Prospective validation of a mobile health application for blood pressure management in patients with hypertensive disorders of pregnancy: study protocol for a randomized controlled trial.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) pose significant risks to both maternal and fetal health, contributing to global morbidity and mortality. Management of HDP is complex, particularly because of concerns regarding potential negative effects on utero-placental circulation and limited therapeutic options due to fetal safety. Our study investigates whether blood pressure monitoring through a mobile health (mHealth) application can aid in addressing the challenges of blood pressure management in pregnant individuals with HDP. Additionally, we aim to assess whether this intervention can improve short-term maternal and fetal outcomes and potentially mitigate long-term cardiovascular consequences. METHODS: This prospective, randomized, single-center trial will include 580 pregnant participants who meet the HDP criteria or who have a heightened risk of pregnancy-related hypertension due to factors such as multiple pregnancies, obesity, diabetes, or a history of HDP in prior pregnancies leading to preterm birth. Participants will be randomized to either the mHealth intervention group or the standard care group. The primary endpoint is the difference in systolic blood pressure from enrollment to 1 month after childbirth. The secondary endpoints include various blood pressure parameters, obstetric outcomes, body mass index trajectory, step counts, mood assessment, and drug adherence. CONCLUSIONS: This study emphasizes the potential of mHealth interventions, such as the Heart4U application, to improve blood pressure management in pregnant individuals with HDP. By leveraging technology to enhance engagement, communication, and monitoring, this study aims to positively impact maternal, fetal, and postpartum outcomes associated with HDP. This innovative approach demonstrates the potential of personalized technology-driven solutions for managing complex health conditions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05995106. Registered on 16 August 2023.

Artificial intelligence-enhanced automation of left ventricular diastolic assessment: a pilot study for feasibility, diagnostic validation, and outcome prediction.

Background: Evaluating left ventricular diastolic function (LVDF) is crucial in echocardiography; however, the complexity and time demands of current guidelines challenge clinical use. This study aimed to develop an artificial intelligence (AI)-based framework for automatic LVDF assessment to reduce subjectivity and improve accuracy and outcome prediction. Methods: We developed an AI-based LVDF assessment framework using a nationwide echocardiographic dataset from five tertiary hospitals. This framework automatically identifies views, calculates diastolic parameters, including mitral inflow and annular velocities (E/A ratio, e' velocity, and E/e' ratio), maximal tricuspid regurgitation velocity, left atrial (LA) volume index, and left atrial reservoir strain (LARS). Subsequently, it grades LVDF according to guidelines. The AI-framework was validated on an external dataset composed of randomly screened 173 outpatients who underwent transthoracic echocardiography with suspicion for diastolic dysfunction and 33 individuals from medical check-ups with normal echocardiograms at Seoul National University Bundang Hospital, tertiary medical center in Korea, between May 2012 and June 2022. Additionally, we assessed the predictive value of AI-derived diastolic parameters and LVDF grades for a clinical endpoint, defined as a composite of all-cause death and hospitalization for heart failure, using Cox-regression risk modelling. Results: In an evaluation with 200 echocardiographic examinations (167 suspected diastolic dysfunction patients, 33 controls), it achieves an overall accuracy of 99.1% in identifying necessary views. Strong correlations (Pearson coefficient 0.901-0.959) were observed between AI-derived and manually-derived measurements of diastolic parameters, including LARS as well as conventional parameters. When following the guidelines, whether utilizing AI-derived or manually-derived parameters, the evaluation of LVDF consistently showed high concordance rates (94%). However, both methods exhibited lower concordance rates with the clinician's prior assessments (77.5% and 78.5%, respectively). Importantly, both AI-derived and manually-derived LVDF grades independently demonstrated significant prognostic value [adjusted hazard ratio (HR) =3.03; P=0.03 and adjusted HR =2.75; P=0.04, respectively] for predicting clinical outcome. In contrast, the clinician's prior grading lost its significance as a prognostic indicator after adjusting for clinical risk factors (adjusted HR =1.63; P=0.36). AI-derived LARS values significantly decreased with worsening LVDF (P for trend <0.001), and low LARS (<17%) was associated with increased risk for the clinical outcome (Log-rank P=0.04) relative to that for preserved LARS (≥17%). Conclusions: Our AI-based approach for automatic LVDF assessment on echocardiography is feasible, potentially enhancing clinical diagnosis and outcome prediction.

