Steatosis-induced proteins adducts with lipid peroxidation products and nuclear electrophilic stress in hepatocytes

AbstractAccumulating evidence suggests that fatty livers are particularly more susceptible to several pathological conditions, including hepatic inflammation, cirrhosis and liver cancer. However the exact mechanism of such susceptibility is still largely obscure. The current study aimed to elucidate the effect of hepatocytes lipid accumulation on the nuclear electrophilic stress. Accumulation of intracellular lipids was significantly increased in HepG2 cells incubated with fatty acid (FA) complex (1mM, 2:1 oleic and palmitic acids). In FA-treated cells, lipid droplets were localized around the nucleus and seemed to induce mechanical force, leading to the disruption of the nucleus morphology. Level of reactive oxygen species (ROS) was significantly increased in FA-loaded cells and was further augmented by treatment with moderate stressor (CoCl2). Increased ROS resulted in formation of reactive carbonyls (aldehydes and ketones, derived from lipid peroxidation) with a strong perinuclear accumulation. Mass-spectroscopy analysis indicated that lipid accumulation per-se can results in modification of nuclear protein by reactive lipid peroxidation products (oxoLPP). 235 Modified proteins involved in transcription regulation, splicing, protein synthesis and degradation, DNA repair and lipid metabolism were identified uniquely in FA-treated cells. These findings suggest that steatosis can affect nuclear redox state, and induce modifications of nuclear proteins by reactive oxoLPP accumulated in the perinuclear space upon FA-treatment

Mathematical Modeling of Rechargeable Hybrid Aqueous Batteries

A rechargeable hybrid aqueous battery (ReHAB) system was recently developed by our research group. It has been improved via different experimental approaches, but nobody yet has tried to use mathematical modeling techniques to further understand the system. This thesis tries to investigate the ReHAB system using a few current modeling methods. The study is categorized into empirical level, electrochemical engineering level and atomistic level. At the empirical level, a battery is simply viewed as a whole system, which means detailed descriptions in terms of the cathode, anode or electrolyte are ignored. By using the historical experimental data, researchers can predict the future behavior of a battery regardless of its internal phenomena. They usually employ some general mathematical functions, such as polynomial, logarithmic, exponential or other nonlinear functions. Currently automatic curve fitting and predicting algorithms are commonly used in the battery management system, due to the advantage in coping with the system nonlinearity. The first study in this thesis implements a tracking method called particle filter method on the ReHAB experimental data. The basic math function in the simulation is an empirical formula between the battery capacity and the Coulombic efficiency. The study confirms this correlation in the ReHABs, and proves that particle filter method can be a good option in battery performance tracking and prediction. At the electrochemical engineering level, battery performance is simulated in the continuum models, by incorporating chemical or electrochemical reactions, transport phenomena or interfacial kinetics. This level of simulation can help observe battery electrodes in details. It is more accurate than the empirical level model, and more versatile in simulating various electrochemical problems. This thesis secondly focuses on the ReHAB system cathode and anode using finite element method, which is implemented in COMSOL Multiphysics. The study includes a design of battery system model, investigation of species distribution during cell operation, side-reaction effects and anode corrosion issues. The models designed at this level give consistent results compared with the experimental data, and illustrate some guidance for the potential experiments. At the atomistic level, molecular simulation can model the system dynamics via step-by-step computation. Stochastic method is an efficient molecular method to investigate electrochemical problems coupled with species diffusion and chemical reactions. Atomistic simulation commonly spends longer time, but it can be very accurate regarding the evolution of a dynamic physical system. The study at this level employs the classical stochastic method on the electrochemical deposition of Zn atoms. It is focused on the dendrite formation via implementing diffusion-limited aggregation techniques and the remaining metal ions by using stochastic simulation methods. The simulation schematically illustrates the overpotential influence on the dendrites and ion distribution at the metal surface. These findings prove that overpotential is an important factor and can also help further design of experiments

Byzantine-Robust Clustered Federated Learning

This paper focuses on the problem of adversarial attacks from Byzantine machines in a Federated Learning setting where non-Byzantine machines can be partitioned into disjoint clusters. In this setting, non-Byzantine machines in the same cluster have the same underlying data distribution, and different clusters of non-Byzantine machines have different learning tasks. Byzantine machines can adversarially attack any cluster and disturb the training process on clusters they attack. In the presence of Byzantine machines, the goal of our work is to identify cluster membership of non-Byzantine machines and optimize the models learned by each cluster. We adopt the Iterative Federated Clustering Algorithm (IFCA) framework of Ghosh et al. (2020) to alternatively estimate cluster membership and optimize models. In order to make this framework robust against adversarial attacks from Byzantine machines, we use coordinate-wise trimmed mean and coordinate-wise median aggregation methods used by Yin et al. (2018). Specifically, we propose a new Byzantine-Robust Iterative Federated Clustering Algorithm to improve on the results in Ghosh et al. (2019). We prove a convergence rate for this algorithm for strongly convex loss functions. We compare our convergence rate with the convergence rate of an existing algorithm, and we demonstrate the performance of our algorithm on simulated data

Computational solutions in redox lipidomics – Current strategies and future perspectives

Abstract The high chemical diversity of lipids allows them to perform multiple biological functions ranging from serving as structural building blocks of biological membranes to regulation of metabolism and signal transduction. In addition to the native lipidome, lipid species derived from enzymatic and non-enzymatic modifications (the epilipidome) make the overall picture even more complex, as their functions are still largely unknown. Oxidized lipids represent the fraction of epilipidome which has attracted high scientific attention due to their apparent involvement in the onset and development of numerous human disorders. Development of high-throughput analytical methods such as liquid chromatography coupled on-line to mass spectrometry provides the possibility to address epilipidome diversity in complex biological samples. However, the main bottleneck of redox lipidomics, the branch of lipidomics dealing with the characterization of oxidized lipids, remains the lack of optimal computational tools for robust, accurate and specific identification of already discovered and yet unknown modified lipids. Here we discuss the main principles of high-throughput identification of lipids and their modified forms and review the main software tools currently available in redox lipidomics. Different levels of confidence for software assisted identification of redox lipidome are defined and necessary steps toward optimal computational solutions are proposed

Experimental study of mechanical property for prestressed rubber bearing

To overcome the shortages of existing Rubber Bearings (RBs), an innovative type of isolator, named as Prestressed Rubber Bearing (PRB), is presented in this paper. Base on conventional laminated Rubber Bearing (RB), PRB is developed by increasing the thickness of rubber layers, setting vertical ducts and installing prestress tendons. Through the vertical and horizontal monotonic loading test, the vertical and horizontal stiffness of PRBs are investigated. The empirical formulas for stiffness are proposed. Moreover, the hysteresis behavior and the energy dissipation capacity of PRBs are studied by reversed cyclic loading test. The results show that PRBs not only have the horizontal isolating capacity as conventional RBs, but also have the capacity of horizontal displacement-limitation and improved capacity of energy dissipation