49 resultados para OVER-EXPRESSION


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Lung T lymphocytes are important in pulmonary immunity and inflammation. it has been difficult to study these cells due to contamination with other cell types, mainly alveolar macrophages. We have developed a novel method for isolating lung T cells from lung resection tissue, using a combination of approaches. Firstly the lung tissue was finely chopped and filtered through a nylon mesh. Lymphocytic cells were enriched by Percoll density centrifugation and the T cells purified using human CD3 microbeads, resulting in 90.5% +/- 1.9% (n = 11) pure lymphocytes. The T cell yield from the crude cell preparation was 10.8 +/- 2.1% and viability, calculated using propidium iodide (PI) staining and trypan blue, was typically over 95%. The purification process did not affect expression of CD69 or CD103, nor was there a difference in the proportion of CD4 and CD8 cells between the starting population and the purified cells. Microarray analysis and real time RT-PCR revealed upregulation of GAPDH and CXCR6 of the lung T cells as compared to blood-derived T cells. This technique highly enriches lung T cells to allow detailed investigation of the biology of these cells. (C) 2008 Elsevier B.V. All rights reserved.

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Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository. © 2012 de Matos Simoes, Emmert-Streib.

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Despite being common in epithelial malignancies, the timing of receptor tyrosine kinase (RTK) up-regulation is poorly understood and therefore hampers the identification of the receptor to target for effective treatment. We aimed to determine if RTK expression changes were early events in carcinogenesis. Esophageal adenocarcinoma and its pre-invasive lesion, Barrett's esophagus, were used for immunohistochemical analysis of the RTK panel, EGFR, ErbB2, ErbB3, Met and FGFR2, by utilising a cohort of patients with invasive disease (n = 367) and two cohorts with pre-invasive disease, one cross-sectional (n = 110) and one longitudinal in time (n = 91). The results demonstrated that 51% of esophageal adenocarcinomas over-expressed at least one of the RTK panel; with 21% of these over-expressing multiple receptors. Up-regulation of RTK expression was an early event corresponding with low grade dysplasia development (25% in areas without dysplasia vs. 63% in low grade dysplasia, p

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We have previously shown that phospholipase A2 (PLA2) activity is rapidly activated by epidermal growth factor (EGF) and phorbol 12-myristate 13-acetate (PMA) in renal mesangial cells and other cell systems in a manner that suggests a covalent modification of the PLA2 enzyme(s). This PLA2 activity is cytosolic (cPLA2) and is distinct from secretory forms of PLA2, which are also stimulated in mesangial cells in response to cytokines and other agonists. However, longer-term regulation of cPLA2 in renal cells may also occur at the level of gene expression. Cultured rat mesangial cells were used as a model system to test the effects of EGF and PMA on the regulation of cPLA2 gene expression. EGF and PMA both produced sustained increases in cPLA2 mRNA levels, with a parallel increase in enzyme activity over time. Inhibition of protein synthesis by cycloheximide increased basal cPLA2 mRNA accumulation in serum-starved mesangial cells, and the combination of EGF and cycloheximide resulted in super-induction of cPLA2 gene expression compared with EGF alone. Actinomycin D treatment entirely abrogated the effect of EGF on cPLA2 mRNA accumulation. These findings suggest that regulation of cPLA2 is achieved by factors controlling gene transcription and possibly mRNA stability, in addition to previously characterized posttranslational modifications.

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Age-related changes in the facial expression of pain during the first 18 months of life have important implications for our understanding of pain and pain assessment. We examined facial reactions video recorded during routine immunization injections in 75 infants stratified into 2-, 4-, 6-, 12-, and 18-month age groups. Two facial coding systems differing in the amount of detail extracted were applied to the records. In addition, parents completed a brief questionnaire that assessed child temperament and provided background information. Parents' efforts to soothe the children also were described. While there were consistencies in facial displays over the age groups, there also were differences on both measures of facial activity, indicating systematic variation in the nature and severity of distress. The least pain was expressed by the 4-month age group. Temperament was not related to the degree of pain expressed. Systematic variations in parental soothing behaviour indicated accommodation to the age of the child. Reasons for the differing patterns of facial activity are examined, with attention paid to the development of inhibitory mechanisms and the role of negative emotions such as anger and anxiety.

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Gastric carcinogenesis has been well documented in the step-wise histopathological model, known as Correa pathway. Several biomarkers including CD44, Musashi-1 and CD133 have been reported as putative stem cell (PSC) markers.