Resilient green infrastructure: Navigating environmental resistance for sustainable development, social mobility in climate change policy.

This study explores the complex dynamics of environmental resistance, policy stability, skill development, and green initiatives in light of the growing worldwide concerns about climate change. COP27 and the G20 Summit show that as microcosm of the global discourse, provides a unique opportunity to study it. This research sought to thoroughly investigate, the links among green infrastructure, green technological innovation, policy stability, skill development, and their combined effects on social mobility and climate change (Case-1), it also discusses the global talk on climate change in COP27 and G20 (Case-2). In Case-1 data were analyzed through the use of structural equation modeling (SEM) by adopting a quantitative approach, and in Case-2 data were analyzed using theme analysis by applying a qualitative approach. Using a mixed-method research approach, the study surveyed 375 locals living close to the CPEC corridor quantitatively and interviewed ten important stakeholders, including elected officials, environmental activists, and community leaders, qualitatively. The survey highlighted the complex perspectives and experiences of citizens with green programs and environmental legislation in the CPEC zone. The study revealed the perceptions and experiences of residents regarding green initiatives and environmental policies within the CPEC region. Key stakeholders provided valuable insights into policy formulation and ongoing environmental sustainability efforts. The analysis unveiled intricate relationships between green infrastructure, technological innovation, policy stability, skill development, and their collective impact on climate change and social mobility. Notably, the study identified a critical research gap in understanding these dynamics within regions undergoing substantial economic development. Policy formulation and continuing environmental sustainability efforts were aided by key stakeholders' ideas. Green infrastructure, technological innovation, policy stability, skill development, and their overall influence on climate change and social mobility were all examined. Notably, the study found a critical research vacuum in understanding these processes inside rapidly developing economies. Policymakers, environmental groups, and communities managing the fine line between economic success and environmental responsibility will find great value in the findings. This study is unique because it examines issues on climate change from a local perspective in a region that is rapidly developing economically, it also adds value to the climate change challenges on the global level. This study presents a substantial theoretical contribution by examining the intricate interactions among environmental opposition, policy stability, skill development, and green initiatives within the CPEC against the backdrop of global climate change concerns.

Effects of bisphenol A on reproduction, oxidative stress, and lipid regulation in the marine rotifer Brachionus plicatilis.

This study reports the effects of bisphenol A (BPA) on the rotifer Brachionus plicatilis, focusing on growth performance, reproductive output, oxidative stress responses, and lipid metabolism genes. High BPA levels disrupted peak daily offspring production and led to oxidative stress and increased superoxide dismutase and catalase activity. The research identified distinctive monoacylglycerol O-acyltransferase (MGAT) and diacylglycerol O-acyltransferase (DGAT) genes in B. plicatilis, B. rotundiformis, and B. koreanus, enhancing understanding of lipid metabolism in these species. BPA exposure significantly altered MGAT and DGAT expression, and feeding status affected these regulatory patterns. When food was unavailable, BPA reduced DGAT2 and MGAT2a expression. However, under feeding conditions, DGAT2 and MGAT1 levels increased, indicating that nutritional status and BPA exposure interact to affect gene expression.

Mitral Annular Tissue Velocity Predicts Survival in Patients With Primary Mitral Regurgitation.

