Search

In this study, we measured the enzymatic activity of acetylcholinesterase (AChE) using the Light Addressable Amperometric Sensor (LAAS), an electrochemical sensor that can easily measure redox current values of multiple samples. Acetylthiocholine (ATCh) was used as a substrate. ATCh is hydrolyzed by AChE and releases electrons, making it possible to measure current values in accordance with the amount of substrate using LAAS. When KCl solution was used as the supporting electrolyte and an Ag/AgCl reference electrode as the counter electrode, a correlation between substrate concentration and reaction was confirmed in the range of 1 μM–10 mM. Malathion was then used as an inhibitor of AChE. Malathion phosphorylates and inactivates AChE, which prevents substrate hydrolysis and is expected to decrease the current value. Experimental results showed a decrease in sensor response correlated with inhibitor concentration. [ABSTRACT FROM AUTHOR]

R, an open source and open development software project based on the R programming language for analysing and comprehending genetic data, is one of the most well-liked platforms. The workflow of analysing microarray data is shown in this work using the R analysis package, from different types of annotation, normalisation, expression index calculation, diagnostic plots, to pathway analysis for meaningful data visualisation and interpretation. Aim of the study was to analyse the microarray data of pediatric versus adult cornea using R software. Published microarray data gene expression patterns of pediatric and adult cornea were obtained from ncbi geo database. Integrated bioinformatics tools were used to analyze and compare the gene expression patterns. Data were processed using the software R, function and pathway enrichment analysis of differentially expressed genes (DEGs) was carried out using Gene ontology (GO) and KEGG database, protein protein interaction was studied by string database. A total of 33,297 differentially expressed genes (DEGs) were studied. There were no statistically significant differences in any gene between the groups. Genes enriched by more than 1.5 times were studied in more detail. Of the 20 major genes expressed, 11 were down-regulated and 9 were up-regulated. Volcano, mean difference plot, box plot, histogram, Venn's diagram compared the differentially expressed genes. None of the genes were significantly upregulated/downregulated/enriched in both the groups. On string analysis, 34 nodes, 8 edges were found. Average node degree was 0.471, average local cluster coefficient was 0.191 and p value for PPI enrichment was 0.326. The study displays the effectiveness of bioinformatics analysis methods in screening potential genes expressed in pediatric versus adult cornea using R software. [ABSTRACT FROM AUTHOR]

Cancer is most dangerous disease and most of the deaths are because of this deadly disease. Microarray cancer analysis is currently one of the most popular study topics in machine learning, computational biology. In the case of binary classes, classification and analysis of cancer data play a critical role in diagnosis, distinguishing negative and positive cases and treatment. The curse of dimensionality and a lack of sufficient sample data are the key challenges with microarray cancer datasets. In this paper presents, problems associated with micro array and handling of problems and make datasets ready for analysis. Different classification algorithms explained with pros and cons of each algorithm in detail. [ABSTRACT FROM AUTHOR]

Nonalcoholic fatty liver disease is the most common hepatic disease in western countries and is even more ubiquitous in Asian countries. Our study determined that TH17/Treg cells were imbalanced in animal models. Based on our interest in the mechanism underlying TH17/Treg cell imbalance in nonalcoholic fatty liver mice, we conducted a joint bioinformatics analysis to further investigate this process. Common gene sequencing analysis was based on one trial from one sequencing platform, where gene expression analysis and enrichment analysis were the only analyses performed. We compared different sequencing results from different trials performed using different sequencing platforms, and we utilized the intersection of these analytical results to perform joint analysis. We used a bioinformatics analysis method to perform enrichment analysis and map interaction network analysis and predict potential microRNA sites. Animal experiments were also designed to validate the results of the data analysis based on quantitative polymerase chain reaction (qPCR) and western blotting. Our results revealed 8 coexisting differentially expressed genes (DEGs) and 7 hinge genes. The identified DEGs may influence nonalcoholic steatosis hepatitis through the interleukin-17 pathway. We found that microRNA-29c interacts with FOS and IGFBP1. Polymerase chain reaction analyses revealed both FOS and microRNA-29c expression in NASH mice, and western blot analyses indicated the same trend with regard to FOS protein levels. Based on these results, we suggest that microRNA-29c acts on FOS via the interleukin-17 signaling pathway to regulate TH17/Treg cells in NASH patients.

