Search results for: spatial gene
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3757

Search results for: spatial gene

3697 Evaluation of Promoter Hypermethylation in Tissue and Blood of Non-Small Cell Lung Cancer Patients and Association with Survival

Authors: Ashraf Ali, Kriti Upadhyay, Puja Sohal, Anant Mohan, Randeep Guleria

Abstract:

Background: Gene silencing by aberrant promoter hypermethylation is common in lung cancer and is an initiating event in its development. Aim: To evaluate the gene promoter hypermethylation frequency in serum and tissue of lung cancer patients. Method: 95 newly diagnosed untreated advance stage lung cancer patients and 50 cancer free matched controls were studied. Bisulfite modification of tissue and serum DNA was done; modified DNA was used as a template for methylation-specific PCR analysis. Survival was assessed for one year. Results: Of 95 patients, 82% were non-small cell lung cancer (34% squamous cell carcinoma, 34% non-small cell lung cancer and 14% adenocarcinoma) and 18% were small cell lung cancer. Biopsy revealed that tissue of 89% and 75% of lung cancer patients and 85% and 52% of controls had promoter hypermethylated for MGMT (p=0.35) and p16(p<0.001) gene, respectively. In serum, 33% and 49% of lung cancer patients and 28% and 43% controls were positive for MGMT and p16 gene. No significant correlation was found between survival and clinico-pathological parameters. Conclusion: High gene promoter methylation frequency of p16 gene in tissue biopsy may be linked with early stages of carcinogenesis. Appropriate follow-up is required for confirmation of this finding.

Keywords: lung cancer, MS- PCR, methylation, molecular biology

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3696 Transcriptomic Response of Calmodulin Encoding Gene (CaM) in Pesticide Utilizing Talaromyces Fungal Strains

Authors: M. D. Asemoloye, S. G. Jonathan, A. Rafiq, O. J. Olawuyi, D. O. Adejoye

Abstract:

Calmodulin is one of the intracellular calcium proteins that regulates large spectrum of enzymes and cellular functions including metabolism of cyclic nucleotides and glycogen. The potentials of calmodulin gene in fungi necessitates their genetic response and their strong cassette of enzyme secretions for pesticide degradation. Therefore, this study was carried out to investigate the ‘Transcriptomic’ response of calmodulin encoding genes in Talaromyces fungi in response to 2, 2-dichlorovinyl dimethyl phosphate (DDVP or Dichlorvos) an organophosphate pesticide and γ-Hexachlorocyclohexane (Lindane) an organochlorine pesticide. Fungi strains isolated from rhizosphere from grasses rhizosphere in pesticide polluted sites were subjected to percentage incidence test. Two most frequent fungi were further characterized using ITS gene amplification (ITS1 and ITS4 combinations), they were thereafter subjected to In-vitro DDVP and lindane tolerance tests at different concentrations. They were also screened for presence and expression of calmodulin gene (caM) using RT-PCR technique. The two Talaromyces strains had the highest incidence of 50-72% in pesticide polluted site, they were both identified as Talaromyces astroroseus asemoG and Talaromyces purpurogenum asemoN submitted in NCBI gene-bank with accession numbers KY488464 and KY488468 respectively. T. astroroseus KY488464 tolerated DDVP (1.23±0.023 cm) and lindane (1.11±0.018 cm) at 25 % concentration while T. purpurogenum KY488468 tolerated DDVP (1.33±0.061 cm) and lindane (1.54±0.077 cm) at this concentration. Calmodulin gene was detected in both strains, but RT-PCR expression of caM gene revealed at 900-1000 bp showed an under-expression of caM in T. astrorosues KY488464 but overexpressed in T. purpurogenum KY488464. Thus, the calmodulin gene response of these fungal strains to both pesticides could be considered in monitoring the potentials of fungal strains to pesticide tolerance and bioremediation of pesticide in polluted soil.