BACKGROUND AND OBJECTIVES: Early diastolic mitral annular tissue (e') velocity is a commonly used marker of left ventricular (LV) diastolic function. This study aimed to investigate the prognostic implications of e' velocity in patients with mitral regurgitation (MR). METHODS: This retrospective cohort study included 1,536 consecutive patients aged <65 years with moderate or severe chronic primary MR diagnosed between 2009 and 2018. The primary and secondary outcomes were all-cause and cardiovascular mortality, respectively. According to the current guidelines, the cut-off value of e' velocity was defined as 7 cm/s. RESULTS: A total of 404 individuals were enrolled (median age, 51.0 years; 64.1% male; 47.8% severe MR). During a median 6.0-year follow-up, there were 40 all-cause mortality and 16 cardiovascular deaths. Multivariate analysis revealed a significant association between e' velocity and all-cause death (adjusted hazard ratio [aHR], 0.770; 95% confidence interval [CI], 0.634-0.935; p=0.008) and cardiovascular death (aHR, 0.690; 95% CI, 0.477-0.998; p=0.049). Abnormal e' velocity (≤7 cm/s) independently predicted all-cause death (aHR, 2.467; 95% CI, 1.170-5.200; p=0.018) and cardiovascular death (aHR, 5.021; 95% CI, 1.189-21.211; p=0.028), regardless of symptoms, LV dimension and ejection fraction. Subgroup analysis according to sex, MR severity, mitral valve replacement/repair, and symptoms, showed no significant interactions. Including e' velocity in the 10-year risk score improved reclassification for mortality (net reclassification improvement [NRI], 0.154; 95% CI, 0.308-0.910; p<0.001) and cardiovascular death (NRI, 1.018; 95% CI, 0.680-1.356; p<0.001). CONCLUSIONS: In patients aged <65 years with primary MR, e' velocity served as an independent predictor of all-cause and cardiovascular deaths.

Deep learning-assisted inverse design of nanoparticle-embedded radiative coolers.

Radiative cooling is an energy-efficient technology without consuming power. Depending on their use, radiative coolers (RCs) can be designed to be either solar-transparent or solar-opaque, which requires complex spectral characteristics. Our research introduces a novel deep learning-based inverse design methodology for creating thin-film type RCs. Our deep learning algorithm determines the optimal optical constants, material volume ratios, and particle size distributions for oxide/nitride nanoparticle-embedded polyethylene films. It achieves the desired optical properties for both types of RCs through Mie Scattering and effective medium theory. We also assess the optical and thermal performance of each RCs.

The impact of the COVID-19 pandemic on the rehabilitation therapy of children and adolescents with cerebral palsy: a nationwide, health insurance data-based study.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has profoundly affected the utilization of rehabilitation services. Existing evidence investigating this issue at the nationwide level is lacking, and it is uncertain whether the effects of the COVID-19 pandemic on the use of rehabilitation therapy of children and adolescents with cerebral palsy. This study aimed to investigate the impact of COVID-19 on the rehabilitation therapy of children and adolescents with cerebral palsy. Methods: We obtained data from South Korea's Health Insurance Review and Assessment Agency for 2017-2021. By analyzing the claims data, we focused on rehabilitation therapy in individuals with CP under 18 years of age. We categorized these according to therapy type (physical, occupational, or dysphagia), medical facility, hospital visits, and insurance. We calculated the patient counts and average claims per person and compared the average from before to during the COVID-19 pandemic. Results: Over the 5 years, there was a significant decline in the number of patients undergoing rehabilitation therapy (trend p = 0.004), but the average claims per person remained stable (trend p = 0.971). During the COVID-19 pandemic, the average number of claims per person decreased significantly compared to the control period (p = 0.013). Both the physical (p = 0.049) and occupational therapy groups (p = 0.019) showed significant differences in claims. General hospitals and hospitals experienced a decrease in average cases by 2.2 (p < 0.001) and 2.4 (p < 0.001) respectively, while long-term care hospitals increased by 3.1 cases (p < 0.001). Outpatients showed a decline of 2.0 cases (p < 0.001), whereas inpatients showed an increase of 5.9 cases (p < 0.001). Individuals with health insurance decreased by 0.5 cases (p = 0.007), but the decrease of 0.08 cases among medical aid-covered individuals was not statistically significant (p = 0.898). Conclusion: In 2020-2021, the average number of claims per person showed a significant decrease compared to the pre-COVID-19 pandemic period (2017-2019). Depending on the type of treatment, the number of claims for physical and occupational therapy significantly decreased.