Nonalcoholic fatty liver disease is the most common hepatic disease in western countries and is even more ubiquitous in Asian countries. Our study determined that TH17/Treg cells were imbalanced in animal models. Based on our interest in the mechanism underlying TH17/Treg cell imbalance in nonalcoholic fatty liver mice, we conducted a joint bioinformatics analysis to further investigate this process. Common gene sequencing analysis was based on one trial from one sequencing platform, where gene expression analysis and enrichment analysis were the only analyses performed. We compared different sequencing results from different trials performed using different sequencing platforms, and we utilized the intersection of these analytical results to perform joint analysis. We used a bioinformatics analysis method to perform enrichment analysis and map interaction network analysis and predict potential microRNA sites. Animal experiments were also designed to validate the results of the data analysis based on quantitative polymerase chain reaction (qPCR) and western blotting. Our results revealed 8 coexisting differentially expressed genes (DEGs) and 7 hinge genes. The identified DEGs may influence nonalcoholic steatosis hepatitis through the interleukin-17 pathway. We found that microRNA-29c interacts with FOS and IGFBP1. Polymerase chain reaction analyses revealed both FOS and microRNA-29c expression in NASH mice, and western blot analyses indicated the same trend with regard to FOS protein levels. Based on these results, we suggest that microRNA-29c acts on FOS via the interleukin-17 signaling pathway to regulate TH17/Treg cells in NASH patients. [ABSTRACT FROM AUTHOR]

Gene Expression Analysis seeks to find the highly expressive genes from a highly dimensional Microarray disease gene Database by using some statistical gene selection approaches based on supervised or unsupervised learning. Gene Ontology (GO) introduces a series of method for annotating gene function that combines semantic similarity measures by taking account on the underlying topology of gene interaction networks for structuring the graphs of the gene ontology. Initially, the genes are identified by clustering microarray disease dataset giving gene id of most expressive genes and further the genes are associated based on their biological functionalities using the gene ontology annotations taken from bioinformatics database. Also, t-test is used for finding the up-regulated genes so it can be annotated to find the most significant gene terms in hierarchical graph structure. The proposed method uses term Similarity measures to compare two or more gene ontology terms. Finally, gene functional classification and gene term association is done by forming a graph structure to be readily analysed by medical practitioner intending the nature of disease-causing genes at deeper level of understanding in chronic disorder based health care environments.

Gene Expression Analysis seeks to find the highly expressive genes from a highly dimensional Microarray disease gene Database by using some statistical gene selection approaches based on supervised or unsupervised learning. Gene Ontology (GO) introduces a series of method for annotating gene function that combines semantic similarity measures by taking account on the underlying topology of gene interaction networks for structuring the graphs of the gene ontology. Initially, the genes are identified by clustering microarray disease dataset giving gene id of most expressive genes and further the genes are associated based on their biological functionalities using the gene ontology annotations taken from bioinformatics database. Also, t-test is used for finding the up-regulated genes so it can be annotated to find the most significant gene terms in hierarchical graph structure. The proposed method uses term Similarity measures to compare two or more gene ontology terms. Finally, gene functional classification and gene term association is done by forming a graph structure to be readily analysed by medical practitioner intending the nature of disease-causing genes at deeper level of understanding in chronic disorder based health care environments. [ABSTRACT FROM AUTHOR]

Microarray data and sequencing data are two main types of high-throughput data in cancer related study. The most obvious advantages of microarray data are its sensitivity, rapid detection, and relatively low cost. Due to the fact that microarray data could only identify known genes instead of novel genes and variants, sequencing data have been involved in a lot of cancer mechanism studies. In general, both types of data are crucial in cancer research. Along with development of precision medicine, high-throughput data analysis can help people understand the mechanisms of cancer as well as expedite personalized cancer treatment. [ABSTRACT FROM AUTHOR]

As long as the genetically modified crops are gaining attention globally, their proper approval and commercialization need accurate and reliable diagnostic methods for the transgenic content. These diagnostic techniques are mainly divided into two major groups, i.e., identification of transgenic (1) DNA and (2) proteins from GMOs and their products. Conventional methods such as PCR (polymerase chain reaction) and enzyme-linked immunosorbent assay (ELISA) were routinely employed for DNA and protein based quantification respectively. Although, these Techniques (PCR and ELISA) are considered as significantly convenient and productive, but there is need for more advance technologies that allow for high throughput detection and the quantification of GM event as the production of more complex GMO is increasing day by day. Therefore, recent approaches like microarray, capillary gel electrophoresis, digital PCR and next generation sequencing are more promising due to their accuracy and precise detection of transgenic contents. The present article is a brief comparative study of all such detection techniques on the basis of their advent, feasibility, accuracy, and cost effectiveness. However, these emerging technologies have a lot to do with detection of a specific event, contamination of different events and determination of fusion as well as stacked gene protein are the critical issues to be addressed in future.

As long as the genetically modified crops are gaining attention globally, their proper approval and commercialization need accurate and reliable diagnostic methods for the transgenic content. These diagnostic techniques are mainly divided into two major groups, i.e., identification of transgenic (1) DNA and (2) proteins from GMOs and their products. Conventional methods such as PCR (polymerase chain reaction) and enzyme-linked immunosorbent assay (ELISA) were routinely employed for DNA and protein based quantification respectively. Although, these Techniques (PCR and ELISA) are considered as significantly convenient and productive, but there is need for more advance technologies that allow for high throughput detection and the quantification of GM event as the production of more complex GMO is increasing day by day. Therefore, recent approaches like microarray, capillary gel electrophoresis, digital PCR and next generation sequencing are more promising due to their accuracy and precise detection of transgenic contents. The present article is a brief comparative study of all such detection techniques on the basis of their advent, feasibility, accuracy, and cost effectiveness. However, these emerging technologies have a lot to do with detection of a specific event, contamination of different events and determination of fusion as well as stacked gene protein are the critical issues to be addressed in future. [ABSTRACT FROM AUTHOR]