Keywords: Calmodulin gene, pesticide, RT-PCR, talaromyces, tolerance

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3695 The Instablity of TetM Gene Encode Tetracycline Resistance Gene in Lactobacillus casei FNCC 0090

Authors: Sarah Devi Silvian, Hanna Shobrina Iqomatul Haq, Fara Cholidatun Nabila, Agustin Krisna Wardani

Abstract:

Bacteria ability to survive in antibiotic is controlled by the presence of gene that encodes the antibiotic resistance protein. The instability of the antibiotic resistance gene can be observed by exposing the bacteria under the lethal dose of antibiotic. Low concentration of antibiotic can induce mutation, which may take a role in bacterial adaptation through the antibiotic concentration. Lactobacillus casei FNCC 0090 is one of the probiotic bacteria that has an ability to survive in tetracycline by expressing the tetM gene. The aims of this study are to observe the possibilities of mutation happened in L.casei FNCC 0090 by exposing in sub-lethal dose of tetracycline and also observing the instability of the tetM gene by comparing the sequence between the wild type and mutant. L.casei FNCC 0090 has a lethal dose in 60 µg/ml, low concentration is applied to induce the mutation, the range from 10 µg/ml, 15 µg/ml, 30 µg/ml, 45 µg/ml, and 50 µg/ml. L.casei FNCC 0090 is exposed to the low concentration from lowest to the highest concentration to induce the adaptation. Plasmid is isolated from the highest concentration culture which is 50 µg/ml by using modified alkali lysis method with the addition of lysozyme. The tetM gene is isolated by using PCR (Polymerase Chain Reaction) method, then PCR amplicon is purified and sequenced. Sequencing is done on both samples, wild type and mutant. Both sequences are compared and the mutations can be traced in the presence of nucleotides changes. The changing of the nucleotides means that the tetM gene is instable.

Keywords: L. casei FNCC 0090, probiotic, tetM, tetracycline

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3694 Assessment of Spatial Development in Peri Urban Villages of Baramati

Authors: Rutuja Rajendra Ghadage

Abstract:

Villages surrounding the city undergo the process of peri urbanization, which transforms their original village character. These villages undergo fast and unplanned physical growth and development. Due to the expansion of urban activities, peri-urban villages are experiencing extensive changes. Focusing on the peri-urban villages of Baramati city in Maharashtra, India, this paper assesses the nature and extent of spatial development and identifies the factors contributing to the rapid development of eleven sample Peri-urban villages. After reviewing similar studies, four indicators are selected to assess the spatial development of peri-urban villages; 1) population, 2) road network, 3) land use landcover change, and 4) built-up distribution. The spatial development of peri-urban villages of Baramati is uneven as few villages are still expanding or growing while few villages have started intensifying. The main factor for this development is the presence of industries and educational institutions. They have affected spatial development directly as well as indirectly. In the future, most of the peri-urban villages of Baramati will be in the intensification phase, so if this happens in an unplanned manner, it will create stress on services and facilities.

Keywords: factors and indicators of spatial development, peri urban villages, peri urbanization, spatial development

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3693 Paper-Based Detection Using Synthetic Gene Circuits

Authors: Vanessa Funk, Steven Blum, Stephanie Cole, Jorge Maciel, Matthew Lux

Abstract:

Paper-based synthetic gene circuits offer a new paradigm for programmable, fieldable biodetection. We demonstrate that by freeze-drying gene circuits with in vitro expression machinery, we can use complimentary RNA sequences to trigger colorimetric changes upon rehydration. We have successfully utilized both green fluorescent protein and luciferase-based reporters for easy visualization purposes in solution. Through several efforts, we are aiming to use this new platform technology to address a variety of needs in portable detection by demonstrating several more expression and reporter systems for detection functions on paper. In addition to RNA-based biodetection, we are exploring the use of various mechanisms that cells use to respond to environmental conditions to move towards all-hazards detection. Examples include explosives, heavy metals for water quality, and toxic chemicals.

