Low Expression of DYRK2 (Dual Specificity Tyrosine Phosphorylation Regulated Kinase 2) Correlates with Poor Prognosis in Colorectal Cancer.

Dual-specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) is a member of dual-specificity kinase family, which could phosphorylate both Ser/Thr and Tyr substrates. The role of DYRK2 in human cancer remains controversial. For example, overexpression of DYRK2 predicts a better survival in human non-small cell lung cancer. In contrast, amplification of DYRK2 gene occurs in esophageal/lung adenocarcinoma, implying the role of DYRK2 as a potential oncogene. However, its clinical role in colorectal cancer (CRC) has not been explored. In this study, we analyzed the expression of DYRK2 from Oncomine database and found that DYRK2 level is lower in primary or metastatic CRC compared to adjacent normal colon tissue or non-metastatic CRC, respectively, in 6 colorectal carcinoma data sets. The correlation between DYRK2 expression and clinical outcome in 181 CRC patients was also investigated by real-time PCR and IHC. DYRK2 expression was significantly down-regulated in colorectal cancer tissues compared with adjacent non-tumorous tissues. Functional studies confirmed that DYRK2 inhibited cell invasion and migration in both HCT116 and SW480 cells and functioned as a tumor suppressor in CRC cells. Furthermore, the lower DYRK2 levels were correlated with tumor sites (P = 0.023), advanced clinical stages (P = 0.006) and shorter survival in the advanced clinical stages. Univariate and multivariate analyses indicated that DYRK2 expression was an independent prognostic factor (P < 0.001). Taking all, we concluded that DYRK2 a novel prognostic biomarker of human colorectal cancer

Microvessel density and heparanase over-expression in clear cell renal cell cancer: correlations and prognostic significances

<p>Abstract</p> <p>Background</p> <p>Tumor angiogenesis is important in the progression of malignancies, and heparanase plays an important role in sustaining the pathology of clear cell renal cell cancer (ccRCC). The study was carried out to investigate the correlations between microvessel density (MVD) and heparanase expression containing prognostic significances in the patients with ccRCC.</p> <p>Methods</p> <p>Specimens from 128 patients with ccRCC were investigated by immunohistochemistry for MVD. RT-PCR and immunohistochemistry were used to detect heparanase expression. Correlations between MVD, heparanase expression, and various clinico-pathological factors were studied. The prognostic significances of MVD and heparanase expression were also analysed.</p> <p>Results</p> <p>We discovered a statistically significant prevalence of higher MVD in ccRCC compared with adjacent normal renal tissues. MVD was positively correlated with TNM stage and distant metastasis in ccRCC patients, and was also correlated with the expression level of heparanase.</p> <p>Heparanase is over-expressed and correlated with TNM stage, histologic grade, distant metastasis and lymphatic metastasis in ccRCC. High MVD and heparanase over-expression inversely correlate with the survival of ccRCC patients.</p> <p>Conclusions</p> <p>Heparanase contributes to angiogenesis of ccRCC and over-expression of heparanase is an independent predictors of prognosis for ccRCC. MVD is correlated with tumor development and metastasis in ccRCC.</p

Accelerating Development of Renewable Energy Resources in Guangdong

Abstract: The energy status and trend of Guangdong Province have been evaluated from 1980-2009 in this paper, which maybe is one of the most populated and prosperous areas in China. Based on the analysis of energy system for Guangdong, an integrated optimal energy system model has been established in order to promote renewable energy utilization in large-scale and support provincial sustainable development, and case study of a district of 18km 2 area shows that with the current technologic and economic condition, renewables goal of realizing 10% of total energy consumption is possible in Guangdong. Case selected was very common, which can be a model of cycle-economic and ecological district in Guangdong, even China

Enhancing sensor duty cycle in environmental wireless sensor networks using Quantum Evolutionary Golden Jackal Optimization Algorithm

Environmental wireless sensor networks (EWSNs) are essential in environmental monitoring and are widely used in gas monitoring, soil monitoring, natural disaster early warning and other fields. EWSNs are limited by the sensor battery capacity and data collection range, and the usual deployment method is to deploy many sensor nodes in the monitoring zone. This deployment method improves the robustness of EWSNs, but introduces many redundant nodes, resulting in a problem of duty cycle design, which can be effectively solved by duty cycle optimization. However, the duty cycle optimization in EWSNs is an NP-Hard problem, and the complexity of the problem increases exponentially with the number of sensor nodes. In this way, non-heuristic algorithms often fail to obtain a deployment solution that meets the requirements in reasonable time. Therefore, this paper proposes a novel heuristic algorithm, the Quantum Evolutionary Golden Jackal Optimization Algorithm (QEGJOA), to solve the duty cycle optimization problem. Specifically, QEGJOA can effectively prolong the lifetime of EWSNs by duty cycle optimization and can quickly get a deployment solution in the face of multi-sensor nodes. New quantum exploration and exploitation operators are designed, which greatly improves the global search ability of the algorithm and enables the algorithm to effectively solve the problem of excessive complexity in duty cycle optimization. In addition, this paper designs a new sensor duty cycle model, which has the advantages of high accuracy and low complexity. The simulation shows that the QEGJOA proposed in this paper improves by 18.69, 20.15 and 26.55 compared to the Golden Jackal Optimization (GJO), Whale Optimization Algorithm (WOA) and the Simulated Annealing Algorithm (SA)