The plastic-adherent, fibroblast-like, clonogenic cells found in the human body now defined as multipotent “Mesenchymal Stromal Cells” (MSCs) hold immense potential for cell-based therapies. Recently, research and basic knowledge of these cells has fast-tracked, both from fundamental and translational perspectives. There have been important discoveries with respect to the available variety of tissue sources, the development of protocols for their easy isolation and in vitro expansion and for directed differentiation into various cell types. In addition, there has been discovery of novel abilities such as immune-modulation and further development of the use of biomaterials to aid isolation, expansion and differentiation together with improved delivery to the selected optimal tissue site. However, the molecular fingerprint of MSCs in these contexts remains imprecise and inadequate. Consequently, without this crucial knowledge it is difficult to achieve progress to determine with precision their practical developmental potentials. Detailed investigations on the global gene expression, or transcriptome, of MSCs could offer essential clues in this regard. In this article, we address the challenges associated with MSC transcriptome studies, the paradoxes observed in published experimental results and the need for careful transcriptomic analysis. We describe the exemplary applications with various transcriptome platforms that are used to address the variation in biomarkers and the identification of differentiation processes. The evolution and the potentials for adapting next-generation sequencing (NGS) technology in transcriptome analysis are discussed. Lastly, based on review of the existing understanding and published studies, we propose how NGS may be applied to promote further understanding of the biology of MSCs and their use in allied fields such as regenerative medicine. [ABSTRACT FROM AUTHOR]

Zirconium-based bulk metallic glass (Zr-based BMG) is a potential material for micro/nano molds. In this study, we investigated the flow characteristics of Zr-based BMG in the supercooled liquid region (SLR) with a series of uniaxial compression tests. The Newtonian viscosity model of Zr-based BMG is constructed by fitting with the experimental results based on the Arrhenius equation. The hot embossing process which can be seen as a combination of two kinds of simultaneous flows is theoretically analyzed based on Navier-Stokes (N-S) equations. The velocity and pressure fields in a BMG sample have been evaluated. Two kinds of filling modes are proposed considering the interfacial tension and oxide layer that forms on the BMG surface. The exact solutions are obtained when the cavities of the micro arrays are circular, triangular and rectangular in shape based on N-S equations. The theoretical solutions, considered surface resistance, are in good agreement with our experimental results. These models can be used to describe the fillings of metallic glass in micro hot embossing process. Finally, we studied the effects of micro cavity size and shape on BMG filling, and found that the cavities of micro rectangular array are easier filling in same feature size, however, the cavities of micro circular array are easier filling in same area. The exact models developed in this paper can be used to calculate the BMG filling heights in the cavities of micro arrays and verify the reliability of simulation results in future mold designs. [ABSTRACT FROM AUTHOR]

Unsupervised machine learning and knowledge discovery from large-scale datasets have recently attracted a lot of research interest. The present paper proposes a distributed big data clustering approach-based on adaptive density estimation. The proposed method is developed-based on Apache Spark framework and tested on some of the prevalent datasets. In the first step of this algorithm, the input data is divided into partitions using a Bayesian type of Locality Sensitive Hashing (LSH). Partitioning makes the processing fully parallel and much simpler by avoiding unneeded calculations. Each of the proposed algorithm steps is completely independent of the others and no serial bottleneck exists all over the clustering procedure. Locality preservation also filters out the outliers and enhances the robustness of the proposed approach. Density is defined on the basis of Ordered Weighted Averaging (OWA) distance which makes clusters more homogenous. According to the density of each node, the local density peaks will be detected adaptively. By merging the local peaks, final cluster centers will be obtained and other data points will be a member of the cluster with the nearest center. The proposed method has been implemented and compared with similar recently published researches. Cluster validity indexes achieved from the proposed method shows its superiorities in precision and noise robustness in comparison with recent researches. Comparison with similar approaches also shows superiorities of the proposed method in scalability, high performance, and low computation cost. The proposed method is a general clustering approach and it has been used in gene expression clustering as a sample of its application.