Keywords: cell-free lysates, detection, gene circuits, in vitro

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3692 A Local Tensor Clustering Algorithm to Annotate Uncharacterized Genes with Many Biological Networks

Authors: Paul Shize Li, Frank Alber

Abstract:

A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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3691 Induction of HIV-1 Resistance: The New Approaches Based on Gene Modification and Stem Cell Engineering

Authors: Alieh Farshbaf

Abstract:

Introduction: Current anti-retroviral drugs have some restrictions for treatment of HIV-1 infection. The efficacy of retroviral drugs is not same in different infected patients and the virus rebound from latent reservoirs after stopping them. Recently, the engineering of stem cells and gene therapy provide new approaches to eliminate some drug problems by induction of resistance to HIV-1. Literature review: Up to now, AIDS-restriction genes (ARGs) were suitable candidate for gene and cell therapies, such as cc-chemokine receptor-5 (CCR5). In this manner, CCR5 provide effective cure in Berlin and Boston patients by inducing of HIV-1 resistance with allogeneic stem cell transplantation. It is showed that Zinc Finger Nuclease (ZFN) could induce HIV-1 resistance in stem cells of infected patients by homologous recombination or non-end joining mechanism and eliminate virus loading after returning the modified cells. Then, gene modification by HIV restriction factors, as TRIM5, introduced another gene candidate for HIV by interfering in infection process. These gene modifications/editing provided by stem cell futures that improve treatment in refractory disease such as HIV-1. Conclusion: Although stem cell transplantation has some complications, but in compare to retro-viral drugs demonstrated effective cure by elimination of virus loading. On the other hand, gene therapy is cost-effective for an infected patient than retroviral drugs payment in a person life-long. The results of umbilical cord blood stem cell transplantation showed that gene and cell therapy will be applied easier than previous treatment of AIDS with high efficacy.

Keywords: stem cell, AIDS, gene modification, cell engineering

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3690 Mutations in the GJB2 Gene Are the Cause of an Important Number of Non-Syndromic Deafness Cases

Authors: Habib Onsori, Somayeh Akrami, Mohammad Rahmati

Abstract:

Deafness is the most common sensory disorder with the frequency of 1/1000 in many populations. Mutations in the GJB2 (CX26) gene at the DFNB1 locus on chromosome 13q12 are associated with congenital hearing loss. Approximately 80% of congenital hearing loss cases are recessively inherited and 15% dominantly inherited. Mutations of the GJB2 gene, encoding gap junction protein Connexin 26 (Cx26), are the most common cause of hereditary congenital hearing loss in many countries. This report presents two cases of different mutations from Iranian patients with bilateral hearing loss. DNA studies were performed for the GJB2 gene by PCR and sequencing methods. In one of them, direct sequencing of the gene showed a heterozygous T→C transition at nucleotide 604 resulting in a cysteine to arginine amino acid substitution at codon 202 (C202R) in the fourth extracellular domain (TM4) of the protein. The analyses indicate that the C202R mutation appeared de novo in the proband with a possible dominant effect (GenBank: KF 638275). In the other one, DNA sequencing revealed a compound heterozygous mutation (35delG, 363delC) in the Cx26 gene that is strongly associated with congenital non-syndromic hearing loss (NSHL). So screening the mutations for hearing loss individuals referring to genetics counseling centers before marriage and or pregnancy is recommended.

