Real-world walking behaviors are associated with early-stage heart failure: a Project Baseline Health Study.

BACKGROUND: Data collected via wearables may complement in-clinic assessments to monitor subclinical heart failure (HF). OBJECTIVES: Evaluate the association of sensor-based digital walking measures with HF stage and characterize their correlation with in-clinic measures of physical performance, cardiac function and participant reported outcomes (PROs) in individuals with early HF. METHODS: The analyzable cohort included participants from the Project Baseline Health Study (PBHS) with HF stage 0, A, or B, or adaptive remodeling phenotype (without risk factors but with mild echocardiographic change, termed RF-/ECHO+) (based on available first-visit in-clinic test and echocardiogram results) and with sufficient sensor data. We computed daily values per participant for 18 digital walking measures, comparing HF subgroups vs stage 0 using multinomial logistic regression and characterizing associations with in-clinic measures and PROs with Spearman's correlation coefficients, adjusting all analyses for confounders. RESULTS: In the analyzable cohort (N=1265; 50.6% of the PBHS cohort), one standard deviation decreases in 17/18 walking measures were associated with greater likelihood for stage-B HF (multivariable-adjusted odds ratios [ORs] vs stage 0 ranging from 1.18-2.10), or A (ORs vs stage 0, 1.07-1.45), and lower likelihood for RF-/ECHO+ (ORs vs stage 0, 0.80-0.93). Peak 30-minute pace demonstrated the strongest associations with stage B (OR vs stage 0=2.10; 95% CI:1.74-2.53) and A (OR vs stage 0=1.43; 95% CI:1.23-1.66). Decreases in 13/18 measures were associated with greater likelihood for stage-B HF vs stage A. Strength of correlation with physical performance tests, echocardiographic cardiac-remodeling and dysfunction indices and PROs was greatest in stage B, then A, and lowest for 0. CONCLUSIONS: Digital measures of walking captured by wearable sensors could complement clinic-based testing to identify and monitor pre-symptomatic HF.

Improving Reporting of Exercise Capacity Across Age Ranges Using Novel Workload Reference Equations.

Exercise capacity (EC) is an important predictor of survival in the general population and in subjects with cardiopulmonary disease. Despite its relevance, considering the percent-predicted workload (%pWL) given by current equations may overestimate EC in older adults. Therefore, to improve the reporting of EC in clinical practice, our main objective was to develop workload reference equations (pWL) that better reflect the relation between workload and age. Using the Fitness Registry and the Importance of Exercise National Database (FRIEND), we analyzed a reference group of 6,966 apparently healthy participants and 1,060 participants with heart failure who underwent graded treadmill cardiopulmonary exercise testing. For the first group, the mean age was 44 years (18 to 79); 56.5% of participants were males and 15.4% had obesity. Peak oxygen consumption was 11.6 ± 3.0 METs in males and 8.5 ± 2.4 METs in females. After partition analysis, we first developed sex-specific pWL equations to allow comparisons to a healthy weight reference. For males, pWL (METs) = 14.1-0.9×10-3×age2 and 11.5-0.87×10-3×age2 for females. We used those equations as denominators of %pWL, and based on their distribution, we determined thresholds for EC classification, with average EC defined by the range corresponding to 85% to 115%pWL. Compared with %pWL using current equations, the new equations yielded better-calibrated %pWL across different age ranges. We also derived body mass index-adjusted pWL equations that better assessed EC in subjects with heart failure. In conclusion, the novel pWL equations have the potential to impact the report of EC in practice.

Clinical and biochemical predictors of longitudinal changes in left atrial structure and function: A general population study.