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High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

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Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

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This work investigates the end-to-end performance of randomized distributed space-time codes with complex Gaussian distribution, when employed in a wireless relay network. The relaying nodes are assumed to adopt a decode-and-forward strategy and transmissions are affected by small and large scale fading phenomena. Extremely tight, analytical approximations of the end-to-end symbol error probability and of the end-to-end outage probability are derived and successfully validated through Monte-Carlo simulation. For the high signal-to-noise ratio regime, a simple, closed-form expression for the symbol error probability is further provided.

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Gremlin (Grem1) is a member of the DAN family of secreted bone morphogenetic protein (BMP) antagonists. Bone morphogenetic protein-7 (BMP-7) mediates protective effects during renal fibrosis-associated with diabetes and other renal diseases. The pathogenic mechanism of Grem1 during DN has been suggested to be binding and inhibition of BMP-7. However, the precise interactions between Grem1, BMP-7 and other BMPs have not been accurately defined. Here we show the affinity of Grem1 for BMP-7 is lower than that of BMP-2 and BMP-4, using a combination of surface plasmon resonance and cell culture techniques. Using kidney proximal tubule cells and HEK-293 cell Smad1/5/8 phosphorylation and BMP-dependent gene expression as readout, Grem1 consistently demonstrated a higher affinity for BMP-2>4>7. Cell-associated Grem1 did not inhibit BMP-2 or BMP-4 mediated signalling, suggesting that Grem1-BMP-2 binding occurred in solution, preventing BMP receptor activation. These data suggest that Grem1 preferentially binds to BMP-2 and this may be the dominant complex in a disease situation where levels of Grem1 and BMPs are elevated.

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We consider transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decodeand-forward (DF) relaying in Nakagami-m fading channels. In an effort to assess the performance, the probability density function and the cumulative distribution function of the endto-end SNR are derived using the moment generating function, from which new exact closed-form expressions for the outage probability and the symbol error rate are derived. We then derive a new closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expressions for the outage probability and the symbol error rate, as well as the high SNR approximations of the ergodic capacity, we establish new design insights under the two distinct constraint scenarios: 1) proportional interference power constraint, and 2) fixed interference power constraint. Several pivotal conclusions are reached. For the first scenario, the full diversity order of the
outage probability and the symbol error rate is achieved, and the high SNR slope of the ergodic capacity is 1/2. For the second scenario, the diversity order of the outage probability and the symbol error rate is zero with error floors, and the high SNR slope of the ergodic capacity is zero with capacity ceiling.

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Chronic lymphocytic leukemia (CLL) follows a variable clinical course which is difficult to predict at diagnosis. We assessed somatic mutation (SHM) status, CD38 and ZAP-70 expression in 87 patients (49 male, 38 female) with stage A CLL and known cytogenetic profile to compare their role in predicting disease progression, which was assessed by the treatment free interval (TFI) from diagnosis. Sixty (69%) patients were SHM+, 24 (28%) were CD38+ and ten (12%) were ZAP-70+. The median TFI for: (i) SHM + versus SHM- patients was 124 versus 26 months; hazard ratio (HR) = 3.6 [95% confidence interval (CI) = 1.8 - 7.3; P = 0.001]: (ii) CD38- versus CD38+ patients was 120 versus 34 months; HR = 2.4 (95% CI = 1.4 - 5.3; P = 0.02); and (iii) ZAP70- versus ZAP70+ was 120 versus 16 months; HR = 3.4 (95% CI = 1.4 - 8.7; P = 0.01). SHM status and CD38 retained prognostic significance on multivariate analysis whereas ZAP-70 did not. We conclude that ZAP-70 analysis does not provide additional prognostic information in this group of patients.

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BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

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This letter analyzes the performance of a low complexity detection scheme for a multi-carrier index keying (MCIK) with orthogonal frequency division multiplexing (OFDM) system over two-wave with diffused power (TWDP) fading channels. A closed-form expression for the average pairwise error probability (PEP) over TWDP fading channels is derived. This expression is used to analyze the performance of MCIK-OFDM in moderate, severe and extreme fading conditions. The presented results provide an insight on the performance of MCIK-OFDM for wireless communication systems that operate in enclosed metallic structures such as in-vehicular device-to-device (D2D) wireless networks.

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Spectrum sensing is a key function of cognitive radio systems. Sensing performance is determined by three main factors including the wireless channel between the primary system and the cognitive radio nodes, the detection threshold, and the sensing time. In this letter a closed-form expression for the average probability of detection for energy detection based spectrum sensing over two-wave with diffuse power fading channels is derived. This expression is then used to optimize the detection threshold for cognitive radio nodes, which operate in confined structures that exhibit worse than Rayleigh fading conditions. Such fading conditions can represent a behavioral model of cognitive machine-to-machine systems deployed in enclosed structures such as in-vehicular environments.