Keywords: CX26, deafness, GJB2, mutation

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3689 Robustness Conditions for the Establishment of Stationary Patterns of Drosophila Segmentation Gene Expression

Authors: Ekaterina M. Myasnikova, Andrey A. Makashov, Alexander V. Spirov

Abstract:

First manifestation of a segmentation pattern in the early Drosophila development is the formation of expression domains (along with the main embryo axis) of genes belonging to the trunk gene class. Highly variable expression of genes from gap family in early Drosophila embryo is strongly reduced by the start of gastrulation due to the gene cross-regulation. The dynamics of gene expression is described by a gene circuit model for a system of four gap genes. It is shown that for the formation of a steep and stationary border by the model it is necessary that there existed a nucleus (modeling point) in which the gene expression level is constant in time and hence is described by a stationary equation. All the rest genes expressed in this nucleus are in a dynamic equilibrium. The mechanism of border formation associated with the existence of a stationary nucleus is also confirmed by the experiment. An important advantage of this approach is that properties of the system in a stationary nucleus are described by algebraic equations and can be easily handled analytically. Thus we explicitly characterize the cross-regulation properties necessary for the robustness and formulate the conditions providing this effect through the properties of the initial input data. It is shown that our formally derived conditions are satisfied for the previously published model solutions.

Keywords: drosophila, gap genes, reaction-diffusion model, robustness

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3688 Nonparametric Quantile Regression for Multivariate Spatial Data

Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

Abstract:

Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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3687 Tactile Cues and Spatial Navigation in Mice

Authors: Rubaiyea Uddin

Abstract:

The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated 'reward' arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation.

Keywords: mice, radial arm maze, memory, spatial navigation, tactile cues, hippocampus, reward, sensory skills, Alzheimer’s, neurodegnerative disease

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3686 The Use of Geographically Weighted Regression for Deforestation Analysis: Case Study in Brazilian Cerrado

Authors: Ana Paula Camelo, Keila Sanches

Abstract:

The Geographically Weighted Regression (GWR) was proposed in geography literature to allow relationship in a regression model to vary over space. In Brazil, the agricultural exploitation of the Cerrado Biome is the main cause of deforestation. In this study, we propose a methodology using geostatistical methods to characterize the spatial dependence of deforestation in the Cerrado based on agricultural production indicators. Therefore, it was used the set of exploratory spatial data analysis tools (ESDA) and confirmatory analysis using GWR. It was made the calibration a non-spatial model, evaluation the nature of the regression curve, election of the variables by stepwise process and multicollinearity analysis. After the evaluation of the non-spatial model was processed the spatial-regression model, statistic evaluation of the intercept and verification of its effect on calibration. In an analysis of Spearman’s correlation the results between deforestation and livestock was +0.783 and with soybeans +0.405. The model presented R²=0.936 and showed a strong spatial dependence of agricultural activity of soybeans associated to maize and cotton crops. The GWR is a very effective tool presenting results closer to the reality of deforestation in the Cerrado when compared with other analysis.

Keywords: deforestation, geographically weighted regression, land use, spatial analysis

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3685 A Novel PfkB Gene Cloning and Characterization for Expression in Potato Plants

Authors: Arfan Ali, Idrees Ahmad Nasir

Abstract:

Potato (Solanum tuberosum) is an important cash crop and popular vegetable in Pakistan and throughout the world. Cold storage of potatoes accelerates the conversion of starch into reduced sugars (glucose and fructose). This process causes dry mass and bitter taste in the potatoes that are not acceptable to end consumers. In the current study, the phosphofructokinase B gene was cloned into the pET-30 vector for protein expression and the pCambia-1301 vector for plant expression. Amplification of a 930bp product from an E. coli strain determined the successful isolation of the phosphofructokinase B gene. Restriction digestion using NcoI and BglII along with the amplification of the 930bp product using gene specific primers confirmed the successful cloning of the PfkB gene in both vectors. The protein was expressed as a His-PfkB fusion protein. Western blot analysis confirmed the presence of the 35 Kda PfkB protein when hybridized with anti-His antibodies. The construct Fani-01 was evaluated transiently using a histochemical gus assay. The appearance of blue color in the agroinfiltrated area of potato leaves confirmed the successful expression of construct Fani-01. Further, the area displaying gus expression was evaluated for PfkB expression using ELISA. Moreover, PfkB gene expression evaluated through transient expression determined successful gene expression and highlighted its potential utilization for stable expression in potato to reduce sweetening due to long-term storage.