PURPOSE: There is a need for better understanding the factors that modulate left atrial (LA) dysfunction. Therefore, we determined associations of clinical and biochemical biomarkers with serial changes in echocardiographic indexes of LA function in the general population. METHODS: We measured LA maximal and minimal volume indexes (LAVImax and LAVImin) by echocardiography and LA reservoir strain (LARS) by two-dimensional speckle-tracking in 627 participants (mean age 50.8 years, 51.2% women) at baseline and after 4.8 years. RESULTS: During follow-up, LARS decreased significantly in men (-.90%, P = .033) but not in women (-.23%, P = .60). In stepwise regression analysis, stronger decrease in LARS over time was associated with male sex, a higher age, body mass index (BMI), mean arterial pressure (MAP) and serum insulin at baseline and with a greater increase in BMI and MAP over time (P ≤ .018). Similarly, an increased risk of developing or retaining abnormal LARS was observed in older participants, in subjects with a higher baseline BMI, MAP, heart rate (HR), troponin T and ΔMAP, and in those who used ß-blockers at baseline. Both LAVImax and LAVImin increased significantly over time (P ≤ .0007). This increase was associated with a higher baseline age, pulse pressure and a lower HR at baseline and a greater increase in pulse pressure over time (P ≤ .029). Higher serum insulin and D-dimer were independently associated with a stronger increase in LAVImin (P ≤ .0034). CONCLUSION: Subclinical worsening in LA dysfunction was associated with older age, hypertension, obesity, insulin resistance and troponin T levels. Cardiovascular risk management strategies may delay LA deterioration.

Feature-based clustering of the left ventricular strain curve for cardiovascular risk stratification in the general population.

Objective: Identifying individuals with subclinical cardiovascular (CV) disease could improve monitoring and risk stratification. While peak left ventricular (LV) systolic strain has emerged as a strong prognostic factor, few studies have analyzed the whole temporal profiles of the deformation curves during the complete cardiac cycle. Therefore, in this longitudinal study, we applied an unsupervised machine learning approach based on time-series-derived features from the LV strain curve to identify distinct strain phenogroups that might be related to the risk of adverse cardiovascular events in the general population. Method: We prospectively studied 1,185 community-dwelling individuals (mean age, 53.2 years; 51.3% women), in whom we acquired clinical and echocardiographic data including LV strain traces at baseline and collected adverse events on average 9.1 years later. A Gaussian Mixture Model (GMM) was applied to features derived from LV strain curves, including the slopes during systole, early and late diastole, peak strain, and the duration and height of diastasis. We evaluated the performance of the model using the clinical characteristics of the participants and the incidence of adverse events in the training dataset. To ascertain the validity of the trained model, we used an additional community-based cohort (n = 545) as external validation cohort. Results: The most appropriate number of clusters to separate the LV strain curves was four. In clusters 1 and 2, we observed differences in age and heart rate distributions, but they had similarly low prevalence of CV risk factors. Cluster 4 had the worst combination of CV risk factors, and a higher prevalence of LV hypertrophy and diastolic dysfunction than in other clusters. In cluster 3, the reported values were in between those of strain clusters 2 and 4. Adjusting for traditional covariables, we observed that clusters 3 and 4 had a significantly higher risk for CV (28% and 20%, P ≤ 0.038) and cardiac (57% and 43%, P ≤ 0.024) adverse events. Using SHAP values we observed that the features that incorporate temporal information, such as the slope during systole and early diastole, had a higher impact on the model's decision than peak LV systolic strain. Conclusion: Employing a GMM on features derived from the raw LV strain curves, we extracted clinically significant phenogroups which could provide additive prognostic information over the peak LV strain.

Evaluation of Prevalence of Hepatitis E Clinical Markers among Donors in Estonia.

Hepatitis E virus (HEV) is now considered the most common cause of acute hepatitis worldwide. There are no published data about the prevalence of antibodies to HEV and RNA in donor sera in Estonia, and this precludes planning measures for preventing HEV proliferation through blood transfusion services. Here, were report data from an analysis of 1002 sera on the prevalence of anti-HEV IgG and IgM and the viral RNA. The antibodies were found in 48 donor sera (4.8%); of these, 40 (4%) harbored anti-HEV IgG, 15 (1.5%) contained anti-HEV IgM, and 7 donors had anti-HEV antibodies of both classes simultaneously. HEV RNA was not detected in any blood serum. Statistical associations of infection risk factors (gender, age, travel in the last six months, contact with pigs and/or wild boars in the last six months, consumption of thermally unprocessed/raw pork or boar meat, raw/unfiltered tap water or water from natural sources, unpasteurized farm dairy products, and unwashed berries and/or vegetables) were assessed. None of the listed factors were found to be associated with a higher or lower risk of anti-HEV antibody presence. At the same time, an increasing share of anti-HEV IgG carriers with age was found. The absence of HEV RNA in the analyzed donor plasma samples proves that HEV acute infection prevalence in Estonia does not exceed the average level of European countries. There is no urgent necessity to enter a requirement for a total screening of blood plasma for HEV RNA prevalence in Estonia.

