The role of mitochondria-associated membranes mediated ROS on NLRP3 inflammasome in cardiovascular diseases

Reactive oxygen species (ROS) metabolism is essential for the homeostasis of cells. Appropriate production of ROS is an important signaling molecule, but excessive ROS production can damage cells. ROS and ROS-associated proteins can act as damage associated molecular pattern molecules (DAMPs) to activate the NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome in cardiovascular diseases. Previous studies have shown that there are connected sites, termed mitochondria-associated membranes (MAMs), between mitochondria and the endoplasmic reticulum. In cardiovascular disease progression, MAMs play multiple roles, the most important of which is the ability to mediate ROS generation, which further activates the NLPR3 inflammasome, exacerbating the progression of disease. In this review, the following topics will be covered: 1. Molecular structures on MAMs that can mediate ROS generation; 2. Specific mechanisms of molecule-mediated ROS generation and the molecules' roles in cardiovascular disease, 3. The effects of MAMs-mediated ROS on the NLRP3 inflammasome in cardiovascular disease. The purpose of this review is to provide a basis for subsequent clinical treatment development

Implementation of a Symbolic Circuit Simulator for Topological Network Analysis

Abstract- Many topological approaches to symbolic network analysis have been proposed in the literature, but none are implemented ultimately as a simulator for large network analysis due to their complexity and exponentially increasing number of terms. A novel methodology adopted in this paper uses a graph reduction approach based on a set of graph reduction rules developed recently. Furthermore, a Binary Decision Diagram is used in the implementation of a symbolic simulator that is capable of analyzing large analog circuit blocks. Implementation details and experimental results are reported. Keywords-admissible term, BDD, graph reduction, symbolic analysis I

Earth reflectivity from Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Camera (EPIC)

Poster presented at 2017 AGU Fall Meeting, New Orleans, Louisiana. POSTER ID: A33D-2387Earth reflectivity, which is also specified as Earth albedo or Earth reflectance, is defined as the fraction of incident solar radiation reflected back to space at the top of the atmosphere. It is a key climate parameter that describes climate forcing and associated response of the climate system. Satellite is one of the most efficient ways to measure earth reflectivity. Conventional polar orbit and geostationary satellites observe the Earth at a specific local solar time or monitor only a specific area of the Earth. For the first time, the NASA’s Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR) collects simultaneously radiance data of the entire sunlit earth at 8 km resolution at nadir every 65 to 110 min. It provides reflectivity images in backscattering direction with the scattering angle between 168º and 176º at 10 narrow spectral bands in ultraviolet, visible, and near-Infrared (NIR) wavelengths. We estimate the Earth reflectivity using DSCOVR EPIC observations and analyze errors in Earth reflectivity due to sampling strategy of polar orbit Terra/Aqua MODIS and geostationary Goddard Earth Observing System-R series missions. We also provide estimates of contributions from ocean, clouds, land and vegetation to the Earth reflectivity. Graphic abstract shows enhanced RGB EPIC images of the Earth taken on July-24-2016 at 7:04GMT and 15:48 GMT. Parallel lines depict a 2330 km wide Aqua MODIS swath. The plot shows diurnal courses of mean Earth reflectance over the Aqua swath (triangles) and the entire image (circles). In this example the relative difference between the mean reflectances is +34% at 7:04GMT and -16% at 15:48 GMT. Corresponding daily averages are 0.256 (0.044) and 0.231 (0.025). The relative precision estimated as root mean square relative error is 17.9% in this example

Control spiral wave dynamics using feedback signals from line detectors

We numerically study trajectories of spiral-wave-cores in excitable systems modulated proportionally to the integral of the activity on the straight line, several or dozens of equi-spaced measuring points on the straight line, the double-line and the contour-line. We show the single-line feedback results in the drift of core center along a straight line being parallel to the detector. An interesting finding is that the drift location in $y$ is a piecewise linear-increasing function of both the feedback line location and time delay. Similar trajectory occurs when replacing the feedback line with several or dozens of equi-spaced measuring points on the straight line. This allows to move the spiral core to the desired location along a chosen direction by measuring several or dozens of points. Under the double-line feedback, the shape of the tip trajectory representing the competition between the first and second feedback lines is determined by the distance of two lines. Various drift attractors in spiral wave controlled by square-shaped contour-line feedback are also investigated. A brief explanation is presented.Comment: 6 pages and 7 figures; Accepted for publication in EPL; Figs.5 and 6 are in JPG forma

Role of tumor-associated macrophages in hepatocellular carcinoma: impact, mechanism, and therapy

Hepatocellular carcinoma (HCC) is a highly frequent malignancy worldwide. The occurrence and progression of HCC is a complex process closely related to the polarization of tumor-associated macrophages (TAMs) in the tumor microenvironment (TME). The polarization of TAMs is affected by a variety of signaling pathways and surrounding cells. Evidence has shown that TAMs play a crucial role in HCC, through its interaction with other immune cells in the TME. This review summarizes the origin and phenotypic polarization of TAMs, their potential impacts on HCC, and their mechanisms and potential targets for HCC immunotherapy

Implications of whole-disc DSCOVR EPIC spectral observations for estimating Earth's spectral reflectivity based on low-earth-orbiting and geostationary observations

Earth’s reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)’s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)’s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth’s reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth’s reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth’s reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between −0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between −10% and 23%.The NASA/GSFC DSCOVR project is funded by NASA Earth Science Division. W. Song, G. Yan, and X. Mu were also supported by the key program of National Natural Science Foundation of China (NSFC; Grant No. 41331171). This research was conducted and completed during a 13-month research stay of the lead author in the Department of Earth and Environment, Boston University as a joint Ph.D. student, which was supported by the Chinese Scholarship Council (201606040098). DSCOVR EPIC L1B data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. The authors would like to thank the editor who handled this paper and the two anonymous reviewers for providing helpful and constructive comments and suggestions that significantly helped us improve the quality of this paper. (NASA Earth Science Division; 41331171 - key program of National Natural Science Foundation of China (NSFC); 201606040098 - Chinese Scholarship Council)Accepted manuscrip

Integrated Analysis of Long Noncoding RNA and Coding RNA Expression in Esophageal Squamous Cell Carcinoma

Tumorigenesis is a complex dynamic biological process that includes multiple steps of genetic and epigenetic alterations, aberrant expression of noncoding RNA, and changes in the expression profiles of coding genes. We call the collection of those perturbations in genome space the “cancer initiatome.” Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and they have key regulatory functions in chromatin remodeling and gene expression. Spatiotemporal variation in the expression of lncRNAs has been observed in development and disease states, including cancer. A few dysregulated lncRNAs have been studied in cancers, but the role of lncRNAs in the cancer initiatome remains largely unknown, especially in esophageal squamous cell carcinoma (ESCC). We conducted a genome-wide screen of the expression of lncRNAs and coding RNAs from ESCC and matched adjacent nonneoplastic normal tissues. We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis. Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC. These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer