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The Journal of Maternal-fetal &... Oct 2012Birth defects are very common, affecting two to three infants in every 100 births, and often represent a diagnostic and management challenge. The birth of a child with... (Review)
Review
BACKGROUND
Birth defects are very common, affecting two to three infants in every 100 births, and often represent a diagnostic and management challenge. The birth of a child with multiple malformations is the beginning of a complex diagnostic process, where the primary purpose is to determine a precise nosological definition. An accurate diagnosis is a key prerequisite in providing a care plan, a prognosis and genetic counselling. The poor specificity of birth defects, the aetiology and course of which can vary despite similar phenotypic patterns, often makes the diagnostic path problematic. The advent and application of high-resolution chromosomal microarray, encompassing array-based comparative genome hybridization and single-nucleotide polymorphism arrays, has led to the detection of genomic copy-number abnormalities in patients affected by multiple congenital anomalies, dysmorphisms, developmental delay and mental retardation, but who have a normal karyotype.
AIM
We discuss current guidelines and recommendations for chromosomal microarray use and how its application can help clinicians make accurate diagnoses in order to appropriately manage and treat affected newborns.
CONCLUSIONS
Current guidelines strongly support the application of chromosomal microarray analysis as a first-tier cytogenetic diagnostic test alternative to karyotyping for patients with multiple congenital anomalies, or developmental delay, intellectual disability and autism spectrum disorders.
Topics: Algorithms; Chromosome Aberrations; Comparative Genomic Hybridization; Congenital Abnormalities; Diagnostic Techniques and Procedures; Humans; Infant, Newborn; Karyotyping; Microarray Analysis; Predictive Value of Tests
PubMed: 22958042
DOI: 10.3109/14767058.2012.715004 -
Methods in Molecular Biology (Clifton,... 2011Bioinformatics has become an increasingly important tool for molecular biologists, especially for the analysis of microarray data. Microarrays can produce vast amounts...
Bioinformatics has become an increasingly important tool for molecular biologists, especially for the analysis of microarray data. Microarrays can produce vast amounts of information requiring a series of consecutive analyses to render the data interpretable. The direct output of microarrays cannot be directly interpreted to show differences in settings, conditions of samples, or time points. To make microarray experiments interpretable, it is necessary that a series of algorithms and approaches be applied. After normalization of generated data, which is necessary to make a comparison feasible, significance analysis, clustering of samples and biological compounds of interest and visualization are generally performed. This chapter will focus on providing a basic understanding of the generally approaches and algorithms currently employed in microarray bioinformatics.
Topics: Algorithms; Cluster Analysis; Computational Biology; Microarray Analysis
PubMed: 20967638
DOI: 10.1007/978-1-59745-551-0_18 -
Veterinary Pathology Jul 2005Immunohistochemistry is an integral technique in many veterinary laboratories for diagnostic and research purposes. In the last decade, the ability to detect antigens... (Review)
Review
Immunohistochemistry is an integral technique in many veterinary laboratories for diagnostic and research purposes. In the last decade, the ability to detect antigens (Ags) in tissue sections has improved dramatically, mainly by countering the deleterious effects of formaldehyde with antigen retrieval (AR) and increasing sensitivity of the detection systems. In this review, I address these topics and provide an overview of technical aspects of immunohistochemistry, including those related to antibodies (Abs) and Ags, fixation, AR, detection methods, background, and troubleshooting. Microarray technology and the use of rabbit monoclonal Abs in immunohistochemistry are also discussed.
Topics: Alcohols; Antibodies; Antigens; Fixatives; Formaldehyde; Immunoglobulins; Immunohistochemistry; Microarray Analysis; Proteins
PubMed: 16006601
DOI: 10.1354/vp.42-4-405 -
Reproduction (Cambridge, England) Dec 2010The rise of the 'omics' technologies started nearly a decade ago and, among them, transcriptomics has been used successfully to contrast gene expression in mammalian... (Review)
Review
The rise of the 'omics' technologies started nearly a decade ago and, among them, transcriptomics has been used successfully to contrast gene expression in mammalian oocytes and early embryos. The scarcity of biological material that early developmental stages provide is the prime reason why the field of transcriptomics is becoming more and more popular with reproductive biologists. The potential to amplify scarce mRNA samples and generate the necessary amounts of starting material enables the relative measurement of RNA abundance of thousands of candidates simultaneously. So far, microarrays have been the most commonly used high-throughput method in this field. Microarray platforms can be found in a wide variety of formats, from cDNA collections to long or short oligo probe sets. These platforms generate large amounts of data that require the integration of comparative RNA abundance values in the physiological context of early development for their full benefit to be appreciated. Unfortunately, significant discrepancies between datasets suggest that direct comparison between studies is difficult and often not possible. We have investigated the sample-handling steps leading to the generation of microarray data produced from prehatching embryo samples and have identified key steps that significantly impact the downstream results. This review provides a discussion on the best methods for the preparation of samples from early embryos for microarray analysis and focuses on the challenges that impede dataset comparisons from different platforms and the reasons why methodological benchmarking performed using somatic cells may not apply to the atypical nature of prehatching development.