Serum proteomic profiling of carotid arteriopathy: A population outcome study.

BACKGROUND AND AIMS: Circulating proteins reflecting subclinical vascular disease may improve prediction of atherosclerotic cardiovascular disease (ASCVD). We applied feature selection and unsupervised clustering on proteomic data to identify proteins associated with carotid arteriopathy and construct a protein-based classifier for ASCVD event prediction. METHODS: 491 community-dwelling participants (mean age, 58 ± 11 years; 51 % women) underwent carotid ultrasonography and proteomic profiling (CVD II panel, Olink Proteomics). ASCVD outcome was collected (median follow-up time: 10.2 years). We applied partial least squares (PLS) to identify proteins linked to carotid intima-media thickness (cIMT). Next, we assessed the association between future ASCVD events and protein-based phenogroups derived by unsupervised clustering (Gaussian Mixture modelling) based on proteins selected in PLS. RESULTS: PLS identified 19 proteins as important, which were all associated with cIMT in multivariable-adjusted linear regression. 8 of the 19 proteins were excluded from the clustering analysis because of high collinearity. Based on the 11 remaining proteins, the clustering algorithm subdivided the cohort into two phenogroups. Compared to the first phenogroup (n = 177), participants in the second phenogroup (n = 314) presented: i) a more unfavorable lipid profile with higher total cholesterol and triglycerides and lower HDL cholesterol (p ≤ 0.014); ii) higher cIMT (p = 0.0020); and iii) a significantly higher risk for future ASCVD events (multivariable-adjusted hazard ratio (95 % CI) versus phenogroup 1: 2.05 (1.26-3.52); p = 0.0093). The protein-based phenogrouping supplemented ACC/AHA 10-year ASCVD risk scoring for prediction of a first ASCVD event. CONCLUSIONS: Focused protein-based phenogrouping identified individuals at high risk for future ASCVD and may complement current risk stratification strategies.

Epicardial fat and Stage B heart failure among overweight/obese and normal weight individuals with diabetes mellitus.

PURPOSE: Although up to 20% of people with type 2 diabetes (DM) have normal BMI (< 25 kg/m2), it remains unclear whether there is a difference in the development of cardiac dysfunction between those with normal and higher BMI. Furthermore, little is known about the relationship of visceral fat with BMI or fitness in asymptomatic patients with DM. METHODS: We prospectively enrolled asymptomatic patients with DM and divided into two groups: BMI ≥ 25kg/m2 (overweight/obese group) versus < 25kg/m2(normal-weight group). Resting echocardiogram followed by exercise stress echocardiogram and exercise gas exchange analysis (in a subgroup) was performed. Cardiac function was evaluated using left ventricular longitudinal strain (LVLS), E/e', and relative wall thickness (RWT). In addition, epicardial fat thickness (EFT) was measured to estimate visceral fat. RESULTS: Normal-weight patients with DM had more EFT compared with overweight/obese patients (0.66 ± 0.17 cm vs. 0.59 ± 0.22 cm, p < 0.05), despite the overlap between the groups. There was no significant difference in the prevalence of LV remodeling (p = 0.49), impaired LVLS (p = 0.22), or increased E/e' (p = 0.26), and these were consistently observed when matched for race. The majority of patients (63%) achieved ≥ 85% of percent peak-predicted VO2. At peak, there was no significant difference in peak VO2 normalized by eLBM (36.4 ± 7.7 vs. 37.8 ± 7.1 ml/kg eLBM/min, p = 0.43) while VO2 normalized by weight (23.6 ± 6.5 vs. 29.6 ± 6.7 ml/kg/min, p < 0.001) and VO2 ratio (5.7 ± 1.7 vs. 7.3 ± 2.4 METs, p = 0.001) were significantly lower in patients with obese/overweight group. There was no significant difference between patients with higher and lower EFT. CONCLUSIONS: Patients with DM and normal BMI have excess epicardial fat compared to those with overweight/obese. Epicardial fat was not directly linked to prevalence of subclinical dysfunction.

