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11-SEPTEMBER-2008 13:54:10 - microarray Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. Example of an approximately 40,000 probe spotted oligo microarray with enlarged inset to show detail. For terminology, see glossary below A DNA microarray is a high-throughput technology used in molecular biology and in medicine. It consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, each containing picomoles of a specific DNA sequence. This can be a short section of a gene or other DNA element that are used as probes to hybridize a cDNA or cRNA sample called target under high-stringency conditions. Probe-target hybridization is usually detected and quantified by fluorescence-based detection of fluorophore-labeled targets to determine relative abundance of nucleic acid sequences in the target. In standard microarrays, the probes are attached to a solid surface by a covalent bond to a chemical matrix via epoxy-silane, amino-silane, lysine, polyacrylamide or others. The solid surface can be glass or a silicon chip, in which case they are commonly known as gene chip or colloquially Affy chip when an Affymetrix chip is used. Other microarray platforms, such as Illumina, use microscopic beads, instead of the large solid support. DNA arrays are different from other types of microarray only in that they either measure DNA or use DNA as part of its detection system. DNA microarrays can be used to measure changes in expression levels or to detect single nucleotide polymorphisms SNPs see Types of arrays section. Microarrays also differ in fabrication, workings, accuracy, efficiency, and cost see fabrication section. Additional factors for microarray experiments are the experimental design and the methods of analyzing the data see Bioinformatics section. For a detailed explanation of how a microarray experiment is done, see DNA microarray experiment. Contents 1 History 2 Uses and types 3 Fabrication 3.1 Spotted vs. oligonucleotide arrays 3.2 Two-channel vs. one-channel detection 4 Microarrays and bioinformatics 4.1 Experimental Design 4.2 Standardization 4.3 Statistical analysis 4.4 Relation between probe and gene 4.5 Data Warehousing 5 See also 6 References 7 Glossary 8 External links History Microarray technology evolved from Southern blotting, where fragmented DNA is attached to a substrate and then probed with a known gene or fragment. The use of a collection of distinct DNAs in arrays for expression profiling was first described in 1987, and the arrayed DNAs were used to identify genes whose expression is modulated by interferon.1 These early gene arrays were made by spotting cDNAs onto filter paper with a pin-spotting device. The use of miniaturized microarrays for gene expression profiling was first reported in 1995, 2 and a complete eukaryotic genome Saccharomyces cerevisiae on a microarray was published in 1997. 3 Uses and types Two Affymetrix chips Two Affymetrix chips Arrays of DNA can be spatially arranged, as in the commonly known gene chip also called genome chip, DNA chip or gene array, or can be specific DNA sequences labelled such that they can be independently identified in solution. The traditional solid-phase array is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon biochip. The affixed DNA segments are known as probes although some sources use different terms such as reporters. Thousands of them can be placed in known locations on a single DNA microarray. DNA microarrays can be used to detect DNA as in comparative genomic hybridization, or detect RNA most commonly as cDNA after reverse transcription that may or may not be translated into proteins. The process of measuring gene expression via cDNA is called expression analysis or expression profiling. Since an array can contain tens of thousands of probes, a microarray experiment can accomplish that many genetic tests in parallel. Therefore arrays have dramatically accelerated many types of investigation. Applications include: Technology or Application Synopsis Gene expression profiling In an mRNA or gene expression profiling experiment the expression levels of thousands of genes are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on gene expression. For example, microarray-based gene expression profiling can be used to identify genes whose expression is changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. 4 Comparative genomic hybridization Assessing genome content in different cells or closely related organisms. 