Grace-AKO: a novel and stable knockoff filter for variable selection incorporating gene network structures

Motivation Variable selection is a common statistical approach to identifying genes associated with clinical outcomes of scientific interest. There are thousands of genes in genomic studies, while only a limited number of individual samples are available. Therefore, it is important to develop a method to identify genes associated with outcomes of interest that can control finite-sample false discovery rate (FDR) in high-dimensional data settings. Results This article proposes a novel method named Grace-AKO for graph-constrained estimation (Grace), which incorporates aggregation of multiple knockoffs (AKO) with the network-constrained penalty. Grace-AKO can control FDR in finite-sample settings and improve model stability simultaneously. Simulation studies show that Grace-AKO has better performance in finite-sample FDR control than the original Grace model. We apply Grace-AKO to the prostate cancer data in The Cancer Genome Atlas program by incorporating prostate-specific antigen (PSA) pathways in the Kyoto Encyclopedia of Genes and Genomes as the prior information. Grace-AKO finally identifies 47 candidate genes associated with PSA level, and more than 75% of the detected genes can be validated

A dimeric Smac/ diablo peptide directly relieves caspase-3 inhibition by XIAP. Dynamic and cooperative regulation of XIAP by Smac/Diablo

Caspase activation, the executing event of apoptosis, is under deliberate regulation. IAP proteins inhibit caspase activity, whereas Smac/Diablo antagonizes IAP. XIAP, a ubiquitous IAP, can inhibit both caspase-9, the initiator caspase of the mitochondrial apoptotic pathway, and the downstream effector caspases, caspase-3 and caspase-7. Smac neutralizes XIAP inhibition of caspase-9 by competing for binding of the BIR3 domain of XIAP with caspase-9, whereas how Smac liberates effector caspases from XIAP inhibition is not clear. It is generally believed that binding of Smac with IAP generates a steric hindrance that prevents XIAP from inhibiting effector caspases, and therefore small molecule mimics of Smac are not able to reverse inhibition of the effector caspases. Surprisingly, we show here that binding of a dimeric Smac N-terminal peptide with the BIR2 domain of XIAP effectively antagonizes inhibition of caspase-3 by XIAP. Further, we defined the dynamic and cooperative interaction of Smac with XIAP: binding of Smac with the BIR3 domain anchors the subsequent binding of Smac with the BIR2 domain, which in turn attenuates the caspase-3 inhibitory function of XIAP. We also show that XIAP homotrimerizes via its C-terminal Ring domain, making its inhibitory activity toward caspase-3 more susceptible to Smac

SEIPIN Regulates Lipid Droplet Expansion and Adipocyte Development by Modulating the Activity of Glycerol-3-phosphate Acyltransferase

Berardinelli-Seip congenital lipodystrophy 2 (BSCL2) is caused by loss-of-function mutations in SEIPIN, a protein implicated in both adipogenesis and lipid droplet expansion but whose molecular function remains obscure. Here, we identify physical and functional interactions between SEIPIN and microsomal isoforms of glycerol-3-phosphate acyltransferase (GPAT) in multiple organisms. Compared to controls, GPAT activity was elevated in SEIPIN-deficient cells and tissues and GPAT kinetic values were altered. Increased GPAT activity appears to underpin the block in adipogenesis and abnormal lipid droplet morphology associated with SEIPIN loss. Overexpression of Gpat3 blocked adipogenesis, and Gpat3 knockdown in SEIPIN-deficient preadipocytes partially restored differentiation. GPAT overexpression in yeast, preadipocytes, and fly salivary glands also formed supersized lipid droplets. Finally, pharmacological inhibition of GPAT in Seipin-/- mouse preadipocytes partially restored adipogenesis. These data identify SEIPIN as an evolutionarily conserved regulator of microsomal GPAT and suggest that GPAT inhibitors might be useful for the treatment of human BSCL2 patients