Atomic insights into thickness-dependent deformation mechanism and mechanical properties of Ag/PMMA ultra-thin nanofilms.

In this work, the nanoindentations on bilayer composite nanofilms composed of metal Ag and polymer PMMA were simulated using molecular dynamics. The effects of the thickness of Ag and PMMA on the elastic moduli of the composite films were analyzed from Hertz contact theory, dislocation evolution and atomic migration. The results show that the maximum penetration depth that the Hertz model could well describe is about 6 Å, and this limiting value is almost independent on the film thickness. The deformation mode of the Ag films gradually changes from bending mode to indentation mode with an increase in Ag thickness, which improves the elastic modulus of the composite films. The rule of mixtures could give a theoretical prediction about the elastic modulus of the composite film close to the nanoindentation, and Hertz theory could also be used as long as the thickness of Ag films exceeded a certain value. The introduction of a PMMA layer impedes the development of dislocation in the Ag layer and improves the elastic limit of the composite films. This work provides an important basis for experimentally measuring the overall elastic modulus of metal/polymer composite film based on nanoindentation or extracting the elastic modulus of metal film from the overall indentation response of the composite film.

Deep neural network-based clustering of deformation curves reveals novel disease features in PLN pathogenic variant carriers.

Echocardiographic deformation curves provide detailed information on myocardial function. Deep neural networks (DNNs) may enable automated detection of disease features in deformation curves, and improve the clinical assessment of these curves. We aimed to investigate whether an explainable DNN-based pipeline can be used to detect and visualize disease features in echocardiographic deformation curves of phospholamban (PLN) p.Arg14del variant carriers. A DNN was trained to discriminate PLN variant carriers (n = 278) from control subjects (n = 621) using raw deformation curves obtained by 2D-speckle tracking in the longitudinal axis. A visualization technique was used to identify the parts of these curves that were used by the DNN for classification. The PLN variant carriers were clustered according to the output of the visualization technique. The DNN showed excellent discriminatory performance (C-statistic 0.93 [95% CI 0.87-0.97]). We identified four clusters with PLN-associated disease features in the deformation curves. Two clusters showed previously described features: apical post-systolic shortening and reduced systolic strain. The two other clusters revealed novel features, both reflecting delayed relaxation. Additionally, a fifth cluster was identified containing variant carriers without disease features in the deformation curves, who were classified as controls by the DNN. This latter cluster had a very benign disease course regarding development of ventricular arrhythmias. Applying an explainable DNN-based pipeline to myocardial deformation curves enables automated detection and visualization of disease features. In PLN variant carriers, we discovered novel disease features which may improve individual risk stratification. Applying this approach to other diseases will further expand our knowledge on disease-specific deformation patterns. Overview of the deep neural network-based pipeline for feature detection in myocardial deformation curves. Firstly, phospholamban (PLN) p.Arg14del variant carriers and controls were selected and a deep neural network (DNN) was trained to detect the PLN variant carriers. Subsequently, a clustering-based approach was performed on the attention maps of the DNN, which revealed 4 distinct phenotypes of PLN variant carriers with different prognoses. Moreover, a cluster without features and a benign prognosis was detected.

Personalized remotely guided preventive exercise therapy for a healthy heart (PRIORITY): protocol for an assessor-blinded, multicenter randomized controlled trial.

