Wuhan University

About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Feature extraction. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.

STING-IRF3 contributes to lipopolysaccharide-induced cardiac dysfunction, inflammation, apoptosis and pyroptosis by activating NLRP3

Abstract: Mountainous evidence suggests that inflammation, cardiomyocyte apoptosis and pyroptosis are involved in the development of sepsis and sepsis-induced cardiomyopathy (SIC). Stimulator of interferon genes (STING) is an indispensable molecule that could regulate inflammation and immune response in multiple diseases. However, the role of STING in cardiovascular disease, especially SIC remains unclear. This study was designed to investigate the potential molecular mechanisms of STING in lipopolysaccharide (LPS)-induced cardiac injury using STING global knockout mice. In wild type mice and cardiomyocytes, LPS stimulation triggered the perinuclear translocation of STING, which further bound to Type-I interferons (IFN) regulatory factor 3 (IRF3) and phosphorylated IRF3. Phosphorylated (P-) IRF3 subsequently translocated into nucleus and increased the expression of NOD-like receptor protein 3 (NLRP3). Knockout of STING in mice significantly improved survival rate and cardiac function, apart from suppressing myocardial and serum inflammatory cytokines, apoptosis, as well as cardiomyocyte pyroptosis. In vitro experiments revealed that NLRP3 overexpression by adenovirus could offset protective effects of STING knockdown in LPS-induced cardiomyocytes. Additionally, LPS stimulation also promoted the production of intracellular reactive oxygen (ROS), which further induced the NLRP3 translocation to the cytoplasm from the nucleus. Dissociative TXNIP could directly interact with cytoplasmic NLRP3 and form inflammasome, eventually triggering cardiomyocyte injury. Collectively, our findings disclose that STING deficiency could alleviate LPS-induced SIC in mice. Hence, targeting STING in cardiomyocytes may be a promising therapeutic strategy for preventing SIC.

A Discriminative Metric Learning Based Anomaly Detection Method

Abstract: Due to the high spectral resolution, anomaly detection from hyperspectral images provides a new way to locate potential targets in a scene, especially those targets that are spectrally different from the majority of the data set. Conventional Mahalanobis-distance-based anomaly detection methods depend on the background statistics to construct the anomaly detection metric. One of the main problems with these methods is that the Gaussian distribution assumption of the background may not be reasonable. Furthermore, these methods are also susceptible to contamination of the conventional background covariance matrix by anomaly pixels. This paper proposes a new anomaly detection method by effectively exploiting a robust anomaly degree metric for increasing the separability between anomaly pixels and other background pixels, using discriminative information. First, the manifold feature is used so as to divide the pixels into the potential anomaly part and the potential background part. This procedure is called discriminative information learning. A metric learning method is then performed to obtain the robust anomaly degree measurements. Experiments with three hyperspectral data sets reveal that the proposed method outperforms other current anomaly detection methods. The sensitivity of the method to several important parameters is also investigated.

Efficient System Reliability Analysis of Slope Stability in Spatially Variable Soils Using Monte Carlo Simulation

Abstract: Monte Carlo simulation (MCS) provides a conceptually simple and robust method to evaluate the system reliability of slope stability, particularly in spatially variable soils. However, it suffers from a lack of efficiency at small probability levels, which are of great interest in geotechnical design practice. To address this problem, this paper develops a MCS-based approach for efficient evaluation of the system failure probability P f , s of slope stability in spatially variable soils. The proposed approach allows explicit modeling of the inherent spatial variability of soil properties in a system reliability analysis of slope stability. It facilitates the slope system reliability analysis using representative slip surfaces (i.e., dominating slope failure modes) and multiple stochastic response surfaces. Based on the stochastic response surfaces, the values of P f , s are efficiently calculated using MCS with negligible computational effort. For illustration, the proposed MCS-based system reliab...