5 6 Chromatin immunoprecipitation on Chip DNA sequences bound to a particular protein can be isolated by immunoprecipitating that protein ChIP, these fragments can be then hybridized to a microarray such as a tiling array allowing the determination of protein binding site occupancy throughout the genome. Example protein to immunoprecipitate are histone modifications H3K27me3, H3K4me2, H3K9me3, etc, Polycomb-group protein PRC2:Suz12, PRC1:YY1 and trithorax-group protein Ash1 to study the epigenetic landscape or RNA Polymerase II to study the transcription lanscape. SNP detection Identifying single nucleotide polymorphism among alleles within or between populations.7 Several applications of microarrays make use of SNP detection, including Genotyping, forensic analysis, measuring predisposition to disease, identifying drug-candidates, evaluating germline mutations in individuals or somatic mutations in cancers, assessing loss of heterozygosity, or genetic linkage analysis. Alternative splicing detection An 'exon junction array design uses probes specific to the expected or potential splice sites of predicted exons for a gene. It is of intermediate density, or coverage, to a typical gene expression array with 1-3 probes per gene and a genomic tiling array with hundreds or thousands of probes per gene. It is used to assay the expression of alternative splice forms of a gene. Tiling array Genome tiling arrays consist of overlapping probes designed to densely represent a genomic region of interest, sometimes as large as an entire human chromosome. The purpose is to empirically detect expression of transcripts or alternatively splice forms which may not have been previously known or predicted. Fabrication Microarrays can be manufactured in different ways, depending on the number of probes under examination, costs, customization requirements, and the type of scientific question being asked. Arrays may have as few as 10 probes to up to 2.1 million NimbleGen, Roche micron-scale probes from commercial vendors. Spotted vs. oligonucleotide arrays A DNA microarray being printed by a robot at the University of Delaware Play video A DNA microarray being printed by a robot at the University of Delaware Microarrays can be fabricated using a variety of technologies, including printing with fine-pointed pins onto glass slides, photolithography using pre-made masks, photolithography using dynamic micromirror devices, ink-jet printing, 8 or electrochemistry on microelectrode arrays. In spotted microarrays, the probes are oligonucleotides, cDNA or small fragments of PCR products that correspond to mRNAs. The probes are synthesized prior to deposition on the array surface and are then spotted onto glass. A common approach utilizes an array of fine pins or needles controlled by a robotic arm that is dipped into wells containing DNA probes and then depositing each probe at designated locations on the array surface. The resulting grid of probes represents the nucleic acid profiles of the prepared probes and is ready to receive complementary cDNA or cRNA targets derived from experimental or clinical samples. This technique is used by research scientists around the world to produce in-house printed microarrays from their own labs. These arrays may be easily customized for each experiment, because researchers can choose the probes and printing locations on the arrays, synthesize the probes in their own lab or collaborating facility, and spot the arrays. They can then generate their own labeled samples for hybridization, hybridize the samples to the array, and finally scan the arrays with their own equipment. This provides a relatively low-cost microarray that may be customized for each study, and avoids the costs of purchasing often more expensive commercial arrays that may represent vast numbers of genes that are not of interest to the investigator. Publications exist which indicate in-house spotted microarrays may not provide the same level of sensitivity compared to commercial oligonucleotide arrays, 9 possibly owing to the small batch sizes and reduced printing efficiencies when compared to industrial manufactures of oligo arrays. In oligonucleotide microarrays, the probes are short sequences designed to match parts of the sequence of known or predicted open reading frames. Although oligonucleotide probes are often used in spotted microarrays, the term oligonucleotide array most often refers to a specific technique of manufacturing. Oligonucleotide arrays are produced by printing short oligonucleotide sequences designed to represent a single gene or family of gene splice-variants by synthesizing this sequence directly onto the array surface instead of depositing intact sequences. Sequences may be longer 60-mer probes such as the Agilent design or shorter 25-mer probes produced by Affymetrix depending on the desired purpose; longer probes are more specific to individual target genes, shorter probes may be spotted in higher density across the array and are cheaper to manufacture. One technique used to produce oligonucleotide arrays include photolithographic synthesis Agilent and Affymetrix on a silica substrate where light and light-sensitive masking agents are used to build a sequence one nucleotide at a time across the entire array. 