Machine Learning-Based Discrimination of Cardiovascular Outcomes in Patients With Hypertrophic Cardiomyopathy.

Background: Current risk stratification strategies for patients with hypertrophic cardiomyopathy (HCM) are limited to traditional methodologies. Objectives: The authors aimed to establish machine learning (ML)-based models to discriminate major cardiovascular events in patients with HCM. Methods: We enrolled consecutive HCM patients from 2 tertiary referral centers and used 25 clinical and echocardiographic features to discriminate major adverse cardiovascular events (MACE), including all-cause death, admission for heart failure (HF-adm), and stroke. The best model was selected for each outcome using the area under the receiver operating characteristic curve (AUROC) with 20-fold cross-validation. After testing in the external validation cohort, the relative importance of features in discriminating each outcome was determined using the SHapley Additive exPlanations (SHAP) method. Results: In total, 2,111 patients with HCM (age 61.4 ± 13.6 years; 67.6% men) were analyzed. During the median 4.0 years of follow-up, MACE occurred in 341 patients (16.2%). Among the 4 ML models, the logistic regression model achieved the best AUROC of 0.800 (95% CI: 0.760-0.841) for MACE, 0.789 (95% CI: 0.736-0.841) for all-cause death, 0.798 (95% CI: 0.736-0.860) for HF-adm, and 0.807 (95% CI: 0.754-0.859) for stroke. The discriminant ability of the logistic regression model remained excellent when applied to the external validation cohort for MACE (AUROC = 0.768), all-cause death (AUROC = 0.750), and HF-adm (AUROC = 0.806). The SHAP analysis identified left atrial diameter and hypertension as important variables for all outcomes of interest. Conclusions: The proposed ML models incorporating various phenotypes from patients with HCM accurately discriminated adverse cardiovascular events and provided variables with high importance for each outcome.

Artificial intelligence-enhanced automation for M-mode echocardiographic analysis: ensuring fully automated, reliable, and reproducible measurements.

To enhance M-mode echocardiography's utility for measuring cardiac structures, we developed and evaluated an artificial intelligence (AI)-based automated analysis system for M-mode images through the aorta and left atrium [M-mode (Ao-LA)], and through the left ventricle [M-mode (LV)]. Our system, integrating two deep neural networks (DNN) for view classification and image segmentation, alongside an auto-measurement algorithm, was developed using 5,958 M-mode images [3,258 M-mode (LA-Ao), and 2,700 M-mode (LV)] drawn from a nationwide echocardiographic dataset collated from five tertiary hospitals. The performance of view classification and segmentation DNNs were evaluated on 594 M-mode images, while automatic measurement accuracy was tested on separate internal test set with 100 M-mode images as well as external test set with 280 images (140 sinus rhythm and 140 atrial fibrillation). Performance evaluation showed the view classification DNN's overall accuracy of 99.8% and segmentation DNN's Dice similarity coefficient of 94.3%. Within the internal test set, all automated measurements, including LA, Ao, and LV wall and cavity, resonated strongly with expert evaluations, exhibiting Pearson's correlation coefficients (PCCs) of 0.81-0.99. This performance persisted in the external test set for both sinus rhythm (PCC, 0.84-0.98) and atrial fibrillation (PCC, 0.70-0.97). Notably, automatic measurements, consistently offering multi-cardiac cycle readings, showcased a stronger correlation with the averaged multi-cycle manual measurements than with those of a single representative cycle. Our AI-based system for automatic M-mode echocardiographic analysis demonstrated excellent accuracy, reproducibility, and speed. This automated approach has the potential to improve efficiency and reduce variability in clinical practice.

Integrative Assessment of Cardiopulmonary Fitness Using Cardiopulmonary Exercise Test With Supine Bicycle Echocardiography in Patients Presenting Dyspnea.