Topics: Animals; Blastocyst; Embryo, Mammalian; Gene Expression Profiling; Gene Expression Regulation, Developmental; Humans; Microarray Analysis; Models, Biological; Oocytes
PubMed: 20833752
DOI: 10.1530/REP-10-0191 -
Advances in Biochemical... 2024Microarrays are widely utilized in bioanalysis. Electrochemical biosensing techniques are often applied in microarray-based assays because of their simplicity, low cost,... (Review)
Review
Microarrays are widely utilized in bioanalysis. Electrochemical biosensing techniques are often applied in microarray-based assays because of their simplicity, low cost, and high sensitivity. In such systems, the electrodes and sensing elements are arranged in arrays, and the target analytes are detected electrochemically. These sensors can be utilized for high-throughput bioanalysis and the electrochemical imaging of biosamples, including proteins, oligonucleotides, and cells. In this chapter, we summarize recent progress on these topics. We categorize electrochemical biosensing techniques for array detection into four groups: scanning electrochemical microscopy, electrode arrays, electrochemiluminescence, and bipolar electrodes. For each technique, we summarize the key principles and discuss the advantages, disadvantages, and bioanalysis applications. Finally, we present conclusions and perspectives about future directions in this field.
Topics: Biosensing Techniques; Electrochemical Techniques; Microarray Analysis; Electrodes; Humans
PubMed: 37306698
DOI: 10.1007/10_2023_229 -
Cold Spring Harbor Protocols Mar 2017Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple...
Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple experiments spanning a variety of cell types, treatments, or environmental conditions. Expression profiling is accomplished by assaying mRNA levels with microarrays or next-generation sequencing technologies (RNA-seq). This introduction describes normalization and analysis of data generated from microarray or RNA-seq experiments.
Topics: Computational Biology; Gene Expression Profiling; Microarray Analysis; Sequence Analysis, RNA
PubMed: 27574194
DOI: 10.1101/pdb.top093104 -
Methods in Molecular Biology (Clifton,... 2012The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational...
The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).
Topics: Algorithms; Biostatistics; Computational Biology; Gene Expression Profiling; Genomics; Humans; Microarray Analysis; Oligonucleotide Array Sequence Analysis; Software
PubMed: 22081356
DOI: 10.1007/978-1-60327-216-2_22 -
Methods in Molecular Biology (Clifton,... 2007Microarray analysis results in the gathering of massive amounts of information concerning gene expression profiles of different cells and experimental conditions.... (Review)
Review
Microarray analysis results in the gathering of massive amounts of information concerning gene expression profiles of different cells and experimental conditions. Analyzing these data can often be a quagmire, with endless discussion as to what the appropriate statistical analyses for any given experiment might be. As a result many different methods of data analysis have evolved, the basics of which are outlined in this chapter.
Topics: Cluster Analysis; Data Interpretation, Statistical; Databases, Genetic; Forecasting; Gene Expression Profiling; Humans; Microarray Analysis; Molecular Biology
PubMed: 17634607
DOI: 10.1007/978-1-59745-390-5_1 -
Combinatorial Chemistry & High... Jun 2006Over the last years microarray technology has become one of the principal platform technologies for the high-throughput analysis of biological systems. Starting with the... (Review)
Review
Over the last years microarray technology has become one of the principal platform technologies for the high-throughput analysis of biological systems. Starting with the construction of first DNA microarrays in the 1990s, microarray technology has flourished in the last years and many different new formats have been developed. Peptide and protein microarrays are now applied for the elucidation of interaction partners, modification sites and enzyme substrates. Antibody microarrays are envisaged to be of high importance for the high-throughput determination of protein abundances in translational profiling approaches. First cell microarrays have been constructed to transform microarray technology from an in vitro technology to an in vivo functional analysis tool. All of these approaches share a common prerequisite: the solid support on which they are generated. The demands on this solid support are thereby as manifold as the applications themselves. This review is aimed to display the recent developments in surface chemistry and derivatization, and to summarize the latest developments in the different application areas of microarray technology.
Topics: Antibodies, Monoclonal; Antibody Specificity; Combinatorial Chemistry Techniques; Drug Evaluation, Preclinical; Microarray Analysis; Oligonucleotide Array Sequence Analysis; Protein Array Analysis; Tissue Array Analysis; Transfection
PubMed: 16787150
DOI: 10.2174/138620706777452429 -
Mikrochimica Acta Jun 2023High-throughput screening platforms are fundamental for the rapid and efficient processing of large amounts of experimental data. Parallelization and miniaturization of... (Review)
Review
High-throughput screening platforms are fundamental for the rapid and efficient processing of large amounts of experimental data. Parallelization and miniaturization of experiments are important for improving their cost-effectiveness. The development of miniaturized high-throughput screening platforms is essential in the fields of biotechnology, medicine, and pharmacology. Currently, most laboratories use 96- or 384-well microtiter plates for screening; however, they have disadvantages, such as high reagent and cell consumption, low throughput, and inability to avoid cross-contamination, which need to be further optimized. Droplet microarrays, as novel screening platforms, can effectively avoid these shortcomings. Here, the preparation method of the droplet microarray, method of adding compounds in parallel, and means to read the results are briefly described. Next, the latest research on droplet microarray platforms in biomedicine is presented, including their application in high-throughput culture, cell screening, high-throughput nucleic acid screening, drug development, and individualized medicine. Finally, the challenges and future trends in droplet microarray technology are summarized.
Topics: High-Throughput Screening Assays; Drug Evaluation, Preclinical; Microarray Analysis
PubMed: 37318602
DOI: 10.1007/s00604-023-05833-9