Keywords: potato, Solanum tuberosum, transformation, PfkB, anti-sweetening

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3684 Association of Xeroderma pigmentosum Group D Gene Polymorphism with Colorectal Cancer Risk in Kashmiri Population

Authors: Syed Sameer Aga, Saniya Nissar

Abstract:

The Xeroderma pigmentosum group D gene (XPD) plays a key role in nucleotide excision repair (NER) pathway of the damaged DNA. Genetic polymorphisms in the coding region of the XPD gene may alter DNA repair capacity of the protein and hence can modulate the risk of colorectal cancer (CRC) risk. The aim of the study was to determine the genetic association of XPD Lys751Gln polymorphism with the risk of colorectal cancer (CRC) development. 120 CRC patients and 160 normal controls were assessed for genotype frequencies of XPD Lys751Gln polymorphism using PCR-RFLP technique. We observed a significant association (p < 0.05) between the XPD Lys751Gln polymorphism and the risk of developing CRC (p < 0.05). Additionally, Gln/Gln genotype of the XPD gene doubled the risk for the development of CRC [p < 0.05; OR=2.25 95% CI (1.07-4.7)]. Our results suggest that there is a significant association between the XPD Lys751Gln polymorphism and the risk of CRC.

Keywords: colorectal cancer, polymorphism, RFLP, DNA Repair, NER, XPD

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3683 Identification of Two Novel Carbapenemase Gene Variants from a Carbapenem-Resistant Aeromonas Veronii Environmental Isolate

Authors: Rafael Estrada, Cristian Ruiz Rueda

Abstract:

Carbapenems are last-resort antibiotics used in clinical settings to treat antibiotic-resistant bacterial infections. Thus, the emergence and spread of resistance to carbapenems is a major public health concern. Here, we have studied a carbapenem-resistant Aeromonas veronii strain previously isolated from a water sample from Sam Simeon Creek (Hearst San Simeon State Park, CA). Analysis of this isolate using disk-diffusion, CarbaNP, eCIM and mCIM assays revealed that it was resistant to amoxicillin-clavulanic acid and all carbapenems tested and that this isolate produced a potentially novel carbapenemase of the Metallo-β-lactamase family. Whole genome sequencing analysis revealed that this A. veronii isolate carries a novel variant of the blacₚₕₐ class β-carbapenemase gene that was closely related to the blacₚₕₐ₇ gene of Aeromonas jandaei. This isolate also carried a novel variant of the blaₒₓₐ class D carbapenemase gene that was most closely related to the blaₒₓₐ-₉₁₂ gene found in other Aeromonas veronii isolates. Finally, we also identified a novel class C β-lactamase gene moderately related to the blaFₒₓ-₁₇ gene of Providencia stuartii and other blaFₒₓ variants identified in Klebsiella pneumoniae, Escherichia coli and other Enterobacteriaceae. Overall, our findings reveal that environmental isolates are an important reservoir of multiple carbapenemases and other β-lactamases of clinical significance.

Keywords: β-lactamases, carbapenem, antibiotic-resistant, aeromonas veronii

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3682 Data Mining Spatial: Unsupervised Classification of Geographic Data

Authors: Chahrazed Zouaoui

Abstract:

In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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3681 Multi-Scale Urban Spatial Evolution Analysis Based on Space Syntax: A Case Study in Modern Yangzhou, China

Authors: Dai Zhimei, Hua Chen

Abstract:

The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.