Aims: A key treatment for patients with varying stages of heart failure with preserved ejection fraction (HFpEF) is exercise. Yet, despite a Class 1A recommendation, only one-third of patients exercise sufficiently. A huge treatment gap exists between guidelines and clinical practice. PRIORITY aims to establish the feasibility, clinical effectiveness and cost-effectiveness of a hybrid centre and home-based personalized exercise and physical activity intervention for patients along the HFpEF continuum. Methods: An assessor-blinded, multicenter randomized controlled trial will be conducted among 312 patients along the HFpEF continuum. Participants will be randomized (1:1) to the PRIORITY intervention or a comparator group receiving only a written exercise prescription. Participants in the PRIORITY group will receive 18 supervised centre-based exercise sessions during one year, supplemented with a remotely guided home-based physical activity program. Outcomes will be assessed at baseline, 4 months, one and two years. The primary outcome is the peak oxygen uptake (pVO2) at 1-year. Secondary outcomes include physical activity, other physical fitness parameters, cardiovascular health, echocardiographic parameters, health-related quality of life and costs at 1-year FU. Machine learning algorithms will analyse big data on physical activity collected during the 1-year intervention to develop models that can predict physical activity uptake and adherence as well as changes in fitness and health. A cost-utility analysis will be performed to evaluate the cost-effectiveness of the PRIORITY intervention compared to the control condition. Discussion: We anticipate that participants in the supervised home-based exercise intervention group will have a greater increase in pVO2 compared to those receiving a written exercise prescription. Trial registration number: This trial is registered at ClinicalTrials.gov (NCT04745013) and is currently in the recruitment stage.

Anthropogenic Neighborhood Impact on Bacterial and Fungal Communities in Polar Bear Feces.

Climate changes cause a dramatical increase in the ice-free season in the Arctic, forcing polar bears ashore, closer to human settlements associated with new and non-natural food objects. Such a diet may crucially transform the intestinal microbiome and metabolism of polar bears. The aim of this study was to characterize changes in the gut bacterial and fungal communities resulting from the transition to anthropogenic food objects by the means of 16S and ITS metabarcoding. Thus, rectal samples from 16 wild polar bears from the Kara-Barents subpopulation were studied. Human waste consuming resulted in a significant increase in the relative abundance of fermentative bacteria (Lactobacillaceae, Leuconostocaceae, and Streptococcaceae) and a decrease in proteolytic Enterobacteriaceae. However, the alpha-diversity parameters remained similar. Also, for the first time, the composition of the fungal community of the polar bear intestine was determined. Diet change is associated with the displacement of eurybiontic fungi (Thelebolus, Dipodascus, Candida (sake), and Geotrichum) by opportunistic Candida (tropicalis), Kazachstania, and Trichosporon. Feeding on human waste does not cause any signs of dysbiosis and probably leads to adaptive changes in the bacterial microbiome. However, the emergence of fungal facultative pathogens increases the risk of infections.

Cardiorespiratory fitness components in relation to clinical characteristics, disease state and medication intake: A patient registry study.

BACKGROUND: Interpretation of cardiopulmonary exercise testing (CPET) results requires thorough understanding of test confounders such as anthropometrics, comorbidities and medication. Here, we comprehensively assessed the clinical determinants of cardiorespiratory fitness and its components in a heterogeneous patient sample. METHODS: We retrospectively collected medical and CPET data from 2320 patients (48.2% females) referred for cycle ergometry at the University Hospital Leuven, Belgium. We assessed clinical determinants of peak CPET indexes of cardiorespiratory fitness (CRF) and its hemodynamic and ventilatory components using stepwise regression and quantified multivariable-adjusted differences in indexes between cases and references. RESULTS: Lower peak load and peak O2 uptake were related to: higher age, female sex, lower body height and weight, and higher heart rate; to the intake of beta blockers, analgesics, thyroid hormone replacement and benzodiazepines; and to diabetes mellitus, chronic kidney disease, non-ST elevation myocardial infarction and atrial fibrillation (p < 0.05 for all). Lower peak load also correlated with obstructive pulmonary diseases. Stepwise regression revealed associations of hemodynamic and ventilatory indexes (including heart rate, O2 pulse, systolic blood pressure and ventilation at peak exercise and ventilatory efficiency) with age, sex, body composition and aforementioned diseases and medications. Multivariable-adjusted differences in CPET metrics between cases and controls confirmed the associations observed. CONCLUSION: We described known and novel associations of CRF components with demographics, anthropometrics, cardiometabolic and pulmonary diseases and medication intake in a large patient sample. The clinical implications of long-term noncardiovascular drug intake for CPET results require further investigation.