Fibroblast growth factor 2 (FGF-2) is an abundant growth factor in the brain and exerts multiple functions on neural cells ranging from cell division, cell fate determination to differentiation. However, many details of the molecular mechanisms underlying the diverse functions of FGF-2 are poorly understood. In a comparative microarray analysis of motor sensory cortex (MSC) tissue of adult knockout (FGF-2 −/− ) and control (FGF-2 +/+ ) mice, we found a substantial number of regulated genes, which are implicated in cytoskeletal machinery dynamics. Specifically, we found a prominent downregulation of Arhgef6. Arhgef6 mRNA was significantly reduced in the FGF-2 −/− cortex, and Arhgef6 protein virtually absent, while RhoA protein levels were massively increased and Cdc42 protein levels were reduced. Since Arhgef6 is localized to dendritic spines, we next analyzed dendritic spines of adult FGF2 −/− and control mouse cortices. Spine densities were significantly increased, whereas mean length of spines on dendrites of layer V of MSC neurons in adult FGF-2 −/− mice was significantly decreased as compared to respective controls. Furthermore, neurite length in dissociated cortical cultures from E18 FGF-2 −/− mice was significantly reduced at DIV7 as compared to wildtype neurons. Despite the fact that altered neuronal morphology and alterations in dendritic spines were observed, FGF-2 −/− mice behave relatively unsuspicious in several behavioral tasks. However, FGF-2 −/− mice exhibited decreased thermal pain sensitivity in the hotplate-test. [ABSTRACT FROM AUTHOR]

Induced regulatory T cells (iTreg) are imperative for tolerance induction and spreading of infectious tolerance. Ex vivo generated tolerogenic dendritic cells (tDCs) have strong therapeutic potential to induce antigen-specific iTreg. We previously demonstrated that IL-10 tDC-primed T cells are very suppressive and produce IL-10. Here, we show that the majority of IL-10 + T cells co-express IFNγ, giving rise to the question whether these cells are proinflammatory or regulatory. Whole genome gene expression analysis revealed a strong regulatory gene profile and a suppressed Th1 gene profile for IL-10/IFNγ co-expressing CD4 + T cells. Protein analysis confirmed an extensive regulatory phenotype for IL-10 + /IFNγ + T cells, with specific enhanced expression of GARP and PD-1. In line with these data, isolated IL-10 + /IFNγ + T cells displayed potent suppressive capacity. Thus, IL-10/IFNγ co-expressing CD4 + T cells induced by IL-10 tDC show dominance of immunomodulation over Th1-mediated immunoactivation and can contribute to induction or spreading of immunological tolerance. [ABSTRACT FROM AUTHOR]

Dental implants are one of the most frequently used treatment options for tooth replacement. Approximately 30% of patients with dental implants develop peri-implantitis, which is an oral inflammatory disease that leads to loss of the supporting tissues, predominately the bone. For the development of future therapeutic strategies, it is essential to understand the molecular pathophysiology of human dental peri-implant infections. Here, we describe the gene and protein expression patterns of peri-implantitis bone tissue compared with healthy peri-implant bone tissue. Furthermore, cells from the osteoblastic lineage derived from peri-implantitis samples were immortalized and characterized. We applied microarray, quantitative reverse transcription polymerase chain reaction, fluorescence-activated cell sorting, and Western blot analyses. The levels of typical bone matrix molecules, including SPP1, BGLAP, and COL9A1, in patients with peri-implantitis were reduced, while the inflammation marker interleukin 8 (IL8) was highly expressed. RUNX2, one of the transcription factors of mature osteoblasts, was also decreased in peri-implantitis. Finally, the human telomerase reverse transcriptase immortalized cell line from peri-implantitis exhibited a more fibro-osteoblastic character than did the healthy control. [ABSTRACT FROM PUBLISHER]

Copyright of Der Gynäkologe is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Management of Retinoblastoma (RB), a pediatric ocular cancer is limited by drug-resistance and drug-dosage related side effects during chemotherapy. Molecular de-regulation in post-chemotherapy RB tumors was investigated. Materials and Methods: cDNA microarray analysis of two post-chemotherapy and one pre-chemotherapy RB tumor tissues was per¬formed, followed by Principle Component Analysis, Gene ontology, Pathway Enrichment analysis and Biological Analysis Network (BAN) modeling. The drug modulation role of two significantly up-regulated genes (p0.05) ― Ect2 (Epithelial-cell-transforming-sequence-2), and PRAME (preferentially-expressed-Antigen-in-Melanoma) was assessed by qRT-PCR, immunohistochemistry and cell viability assays. Results: Differential up-regulation of 1672 genes and down-regulation of 2538 genes was observed in RB tissues (relative to normal adult retina), while 1419 genes were commonly de-regulated between pre-chemotherapy and post- chemotherapy RB. Twenty one key gene ontology categories, pathways, biomarkers and phenotype groups harboring 250 differentially expressed genes were dys-regulated (EZH2, NCoR1, MYBL2, RB1, STAMN1, SYK, JAK1/2, STAT1/2, PLK2/4, BIRC5, LAMN1, Ect2, PRAME and ABCC4). Differential molecular expressions of PRAME and Ect2 in RB tumors with and without chemotherapy were analyzed. There was neither up- regula¬tion of MRP1, nor any significant shift in chemotherapeutic IC50, in PRAME over-expressed versus non-transfected RB cells. Conclusion: Cell cycle regulatory genes were dys-regulated post-chemotherapy. Ect2 gene was expressed in response to chemotherapy-induced stress. PRAME does not contribute to drug resistance in RB, yet its nuclear localization and BAN information, points to its possible regulatory role in RB. [ABSTRACT FROM AUTHOR]