Keywords: block, space syntax and methodology, street, urban space, Yangzhou

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3680 Analysis of Expression Data Using Unsupervised Techniques

Authors: M. A. I Perera, C. R. Wijesinghe, A. R. Weerasinghe

Abstract:

his study was conducted to review and identify the unsupervised techniques that can be employed to analyze gene expression data in order to identify better subtypes of tumors. Identifying subtypes of cancer help in improving the efficacy and reducing the toxicity of the treatments by identifying clues to find target therapeutics. Process of gene expression data analysis described under three steps as preprocessing, clustering, and cluster validation. Feature selection is important since the genomic data are high dimensional with a large number of features compared to samples. Hierarchical clustering and K Means are often used in the analysis of gene expression data. There are several cluster validation techniques used in validating the clusters. Heatmaps are an effective external validation method that allows comparing the identified classes with clinical variables and visual analysis of the classes.

Keywords: cancer subtypes, gene expression data analysis, clustering, cluster validation

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3679 Spatial Differentiation Patterns and Influencing Mechanism of Urban Greening in China: Based on Data of 289 Cities

Authors: Fangzheng Li, Xiong Li

Abstract:

Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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3678 An Analysis on Clustering Based Gene Selection and Classification for Gene Expression Data

Authors: K. Sathishkumar, V. Thiagarasu

Abstract:

Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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3677 The Role of MAOA Gene in the Etiology of Autism Spectrum Disorder in Males

Authors: Jana Kisková, Dana Gabriková

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Monoamine oxidase A gene (MAOA) is suggested to be a candidate gene implicated in many neuropsychiatric disorders, including autism spectrum disorder (ASD). This meta-analytic review evaluates the relationship between ASD and MAOA markers such as 30 bp variable number tandem repeats in the promoter region (uVNTR) and single nucleotide polymorphisms (SNPs) by using findings from recently published studies. It seems that in Caucasian males, the risk of developing ASD increase with the presence of 4-repeat allele in the promoter region of MAOA gene whereas no differences were found between autistic patients and controls in Egyptian, West Bengal and Korean population. Some studies point to the importance specific haplotype groups of SNPs and interaction of MAOA with others genes (e.g. FOXP2 or SRY). The results of existing studies are insufficient and further research is needed.

Keywords: autism spectrum disorder, MAOA, uVNTR, single nucleotide polymorphism

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3676 Explore Urban Spatial Density with Boltzmann Statistical Distribution

Authors: Jianjia Wang, Tong Yu, Haoran Zhu, Kun Liu, Jinwei Hao

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The underlying pattern in the modern city is agglomeration. To some degree, the distribution of urban spatial density can be used to describe the status of this assemblage. There are three intrinsic characteristics to measure urban spatial density, namely, Floor Area Ratio (FAR), Building Coverage Ratio (BCR), and Average Storeys (AS). But the underlying mechanism that contributes to these quantities is still vague in the statistical urban study. In this paper, we explore the corresponding extrinsic factors related to spatial density. These factors can further provide the potential influence on the intrinsic quantities. Here, we take Shanghai Inner Ring Area and Manhattan in New York as examples to analyse the potential impacts on urban spatial density with six selected extrinsic elements. Ebery single factor presents the correlation to the spatial distribution, but the overall global impact of all is still implicit. To handle this issue, we attempt to develop the Boltzmann statistical model to explicitly explain the mechanism behind that. We derive a corresponding novel quantity, called capacity, to measure the global effects of all other extrinsic factors to the three intrinsic characteristics. The distribution of capacity presents a similar pattern to real measurements. This reveals the nonlinear influence on the multi-factor relations to the urban spatial density in agglomeration.

Keywords: urban spatial density, Boltzmann statistics, multi-factor correlation, spatial distribution

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3675 THRAP2 Gene Identified as a Candidate Susceptibility Gene of Thyroid Autoimmune Diseases Pedigree in Tunisian Population

Authors: Ghazi Chabchoub, Mouna Feki, Mohamed Abid, Hammadi Ayadi

Abstract:

Autoimmune thyroid diseases (AITDs), including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT), are inherited as complex traits. Genetic factors associated with AITDs have been tentatively identified by candidate gene and genome scanning approaches. We analysed three intragenic microsatellite markers in the thyroid hormone receptor associated protein 2 gene (THRAP2), mapped near D12S79 marker, which have a potential role in immune function and inflammation [THRAP2-1(TG)n, THRAP2-2 (AC)n and THRAP2-3 (AC)n]. Our study population concerned 12 patients affected with AITDs belonging to a multiplex Tunisian family with high prevalence of AITDs. Fluorescent genotyping was carried out on ABI 3100 sequencers (Applied Biosystems USA) with the use of GENESCAN for semi-automated fragment sizing and GENOTYPER peak-calling software. Statistical analysis was performed using the non parametric Lod score (NPL) by Merlin software. Merlin outputs non-parametric NPLall (Z) and LOD scores and their corresponding asymptotic P values. The analysis for three intragenic markers in the THRAP2 gene revealed strong evidence for linkage (NPL=3.68, P=0.00012). Our results suggested the possible role of THRAP2 gene in AITDs susceptibility in this family.

Keywords: autoimmunity, autoimmune disease, genetic, linkage analysis

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3674 Polymorphism in Myostatin Gene and Its Association with Growth Traits in Kurdi Sheep of Northern Khorasan

Authors: Masoud Alipanah, Sekineh Akbari, Gholamreza Dashab

Abstract:

Myostatin genes or factor 8 affecting on growth and making differentiation works (GDF8) as a moderator in the development of skeletal muscle inhibitor. If mutations occurs in the coding region of myostatin, alter its inhibitory role and the muscle growth is increased. In this study, blood samples were collected randomly from 60 Kurdish sheep in northern Khorasan and DNA extraction was performed using a modified salt. A fragment 337 bp from exon 3 myostatin gene and-specific primers by using a polymerase chain reaction (PCR) were amplified. In order to detect different forms of an allele at this locus HaeΙΙΙ restriction enzymes and PCR-RFLP analysis were used. Band patterns clarification was performed using agarose gel electrophoresis. The frequency of genotypes mm, Mm, and MM, were respectively detected, 0, 0.15 and 0.85. The allele frequency for alleles m and M, were respectively, 0.07 and 0.93. The statistical analyses indicated that m allele was significantly associated with body weight. The results of this study suggest that the Myostatin gene possibly is a candidate gene that affects growth traits in Kurdish sheep.

Keywords: GDF8 gene, Kurdi Sheep of Northern Khorasan, polymorphism, weight traits

Procedia PDF Downloads 316
3673 MHC Class II DRB1 Gene Polymorphism in Lori Sheep Breed

Authors: Shahram Nanekarani, Majid Goodarzi, Majid Khosravi

Abstract:

The present study aimed at analyzing of ovine major histocompatibility complex class II (Ovar II) DRB1 gene second exon in Lori Sheep breed. The MHC plays a central role in the control of disease resistance and immunological response. Genomic DNA from blood samples of 124 sheep was extracted and a 296 bp MHC exon 2 fragment was amplified using polymerase chain reaction. PCR products were characterized by the restriction fragment length polymorphism technique using Hin1I restriction enzyme. The PCRRFLP patterns showed three genotypes, AA, AB and BB with frequency of 0.282, 0.573 and 0.145, respectively. There was no significant (P > 0.05) deviation from Hardy–Weinberg equilibrium for this locus in this population. The results of the present study indicate that exon 2 of the Ovar-DRB1 gene is highly polymorphic in Lori sheep and could be considered as an important marker assisted selection, for improvement of immunity in sheep.