Integrative Interpretation of Cardiopulmonary Exercise Tests for Cardiovascular Outcome Prediction: A Machine Learning Approach.

Integrative interpretation of cardiopulmonary exercise tests (CPETs) may improve assessment of cardiovascular (CV) risk. Here, we identified patient phenogroups based on CPET summary metrics and evaluated their predictive value for CV events. We included 2280 patients with diverse CV risk who underwent maximal CPET by cycle ergometry. Key CPET indices and information on incident CV events (median follow-up time: 5.3 years) were derived. Next, we applied unsupervised clustering by Gaussian Mixture modeling to subdivide the cohort into four male and four female phenogroups solely based on differences in CPET metrics. Ten of 18 CPET metrics were used for clustering as eight were removed due to high collinearity. In males and females, the phenogroups differed significantly in age, BMI, blood pressure, disease prevalence, medication intake and spirometry. In males, phenogroups 3 and 4 presented a significantly higher risk for incident CV events than phenogroup 1 (multivariable-adjusted hazard ratio: 1.51 and 2.19; p ≤ 0.048). In females, differences in the risk for future CV events between the phenogroups were not significant after adjustment for clinical covariables. Integrative CPET-based phenogrouping, thus, adequately stratified male patients according to CV risk. CPET phenomapping may facilitate comprehensive evaluation of CPET results and steer CV risk stratification and management.

2023 ESH Guidelines for the management of arterial hypertension The Task Force for the management of arterial hypertension of the European Society of Hypertension: Endorsed by the International Society of Hypertension (ISH) and the European Renal Association (ERA).

DOCUMENT REVIEWERS: Luis Alcocer (Mexico), Christina Antza (Greece), Mustafa Arici (Turkey), Eduardo Barbosa (Brazil), Adel Berbari (Lebanon), Luís Bronze (Portugal), John Chalmers (Australia), Tine De Backer (Belgium), Alejandro de la Sierra (Spain), Kyriakos Dimitriadis (Greece), Dorota Drozdz (Poland), Béatrice Duly-Bouhanick (France), Brent M. Egan (USA), Serap Erdine (Turkey), Claudio Ferri (Italy), Slavomira Filipova (Slovak Republic), Anthony Heagerty (UK), Michael Hecht Olsen (Denmark), Dagmara Hering (Poland), Sang Hyun Ihm (South Korea), Uday Jadhav (India), Manolis Kallistratos (Greece), Kazuomi Kario (Japan), Vasilios Kotsis (Greece), Adi Leiba (Israel), Patricio López-Jaramillo (Colombia), Hans-Peter Marti (Norway), Terry McCormack (UK), Paolo Mulatero (Italy), Dike B. Ojji (Nigeria), Sungha Park (South Korea), Priit Pauklin (Estonia), Sabine Perl (Austria), Arman Postadzhian (Bulgaria), Aleksander Prejbisz (Poland), Venkata Ram (India), Ramiro Sanchez (Argentina), Markus Schlaich (Australia), Alta Schutte (Australia), Cristina Sierra (Spain), Sekib Sokolovic (Bosnia and Herzegovina), Jonas Spaak (Sweden), Dimitrios Terentes-Printzios (Greece), Bruno Trimarco (Italy), Thomas Unger (The Netherlands), Bert-Jan van den Born (The Netherlands), Anna Vachulova (Slovak Republic), Agostino Virdis (Italy), Jiguang Wang (China), Ulrich Wenzel (Germany), Paul Whelton (USA), Jiri Widimsky (Czech Republic), Jacek Wolf (Poland), Grégoire Wuerzner (Switzerland), Eugene Yang (USA), Yuqing Zhang (China).

Interneuronal GluK1 kainate receptors control maturation of GABAergic transmission and network synchrony in the hippocampus.