BACKGROUND: Cardiopulmonary exercise test (CPET) with supine bicycle echocardiography (SBE) enables comprehensive physiologic assessment during exercise. We characterized cardiopulmonary fitness by integrating CPET-SBE parameters and evaluated its prognostic value in patients presenting with dyspnea. METHODS AND RESULTS: We retrospectively reviewed 473 consecutive patients who underwent CPET-SBE for dyspnea evaluation. A dimensionality reduction process was applied, transforming 24 clinical and CPET-SBE parameters into a 2-dimensional feature map, followed by patient clustering based on the data distribution. Clinical and exercise features were compared among the clusters in addition to the 5-year risk of clinical outcome (a composite of cardiovascular death and heart failure hospitalization). Maximum exercise effort (R >1) was achieved in 95% of cases. Through dimensionality reduction, 3 patient clusters were derived: Group 1 (n=157), 2 (n=104), and 3 (n=212). Median age and female proportion increased from Group 1 to 2, and 3, although resting echocardiography parameters showed no significant abnormalities among the groups. There was a worsening trend in the exercise response from Group 1 to 2 and 3, including left ventricular diastolic function, oxygen consumption, and ventilatory efficiency. During follow-up (median 6.0 [1.6-10.4] years), clinical outcome increased from Group 1 to 2 and 3 (5-year rate 3.7% versus 7.0% versus 13.0%, respectively; log-rank P=0.02), with higher risk in Group 2 (hazard ratio, 1.94 [95% CI, 0.52-7.22]) and Group 3 (3.92 [1.34-11.42]) compared with Group 1. CONCLUSIONS: Comprehensive evaluation using CPET-SBE can reveal distinct characteristics of cardiopulmonary fitness in patients presenting with dyspnea, potentially enhancing outcome prediction.

Performance Assessment of Sysmex DI-60: Is Digital Morphology Analyzer Reliable for White Blood Cell Differentials in Body Fluids?

BACKGROUND: Few studies have evaluated digital morphology (DM) analyzers on body fluids (BF). We evaluated the performance of a DM analyzer, Sysmex DI-60 (Sysmex, Kobe, Japan) for white blood cell (WBC) differentials in BF samples. METHODS: In five BF samples (two pleural fluids and three ascites) containing a single, dominant cell type (>80%, neutrophils, lymphocytes, macrophages, abnormal lymphocytes, and malignant cells in each sample), we evaluated the precision of the DI-60 and compared the WBC differentials and turnaround times (TAT) between DI-60 and manual counting. RESULTS: The precision of the DI-60 pre-classification and verification was excellent (%CV, 0.01-3.16%). After verification, the DI-60 showed high sensitivity, specificity, and efficiency (ranges: 90.8-98.1%, 96.8-97.9%, and 92.5-98.0%, respectively) for the dominant cell types in neutrophil- and lymphocyte-dominant samples. For all samples, the DI-60 and manual counting showed high correlations for major cell types (neutrophils, lymphocytes, macrophages, and others, r = 0.72 to 0.94) after verification. The agreement between the pre-classification and verification of the DI-60 was strong in the neutrophil-dominant sample (κ = 0.81). The DI-60 showed a significantly longer TAT (min: s) than manual counting for all samples (median TAT/slide: 6:28 vs. 1:53, p < 0.0001), with remarkable differences in abnormal lymphocyte- and malignant cell-dominant samples (21:05 vs. 2:06; 12:34 vs. 2:25). CONCLUSIONS: The DI-60 may provide reliable data in neutrophil- and lymphocyte-dominant BF samples. However, it may require longer times and higher workloads for WBC differentials especially in BF samples containing atypical cells. Further improvement would be needed before applying DM analyzers for routine clinical practice in BF analysis.

Mildly Reduced Renal Function Is Associated With Increased Heart Failure Admissions in Patients With Hypertrophic Cardiomyopathy.

