BACKGROUND: In a prospective study, we measured plasma markers of myocardial damage induced by radiofrequency catheter ablation (RFA) with the protein biochip microarray system. METHODS: A total of 32 consecutive patients undergoing RFA for atrioventricular nodal re-entry tachycardia (AVNRT), right atrial flutter (AFL) and atrial fibrillation (AF) were included in the study. Cardiac troponin I (cTnI), creatine kinase isoenzyme MB (CK-MB), heart-type fatty acid binding protein (hFABP) and glycogen phosphorylase BB (GPBB) were measured using biochip array technology at baseline and 24 h after the procedure. RESULTS: Values for all markers increased 24 h after RFA (cTnI: 0.92+/-0.49 microg/L vs. 0.33+/-0.06 microg/L, p<0.001; CK-MB: 3.79+/-2.04 microg/L vs. 1.85+/-0.55 microg/L, p<0.001; hFABP: 2.82+/-0.95 microg/L vs. 2.00+/-0.95 microg/L, p<0.001; GPBB: 9.07+/-5.83 microg/L vs. 4.70+/-2.50 microg/L, p<0.001). The correlations between plasma marker levels and RFA time were cTnI: r=0.63, p<0.01; CK-MB: r=0.75, p<0.01; hFABP: r=0.55, p<0.05, GPBB: r=0.51, p<0.05; the correlation between RFA time and number of RF applications was significant (r=0.81, p<0.001). Patients with RFA due to AF or flutter had elevated cTnI, CK-MB and hFABP levels compared to patients with AVNRT (cTnI: 1.14+/- 0.49 microg/L vs. 0.59+/-0.25 microg/L, p<0.05; CK-MB: 4.46+/- 2.07 microg/L vs. 2.81+/-1.54 mug/L, p<0.05; hFABP: 3.21+/- 0.98 microg/L vs. 2.25+/-0.54 microg/L, p<0.01). CONCLUSIONS: Myocardial injury induced by RFA can be detected by cTnI, CK-MB, hFABP and GPBB. Plasma cTnI, CK-MB and hFABP levels significantly increased in patients with AFL and AF compared to patients with AVNRT. The increase of cTnI, CK-MB and GPBB levels correlates with the total duration of RFA.
- MeSH
- Biomarkers analysis blood MeSH
- Adult MeSH
- Myocardial Infarction diagnosis etiology MeSH
- Catheter Ablation adverse effects MeSH
- Middle Aged MeSH
- Humans MeSH
- Microarray Analysis methods MeSH
- Young Adult MeSH
- Prospective Studies MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
Mohutný rozvoj molekulárně biologických metod v posledních deseti letech je charakterizován produkcí velkého množství dat. Nejinak je tomu i v případě technologie DNA mikročipů, která umožňuje v jednom experimentu sledovat expresi desítek tisíc genů najednou. Kvantum získaných experimentálních dat je však pro relevantní medicínské závěry nutné vhodně analyzovat a interpretovat. Tento článek je věnován statistickým metodám, které lze pro hodnocení dat získaných z DNA mikročipů použít. Tyto metody lze rozdělit do tří velkých skupin: shlukovací metody, metody pro identifikaci rozdílně exprimovaných genů a klasifikační metody. Shlukovací metody slouží k nalezení homogenních skupin pacientů s podobným expresním profilem nebo skupin genů s podobným chováním, metody pro identifikaci rozdílně exprimovan ých genů hledají geny specifické svojí aktivitou pro určitou biologickou tkáň, zatímco klasifikační metody slouží k nalezení diskriminačního pravidla pro přesnou diagnostiku nových pacientů do jedné z definovaných skupin.
Last decade led to massive progress in the molecular biology methods which was accompanied by the production of large amount of data. This is also the case of the gene expression microarray technology that makes it feasible to study thousands of genes simultaneously. However, for relevant medical inference there is the need for appropriate evaluation and interpretation of this large quantity of experimental data. This paper is dedicated to statistical methods that can be used for the evaluation of gene expression data. These methods can be split into three main categories: clustering methods, methods for identification of differentially expressed genes and classification techniques. Clustering methods can be used for finding of homogenous groups of patients or genes with similar expression profile, methods for identification of differentially expressed genes find genes specific for activity of certain biological tissue while classification techniques are used for setting up a discrimination rule for precise diagnostics of newly diagnosed patients to one of the previously defined classes.
