Monocytes are critical in controlling tissue infections and inflammation. Monocyte dysfunction contributes to the inflammatory pathogenesis of cystic fibrosis (CF) caused by CF transmembrane conductance regulator (CFTR) mutations, making CF a clinically relevant disease model for studying the contribution of monocytes to inflammation. Although CF monocytes exhibited adhesion defects, the precise mechanism is unclear.
View Article and Find Full Text PDFWe aimed to explore the association between plant-based dietary (PBD) patterns and obesity trajectories in middle-aged and elderly, as well as obesity trajectories linked to cardiovascular disease (CVD) risk. A total of 7108 middle-aged and elderly UK Biobank participants with at least three physical measurements were included. Dietary information collected at enrolment was used to calculate the healthful plant-based diet index (hPDI).
View Article and Find Full Text PDFMicrobiome-metabolome association analysis is critical to reveal the key pairs of gut microbiota and metabolites for discovery of the microbial biomarkers in chronic diseases. However, the characteristics of microbiome data, such as zero inflation, over dispersion, may impair the confidence of association analysis between microbiome and metabolome data. The objectives of this study are to evaluate the strengths and weaknesses of existing statistical methods and to develop a computational framework tailored to the unique characteristics of microbiome data.
View Article and Find Full Text PDFPositive results from cancer screenings, like a cancer diagnosis, can increase the risk of cardiovascular disease (CVD) mortality due to heightened psychological stress. However, positive screening results may also serve as a teachable moment to encourage the adoption of a healthier lifestyle. Consequently, the overall association between positive screenings and CVD mortality risk remains unclear.
View Article and Find Full Text PDFInterfacial tension () between CO and brine depends on chemical components in multiphase systems, intricately evolving with a change in temperature. In this study, we developed a convolutional neural network with a multibranch structure (MBCNN), which, in combination with a compiled data set containing measurement data of 1716 samples from 13 available literature sources at wide temperature and pressure ranges (273.15-473.
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