Kainate type glutamate receptors (KARs) are strongly expressed in GABAergic interneurons and have the capability of modulating their functions via ionotropic and G-protein coupled mechanisms. GABAergic interneurons are critical for generation of coordinated network activity in both neonatal and adult brain, yet the role of interneuronal KARs in network synchronization remains unclear. Here, we show that GABAergic neurotransmission and spontaneous network activity is perturbed in the hippocampus of neonatal mice lacking GluK1 KARs selectively in GABAergic neurons. Endogenous activity of interneuronal GluK1 KARs maintains the frequency and duration of spontaneous neonatal network bursts and restrains their propagation through the hippocampal network. In adult male mice, the absence of GluK1 in GABAergic neurons led to stronger hippocampal gamma oscillations and enhanced theta-gamma cross frequency coupling, coinciding with faster spatial relearning in the Barnes maze. In females, loss of interneuronal GluK1 resulted in shorter sharp wave ripple oscillations and slightly impaired abilities in flexible sequencing task. In addition, ablation of interneuronal GluK1 resulted in lower general activity and novel object avoidance, while causing only minor anxiety phenotype. These data indicate a critical role for GluK1 containing KARs in GABAergic interneurons in regulation of physiological network dynamics in the hippocampus at different stages of development.

Novel left ventricular mechanical index in pulmonary arterial hypertension.

Ventricular interdependence plays an important role in pulmonary arterial hypertension (PAH). It can decrease left ventricular (LV) longitudinal strain (LVLS) and lead to a leftward displacement ("transverse shortening") of the interventricular septum (sTS). For this study, we hypothesized the ratio of LVLS/sTS would be a sensitive marker of systolic ventricular interactions in PAH. In a cross-sectional cohort of patients with PAH (n = 57) and matched controls (n = 57), we quantified LVLS and septal TS in the amplitude and time domain. We then characterized LV phenotypes using upset plots, ventricular interactions using network analysis, and longitudinal analysis in a representative cohort of 45 patients. We also measured LV metrics in mice subjected to pulmonary arterial banding (PAB) using a 7 T magnetic resonance imaging at baseline, Week 1, and Week 7 post-PAB (N = 9). Patients with PAH had significantly reduced absolute LVLS (15.4 ± 3.4 vs. 20.1 ± 2.3%, p < 0.0001), higher sTS (53.0 ± 12.2 vs. 28.0 ± 6.2%, p < 0.0001) and lower LVLS/sTS (0.30 ± 0.09 vs. 0.75 ± 0.16, p < 0.0001) compared to controls. Reduced LVLS/sTS was observed in 89.5% of patients, while diastolic dysfunction, impaired LVLS (<16%), and LV atrophy were observed in 73.7%, 52.6%, and 15.8%, respectively. In the longitudinal cohort, changes in LVLS/sTS were closely associated with changes in N-terminal pro B-type natriuretic peptide (r = 0.73, p < 0.0001) as well as survival. Mice subjected to PAB showed significant RV systolic dysfunction and decreased LVLS/sTS compared to sham animals. We conclude that in PAH, LVLV/sTS is a simple ratio that can reflect ventricular systolic interactions.

Clinical and Echocardiographic Diversity Associated With Physical Fitness in the Project Baseline Health Study: Implications for Heart Failure Staging.