- MeSH
- Discriminant Analysis MeSH
- Gene Expression genetics MeSH
- Financing, Organized MeSH
- Humans MeSH
- Oligonucleotide Array Sequence Analysis methods statistics & numerical data utilization MeSH
- Cluster Analysis MeSH
- Models, Statistical MeSH
- Statistics as Topic MeSH
- Models, Theoretical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Review MeSH
Metallothioneins (MTs), low molecular mass cysteine-rich proteins, which are able to bind up to 20 monovalent and up to 7 divalent heavy metal ions are widely studied due to their functions in detoxification of metals, scavenging free radicals and cells protection against the oxidative stress. It was found that the loss of the protective effects of MT leads to an escalation of pathogenic processes and carcinogenesis. The most extensive area is MTs expression for oncological applications, where the information about gene patterns is helpful for the identification biological function, resistance to drugs and creating the correct chemotherapy. In other medical applications the effect of oxidative stress to cell lines exposed to heavy metals and hydrogen peroxide is studied as well as influence of drugs and cytokines on MTs expression and MTs expression in the adipose tissue. The precise detection of low metallothionein concentrations and its isoforms is necessary to understand the connection between quantity and isoforms of MTs to size, localization and type of cancer. This information is necessary for well-timed therapy and increase the chance to survival. Microarray chips appear as good possibility for finding all information about expression of MTs genes and isoforms not only in cancer, but also in other diseases, especially diabetes, obesity, cardiovascular diseases, ageing, osteoporosis, psychiatric disorders and as the effects of toxic drugs and pollutants, which is discussed in this review.
- MeSH
- Humans MeSH
- Metallothionein analysis genetics metabolism MeSH
- Microarray Analysis methods MeSH
- Neoplasms diagnosis genetics metabolism MeSH
- Oxidative Stress physiology MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
Renální karcinom tvoří přibližně 3 % zhoubných nádorů dospělé populace a z urologických malignit dosahuje nejvyšší letality. Výzkum v oblastech vzniku a vývoje renálního karcinomu vedl k identifikaci klíčových signálních drah a následně i cílené protinádorové léčby prodlužující čas do progrese onemocnění, případně i celkové přežití léčených pacientů. Mikročipové technologie patří v současnosti mezi nejefektivnější metody studia genové exprese. Pomocí jednoho čipu lze paralelně detekovat expresi až desítek tisíc genů, a výrazně tak urychlit výzkum studovaných biologických modelů. K nejčastěji používaným mikročipům patří DNA čipy analyzující expresi mediátorové RNA (mRNA), nově se začínají uplatňovat mikročipové platformy detekující krátké nekódující RNA (mikroRNA), tzv. mikroRNA čipy. MikroRNA post-transkripčně regulují genovou expresi, a tak zásadním způsobem ovlivňují vlastnosti buňky. Ve výzkumu renálního karcinomu byly za posledních pět let využity mikročipové technologie ve více než dvaceti studiích. Tyto práce popisovaly schopnost mikročipů odlišit nádorovou tkáň od normálního renálního parenchymu, klasifikovat zhoubné novotvary ledviny podle histologických podtypů, identifikovat genové profily predikující metastazování renálního karcinomu a determinující prognózu jednotlivých pacientů. Cílem tohoto přehledu je shrnout výsledky z dosud provedených mikročipových studií u renálního karcinomu a prezentovat jejich potenciální uplatnitelnost v diagnostických a léčebných postupech.
Renal cell carcinoma accounts for approximately 3% of adult cancers and has the highest lethality of urological malignancies. Research focusing on carcinogenesis and development of renal cell carcinoma has led to the identification of the key signalling pathways and consequently targeted cancer therapy which improves time to progression or overall survival of renal cell carcinoma patients. Today, microarray technologies are some of the most efficient methods used in gene expression studies. Through one microarray experiment we can simultaneously determine the expression of thousands of genes, thus facilitating research of examined biological models. The most frequently used of the microarray technologies are DNA microarrays enabling global analysis of the mRNA (messenger RNA) expression, while recently, microarray platforms modified to detect short non-coding RNAs (microRNAs) have been employed (microRNA microarrays). MicroRNAs significantly affect the behaviour of tumour cells by post-transcriptional regulation of the gene expression. In the research into renal cell carcinoma, microarray technologies have been applied in more than twenty studies over the past five years. These papers describe the potential of microarrays to distinguish tumour tissue from normal renal parenchyma, to classify renal cell carcinomas according to histological subtypes, to identify expression profiles predicting metastasizing in primary renal tumours, and to determine the prognosis of particular renal cell carcinoma patients. The aim of this review is to summarize the results from microarray studies of renal cell carcinoma realized to date and to present their potential usage in diagnostic and therapeutic protocols.
Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection.
Microarrays represent a modern powerful technology, which have potential applications in many areas of biological research and provide new insights into the genomics and transcriptomics of living systems. The aim of this review is to describe the application of microarray technology for Mycobacterium avium subsp. paratuberculosis (MAP) research. The main focus points include a summary of results obtained for MAP using microarrays, examination of the fields of MAP research which are currently being investigated and possible areas of future research. This article is divided into two parts according to the type of nucleic acid used for array hybridisation. Articles related to MAP research using microarray technology are then divided according to the field of study, such as comparative genome analysis, diagnostics, expression or environmental studies.