10 Each applicable probe is selectively unmasked prior to bathing the array in a solution of a single nucleotide, then a masking reaction takes place and the next set of probes are unmasked in preparation for a different nucleotide exposure. After many repetitions, the sequences of every probe become fully constructed. More recently, Maskless Array Synthesis from NimbleGen Systems has combined flexibility with large numbers of probes. 11 Two-channel vs. one-channel detection Diagram of typical dual-colour microarray experiment. Diagram of typical dual-colour microarray experiment. Two-color microarrays or two-channel microarrays are typically hybridized with cDNA prepared from two samples to be compared e.g. diseased tissue versus healthy tissue and that are labeled with two different fluorophores. 12 Fluorescent dyes commonly used for cDNA labelling include Cy3, which has a fluorescence emission wavelength of 570 nm corresponding to the green part of the light spectrum, and Cy5 with a fluorescence emission wavelength of 670 nm corresponding to the red part of the light spectrum. The two Cy-labelled cDNA samples are mixed and hybridized to a single microarray that is then scanned in a microarray scanner to visualize fluorescence of the two fluorophores after excitation with a laser beam of a defined wavelength. Relative intensities of each fluorophore may then be used in ratio-based analysis to identify up-regulated and down-regulated genes. 13 Oligonucleotide microarrays often contain control probes designed to hybridize with RNA spike-ins. The degree of hybridization between the spike-ins and the control probes is used to normalize the hybridization measurements for the target probes. Although absolute levels of gene expression may be determined in the two-color array, the relative differences in expression among different spots within a sample and between samples is the preferred method of data analysis for the two-color system. Examples of providers for such microarrays includes Agilent with their Dual-Mode platform, Eppendorf with their DualChip platform for fluorescence labeling, and TeleChem International with Arrayit. In single-channel microarrays or one-color microarrays, the arrays are designed to give estimations of the absolute levels of gene expression. Therefore the comparison of two conditions requires two separate single-dye hybridizations. As only a single dye is used, the data collected represent absolute values of gene expression. These may be compared to other genes within a sample or to reference normalizing probes used to calibrate data across the entire array and across multiple arrays. Three popular single-channel systems are the Affymetrix Gene Chip, the Applied Microarrays CodeLink arrays, and the Eppendorf DualChip Silverquant. One strength of the single-dye system lies in the fact that an aberrant sample cannot affect the raw data derived from other samples, because each array chip is exposed to only one sample as opposed to a two-color system in which a single low-quality sample may drastically impinge on overall data precision even if the other sample was of high quality. Another benefit is that data are more easily compared to arrays from different experiments; the absolute values of gene expression may be compared between studies conducted months or years apart. A drawback to the one-color system is that, when compared to the two-color system, twice as many microarrays are needed to compare samples within an experiment. Microarrays and bioinformatics Gene expression values from microarray experiments can be represented as heat maps to visualize the result of data analysis. Gene expression values from microarray experiments can be represented as heat maps to visualize the result of data analysis. For a detailed explanation of how a microarray experiment is done, see DNA microarray experiment. The advent of inexpensive microarray experiments created several specific bioinformatics challenges: the multiple levels of replication in experimental design Experimental Design the number of platforms and independent groups and data format Standardization the treatment of the data Statistical Analysis what exactly are we measuring Relation between probe and gene the sheer volume of data and the ability to share it Data Warehousing Experimental Design Due to the biological complexity of gene expression, the considerations of experimental design that are discussed in the expression profiling article are of critical importance if statistically and biologically