Worldwide, the incidence of oral tongue cancer is on the rise, adding to the existing burden due to prevailing low survival and high recurrence rates. This study uses high-throughput expression profiling to identify candidate markers of resistance/response in patients with oral tongue cancer. Analysis of primary and post-treatment samples (12 tumor and 8 normal) by the Affymetrix platform (HG U133 plus 2) identified 119 genes as differentially regulated in recurrent tumors. The study groups had distinct profiles, with induction of immune response and apoptotic pathways in the non-recurrent and metastatic/invasiveness pathways in the recurrent group. Validation was carried out in tissues by Quantitative Real-Time PCR (QPCR) (n=30) and immunohistochemistry (IHC) (n=35) and in saliva by QPCR (n=37). The markers, COL5A1, HBB, IGLA and TSC individually and COL5A1 and HBB in combination had the best predictive power for treatment response in the patients. A subset of markers identified (COL5A1, ABCG1, MMP1, IL8, FN1) could be detected in the saliva of patients with oral cancers with their combined sensitivity and specificity being 0.65 and 0.87 respectively. The study thus emphasizes the extreme prognostic value of exploring markers of treatment resistance that are expressed in both tissue and saliva. [ABSTRACT FROM AUTHOR]

We hypothesized that circulating leukocyte RNA profiles or “riboleukograms” detect ventilator-associated pneumonia after blunt trauma.A pilot microarray study of 11 ventilator-associated pneumonia (VAP) patients suggested that 85 leukocyte genes can be used to diagnose VAP. Validation of this gene set to detect VAP was tested using data from an independent patient cohort.A total of 158 intubated blunt trauma patients were enrolled at 5 centers, where 57 (36%) developed VAP. Patient age was 34.2 ± 11.1 years; 65% were male. Circulating leukocyte GeneChip U133 2.0 expression values were measured at time 0.5, 1, 4, 7, 14, 21, and 28 days after injury. DChip normalized leukocyte transcriptional profiles were analyzed using repeated measures logistic regression. A compound covariate model based on leukocyte gene transcriptional profiles in a training subset of patients was tested to determine predictive accuracy for VAP 4 days prior to clinical diagnosis in the test subset.Using gene expression values measured on each study day at an FDR <0.05, 27 (32%) of the 85 genes were associated with the diagnosis of VAP 1 to 4 days before diagnosis. However, the compound covariate model based on these 85-genes did not predict VAP in the test cohort better than chance (P = 0.27). In contrast, a compound covariate model based upon de novo transcriptional analysis of the 158 patients predicted VAP better than chance 4 days before diagnosis with a sensitivity of 57% and a specificity of 69%.Our results validate those described in a pilot study, confirming that riboleukograms are associated with the development of VAP days prior to clinical diagnosis. Similarly, a riboleukogram predictive model tested on a larger cohort of 158 patients was better than chance at predicting VAP days prior to clinical diagnosis. [ABSTRACT FROM AUTHOR]

This paper describes a microfluidic chip in which two perpendicular laminar-flow streams can be operated to sequentially address the surface of a flow-chamber with semi-parallel sample streams. The sample streams can be controlled in position and width by the method of electrokinetic focusing. For this purpose, each of the two streams is sandwiched by two parallel sheath flow streams containing just a buffer solution. The streams are being electroosmotically pumped, allowing a simple chip design and a setup with no moving parts. Positioning of the streams was adjusted in real-time by controlling the applied voltages according to an analytical model. The perpendicular focusing gives rise to overlapping regions, which, by combinatorial (bio) chemistry, might be used for fabrication of spot arrays of immobilized proteins and other biomolecules. Since the patterning procedure is done in a closed, liquid filled flow-structure, array spots will never be exposed to air and are prevented from drying. With this device configuration, it was possible to visualize an array of 49 spots on a surface area of 1 mm2. This article describes the principle, fabrication, experimental results, analytical modeling and numerical simulations of the microfluidic chip. [ABSTRACT FROM AUTHOR]