- MeSH
- Crohn Disease genetics MeSH
- Genomics MeSH
- Humans MeSH
- Mycobacterium avium subsp. paratuberculosis genetics MeSH
- Paratuberculosis diagnosis genetics MeSH
- Oligonucleotide Array Sequence Analysis methods MeSH
- Gene Expression Profiling MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
The urokinase-type plasminogen activator (uPA) and PA inhibitor 1 (PAI-1) play important roles in breast cancer metastasis through cell migration and invasion. They are clinically applicable prognostic and predictive markers. High levels of uPA and PAI-1 are associated with high risk of recurrence and adjuvant chemotherapy provides substantial benefit for this breast cancer population. The current sole validated method for quantifying uPA level in breast tumour tissue is ELISA assay. It requires 50–300 mg of fresh or frozen tissue, which is the main limitation for routine use. In this study, we evaluated the performances of customized antibody microarray to quantify uPA concentration from reduced extraction solution of breast tumour tissue and compared it with standard ELISA kit. We firstly optimized the elaboration of customized antibody microarray in order to sensitively detect and quantify uPA standard solutions. In the best conditions, we analysed uPA concentration in 16 cytosolic extracts from breast tumour tissue. Results showed that our customized antibody microarray could correctly quantify uPA concentration while consuming 100 times less volume of tumour tissue extraction solution than ELISA. Our antibody microarray is a powerful and promising tool for the miniaturization of the immunoassay quantification of uPA from breast tumour tissue extracts.
- MeSH
- Urokinase-Type Plasminogen Activator * analysis immunology adverse effects MeSH
- Biomarkers MeSH
- Tissue Array Analysis * methods instrumentation MeSH
- Enzyme-Linked Immunosorbent Assay MeSH
- Immunoassay methods MeSH
- Humans MeSH
- Neoplasm Metastasis MeSH
- Breast Neoplasms * diagnosis immunology MeSH
- Prognosis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
- Comparative Study MeSH
Wiley series in probability and statistics
1st ed. xx, 320 s.
To define the molecular response of Acidithiobacillus ferrooxidans under pH up-shift, temporal gene expression profiles were examined by using whole-genome DNA microarrays for A. ferrooxidans. Approximately 30% of the 3,132 genes represented on the microarray were significantly upregulated over a 160-min period, while about 14% were significantly downregulated. Our results revealed that A. ferrooxidans showed potential self-protection and self-regulation performance in response to pH up-shift stress. Many genes involved in regulation of membrane components were differentially expressed under the pH up-shift stress. Likewise, most of genes involved in phosphate metabolism, sulfur assimilation, and CO(2) fixation were obviously induced. Conversely, the transcription of a polyphosphate kinase gene (AFE1210) associated with phosphate storage was significantly repressed, which probably stemmed from the depletion of polyphosphate. Besides, most of the genes involved in hydrogen uptake were significantly induced, whereas many genes involved in nitrogen fixation were obviously repressed, which suggested that hydrogen uptake and nitrogen fixation could contribute to cytoplasmic pH homeostasis.
- MeSH
- Acidithiobacillus genetics metabolism MeSH
- Genes, Bacterial MeSH
- Nitrogen Fixation genetics MeSH
- Phosphates metabolism MeSH
- Stress, Physiological MeSH
- Genome, Bacterial MeSH
- Hydrogen-Ion Concentration MeSH
- Carbon Dioxide metabolism MeSH
- Proteomics methods MeSH
- Industrial Microbiology methods MeSH
- Gene Expression Regulation, Bacterial physiology MeSH
- Oligonucleotide Array Sequence Analysis MeSH
- Sulfur metabolism MeSH
- Gene Expression Profiling MeSH
- Hydrogen metabolism MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The scope of the study was to apply Phenotype Biolog MicroArray (PM) technology to test the antibiotic sensitivity of the bacterial strains isolated from on-site wastewater treatment facilities. In the first step of the study, the percentage values of resistant bacteria from total heterotrophic bacteria growing on solid media supplemented with various antibiotics were determined. In the untreated wastewater, the average shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria were 53, 56, and 42%, respectively. Meanwhile, the shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria in the treated wastewater were 39, 33, and 29%, respectively. To evaluate the antibiotic susceptibility of the bacteria present in the wastewater, using the phenotype microarrays (PMs), the most common isolates from the treated wastewater were chosen: Serratia marcescens ss marcescens, Pseudomonas fluorescens, Stenotrophomonas maltophilia, Stenotrophomonas rhizophila, Microbacterium flavescens, Alcaligenes faecalis ss faecalis, Flavobacterium hydatis, Variovorax paradoxus, Acinetobacter johnsonii, and Aeromonas bestiarum. The strains were classified as multi-antibiotic-resistant bacteria. Most of them were resistant to more than 30 antibiotics from various chemical classes. Phenotype microarrays could be successfully used as an additional tool for evaluation of the multi-antibiotic resistance of environmental bacteria and in preliminary determination of the range of inhibition concentration.
- MeSH
- Anti-Bacterial Agents pharmacology MeSH
- Bacteria classification drug effects genetics isolation & purification MeSH
- Drug Resistance, Bacterial MeSH
- Water Purification instrumentation MeSH
- Microarray Analysis methods MeSH
- Wastewater chemistry microbiology MeSH
- Publication type
- Journal Article MeSH
- Evaluation Study MeSH
