EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

<p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

Towards sustainability: An assessment of an urbanisation bubble in China using a hierarchical - stochastic multicriteria acceptability analysis - Choquet integral method

Urbanisation bubbles have become an increasingly serious problem. Attention has been paid to the speed of urbanisation; however, the issue of quality has been neglected, particularly in the case of China. Therefore, the aim of this research is to evaluate China’s urbanisation bubbles by employing a hierarchical - stochastic multicriteria acceptability analysis (SMAA) - Choquet integral method. In order to highlight regional disparities, we measure the urbanisation bubbles at a provincial level. Our study aggregates the urbanisation bubble indices using the Choquet integral preference model, and considers the interactions between various indicators. Furthermore, robust ordinal regression and SMAA are applied to resolve the robustness issues associated with the entire set of weights assigned to the urbanisation bubble composite indicator. In addition, by employing a multiple criteria hierarchy process, the study aggregates urbanisation bubble indices not only at the comprehensive level, but also at the intermediate levels of the hierarchy. Our findings suggest that the ranking of urbanisation bubbles is positively related to the level of regional development. This study contributes to the evaluation of regional urbanisation and sustainable development

Existence of Three Positive Solutions for m-Point Discrete Boundary Value Problems with p-Laplacian

We consider the multi-point discrete boundary value problem with one-dimensional p-Laplacian operator Δ(ϕp(Δu(t−1))+q(t)f(t,u(t),Δu(t))=0, t∈{1,…,n−1} subject to the boundary conditions: u(0)=0, u(n)=∑i=1m−2aiu(ξi), where ϕp(s)=|s|p−2s,p>1,ξi∈{2,…,n−2} with 1<ξ1<⋯<ξm−2<n−1 and ai∈(0,1),0<∑i=1m−2ai<1. Using a new fixed point theorem due to Avery and Peterson, we study the existence of at least three positive solutions to the above boundary value problem

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system-0

O analyze previously published data. The sample information is automatically populated in the project based on the subset information stored in GEO GDS records. (B) Selecting samples to start new Express Analysis. While in most cases, default analysis methods and parameters can be used directly due to our built-in logics, experienced users have options to select methods and enter specific analysis parameters. Once the analysis is started, a pop-up window will appear showing currently running jobs. On the pop-up window, users can stop running jobs, remove failed jobs, or review finished jobs. In addition, users do not have to wait for results; instead, they can bookmark the page and come back later to review the results. (C) Example execution results from a run of Express Analysis with data shown in (B). The resulting files, including executed scripts and execution logs, are classified, listed, hyper-linked, and compressed in one file for easy downloading.<p><b>Copyright information:</b></p><p>Taken from "EzArray: A web-based highly automated Affymetrix expression array data management and analysis system"</p><p>http://www.biomedcentral.com/1471-2105/9/46</p><p>BMC Bioinformatics 2008;9():46-46.</p><p>Published online 24 Jan 2008</p><p>PMCID:PMC2265266.</p><p></p

Construction of the metabolic reprogramming-associated gene signature for clear cell renal cell carcinoma prognosis prediction

Abstract Background Metabolism reprogramming is a hallmark that associates tumor growth, metastasis, progressive, and poor prognosis. However, the metabolism-related molecular patterns and mechanism in clear cell renal cell carcinoma (ccRCC) remain unclear. Herein, the purpose of this study was to identify metabolism-related molecular pattern and to investigate the characteristics and prognostic values of the metabolism-related clustering. Methods We comprehensively analyzed the differentially expressed genes (DEGs), and metabolism-related genes (MAGs) in ccRCC based on the TCGA database. Consensus clustering was used to construct a metabolism-related molecular pattern. Then, the biological function, molecular characteristics, Estimate/immune/stomal scores, immune cell infiltration, response to immunotherapy, and chemotherapy were analyzed. We also identified the DEGs between subclusters and constructed a poor signature and risk model based on LASSO regression cox analysis and univariable and multivariable cox regression analyses. Then, a predictive nomogram was constructed and validated by calibration curves. Results A total of 1942 DEGs (1004 upregulated and 838 downregulated) between ccRCC tumor and normal samples were identified, and 254 MRGs were screened out from those DEGs. Then, 526 ccRCC patients were divided into two subclusters. The 7 metabolism-related pathways enriched in cluster 2. And cluster 2 with high Estimate/immune/stomal scores and poor survival. While, cluster 1 with higher immune cell infiltrating, expression of the immune checkpoint, IFN, HLA, immune activation-related genes, response to anti-CTLA4 treatment, and chemotherapy. Moreover, we identified 295 DEGs between two metabolism-related subclusters and constructed a 15-gene signature and 9 risk factors. Then, a risk score was calculated and the patients into high- and low-risk groups in TCGA-KIRC and E-MTAB-1980 datasets. And the prediction viability of the risk score was validated by ROC curves. Finally, the clinicopathological characteristics (age and stage), risk score, and molecular clustering, were identified as independent prognostic variables, and were used to construct a nomogram for 1-, 3-, 5-year overall survival predicting. The calibration curves were used to verify the performance of the predicted ability of the nomogram. Conclusion Our finding identified two metabolism-related molecular subclusters for ccRCC, which facilitates the estimation of response to immunotherapy and chemotherapy, and prognosis after treatment