BACKGROUND: The association between renal dysfunction and cardiovascular outcomes has yet to be determined in patients with hypertrophic cardiomyopathy (HCM). We aimed to investigate whether mildly reduced renal function is associated with the prognosis in patients with HCM. METHODS: Patients with HCM were enrolled at two tertiary HCM centers. Patients who were on dialysis, or had a previous history of heart failure (HF) or stroke were excluded. Patients were categorized into 3 groups by estimated glomerular filtration rate (eGFR): stage I (eGFR ≥ 90 mL/min/1.73 m², n = 538), stage II (eGFR 60-89 mL/min/1.73 m², n = 953), and stage III-V (eGFR < 60 mL/min/1.73 m², n = 265). Major adverse cardiovascular events (MACEs) were defined as a composite of cardiovascular death, hospitalization for HF (HHF), or stroke during median 4.0-year follow-up. Multivariable Cox regression model was used to adjust for covariates. RESULTS: Among 1,756 HCM patients (mean 61.0 ± 13.4 years; 68.1% men), patients with stage III-V renal function had a significantly higher risk of MACEs (adjusted hazard ratio [aHR], 2.71; 95% confidence interval [CI], 1.39-5.27; P = 0.003), which was largely driven by increased incidence of cardiovascular death and HHF compared to those with stage I renal function. Even in patients with stage II renal function, the risk of MACE (vs. stage I: aHR, 2.21' 95% CI, 1.23-3.96; P = 0.008) and HHF (vs. stage I: aHR, 2.62; 95% CI, 1.23-5.58; P = 0.012) was significantly increased. CONCLUSION: This real-world observation showed that even mildly reduced renal function (i.e., eGFR 60-89 mL/min/1.73 m²) in patients with HCM was associated with an increased risk of MACEs, especially for HHF.

Age-dependent implications of left ventricular hypertrophy regression in patients with hypertension.

Left ventricular hypertrophy (LVH) is a significant risk factor for cardiovascular mortality and morbidity in patients with hypertension. However, the effect of age on LVH regression or persistence and its differential prognostic value remain unclear. Therefore, we investigated the clinical implications of LVH regression in 1847 patients with hypertension and echocardiography data (at baseline and during antihypertensive treatment at an interval of 6-18 months) according to age. LVH was defined as a left ventricular mass index (LVMI) > 115 g/m2 and >95 g/m2 in men and women, respectively. LVH prevalence at baseline was not different according to age (age < 65 years: 42.6%; age ≥65 years: 45.7%; p = 0.187), but LVH regression was more frequently observed in the younger group (36.4% vs. 27.5%; p = 0.008). Spline curves and multiple linear regression analysis showed a significant relationship between reductions in systolic blood pressure and LVMI in the younger group (ß = 0.425; p < 0.001), but not the elderly group (ß = 0.044; p = 0.308). LVH regression was associated with a lower risk of the study outcome (composite of cardiovascular death and hospitalization for heart failure) regardless of age. In conclusion, the association between the reduction in blood pressure and LVH regression was prominent in patients with age < 65 years, but not in those with age ≥65 years. However, an association between LVH regression and lower risk of cardiovascular death and hospitalization for heart failure was observed regardless of patient age, suggesting the prognostic value of the LVH regression not only in the younger patients but also in elderly patients.

A roadmap to SDGs-emergence of technological innovation and infrastructure development for social progress and mobility.

The goal of this study was to conduct a thorough investigation on understanding how infrastructure growth and technological innovation affect social mobility and the Sustainable Development Goals (SDGs). This study aimed to illuminate the underlying mechanisms by exploring the mediating function of psychological empowerment and the moderating impact of community satisfaction. The study carefully chose a sizeable sample of 370 connected to the mega project CPEC. Data collection was carried out using a questionnaire-based approach. Notably, the study confirmed the large and favorable influence of technical innovation and infrastructural development on both the SDGs-13 (climate change) and social mobility. Furthermore, this study provided light on the critical function of environmental impacts identifying it as an important mediating mechanism that magnifies the effects of innovation and infrastructure on long-term development outcomes. It gives decision-makers in government, business, international organizations, and local communities useful information by offering empirical data and insights. This study offers a novel perspective and explores the relationship between infrastructure growth, technological innovation, social mobility, and SDGs-13-climate change. It uncovers the pivotal roles of psychological empowerment and community satisfaction, offering fresh insights into global development strategies influencing SDGs.

Irreversible myocardial injury attenuates the benefits of sacubitril/valsartan in heart failure patients.