valid conclusions are to be drawn from the data. There are three main elements to consider when designing a microarray experiment. First, replication of the biological samples is essential for drawing conclusions from the experiment. Second, technical replicates two RNA samples obtained from each experimental unit help to ensure precision and allow for testing differences within treatment groups. The technical replicates may be two independent RNA extractions or two aliquots of the same extraction. Third, spots of each cDNA clone or oligonucleotide are present as replicates at least duplicates on the microarray slide, to provide a measure of technical precision in each hybridization. It is critical that information about the sample preparation and handling is discussed, in order to help identify the independent units in the experiment and to avoid inflated estimates of statistical significance.14 Standardization Microarray data is difficult to exchange due to the lack of standardization in arrays. This presents an interoperability problem in bioinformatics. Various grass-roots open-source projects are trying to ease the exchange and analysis of data produced with non-proprietary chips: For example, the Minimum Information About a Microarray Experiment MIAME checklist helps define the level of detail that should exist and is being adopted by many journals as a requirement for the submission of papers incorporating microarray results. But MIAME does not describe the format for the information, so while many formats can support the MIAME requirements, as of 2007 no format permits verification of complete semantic compliance. The MicroArray Quality Control MAQC Project is being conducted by the US Food and Drug Administration FDA to develop standards and quality control metrics which will eventually allow the use of MicroArray data in drug discovery, clinical practice and regulatory decision-making. 15 The MicroArray and Gene Expression Data MGED group is working on the standardization of the representation of gene expression data and relevant annotations. Statistical analysis The analysis of DNA microarrays poses a large number of statistical problems, including the normalization of the data. There are several normalization methods in the published literature some of which are platform specific;citation needed as in many other cases where authorities disagree, a sound conservative approach is to directly compare different normalization methods to determine the effects of these different methods on the results obtained. This can be done, for example, by investigating the performance of various methods on data from spike-in experiments.citation needed Also, experimenters must account for multiple comparisons: even if the statistical P-value assigned to a gene indicates that it is extremely unlikely that differential expression of this gene was due to random rather than treatment effects, the very high number of genes on an array makes it likely that differential expression of some genes represent false positives or false negatives. Statistical methods tailored to microarray analyses have recently become available that assess statistical power based on the variation present in the data and the number of experimental replicates, and can help minimize type I and type II errors in the analyses.16 A basic difference between microarray data analysis and much traditional biomedical research is the dimensionality of the data. A large clinical study might collect 100 data items per patient for thousands of patients. A medium-size microarray study will obtain many thousands of numbers per sample for perhaps a hundred samples. Many analysis techniques treat each sample as a single point in a space with thousands of dimensions, then attempt by various techniques to reduce the dimensionality of the data to something humans can visualize. 17 Relation between probe and gene The relation between a probe and the mRNA that it is expected to detect is problematic. On the one hand, some mRNAs may cross-hybridize probes in the array that are supposed to detect another mRNA. On the other hand, probes that are designed to detect the mRNA of a particular gene may be relying on genomic EST information that is incorrectly associated with that gene. Data Warehousing Microarray data was found to be more useful when compared to other similar datasets. The sheer volume in bytes, specialized formats such as MIAME, and curation efforts associated with the datasets require specialized databases to store the data. For more information about specific Microarray Databases, see Microarray databases. See also Microfluidics or Lab-on-chip Cyanine dyes, such as Cy3 and Cy5, are commonly used fluorophores with microarrays Serial Analysis of Gene Expression Significance Analysis of Microarrays References ^ Kulesh DA, Clive DR, Zarlenga DS, Greene JJ 1987. Identification of interferon-modulated proliferation-related cDNA sequences. Proc Natl Acad Sci USA 84: 8453-8457. doi:10.1073/pnas.84.23.8453. PMID 2446323. ^ Schena M, Shalon D, Davis RW, Brown PO 1995. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270: 467-470. doi:10.1126/science.270.5235.467. PMID 7569999. ^ Lashkari DA, DeRisi JL, McCusker JH, Namath AF, Gentile C, Hwang SY, Brown PO, Davis RW 1997. Yeast microarrays for genome wide parallel genetic and gene expression analysis. Proc Natl Acad Sci USA 94: 13057-13062. doi:10.1073/pnas.94.24.13057. PMID 9371799. ^ Adomas A, Heller G, Olson A, Osborne J, Karlsson M, Nahalkova J, Van Zyl L, Sederoff R, Stenlid J, Finlay R, Asiegbu FO 2008. Comparative analysis of transcript abundance in Pinus sylvestris after challenge with a saprotrophic, pathogenic or mutualistic fungus. Tree Physiol. 28: 885-897. PMID 18381269. ^ Pollack JR, Perou CM, Alizadeh AA, Eisen MB, Pergamenschikov A, Williams CF, Jeffrey SS, Botstein D, Brown PO 1999. Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet 23: 41-46. doi:10.1038/14385. PMID 10471496. ^ Moran G, Stokes C, Thewes S, Hube B, Coleman DC, Sullivan D 2004. Comparative genomics using Candida albicans DNA microarrays reveals absence and divergence of virulence-associated genes in Candida dubliniensis. Microbiology 150: 3363-3382. doi:10.1099/mic.0.27221-0. PMID 15470115. ^ Hacia JG, Fan JB, Ryder O, Jin L, Edgemon K, Ghandour G, Mayer RA, Sun B, Hsie L, Robbins CM, Brody LC, Wang D, Lander ES, Lipshutz R, Fodor SP, Collins FS 1999. Determination of ancestral alleles for human single-nucleotide polymorphisms using high-density oligonucleotide arrays. Nat Genet 22: 164-167. doi:10.1038/9674. PMID 10369258. ^ Lausted C et al. 2004. POSaM: a fast, flexible, open-source, inkjet oligonucleotide synthesizer and microarrayer. Genome Biology 5: R58. doi:10.1186/gb-2004-5-8-r58. PMID 15287980. ^ Bammler T, Beyer RP, Bhattacharya S, Boorman GA, Boyles A, Bradford BU, Bumgarner RE, Bushel PR, Chaturvedi K, Choi D, Cunningham ML, Deng S, Dressman HK, Fannin RD, Farin FM, Freedman JH, Fry RC, Harper A, Humble MC, Hurban P, Kavanagh TJ, Kaufmann WK, Kerr KF, Jing L, Lapidus JA, Lasarev MR, Li J, Li YJ, Lobenhofer EK, Lu X, Malek RL, Milton S, Nagalla SR, O'malley JP, Palmer VS, Pattee P, Paules RS, Perou CM, Phillips K, Qin LX, Qiu Y, Quigley SD, Rodland M, Rusyn I, Samson LD, Schwartz DA, Shi Y, Shin JL, Sieber SO, Slifer S, Speer MC, Spencer PS, Sproles DI, Swenberg JA, Suk WA, Sullivan RC, Tian R, Tennant RW, Todd SA, Tucker CJ, Van Houten B, Weis BK, Xuan S, Zarbl H; Members of the Toxicogenomics Research Consortium. 2005. Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods 2: 351-356. doi:10.1038/nmeth0605-477a. PMID 15846362. ^ Pease AC, Solas D, Sullivan EJ, Cronin MT, Holmes CP, Fodor SP. 1994. Light-generated oligonucleotide arrays for rapid DNA sequence analysis. PNAS 91: 5022-5026. doi:10.1073/pnas.91.11.5022. PMID 8197176. ^ Nuwaysir EF, Huang W, Albert TJ, Singh J, Nuwaysir K, Pitas A, Richmond T, Gorski T, Berg JP, Ballin J, McCormick M, Norton J, Pollock T, Sumwalt T, Butcher L, Porter D, Molla M, Hall C, Blattner F, Sussman MR, Wallace RL, Cerrina F, Green RD. 2002. Gene expression analysis using oligonucleotide arrays produced by maskless photolithography. Genome Res 12: 1749-1755. doi:10.1101/gr.362402. PMID 12421762. ^ Shalon D, Smith SJ, Brown PO 1996. A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. Genome Res 6: 639-645. doi:10.1101/gr.6.7.639. PMID 8796352. ^ Tang T, François N, Glatigny A, Agier N, Mucchielli MH, Aggerbeck L, Delacroix H 2007. Expression ratio evaluation in two-colour microarray experiments is significantly improved by correcting image misalignment. Bioinformatics 23: 2686-2691. doi:10.1093/bioinformatics/btm399. PMID 17698492. ^ Churchill GA 2002. Fundamentals of experimental design for cDNA microarrays. Nature genetics suppliment 32: 490. doi:10.1038/ng1031. ^ NCTR Center for Toxicoinformatics - MAQC Project ^ Wei C, Li J, Bumgarner RE. 2004. Sample size for detecting differentially expressed genes in microarray experiments. BMC Genomics 5: 87. doi:10.1186/1471-2164-5-87. PMID 15533245. ^ Wouters L, Gõhlmann HW, Bijnens L, Kass SU, Molenberghs G, Lewi PJ 2003. Graphical exploration of gene expression data: a comparative study of three multivariate methods. Biometrics 59: 1131-1139. doi:10.1111/j.0006-341X.2003.00130.x. Glossary An Array or slide is a collection of features spatially arranged in a two dimensional grid, arranged in columns and rows. Block or subarray: a group of spots, typically made in one print round; several subarrays/blocks form an array. Case/control: