345 research outputs found
Design of Energy Management System of a PEMFC–Battery– Supercapacitor Hybrid Tramway
In this chapter, a hybrid power system that consists of multiple proton exchange membrane fuel cell (PEMFC) systems, batteries, and supercapacitors (SCs) is developed for a hybrid tramway. Three energy management strategies that included a fuzzy logic control (FLC), an equivalent consumption minimization strategy (ECMS), and a state machine strategy based on droop control (SMS-DC) are utilized to coordinate multiple power sources, avoid the transients and rapid changes of power demand, and achieve high efficiency without degrading the mechanism performance for an energy management system of hybrid tramway. A hybrid system model of tramway is established with commercially available devices, and then the different energy management strategies are evaluated with a real driving cycle of tramway from Turkey. The results compared with these strategies demonstrate that the higher average efficiencies of the tramway, the lower tramway-equivalent hydrogen consumptions, and more efficient use of the batteries and SCs energy are achieved by the SMS-DC. Therefore, the appropriate energy management system for high-power hybrid tramway will improve the hydrogen consumptions of overall hybrid system and the efficiencies of each power source
Characterization and density functional theory study of the antioxidant activity of quercetin and its sugar-containing analogues
Inhibition of free radicals using quercetin, hyperin and rutin is examined to determine their antioxidant effects and the structure-activity relationships of flavonoids. Two species of the free radicals are used, including hydroxyl radical (.OH) and superoxide anion radical (O-2(-)). Density functional theory calculations under the level of B3LYP/6-311G (d) have been utilized to explore the structure, molecular properties and antioxidant abilities of the three flavonoids. Bond dissociation enthalpy (BDE) and frontier molecular orbital energy gap are investigated. They are compared with the experiment results assayed by the spectrophotometric. All of the flavonoids show a high activity on inhibiting OH and O-2(-) radicals. Scavenging activity determined by half maximal inhibitory concentration (IC50) values of the three flavonoids decreases in the order: quercetin > hyperin > rutin. The calculations show that quercetin owns the lowest BDE values, which agree well with the experimental results of antioxidant activity determined by IC50 values
Analysis on relationship between extreme pathways and correlated reaction sets
Background: Constraint-based modeling of reconstructed genome-scale metabolic networks has been successfully applied on several microorganisms. In constraint-based modeling, in order to characterize all allowable phenotypes, network-based pathways, such as extreme pathways and elementary flux modes, are defined. However, as the scale of metabolic network rises, the number of extreme pathways and elementary flux modes increases exponentially. Uniform random sampling solves this problem to some extent to study the contents of the available phenotypes. After uniform random sampling, correlated reaction sets can be identified by the dependencies between reactions derived from sample phenotypes. In this paper, we study the relationship between extreme pathways and correlated reaction sets.Results: Correlated reaction sets are identified for E. coli core, red blood cell and Saccharomyces cerevisiae metabolic networks respectively. All extreme pathways are enumerated for the former two metabolic networks. As for Saccharomyces cerevisiae metabolic network, because of the large scale, we get a set of extreme pathways by sampling the whole extreme pathway space. In most cases, an extreme pathway covers a correlated reaction set in an \u27all or none\u27 manner, which means either all reactions in a correlated reaction set or none is used by some extreme pathway. In rare cases, besides the \u27all or none\u27 manner, a correlated reaction set may be fully covered by combination of a few extreme pathways with related function, which may bring redundancy and flexibility to improve the survivability of a cell. In a word, extreme pathways show strong complementary relationship on usage of reactions in the same correlated reaction set.Conclusion: Both extreme pathways and correlated reaction sets are derived from the topology information of metabolic networks. The strong relationship between correlated reaction sets and extreme pathways suggests a possible mechanism: as a controllable unit, an extreme pathway is regulated by its corresponding correlated reaction sets, and a correlated reaction set is further regulated by the organism\u27s regulatory network.<br /
Mapping Aboveground and Foliage Biomass Over the Porcupine Caribou Habitat in Northern Yukon and Alaska Using Landsat and JERS-1/SAR Data
Model-based Comparative Prediction of Transcription-Factor Binding Motifs in Anabolic Responses in Bone.
Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both “anabolic responses of mechanical loading” and “BMP-mediated osteogenic signaling”? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated receptor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells supported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation
Targeted Deletion of the Claudin12 Gene in Mice Increases Articular Cartilage and Inhibits Chondrocyte Differentiation
To study the role of Claudin (CLDN)12 in bone, we developed mice with a targeted deletion of exon2 in the Cldn12 gene for skeletal phenotype analysis. Micro-CT analysis of the secondary spongiosa of distal femurs of mice with targeted disruption of the Cldn12 gene and control littermates showed no significant genotype-specific differences in either cortical or trabecular bone parameters for either gender in 13-week-old mice. Immunohistochemistry revealed that while CLDN12 was expressed in both differentiating chondrocytes and osteoblasts of the secondary spongiosa of 3-week-old wild-type mice, its expression was restricted to differentiating chondrocytes in the articular cartilage and growth plate in adult mice. Articular cartilage area at the knee were increased by 47% in Cldn12 knockout (KO) mice compared to control littermates. Micro-CT analyses found that while the trabecular number was increased by 9% and the trabecular spacing was reduced by 9% in the femoral epiphysis of Cldn12 KO mice, neither bone volume nor bone volume adjusted for tissue volume was different between the two genotypes. The expression levels of Clusterin, Lubricin and Mmp13 were increased by 56%, 46%, and 129%, respectively, in primary articular chondrocytes derived from KO compared to control mice. Our data indicate that targeted deletion of the Cldn12 gene in mice increases articular cartilage, in part, by promoting articular chondrocyte phenotype
Gene expression profile analysis of human hepatocellular carcinoma using SAGE and LongSAGE
<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and the second cancer killer in China. The initiation and malignant transformation of cancer result from accumulation of genetic changes in the sequences or expression level of cancer-related genes. It is of particular importance to determine gene expression profiles of cancers on a global scale. SAGE and LongSAGE have been developed for this purpose.</p> <p>Methods</p> <p>We performed SAGE in normal liver and HCC samples as well as the liver cancer cell line HepG2. Meanwhile, the same HCC sample was simultaneously analyzed using LongSAGE. Computational analysis was carried out to identify differentially expressed genes between normal liver and HCC which were further validated by real-time quantitative RT-PCR.</p> <p>Results</p> <p>Approximately 50,000 tags were sequenced for each of the four libraries. Analysis of the technical replicates of HCC indicated that excluding the low abundance tags, the reproducibility of SAGE data is high (R = 0.97). Compared with the gene expression profile of normal liver, 224 genes related to biosynthesis, cell proliferation, signal transduction, cellular metabolism and transport were identified to be differentially expressed in HCC. Overexpression of some transcripts selected from SAGE data was validated by real-time quantitative RT-PCR. Interestingly, sarcoglycan-ε (SGCE) and paternally expressed gene (PEG10) which is a pair of close neighboring genes on chromosome 7q21, showed similar enhanced expression patterns in HCC, implicating that a common mechanism of deregulation may be shared by these two genes.</p> <p>Conclusion</p> <p>Our study depicted the expression profile of HCC on a genome-wide scale without the restriction of annotation databases, and provided novel candidate genes that might be related to HCC.</p
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