Fractal analysis of left ventricular trabeculations is associated with impaired myocardial deformation in healthy Chinese

Background: Left ventricular (LV) non-compaction (LVNC) is defined by extreme LV trabeculation, but is measured variably. Here we examined the relationship between quantitative measurement in LV trabeculation and myocardial deformation in health and disease and determined the clinical utility of semi-automated assessment of LV trabeculations. Methods: Cardiovascular magnetic resonance (CMR) was performed in 180 healthy Singaporean Chinese (age 20–69 years; males, n = 91), using balanced steady state free precession cine imaging at 3T. The degree of LV trabeculation was assessed by fractal dimension (FD) as a robust measure of trabeculation complexity using a semi-automated technique. FD measures were determined in healthy men and women to derive normal reference ranges. Myocardial deformation was evaluated using feature tracking. We tested the utility of this algorithm and the normal ranges in 10 individuals with confirmed LVNC (non-compacted/compacted; NC/C ratio > 2.3 and ≥1 risk factor for LVNC) and 13 individuals with suspected disease (NC/C ratio > 2.3). Results: Fractal analysis is a reproducible means of assessing LV trabeculation extent (intra-class correlation coefficient: intra-observer, 0.924, 95% CI [0.761–0.973]; inter-observer, 0.925, 95% CI [0.821–0.970]). The overall extent of LV trabeculation (global FD: 1.205 ± 0.031) was independently associated with increased indexed LV end-diastolic volume and mass (sβ = 0.35; p  2.3. Conclusion: This study defines the normal range of LV trabeculation in healthy Chinese that can be used to make or refute a diagnosis of LVNC using the fractal analysis tool, which we make freely available. We also show that increased myocardial trabeculation is associated with higher LV volumes, mass and reduced myocardial strain

Harnessing technology and molecular analysis to understand the development of cardiovascular diseases in Asia: a prospective cohort study (SingHEART)

BACKGROUND: Cardiovascular disease (CVD) imposes much mortality and morbidity worldwide. The use of "deep learning", advancements in genomics, metabolomics, proteomics and devices like wearables have the potential to unearth new insights in the field of cardiology. Currently, in Asia, there are no studies that combine the use of conventional clinical information with these advanced technologies. We aim to harness these new technologies to understand the development of cardiovascular disease in Asia. METHODS: Singapore is a multi-ethnic country in Asia with well-represented diverse ethnicities including Chinese, Malays and Indians. The SingHEART study is the first technology driven multi-ethnic prospective population-based study of healthy Asians. Healthy male and female subjects aged 21-69 years old without any prior cardiovascular disease or diabetes mellitus will be recruited from the general population. All subjects are consented to undergo a detailed on-line questionnaire, basic blood investigations, resting and continuous electrocardiogram and blood pressure monitoring, activity and sleep tracking, calcium score, cardiac magnetic resonance imaging, whole genome sequencing and lipidomic analysis. Outcomes studied will include mortality and cause of mortality, myocardial infarction, stroke, malignancy, heart failure, and the development of co-morbidities. DISCUSSION: An initial target of 2500 patients has been set. From October 2015 to May 2017, an initial 683 subjects have been recruited and have completed the initial work-up the SingHEART project is the first contemporary population-based study in Asia that will include whole genome sequencing and deep phenotyping: including advanced imaging and wearable data, to better understand the development of cardiovascular disease across different ethnic groups in Asia

The application of exercise stress cardiovascular magnetic resonance in patients with suspected dilated cardiomyopathy

Objectives The imaging features of dilated cardiomyopathy (DCM) overlap with physiological exercise-induced cardiac remodeling in active and otherwise healthy individuals. Distinguishing the two conditions is challenging. This study examined the diagnostic and prognostic roles of exercise stress imaging in asymptomatic patients with suspected DCM. Methods Exercise stress cardiovascular magnetic resonance (CMR) was performed in 60 asymptomatic patients with suspected DCM (dilated left ventricle and/or impaired systolic function on CMR), who also underwent DNA sequencing for DCM-causing genetic variants. Confirmed DCM was defined as genotype- and phenotype-positive (G+P+). Another 100 healthy subjects were recruited to establish normal exercise capacities (peak exercise cardiac index; PeakCI). The primary outcome was a composite of all-cause mortality, cardiac decompensation and ventricular arrhythmic events. Results No patients with confirmed G+P+ DCM had PeakCI exceeding the 35th percentile specific for age and sex. Applying this threshold in G-P+ patients, those with PeakCI below 35th percentile had characteristics similar to confirmed DCM while patients with higher PeakCI were younger, more active and higher longitudinal strain. Adverse cardiovascular events occurred only in patients with low exercise capacity (P = 0.004). Conclusions In individuals with suspected DCM, exercise stress CMR demonstrates diagnostic and prognostic potential in distinguishing between pathological DCM and physiological exercise-induced cardiac remodeling