an experimental design paradigm especially suited to the two-colour array system, in which a condition chosen as control such as healthy tissue or state is compared to an altered condition such as a diseased tissue or state. Channel: the fluorescence output recorded in the scanner for an individual fluorophore and can even be ultraviolet. Dye flip or Dye swap or Fluor reversal: reciprocal labelling of DNA targets with the two dyes to account for dye bias in experiments. Scanner: an instrument used to detect and quantify the intensity of fluorescence of spots on a microarray slide, by selectively exciting fluorophores with a laser and measuring the fluorescence with a filter optics photomultiplier system. Spot or feature: a small area on an array slide that contains picomoles of specific DNA samples. For other relevant terms see: Glossary of gene expression terms Protocol natural sciences External links Many important links can be found at the Open Directory Project Gene Expression at the Open Directory Project Micro Scale Products and Services for Biochemistry and Molecular Biology at the Open Directory Project Products and Services for Gene Expression at the Open Directory Project PLoS Biology Primer: Microarray Analysis Rundown of microarray technology CLASSIFI - Gene Ontology-based gene cluster classification resource Microarray data processing using Self-Organizing Maps tutorial: Part 1 Part 2 v d e Molecular Biology Central Dogma DNA Replication DNA, Transcription RNA - Translation protein gene regulation Epigenetic · genetic · post-transcriptional · post-translational regulation other key concepts mitosis · cell signalling · Post-transcriptional modification and Post-translational modification · Dry Lab/Wet lab · Development · History of molecular biology · genetic elements Promoter Pribnow box, TATA box · Operon gal operon, lac operon, trp operon · Terminator · Enhancer · Repressor lac repressor, trp repressor · Silencer · Histone methylation Techniques Cell culture · model organisms such as C57BL/6 mice · Nucleic acid methods · Protein methods High-throughput -omicsTechniques DNA microarray · Mass spectrometry · Lab-on-a-chip Linked Life science disciplines Cell Biology · Biochemistry · Computational Biology Glossary gene expression terms · Academic rank v d e Glass science topics Basics Glass definition · Is glass a liquid or a solid? · Glass-liquid transition · Glass transition temperature · Kauzmann paradox Glass formulation AgInSbTe · Antimony glass · Bioglass · Borophosphosilicate glass · Borosilicate glass · Ceramic glaze · Chalcogenide glass · Cobalt glass · Cranberry glass · Crown glass · Flint glass · Fluorosilicate glass · Fused quartz · GeSbTe · Gold ruby glass · Lead glass · Milk glass · Phosphosilicate glass · Photochromic lens glass · Silicate glass · Soda-lime glass · Sodium hexametaphosphate · Soluble glass · Ultra low expansion glass · Uranium glass · Vitreous enamel · ZBLAN Glass-ceramics Bioactive glass · CorningWare · Glass-ceramic-to-metal seals · Macor · Zerodur Glass preparation Annealing · Chemical vapor deposition · Glass batch calculation · Glass forming · Glass melting · Glass modeling · Ion implantation · Liquidus temperature · Sol-gel technique · Viscosity Optics Dispersion · Gradient index optics · Hydrogen darkening · Optical amplifier · Optical fiber · Optical lens design · Photochromic lens · Refraction Surface modification Anti-reflective coating · Chemically strengthened glass · Corrosion · Dealkalization · DNA microarray · Hydrogen darkening · Insulated glazing · Self-cleaning glass · Sol-gel technique · Toughened glass Diverse topics Diffusion · Glass-coated wire · Glass databases · Glass electrode · Glass fiber reinforced concrete · Glass ionomer cement · Glass microspheres · Glass history · Glass-reinforced plastic · Glass science institutes · Radioactive waste vitrification · Windshield Retrieved from http://en..org/wiki/DNA_microarray Categories: Molecular biology | Gene expression | Bioinformatics | Glass engineering and science | DNA | MicrotechnologyHidden categories: All articles with statements | Articles with statements since July 2008 | Articles containing video clips Views Article Discussion this page History Personal tools Log in / create account Navigation Main page Contents Featured content Current events Random article Search Go Search Interaction Community portal Recent changes Contact Donate to Help Toolbox What links here Related changes Upload file Special pages Printable version Permanent link Cite this page Languages العربية Deutsch Ελληνικά Español Français Italiano עברית Nederlands 日本語 Polski Português Svenska Tiếng Việt اردو 中文 This page was last modified on 10 September 2008, at 07:56
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