Keywords: MHC-DRB1 gene, polymorphism, PCR-RFLP, lori sheep

Procedia PDF Downloads 369
3672 Detection of Polymorphism of Growth Hormone Gene in Holstein Cattle

Authors: Emine Şahin, Murat Soner Balcıoğlu

Abstract:

The aim of this study was to determine the growth hormone (bGH) gene polymorphism in the Holstein cattle growing around Antalya in Turkey. In order to determine the bGH-AluI polymorphism, polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) method was performed. A 891 bp fragment of bGH was amplified and two types of alleles C and D for bGH were observed. In this study, the frequencies of C and D alleles were 0.8438 and 0.1562, respectively. The genotype frequencies for CC, CD and DD were 0.787, 0.191 and 0.022, respectively. According to the results of the chi-square test, a significant deviation from the Hardy-Weinberg equilibrium was not determined for the bGH locus in the population.

Keywords: Growth Hormone Gene, Holstein , Polymorphism, RFLP

Procedia PDF Downloads 341
3671 Fast Bayesian Inference of Multivariate Block-Nearest Neighbor Gaussian Process (NNGP) Models for Large Data

Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

Abstract:

Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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3670 The Impact of an Interactive E-Book on Mathematics Reading and Spatial Ability in Middle School Students

Authors: Abebayehu Yohannes, Hsiu-Ling Chen, Chiu-Chen Chang

Abstract:

Mathematics reading and spatial ability are important learning components in mathematics education. However, many students struggle to understand real-world problems and lack the spatial ability to form internal imagery. To cope with this problem, in this study, an interactive e-book was developed. The result indicated that both groups had a significant increase in the mathematics reading ability test, and a significant difference was observed in the overall mathematics reading score in favor of the experimental group. In addition, the interactive e-book learning mode had significant impacts on students’ spatial ability. It was also found that the richness of content with visual and interactive elements provided in the interactive e-book enhanced students’ satisfaction with the teaching material.

Keywords: interactive e-books, spatial ability, mathematics reading, satisfaction, three view

Procedia PDF Downloads 156
3669 Elucidation of the Sequential Transcriptional Activity in Escherichia coli Using Time-Series RNA-Seq Data

Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

Abstract:

Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

Procedia PDF Downloads 340
3668 Identification of Genes Regulating Differentiation and Stemness of Human Mesenchymal Stem Cells for Gene Therapy in Regenerative Medicine

Authors: Tong Ming Liu

Abstract:

Human mesenchymal stem cells (MSCs) represent the most used stem cells for clinical application, which have been used in over 1000 clinical trials to treat over 30 diseases due to multilineage differentiation potential, secretome and immunosuppression. Gene therapies of MSCs hold great promise in the treatment of many diseases due to enhanced MSC-based clinical outcomes. To identify genes for gene therapy of MSCs, by comparing gene expression profile before and after MSC differentiation following by functional screening, we have identified ZNF145 that regulated MSC differentiation. Forced expression of ZNF145 resulted in enhanced in vitro chondrogenesis of MSCs as an upstream factor of SOX9 and improved osteochondral repair upon implant into osteochondral defects in rodents. By comparing gene expression profile during differentiation of iPSCs toward MSCs, we also identified gene HOX regulating MSC stemness, which was much downregulated in late-passaged MSCs. Knockdown of this gene greatly compromised MSC stemness including abolished proliferation, decreased CFU-F, promoted senescence and reduced expression of cell surface antigens linked to the MSC phenotype. In addition, multi-linage differentiation was also greatly impaired. Notably, HOX overexpression resulted in improved multi-lineage differentiation. In the mechanism, HOX expression significantly deceased in late passage of MSCs compared with early passage of MSCs, correlating with MSC important genes. ChIP-seq data shown that HOX binds to genes related to MSC self-renewal and differentiation. Most importantly, most HOX binding sites are lost in late passage of MSCs. HOX exerts its effects by directing binding Twist1, one important gene of MSCs. The identification of the genes regulating MSC differentiation and stemness will provide and promising strategies for gene therapy of MSCs in regenerative medicine.

Keywords: mesenchymal stem cell, novel transcription factor, stemness, gene therapy, cartilage repair, signaling pathway

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