Antifungal Effects of Seven Biological Fungicides Against the Pathogen Causing Stem Rot Disease in Passion Fruits

【Objective】In order to screen safe and effective fungicides to provide guidance for passion fruit production, seven biological fungicides were used as materials to study their control effects on the pathogen causing stem rot disease in passion fruits.【Method】Seven botanical and microbiological fungicides were used to determine their toxicity effects on the pathogen causing stem rot disease in passion fruits by mycelium growth rate method, the effects of fungicides on mycelium growth and spore morphology were observed, and their control effects were tested by in vivo inoculation method.【Result】All the selected fungicides showed inhibition effects on mycelium growth but had different effects on spore growth and morphology. Based on the indoor toxicity test results, among the botanical fungicides, Jinggangmycin showed the best inhibition effect with an EC50 of 7.79 mg/L, followed by Chunleimycin, ethylallicin and matrine, with the EC50 of 26.35 mg/L, 28.65 mg/L and 339.13 mg/L, respectively. Polyxins showed the lowest effect with an EC50 of 1 150.29 mg/L. Microbiological fungicide of Bacillus subtilis showed better effect than Trichoderma harzianum, with an EC50 of 3.2×106 CFU/g. The four screened fungicides of Jinggangmycin, Chunleimycin, ethylallicin and B. subtilis showed antifungal effects on different strains of fusarium pathogen. The in vivo inoculation test and field test showed that Jinggangmycin and B. subtilis had remarkable control effects on the pathogen causing stem rot disease in passion fruits, with in vivo inoculation control efficacy of 58.8% and 70.6%, respectively, and field control efficacy of 53.7% and 61.3%, respectively.【Conclusion】Two biological fungicides of B. subtilis and Jinggangmycin were screened out for their optimal control effects on the stem rot disease in passion fruits. It can provide alternatives or effective supplements for chemical fungicides for the control of stem rot disease, which could be promoted and applied

A Functional Study Identifying Critical Residues Involving Metal Transport Activity and Selectivity in Natural Resistance-Associated Macrophage Protein 3 in Arabidopsis thaliana

Arabidopsis thaliana natural resistance-associated macrophage protein 3 (AtNRAMP3) is involved in the transport of cadmium (Cd), iron (Fe), and manganese (Mn). Here, we present a structure-function analysis of AtNRAMP3 based on site-directed mutagenesis and metal toxicity growth assays involving yeast mutants, combined with three-dimensional (3D) structure modeling based on the crystal structure of the Eremococcus coleocola NRAMP family transporter, EcoDMT. We demonstrated that two conservative sites, D72 and N75, are essential for the transport activity. The M248A mutation resulted in a decrease in Cd sensitivity, while maintaining Mn transport. The mutation involving G61 caused a significant impairment of Fe and Mn transport, thereby indicating the importance of the conserved residue for proper protein function. The mutation involving G171 disrupted Fe transport activity but not that of Mn and Cd, suggesting that G171 is essential to metal binding and selectivity. Two residues, E194 and R262, may play an important role in stabilizing outward-facing conformation, which is essential for transport activity. Deletion assays indicated that the N-terminus is necessary for the function of AtNRAMP3. The findings of the present study revealed the structure-function relationship of AtNRAMP3 and metal transport activity and selectivity, which may possibly be applied to other plant NRAMP proteins

Gear Mapping Technology Based on Differential Envelope Principle

It is proposed that the complex molding process and the scanning process should be unified through the differential envelope principle. After scanning the surface of the part with the contact sensor, the contour coordinates of the measured surface are calculated by the trajectory of the center of the ball, and the contour data of the complex linear surface is extracted. Then, the intelligent analysis and calculation of precision generating surface parameters and quantitative adjustment are carried out, and the exact reverse method of the special line parts with characteristic parameters is studied. There is only micron scale difference between the reverse result and the nominal value. This technology is applied to the closed-loop manufacturing process of gear parts, which reduces the dependence on the artificial experience when the machining parameters of the cylindrical gear processing equipment is adjusted and provides an effective solution for the digital and intelligent manufacturing of the parts