A key assumption in studying mRNA expression is that it is informative in the prediction of protein expression. However, only limited studies have explored the mRNA-protein expression correlation in yeast or human tissues and the results have been relatively inconsistent. We carried out correlation analyses on mRNA-protein expressions in freshly isolated human circulating monocytes from 30 unrelated women. The expressed proteins for 71 genes were quantified and identified by 2-D electrophoresis coupled with mass spectrometry. The corresponding mRNA expressions were quantified by Affymetrix gene chips. Significant correlation (r=0.235, P<0.0001) was observed for the whole dataset including all studied genes and all samples. The correlations varied in different biological categories of gene ontology. For example, the highest correlation was achieved for genes of the extracellular region in terms of cellular component (r=0.643, P<0.0001) and the lowest correlation was obtained for genes of regulation (r=0.099, P=0.213) in terms of biological process. In the genome, half of the samples showed significant positive correlation for the 71 genes and significant correlation was found between the average mRNA and the average protein expression levels in all samples (r=0.296, P<0.01). However, at the study group level, only five studied genes had significant positive correlation across all the samples. Our results showed an overall positive correlation between mRNA and protein expression levels. However, the moderate and varied correlations suggest that mRNA expression might be sometimes useful, but certainly far from perfect, in predicting protein expression levels.

To comprehensively identify proteins of the rat liver plasma membrane (PM), we have adopted a proteomics strategy that utilizes sucrose density centrifugation in conjunction with aqueous two-phase partition for plasma membrane isolation, followed by SDS-PAGE, mass spectrometry and bioinformatics. Western blot analysis showed that this method results in highly purified plasma membrane fractions, which is a key to successful plasma membrane proteomics. The PM proteins were separated by SDS-PAGE and digested with trypsin. Through nano-ESI-LC MS/MS analysis we identified 428 rat liver membrane proteins, of which 304 had a gene ontology (GO) annotation indicating a cellular component, and 204 (67%) of the latter were known integral membrane proteins or membrane-associated proteins. In addition to proteins known to be associated with the plasma membrane, several hypothetical proteins have also been identified. This study not only provides a tool to study plasma membrane proteins with low levels of contamination, but also provides a data set for proteins of high to moderate abundance in rat liver plasma membranes, thus allowing for more comprehensive characterization of membrane proteins and a better understanding of membrane dynamics.

In-gel digestion is commonly used after proteins are resolved by polyacrylamide gel electrophoresis (SDS-PAGE, 2-DE). It can also be used on its own in conjunction with tandem mass spectrometry (MS/MS) for the direct analysis of complex proteins. Here, we describe a strategy combining isolation of purified plasma membrane, efficient digestion of plasma membrane proteins in polyacrylamide gel, and high-sensitivity analysis by advanced mass spectrometry to create a new rapid and high-throughput method. The plasma membrane protein mixture is directly incorporated into a polyacrylamide gel matrix, After formation of the gel, proteins in the gel section are digested with trypsin, and the resulting peptides are subjected to reversed-phase, high-performance liquid chromatography followed by electrospray ion-trap tandem mass analysis. Using this optimized strategy, we have identified 883 rat liver membrane proteins, of which 490 had a gene ontology (GO) annotation indicating a cellular component, and 294 (60%) of the latter were known integral membrane proteins or membrane proteins. In total, 333 proteins are predicted by the TMHMM 2.0 algorithm to have transmembrane domains (TMDs) and 52% (175 of 333) proteins to contain 2-16 TMDs. The identified membrane proteins provide a broad representation of the rat plasma membrane proteome with little bias evident due to protein p I and molecular weight (MW). Also, membrane proteins with a high GRAVY score (grand average hydrophobicity score) were identified, and basic and acidic membrane proteins were evenly represented. This study not only offered an efficient and powerful method in shotgun proteomics for the identification of proteins of complex plasma membrane samples but also allowed in-depth study of liver membrane proteomes, such as of rat models of liver-related disease. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of rat liver plasma membrane in general.

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Abstract:As part of the smart grid development, more and more technologies are developed and deployed on the power grid to enhance the system reliability. A primary purpose of the smart grid is to significantly increase the capability of computer-based remote control and automation. As a result, the level of connectivity has become much higher, and cyber security also becomes a potential threat to the cyber-physical systems (CPSs). In this paper, a survey of the state-of-the-art is conducted on the cyber security of the power grid concerning issues of: (1) the structure of CPSs in a smart grid; (2) cyber vulnerability assessment; (3) cyber protection systems; and (4) testbeds of a CPS. At Washington State University (WSU), the Smart City Testbed (SCT) has been developed to provide a platform to test, analyze and validate defense mechanisms against potential cyber intrusions. A test case is provided in this paper to demonstrate how a testbed helps the study of cyber security and the anomaly detection system (ADS) for substations.

The number of distributed energy components and devices continues to increase globally. As a result, distributed control schemes are desirable for managing and utilizing these devices, together with the large amount of data. In recent years, agent-based technology becomes a powerful tool for engineering applications. As a computational paradigm, multi-agent systems (MASs) provide a good solution for distributed control. In this paper, MASs and applications are discussed. A state-ofthe-art literature survey is conducted on the system architecture, consensus algorithm, and multiagent platform, framework, and simulator. In addition, a distributed under-frequency load shedding scheme is proposed using the MAS. Simulation results for a case study are presented. The future of MASs is discussed in the conclusion.

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