reticulum stress and mitochondrial damage.

Cynaropicrin, a sesquiterpene lactone found in artichoke leaves exerts diverse pharmacological effects. This study investigated whether cynaropicrin has a paraptosis-like cell death effect in human hepatocellular carcinoma Hep3B cells in addition to the apoptotic effects reported in several cancer cell lines. Cynaropicrin-induced cytotoxicity and cytoplasmic vacuolation, a key characteristic of paraptosis, were not ameliorated by inhibitors of necroptosis, autophagy, or pan caspase inhibitors in Hep3B cells. Our study showed that cynaropicrin-induced cytotoxicity was accompanied by mitochondrial dysfunction and endoplasmic reticulum stress along with increased cellular calcium ion levels. These effects were significantly mitigated by endoplasmic reticulum stress inhibitor or protein synthesis inhibitor. Moreover, cynaropicrin treatment in Hep3B cells increased reactive oxygen species generation and downregulated apoptosis-linked gene 2-interacting protein X (Alix), a protein that inhibits paraptosis. The addition of the reactive oxygen species scavenger N-acetyl-L-cysteine (NAC) neutralized cynaropicrin-induced changes in Alix expression and endoplasmic reticulum stress marker proteins counteracting endoplasmic reticulum stress and mitochondrial impairment. This demonstrates a close relationship between endoplasmic reticulum stress and reactive oxygen species generation. Additionally, cynaropicrin activated p38 mitogen activated protein kinase and a selective p38 mitogen activated protein kinase blocker alleviated the biological phenomena induced by cynaropicrin. NAC pretreatment showed the best reversal of cynaropicrin induced vacuolation and cellular inactivity. Our findings suggest that cynaropicrin induced oxidative stress in Hep3B cells contributes to paraptotic events including endoplasmic reticulum stress and mitochondrial damage.

Cynaropicrin, a sesquiterpene lactone found in artichoke leaves exerts diverse pharmacological effects. This study investigated whether cynaropicrin has a paraptosis-like cell death effect in human hepatocellular carcinoma Hep3B cells in addition to the apoptotic effects reported in several cancer cell lines. Cynaropicrin-induced cytotoxicity and cytoplasmic vacuolation, a key characteristic of paraptosis, were not ameliorated by inhibitors of necroptosis, autophagy, or pan caspase inhibitors in Hep3B cells. Our study showed that cynaropicrin-induced cytotoxicity was accompanied by mitochondrial dysfunction and endoplasmic reticulum stress along with increased cellular calcium ion levels. These effects were significantly mitigated by endoplasmic reticulum stress inhibitor or protein synthesis inhibitor. Moreover, cynaropicrin treatment in Hep3B cells increased reactive oxygen species generation and downregulated apoptosis-linked gene 2-interacting protein X (Alix), a protein that inhibits paraptosis. The addition of the reactive oxygen species scavenger N-acetyl-L-cysteine (NAC) neutralized cynaropicrin-induced changes in Alix expression and endoplasmic reticulum stress marker proteins counteracting endoplasmic reticulum stress and mitochondrial impairment. This demonstrates a close relationship between endoplasmic reticulum stress and reactive oxygen species generation. Additionally, cynaropicrin activated p38 mitogen activated protein kinase and a selective p38 mitogen activated protein kinase blocker alleviated the biological phenomena induced by cynaropicrin. NAC pretreatment showed the best reversal of cynaropicrin induced vacuolation and cellular inactivity. Our findings suggest that cynaropicrin induced oxidative stress in Hep3B cells contributes to paraptotic events including endoplasmic reticulum stress and mitochondrial damage.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: The number of people with heart failure (HF) is increasing worldwide, and the social burden is increasing as HF has high mortality and morbidity. We aimed to provide updated trends on the epidemiology of HF in Korea to shape future social measures against HF. Methods: We used the National Health Information Database of the National Health Insurance Service to determine the prevalence, incidence, hospitalization rate, mortality rate, comorbidities, in-hospital mortality, and healthcare cost of patients with HF from 2002 to 2020 in Korea. Results: The prevalence of HF in the total Korean population rose from 0.77% in 2002 to 2.58% (1,326,886 people) in 2020. Although the age-standardized incidence of HF decreased over the past 18 years, the age-standardized prevalence increased. In 2020, the hospitalization rate for any cause in patients with HF was 1,166 per 100,000 persons, with a steady increase from 2002. In 2002, the HF mortality was 3.0 per 100,000 persons, which rose to 15.6 per 100,000 persons in 2020. While hospitalization rates and in-hospital mortality for patients with HF increased, the mortality rate for patients with HF did not (5.8% in 2020), and the one-year survival rate from the first diagnosis of HF improved. The total healthcare costs for patients with HF were approximately $2.4 billion in 2020, a 16-fold increase over the $0.15 billion in 2002. Conclusions The study’s results underscore the growing socioeconomic burden of HF in Korea, driven by an aging population and increasing HF prevalence.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.