Abstract: To evaluate the use of stationary phase protein array technology for tear analysis and to characterize the distribution of inflammatory mediators in normal and allergic tears in the open and closed eye states. Microcapillary tube collected Open (OTF) and closed eye tear fluid (CTF) samples from normals (N), from individuals with various active chronic ocular and other allergies (CA), as well as from an individual subsequent to unilateral induction of an acute allergic conjunctivitis were assayed using membrane arrays that were optimized to allow the detection of GM-CSF, ILs-1α, 1β, 2–10, 12–13, INFγ, MCP-1 and TNFα in clinical size samples. The protocol of a micro-well plate array specific for ILs-2, 4, 5, 8, 10, 12, 13, TNFα and INFγ was modified to minimize the impact of tear matrix effects. This was used to carry out parallel analysis on selected samples. By optimizing the protocol as well as the composition of a membrane array it proved possible to significantly increase the signal-to-noise ratio and sensitivity of assay allowing for the detection of some inflammatory mediators into the sub-picogram range. This provided sufficient sensitivity to allow the assay of clinically obtainable size samples. Analysis revealed that OTF from most Ns contained a high level of IL-8 and faint signals if any for the other probed proteins. In contrast, OTF samples from most CA individuals with and without ocular symptoms exhibited to varying degrees detectable levels of most of the other probed entities. The difference between normal and pathological tears and the levels of signals became far more pronounced in the CTF compared to the OTF samples. Use of the micro-well plate assay kit without modification revealed two tear matrix effects that profoundly impact the ability to obtain meaningful ELISA data. Modifying the assay protocol reduces but does not eliminate these artifacts making it possible to approximate the concentration of many of the probed entities. The obtained data is consistent using both methodologies revealing elevated levels of IL-8 and other cytokines in ∼60% of the OTF samples from the CA population. Other than a modest increase in IL-8, no change could be observed in the profile of OTF after induction of an acute allergic reaction. [Copyright &y& Elsevier]

Neuroblastoma is a common childhood tumor comprising cases with rapid disease progression as well as spontaneous regression. Although numerous prognostic factors have been identified, risk evaluation in individual patients remains difficult. To define a reliable prognostic predictor and gene signatures characteristic of biological subgroups, we performed mRNA expression profiling of 68 neuroblastomas of all stages. Expression data were analysed using support vector machines (SVM-rbf), prediction analysis of microarrays (PAM), k-nearest neighbors (k-NN) algorithms and multiple decision trees. SVM-rbf performed best of all methods, and predicted recurrence of neuroblastoma with an accuracy of 85% (sensitivity 77%, specificity 94%). PAM identified a classifier of 39 genes reliably predicting outcome with an accuracy of 80%. In comparison, conventional risk stratification based on stage, age and MYCN-status only reached a predictive accuracy of 64%. Kaplan–Meier analysis using the PAM classifier indicated a 5-year survival of 20 versus 78% for patients with unfavorably versus favorably predicted neuroblastomas, respectively (P=0.0001). Significance analysis of microarrays (SAM) identified additional genes differentially expressed among subgroups. MYCN-amplification and high expression of NTRK1/TrkA demonstrated a strong association with specific gene expression patterns. Our data suggest that microarray-derived data in addition to traditional clinical factors will be useful for risk assessment and defining biological properties of neuroblastoma.Oncogene (2005) 24, 7902–7912. doi:10.1038/sj.onc.1208936; published online 15 August 2005 [ABSTRACT FROM AUTHOR]

Necrotizing enterocolitis (NEC) is the leading intestinal emergency in premature infants. The underlying etiology of NEC remains elusive, but hypoxic conditions and early enteral feeding are consistently implicated as the main risk factors in the pathogenesis of NEC. We postulate that nitric oxide (NO) plays a key role as a molecular signaling “hub” in the generation of gut barrier failure in NEC. Clinical studies suggest that inflammatory cytokines and excessive NO production may contribute to the pathogenesis of NEC. One of the major challenges in defining the critical signaling pathways that lead to the development of NEC is the lack of specific biochemical markers that consistently delineate the early stages of NEC. Intestinal pathology and molecular markers derived from late-stage NEC represent end-stage findings and thus provide little insight into the early events that led to intestinal inflammation. Such markers may not represent viable therapeutic targets for the treatment or prevention of NEC. Therefore, novel strategies are needed to identify the patients at risk for NEC and define the clinically relevant molecules that characterize the early stages of NEC. This review will examine the mechanisms of NO-mediated gut barrier failure and propose novel genetic-based approaches for elucidating the critical molecular pathways in NEC. [Copyright &y& Elsevier]

Tumors of low malignant potential (LMP) represent 20% of epithelial ovarian cancers (EOCs) and are associated with a better prognosis than the invasive tumors (TOV). Defining the relationship between LMPs and TOVs remains an important goal towards understanding the molecular pathways that contribute to prognosis, as well as providing molecular markers, for these EOCs. To this end, DNA microarray analyses were performed either in a primary culture or a tumor tissue model system and selected candidate genes showing a distinctive expression profile between LMPs and TOVs were identified using a class prediction approach based on three statistical methods of analysis. Both model systems appear relevant as candidate genes identified by either model allowed the proper reclassification of samples as either LMPs or TOVs. Selected candidate genes (CAS, CCNE1, LGALS8, ITGβ3, ATP1B1, FLIP, KRT7 and KRT19) were validated by real-time quantitative PCR analysis and show differential expression between LMPs and TOVs. Immunohistochemistry analyses showed that the two tumor classes were distinguishable by their expression of CAS, TNFR1A, FLIP, CKS1 and CCNE1. These results define signature patterns for gene expression of LMPs and TOVs and identify gene candidates that warrant further study to deepen our understanding of the biology of EOC.Oncogene (2005) 24, 4672–4687. doi:10.1038/sj.onc.1208214 Published online 30 May 2005 [ABSTRACT FROM AUTHOR]