BACKGROUND: Clinical and echocardiographic features may carry diverse information about the development of heart failure (HF). Therefore, we determined heterogeneity in clinical and echocardiographic phenotypes and its association with exercise capacity. METHODS: In 2036 community-dwelling individuals, we defined echocardiographic profiles of left and right heart remodeling and dysfunction. We subdivided the cohort based on presence (+) or absence (-) of HF risk factors (RFs) and echocardiographic abnormalities (RF-/Echo-, RF-/Echo+, RF+/Echo-, RF+/Echo+). Multivariable-adjusted associations between subgroups and physical performance metrics from 6-minute walk and treadmill exercise testing were assessed. RESULTS: The prevalence was 35.3% for RF-/Echo-, 4.7% for RF-/Echo+, 39.3% for RF+/Echo-, and 20.6% for RF+/Echo+. We observed large diversity in echocardiographic profiles in the Echo+ group. Participants with RF-/Echo+ (18.6% of Echo+) had predominantly echocardiographic abnormalities other than left ventricular (LV) diastolic dysfunction, hypertrophy and reduced ejection fraction, whereas their physical performance was similar to RF-/Echo-. In contrast, participants with RF+/Echo+ presented primarily with LV hypertrophy or dysfunction, features that related to lower 6-minute walking distance and lower exercise capacity. CONCLUSIONS: Subclinical echocardiographic abnormalities suggest HF pathogenesis, but the presence of HF risk factors and type of echo abnormality should be considered so as to distinguish adverse from benign adaptation and to stratify HF risk.

Synthesis and Functional Characterization of CoxFe3-xO4-BaTiO3 Magnetoelectric Nanocomposites for Biomedical Applications.

Nowadays, magnetoelectric nanomaterials are on their way to finding wide applications in biomedicine for various cancer and neurological disease treatment, which is mainly restricted by their relatively high toxicity and complex synthesis. This study for the first time reports novel magnetoelectric nanocomposites of CoxFe3-xO4-BaTiO3 series with tuned magnetic phase structures, which were synthesized via a two-step chemical approach in polyol media. The magnetic CoxFe3-xO4 phases with x = 0.0, 0.5, and 1.0 were obtained by thermal decomposition in triethylene glycol media. The magnetoelectric nanocomposites were synthesized by the decomposition of barium titanate precursors in the presence of a magnetic phase under solvothermal conditions and subsequent annealing at 700 °C. X-ray diffraction revealed the presence of both spinel and perovskite phases after annealing with average crystallite sizes in the range of 9.0-14.5 nm. Transmission electron microscopy data showed two-phase composite nanostructures consisting of ferrites and barium titanate. The presence of interfacial connections between magnetic and ferroelectric phases was confirmed by high-resolution transmission electron microscopy. Magnetization data showed expected ferrimagnetic behavior and σs decrease after the nanocomposite formation. Magnetoelectric coefficient measurements after the annealing showed non-linear change with a maximum of 89 mV/cm*Oe with x = 0.5, 74 mV/cm*Oe with x = 0, and a minimum of 50 mV/cm*Oe with x = 0.0 core composition, that corresponds with the coercive force of the nanocomposites: 240 Oe, 89 Oe and 36 Oe, respectively. The obtained nanocomposites show low toxicity in the whole studied concentration range of 25-400 µg/mL on CT-26 cancer cells. The synthesized nanocomposites show low cytotoxicity and high magnetoelectric effects, therefore they can find wide applications in biomedicine.

Preparation of a Polyaniline-Modified Hybrid Graphene Aerogel-Like Nanocomposite for Efficient Adsorption of Heavy Metal Ions from Aquatic Media.

This paper considers the synthesis of a novel nanocomposite based on reduced graphene oxide and oxidized carbon nanotubes modified with polyaniline and phenol-formaldehyde resin and developed through the carbonization of a pristine aerogel. It was tested as an efficient adsorbent to purify aquatic media from toxic Pb(II). Diagnostic assessment of the samples was carried out through X-ray diffractometry, Raman spectroscopy, thermogravimetry, scanning and transmission electron microscopy, and infrared spectroscopy. The carbonized aerogel was found to preserve the carbon framework structure. The sample porosity was estimated through nitrogen adsorption at 77 K. It was found that the carbonized aerogel predominantly represented a mesoporous material having a specific surface area of 315 m2/g. After carbonization, an increase in smaller micropores occurred. According to the electron images, the highly porous structure of the carbonized composite was preserved. The adsorption capacity of the carbonized material was studied for liquid-phase Pb(II) extraction in static mode. The experiment results showed that the maximum Pb(II) adsorption capacity of the carbonized aerogel was 185 mg/g (at pH 6.0). The results of the desorption studies showed a very low desorption rate (0.3%) at pH 6.5 and a rate of about 40% in a strongly acidic medium.