BACKGROUND: Despite the established benefits of angiotensin receptor-neprilysin inhibitor (ARNI) in heart failure with reduced ejection fraction (HFrEF) across various etiologies, there are controversies regarding the effects of ARNI in patients with irreversible myocardial injury. The aim of this study is to investigate the impact of irreversible myocardial injury on the benefits of ARNI treatment in patients with HFrEF, consisted of both ischemic and non-ischemic etiologies. METHODS AND RESULTS: We conducted a retrospective single-center study including 409 consecutive patients with HFrEF treated with ARNI between March 2017 and May 2020. Irreversible myocardial injury was defined as nonviable myocardium without contractile reserve, which suggests a limited potential for recovery of left ventricular function and geometry. At baseline, irreversible myocardial injury was observed in 129 (31.5%) patients. Composite outcome was cardiovascular death or hospitalization for heart failure, which occurred in 56 (43.4%) and 61 (21.8%) patients with and without irreversible myocardial injury, respectively. On multivariable analysis, irreversible injury presence, but not ischemic etiology, was an independent predictor of composite outcome (hazard ratio 2.16, 95% confidence interval 1.33-3.49). Mediation analysis revealed that the increased risk of the composite outcome due to irreversible myocardial injury was mediated by attenuated LV reverse remodeling (Z value = 2.02, P = 0.043). CONCLUSIONS: The presence of irreversible myocardial injury was significantly associated with the response to ARNI treatment in patients with HFrEF, regardless of etiology.

Lipid Metabolism Pathway Genes and Lung Cancer: ACADSB rs12220683G>C Is Associated with Better Survival Outcome in Patients with Non-Small Cell Lung Cancer.

INTRODUCTION: Altered lipid metabolism has been reported to be associated with prognosis in multiple cancers. This study aimed to investigate the association of polymorphisms in lipid metabolism pathway genes with survival outcomes in patients with surgically resected non-small cell lung cancer (NSCLC). METHODS: In total, 744 patients with surgically resected NSCLC (380 in the discovery cohort and 364 in the validation cohort) were included in this study. The association between 176 polymorphisms of lipid metabolism pathway genes and the clinical outcomes of NSCLC patients was analyzed. RESULTS: Among the polymorphisms investigated, ACADSB rs10902859G>A was associated with significantly better overall survival (OS) in the discovery, validation, and combined cohorts. ACADSB rs10902859G>A was located in the repressed region and had strong linkage disequilibrium (D' = 1.00 and r2 = 0.94), with rs12220683G>C located in the H3K4me3 peak region, which indicates the presence of active promoters. ACADSB rs12220683G>C was also associated with better OS in the discovery, validation, and combined cohorts (in a dominant model; adjusted hazard ratio [aHR] = 0.53, 95% confidence interval [CI] = 0.30-0.94, p = 0.03; aHR = 0.37, 95% CI = 0.15-0.89, p = 0.03; and aHR = 0.47, 95% CI = 0.29-0.75, p = 0.002, respectively). In vitro luciferase assay demonstrated that the promoter activity of ACADSB was significantly increased in the rs12220683 variant C allele compared with that in the wild G allele (p = 3 × 10-5). CONCLUSION: These results suggest that ACADSB rs12220683G>C increases promoter activity and that increased ACADSB expression may result in better OS in patients with surgically resected NSCLC.

Posterior Mediastinal Paraganglioma With SDHB Gene Mutation:Case Report

Paragangliomas, a term used for tumors of extra-adrenal origin, are chromaffin cell tumors that secrete catecholamines. Approximately one in three patients with paraganglioma has a gene mutation associated with familial paraganglioma syndromes (FPGLs), resulting from mutations in one of the subunits of the succinate dehydrogenase (SDH) gene. Most extraadrenal paragangliomas involve the head and neck, and only 2% of paragangliomas are found in the mediastinum. We report the case of a 37-year-old woman with a posterior mediastinal paraganglioma attached to the heart and recurrent glomus jugulare who underwent glomus tumor resection at the age of 17 years. Genetic testing revealed a mutation in the SDH subunit B gene associated with FPGL type 4 (FPGL4). This case report describes the features of multimodal imaging of a posterior mediastinal paraganglioma and explain how a multidisciplinary approach led to the diagnosis of FPGL4.