Transcriptome analysis and kidney research: Toward systems biology.An enormous amount of data has been generated in kidney research using transcriptome analysis techniques. In this review article, we first describe briefly the principles and major characteristics of several of these techniques. We then summarize the progress in kidney research that has been made by using transcriptome analysis, emphasizing the experience gained and the lessons learned. Several technical issues regarding DNA microarray are highlighted because of the rapidly increased use of this technology. It appears clear from this brief survey that transcriptome analysis is an effective and important tool for question-driven exploratory science. To further enhance the power of this and other high throughput, as well as conventional approaches, in future studies of the kidney, we propose a multidimensional systems biology paradigm that integrates investigation at multiple levels of biologic regulation toward the goal of achieving a global understanding of physiology and pathophysiology. [ABSTRACT FROM AUTHOR]

A recently established transfected cell array (TCA) technology has opened new experimental dimensions in the field of functional genomics. Cell arrays allow for transfection of several thousands different DNA molecules in microarray format. The effects of overexpression of hundreds of proteins on cellular physiology can be observed in a single experiment. The TCA technique has also found its application in RNA interference (RNAi) research. Small interfering RNAs (siRNA) as well as plasmid expressing short hairpin RNAs can be transferred into the cells through the process of reverse transfection. The silencing of numerous genes in spatially separated manner can be thus monitored. This review will provide an overview on current concepts concerning combination of cell array and RNAi for high-throughput loss-of-function studies.Oncogene (2004) 23, 8353-8358. doi:10.1038/sj.onc.1208027 [ABSTRACT FROM AUTHOR]

Ovarian cancer is the most lethal type of gynecologic cancer in the Western world. The high case fatality rate is due in part because most ovarian cancer patients present with advanced stage disease which is essentially incurable. In order to obtain a whole genome assessment of aberrant gene expression in advanced ovarian cancer, we used oligonucleotide microarrays comprising over 40000 features to profile 37 advanced stage papillary serous primary carcinomas. We identified 1191 genes that were significantly (P < 0.001) differentially regulated between the ovarian cancer specimens and normal ovarian surface epithelium. The microarray data were validated using real time RT-PCR on 14 randomly selected differentially regulated genes. The list of differentially expressed genes includes ones that are involved in cell growth, differentiation, adhesion, apoptosis and migration. In addition, numerous genes whose function remains to be elucidated were also identified. The microarray data were imported into Pathway Assist software to identify signaling pathways involved in ovarian cancer tumorigenesis. Based on our expression results, a signaling pathway associated with tumor cell migration, spread and invasion was identified as being activated in advanced ovarian cancer. The data generated in this study represent a comprehensive list of genes aberrantly expressed in serous papillary ovarian adenocarcinoma and may be useful for the identification of potentially new and novel markers and therapeutic targets for ovarian cancer. [ABSTRACT FROM AUTHOR]

Mesenchymal-epithelial interactions are increasingly considered to be of vital importance for epithelial homeostasis and regeneration. In skin, the transcription factor AP-1 was shown to be critically involved in the communication between keratinocytes and dermal fibroblasts. After skin injury, the release of IL-1 from keratinocytes induces the activity of the AP-1 subunits c-Jun and JunB in fibroblasts leading to a global change in gene expression. To identify AP-1 target genes in fibroblasts, which are involved in the process of cutaneous repair, we performed gene expression profiling of wild-type, c-jun- and junB-deficient fibroblasts in response to IL-1, mimicking the initial phase of wound healing. Using a 15K cDNA collection, over 1000 genes were found to be Jun-dependent and additional 300 clones showed IL-1 responsiveness. Combinatorial evaluation allowed for the dissection of the specific contribution of either AP-1 subunit to gene regulation. Besides previously identified genes that are involved in cutaneous repair, we have identified novel genes regulated during wound healing in vivo and showed their expression by fibroblasts on wound sections. The identification of novel Jun target genes should provide a basis for understanding the molecular mechanisms underlying mesenchymal-epithelial interactions and the critical contribution of AP-1 to tissue homeostasis and repair.Oncogene (2004) 23, 7005-7017. doi:10.1038/sj.onc.1207938 Published online 26 July 2004 [ABSTRACT FROM AUTHOR]