Frozen and Invariant Quantum Discord under Local Dephasing Noise

In this chapter, we intend to explore and review some remarkable dynamical properties of quantum discord under various different open quantum system models. Specifically, our discussion will include several concepts connected to the phenomena of time invariant and frozen quantum discord. Furthermore, we will elaborate on the relation of these two phenomena to the non-Markovian features of the open system dynamics and to the usage of dynamical decoupling protocols.Comment: 29 pages, 8 figure

Anal HPV Infection in HIV-Positive Men Who Have Sex with Men from China

BACKGROUND: Anal HPV infection, which contributes to the development of anal warts and anal cancer, is well known to be common among men who have sex with men (MSM), especially among those HIV positives. However, HIV and anal HPV co-infection among MSM has not been addressed in China. METHODS: A cross-sectional study was conducted in Beijing and Tianjin, China. Study participants were recruited using multiple methods with the collaboration of local volunteer organizations. Blood and anal swabs were collected for HIV-1 serological test and HPV genotyping. RESULTS: A total of 602 MSM were recruited and laboratory data were available for 578 of them (96.0%). HIV and anal HPV prevalence were 8.5% and 62.1%, respectively. And 48 MSM (8.3%) were found to be co-infected. The HPV genotypes identified most frequently were HPV06 (19.6%), HPV16 (13.0%), HPV52 (8.5%) and HPV11 (7.6%). Different modes of HPV genotypes distribution were observed with respect to HIV status. A strong dose-response relationship was found between HIV seropositivity and multiplicity of HPV genotypes (p<0.001), which is consistent with the observation that anal HPV infection was an independent predictor for HIV infection. CONCLUSIONS: A high prevalence of HIV and anal HPV co-infection was observed in the MSM community in Beijing and Tianjin, China. Anal HPV infection was found to be independently associated with increased HIV seropositivity, which suggests the application of HPV vaccine might be a potential strategy to reduce the acquisition of HIV infection though controlling the prevalence of HPV

High-resolution digital phenotypes from consumer wearables and their applications in machine learning of cardiometabolic risk markers: cohort study

Background: Consumer-grade wearable devices enable detailed recordings of heart rate and step counts in free-living conditions. Recent studies have shown that summary statistics from these wearable recordings have potential uses for longitudinal monitoring of health and disease states. However, the relationship between higher resolution physiological dynamics from wearables and known markers of health and disease remains largely uncharacterized. Objective: We aimed to derive high-resolution digital phenotypes from observational wearable recordings and to examine their associations with modifiable and inherent markers of cardiometabolic disease risk. Methods: We introduced a principled framework to extract interpretable high-resolution phenotypes from wearable data recorded in free-living conditions. The proposed framework standardizes the handling of data irregularities; encodes contextual information regarding the underlying physiological state at any given time; and generates a set of 66 minimally redundant features across active, sedentary, and sleep states. We applied our approach to a multimodal data set, from the SingHEART study (NCT02791152), which comprises heart rate and step count time series from wearables, clinical screening profiles, and whole genome sequences from 692 healthy volunteers. We used machine learning to model nonlinear relationships between the high-resolution phenotypes on the one hand and clinical or genomic risk markers for blood pressure, lipid, weight and sugar abnormalities on the other. For each risk type, we performed model comparisons based on Brier scores to assess the predictive value of high-resolution features over and beyond typical baselines. We also qualitatively characterized the wearable phenotypes for participants who had actualized clinical events. Results: We found that the high-resolution features have higher predictive value than typical baselines for clinical markers of cardiometabolic disease risk: the best models based on high-resolution features had 17.9% and 7.36% improvement in Brier score over baselines based on age and gender and resting heart rate, respectively (P<.001 in each case). Furthermore, heart rate dynamics from different activity states contain distinct information (maximum absolute correlation coefficient of 0.15). Heart rate dynamics in sedentary states are most predictive of lipid abnormalities and obesity, whereas patterns in active states are most predictive of blood pressure abnormalities (P<.001). Moreover, in comparison with standard measures, higher resolution patterns in wearable heart rate recordings are better able to represent subtle physiological dynamics related to genomic risk for cardiometabolic disease (improvement of 11.9%-22.0% in Brier scores; P<.001). Finally, illustrative case studies reveal connections between these high-resolution phenotypes and actualized clinical events, even for borderline profiles lacking apparent cardiometabolic risk markers. Conclusions: High-resolution digital phenotypes recorded by consumer wearables in free-living states have the potential to enhance the prediction of cardiometabolic disease risk and could enable more proactive and personalized health management