Mildly Reduced Renal Function Is Associated With Increased Heart Failure Admissions in Patients With Hypertrophic Cardiomyopathy

Background@#The association between renal dysfunction and cardiovascular outcomes has yet to be determined in patients with hypertrophic cardiomyopathy (HCM). We aimed to investigate whether mildly reduced renal function is associated with the prognosis in patients with HCM. @*Methods@#Patients with HCM were enrolled at two tertiary HCM centers. Patients who were on dialysis, or had a previous history of heart failure (HF) or stroke were excluded. Patients were categorized into 3 groups by estimated glomerular filtration rate (eGFR): stage I (eGFR ≥ 90 mL/min/1.73 m2 , n = 538), stage II (eGFR 60–89 mL/min/1.73 m2 , n = 953), and stage III–V (eGFR < 60 mL/min/1.73 m2 , n = 265). Major adverse cardiovascular events (MACEs) were defined as a composite of cardiovascular death, hospitalization for HF (HHF), or stroke during median 4.0-year follow-up. Multivariable Cox regression model was used to adjust for covariates. @*Results@#Among 1,756 HCM patients (mean 61.0 ± 13.4 years; 68.1% men), patients with stage III–V renal function had a significantly higher risk of MACEs (adjusted hazard ratio [aHR], 2.71; 95% confidence interval [CI], 1.39–5.27; P = 0.003), which was largely driven by increased incidence of cardiovascular death and HHF compared to those with stage I renal function. Even in patients with stage II renal function, the risk of MACE (vs. stage I: aHR, 2.21’ 95% CI, 1.23–3.96; P = 0.008) and HHF (vs. stage I: aHR, 2.62; 95% CI, 1.23–5.58; P = 0.012) was significantly increased. @*Conclusion@#This real-world observation showed that even mildly reduced renal function (i.e., eGFR 60–89 mL/min/1.73 m2 ) in patients with HCM was associated with an increased risk of MACEs, especially for HHF.

Sibjotang Protects against Cardiac Hypertrophy In Vitro and In Vivo.

Cardiac hypertrophy is developed by various diseases such as myocardial infarction, valve diseases, hypertension, and aortic stenosis. Sibjotang (, Shizaotang, SJT), a classic formula in Korean traditional medicine, has been shown to modulate the equilibrium of body fluids and blood pressure. This research study sought to explore the impact and underlying process of Sibjotang on cardiotoxicity induced by DOX in H9c2 cells. In vitro, H9c2 cells were induced by DOX (1 µM) in the presence or absence of SJT (1-5 µg/mL) and incubated for 24 h. In vivo, SJT was administrated to isoproterenol (ISO)-induced cardiac hypertrophy mice (n = 8) at 100 mg/kg/day concentrations. Immunofluorescence staining revealed that SJT mitigated the enlargement of H9c2 cells caused by DOX in a dose-dependent way. Using SJT as a pretreatment notably suppressed the rise in cardiac hypertrophic marker levels induced by DOX. SJT inhibited the DOX-induced ERK1/2 and p38 MAPK signaling pathways. In addition, SJT significantly decreased the expression of the hypertrophy-associated transcription factor GATA binding factor 4 (GATA 4) induced by DOX. SJT also decreased hypertrophy-associated calcineurin and NFAT protein levels. Pretreatment with SJT significantly attenuated DOX-induced apoptosis-associated proteins such as Bax, caspase-3, and caspase-9 without affecting cell viability. In addition, the results of the in vivo study indicated that SJT significantly reduced the left ventricle/body weight ratio level. Administration of SJT reduced the expression of hypertrophy markers, such as ANP and BNP. These results suggest that SJT attenuates cardiac hypertrophy and heart failure induced by DOX or ISO through the inhibition of the calcineurin/NFAT/GATA4 pathway. Therefore, SJT may be a potential treatment for the prevention and treatment of cardiac hypertrophy that leads to heart failure.