To test the hypothesis that the excess inflammatory response in cystic fibrosis airway epithelial cells is the result of differential activation of genes in response to a laboratory strain of Pseudomonas aeruginosa (PAO1), a 48-h time course of genes expressed following PAO1 stimulation (109CFU for 1 h) was studied in two pairs of airway epithelial cells: 9/HTEo−and 16HBE14o−, each with a matched normal and CF phenotype pair. cRNA was hybridized to Affymetrix HG-U95Av2 chips and pairwise comparisons against zero time (no PAO1) were calculated for each time point. PAO1 elicited profound changes in both cell pairs: for 9/HTEo−, 144 genes changed significantly in the normal pair, and 116 for the CF pair; for the 16HBE14o−pair, 57 genes changed significantly for the normal pair and 53 for the CF pair. Changes were much greater in the 9/HTEo−than in the 16HBE14o−pair, but basal levels of expression of inflammatory genes are higher in the 16HBE14o−pair, so 16HBE14o−was used mainly to corroborate the results of 9/HTEo−. Clustering analysis indicated that the pattern of gene expression is similar in the CF cells and their normal counterparts. However, there were substantial quantitative differences in gene expression. Thus, the difference between CF and normal resides in the magnitude, not the pattern, of the changes. abbreviations: CF – cystic fibrosis; CFTR – cystic fibrosis transmembrane conductance regulator; CFU – colony forming units; PAO1 – laboratory strain of Pseudomonas aeruginosa; BAL – bronchoalveolar lavage; IL – interleukin; NF-kB – nuclear transcription factor kappa B; NOS−2 – nitric oxide synthase; DMEM – Dulbecco’s modified Eagle medium; GM-CSF – granulocyte-macrophage colony-stimulating factor; GROα– melanoma growth stimulating activity, alpha (CXCL1); CXCL2 – chemokine (C-X-C motif) ligand 2, GROβ; TNFAIP3 – tumor necrosis factor, alpha-induced protein 3; NFKBIA – nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha; ELISA – enzyme-linked immunosorbent assay; RT-PCR – reverse transcriptase polymerase chain reaction; GAPDH – glyceraldehyde-3-phosphate dehydrogenase; UPGMA – unweighted pair-group method with arithmetic mean; GO – Gene Ontology. [ABSTRACT FROM AUTHOR]

The article aims to introduce computer scientists to the new field of bioinformatics. This area has arisen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in genomic research--and its more recent counterparts, proteomics and functional genomics. The ultimate goal of bioinformatics is to develop in silico models that will complement in vitro and in vivo biological experiments. The article provides a bird's eye view of the basic concepts in molecular cell biology, outlines the nature of the existing data, and describes the kind of computer algorithms and techniques that are necessary to understand cell behavior. The underlying motivation for many of the bioinformatics approaches is the evolution of organisms and the complexity of working with incomplete and noisy data. The topics covered include: descriptions of the current software especially developed for biologists, computer and mathematical cell models, and areas of computer science that play an important role in bioinformatics. [ABSTRACT FROM AUTHOR]

A novel concept of a membrane-based micro-array biosensor is presented. The methodology is based on a single lipid membrane interrogated with electrochemical impedance techniques followed by multivariate data analysis. A single membrane is designed so that relaxation processes with a range of time constants can be probed at different potentials. A range of other approaches cited in the literature is reviewed. [ABSTRACT FROM AUTHOR]

We have recently reported the development of a DNA maskless array synthesizer (MAS) [Singh-Gasson et al., Nat. Biotechnol. 17 (1999) 974]. In this paper we describe in more details the technical approach and implementation of the system, and show recent results of high-density DNA chips. [Copyright &y& Elsevier]

Pericytes facilitate blood–brain barrier (BBB) integrity; however, the mechanisms involved remain unclear. Hence, using co-cultures of human cerebral microvascular endothelial cells (ECs) and vascular pericytes (PCs) in different spatial arrangements, as well as PC conditioned media, we investigated the impact of PC-EC orientation and PC-derived soluble factors on EC barrier function. We provide the first evidence that barrier-inducing properties of PCs require basolateral contact with ECs. Gene expression analysis (GEA) in ECs co-cultured with PCs versus ECs alone showed significant upregulation of 38 genes and downregulation of 122 genes. Pathway enrichment analysis of modulated genes showed significant regulation of several pathways, including transforming growth factor-β and interleukin-1 regulated extracellular matrix, interferon and interleukin signaling, immune system signaling, receptor of advanced glycation end products (RAGE), and cytokine–cytokine receptor interaction. Transcriptomic analysis showed a reduction in molecules such as pro-inflammatory cytokines and chemokines, which are known to be induced during BBB disruption. Moreover, cytokine proteome array confirmed the downregulation of key pro-inflammatory cytokines and chemokines on the protein level. Other molecules which influence BBB and were favorably modulated upon EC-PC co-culture include IL-18 binding protein, kallikrein-3, CSF2 CSF3, CXCL10, CXCL11 (downregulated) and IL-1-R4; HGF, PDGF-AB/BB, PECAM, SERPIN E1 (upregulated). In conclusion, we provide the first evidence that (1) basolateral contact between ECs and PCs is essential for EC barrier function and integrity; (2) in ECs co-cultured with PCs, the profile of BBB disrupting pro-inflammatory molecules and cytokines/chemokines is downregulated; (3) PCs significantly modulate EC mechanisms known to improve barrier function, including TGF-β regulated ECM pathway, anti-inflammatory cytokines, growth factors and matrix proteins. This human PC-EC co-culture may serve as a viable in vitro model for investigating BBB function and drug transport. [ABSTRACT FROM AUTHOR]