The Infection of Chicken Tracheal Epithelial Cells with a H6N1 Avian Influenza Virus

Sialic acids (SAs) linked to galactose (Gal) in α2,3- and α2,6-configurations are the receptors for avian and human influenza viruses, respectively. We demonstrate that chicken tracheal ciliated cells express α2,3-linked SA, while goblet cells mainly express α2,6-linked SA. In addition, the plant lectin MAL-II, but not MAA/MAL-I, is bound to the surface of goblet cells, suggesting that SA2,3-linked oligosaccharides with Galβ1–3GalNAc subterminal residues are specifically present on the goblet cells. Moreover, both α2,3- and α2,6-linked SAs are detected on single tracheal basal cells. At a low multiplicity of infection (MOI) avian influenza virus H6N1 is exclusively detected in the ciliated cells, suggesting that the ciliated cell is the major target cell of the H6N1 virus. At a MOI of 1, ciliated, goblet and basal cells are all permissive to the AIV infection. This result clearly elucidates the receptor distribution for the avian influenza virus among chicken tracheal epithelial cells and illustrates a primary cell model for evaluating the cell tropisms of respiratory viruses in poultry

Encoding optical control in LCK kinase to quantitatively investigate its activity in live cells.

LCK is a tyrosine kinase that is essential for initiating T-cell antigen receptor (TCR) signaling. A complete understanding of LCK function is constrained by a paucity of methods to quantitatively study its function within live cells. To address this limitation, we generated LCK*, in which a key active-site lysine is replaced by a photocaged equivalent, using genetic code expansion. This strategy enabled fine temporal and spatial control over kinase activity, thus allowing us to quantify phosphorylation kinetics in situ using biochemical and imaging approaches. We find that autophosphorylation of the LCK active-site loop is indispensable for its catalytic activity and that LCK can stimulate its own activation by adopting a more open conformation, which can be modulated by point mutations. We then show that CD4 and CD8, T-cell coreceptors, can enhance LCK activity, thereby helping to explain their effect in physiological TCR signaling. Our approach also provides general insights into SRC-family kinase dynamics

The rate of cellular hydrogen peroxide removal shows dependency on GSH: Mathematical insight into in vivo H2O2 and GPx concentrations

Although its concentration is generally not known, glutathione peroxidase-1 (GPx-1) is a key enzyme in the removal of hydrogen peroxide (H2O2) in biological systems. Extrapolating from kinetic results obtained in vitro using dilute, homogenous buffered solutions, it is generally accepted that the rate of elimination of H2O2 in vivo by GPx is independent of glutathione concentration (GSH). To examine this doctrine, a mathematical analysis of a kinetic model for the removal of H2O2 by GPx was undertaken to determine how the reaction species (H2O2, GSH, and GPx-1) influence the rate of removal of H2O2. Using both the traditional kinetic rate law approximation (classical model) and the generalized kinetic expression, the results show that the rate of removal of H2O2 increases with initial GPxr, as expected, but is a function of both GPxr and GSH when the initial GPxr is less than H2O2. This simulation is supported by the biological observations of Li et al.. Using genetically altered human glioma cells in in vitro cell culture and in an in vivo tumour model, they inferred that the rate of removal of H2O2 was a direct function of GPx activity × GSH (effective GPx activity). The predicted cellular average GPxr and H2O2 for their study are approximately GPxr ≤ 1 μm and H2O2 ≈ 5 μm based on available rate constants and an estimation of GSH. It was also found that results from the accepted kinetic rate law approximation significantly deviated from those obtained from the more generalized model in many cases that may be of physiological importance