A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

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Kalra, Rajkumar S.; Wadhwa, Renu

2015-01-01

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein

A bioinformatics prediction approach towards analyzing the glycosylation, co-expression and interaction patterns of epithelial membrane antigen (EMA/MUC1)

Energy Technology Data Exchange (ETDEWEB)

Kalra, Rajkumar S., E-mail: renu-wadhwa@aist.go.jp; Wadhwa, Renu, E-mail: renu-wadhwa@aist.go.jp [Cell Proliferation Research Group and DBT-AIST International Laboratory for Advanced Biomedicine, National Institute of Advanced Industrial Science and Technology (AIST Central 4), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8562 (Japan)

2015-02-27

Epithelial membrane antigen (EMA or MUC1) is a heavily glycosylated, type I transmembrane glycoprotein commonly expressed by epithelial cells of duct organs. It has been shown to be aberrantly glycosylated in several diseases including cancer. Protein sequence based annotation and analysis of glycosylation profile of glycoproteins by robust computational and comprehensive algorithms provides possible insights to the mechanism(s) of anomalous glycosylation. In present report, by using a number of bioinformatics applications we studied EMA/MUC1 and explored its trans-membrane structural domain sequence that is widely subjected to glycosylation. Exploration of different extracellular motifs led to prediction of N and O-linked glycosylation target sites. Based on the putative O-linked target sites, glycosylated moieties and pathways were envisaged. Furthermore, Protein network analysis demonstrated physical interaction of EMA with a number of proteins and confirmed its functional involvement in cell growth and proliferation pathways. Gene Ontology analysis suggested an involvement of EMA in a number of functions including signal transduction, protein binding, processing and transport along with glycosylation. Thus, present study explored potential of bioinformatics prediction approach in analyzing glycosylation, co-expression and interaction patterns of EMA/MUC1 glycoprotein.

Predictive modelling of gene expression from transcriptional regulatory elements.

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Budden, David M; Hurley, Daniel G; Crampin, Edmund J

2015-07-01

Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Comprehensive analysis of gene expression patterns of hedgehog-related genes

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Baillie David

2006-10-01

Full Text Available Abstract Background The Caenorhabditis elegans genome encodes ten proteins that share sequence similarity with the Hedgehog signaling molecule through their C-terminal autoprocessing Hint/Hog domain. These proteins contain novel N-terminal domains, and C. elegans encodes dozens of additional proteins containing only these N-terminal domains. These gene families are called warthog, groundhog, ground-like and quahog, collectively called hedgehog (hh-related genes. Previously, the expression pattern of seventeen genes was examined, which showed that they are primarily expressed in the ectoderm. Results With the completion of the C. elegans genome sequence in November 2002, we reexamined and identified 61 hh-related ORFs. Further, we identified 49 hh-related ORFs in C. briggsae. ORF analysis revealed that 30% of the genes still had errors in their predictions and we improved these predictions here. We performed a comprehensive expression analysis using GFP fusions of the putative intergenic regulatory sequence with one or two transgenic lines for most genes. The hh-related genes are expressed in one or a few of the following tissues: hypodermis, seam cells, excretory duct and pore cells, vulval epithelial cells, rectal epithelial cells, pharyngeal muscle or marginal cells, arcade cells, support cells of sensory organs, and neuronal cells. Using time-lapse recordings, we discovered that some hh-related genes are expressed in a cyclical fashion in phase with molting during larval development. We also generated several translational GFP fusions, but they did not show any subcellular localization. In addition, we also studied the expression patterns of two genes with similarity to Drosophila frizzled, T23D8.1 and F27E11.3A, and the ortholog of the Drosophila gene dally-like, gpn-1, which is a heparan sulfate proteoglycan. The two frizzled homologs are expressed in a few neurons in the head, and gpn-1 is expressed in the pharynx. Finally, we compare the

Membrane expression of MRP-1, but not MRP-1 splicing or Pgp expression, predicts survival in patients with ESFT.

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Roundhill, E; Burchill, S

2013-07-09

Primary Ewing's sarcoma family of tumours (ESFTs) may respond to chemotherapy, although many patients experience subsequent disease recurrence and relapse. The survival of ESFT cells following chemotherapy has been attributed to the development of resistant disease, possibly through the expression of ABC transporter proteins. MRP-1 and Pgp mRNA and protein expression in primary ESFTs was determined by quantitative reverse-transcriptase PCR (RT-qPCR) and immunohistochemistry, respectively, and alternative splicing of MRP-1 by RT-PCR. We observed MRP-1 protein expression in 92% (43 out of 47) of primary ESFTs, and cell membrane MRP-1 was highly predictive of both overall survival (PMRP-1 was detected in primary ESFTs, although the pattern of splicing variants was not predictive of patient outcome, with the exception of loss of exon 9 in six patients, which predicted relapse (P=0.041). Pgp protein was detected in 6% (38 out of 44) of primary ESFTs and was not associated with patient survival. For the first time we have established that cell membrane expression of MRP-1 or loss of exon 9 is predictive of outcome but not the number of splicing events or expression of Pgp, and both may be valuable factors for the stratification of patients for more intensive therapy.

miR-21 Expression in Cancer Cells may Not Predict Resistance to Adjuvant Trastuzumab in Primary Breast Cancer

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Nielsen, Boye Schnack; Balslev, Eva; Poulsen, Tim Svenstrup

2014-01-01

, predominantly in cancer cells, or in both stromal and cancer cells. There was no obvious difference between the HER2-positive and HER2-negative tumors in terms of the miR-21 expression patterns and intensities. To explore the possibility that miR-21 expression levels and/or cellular localization could predict...... expression patterns and intensities revealed no association between the miR-21 scores in the cancer cell population (p = 0.69) or the stromal cells population (p = 0.13) and recurrent disease after adjuvant trastuzumab. Thus, our findings show that elevated miR-21 expression does not predict resistance......Trastuzumab is established as standard care for patients with HER2-positive breast cancer both in the adjuvant and metastatic setting. However, 50% of the patients do not respond to the trastuzumab therapy, and therefore new predictive biomarkers are highly warranted. MicroRNAs (miRs) constitute...

Don’t look blank, happy, or sad: patterns of facial expressions of speakers in banks’ YouTube videos predict video’s popularity over time

OpenAIRE

Lewinski, P.

2015-01-01

There has been little focus on nonverbal communication in social media advertising campaigns. We propose that specific patterns of facial expressions predict the popularity of YouTube videos among users of social media. To test that proposition, we used a neuromarketing tool—FaceReader—to code facial videos of professional speakers who participated in the YouTube social media campaigns of 2 large commercial banks. We analyzed more than 25,000 video frames of 16 speakers’ 6 basic facial expres...

Genetic Networks and Anticipation of Gene Expression Patterns

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Gebert, J.; Lätsch, M.; Pickl, S. W.; Radde, N.; Weber, G.-W.; Wünschiers, R.

2004-08-01

An interesting problem for computational biology is the analysis of time-series expression data. Here, the application of modern methods from dynamical systems, optimization theory, numerical algorithms and the utilization of implicit discrete information lead to a deeper understanding. In [1], we suggested to represent the behavior of time-series gene expression patterns by a system of ordinary differential equations, which we analytically and algorithmically investigated under the parametrical aspect of stability or instability. Our algorithm strongly exploited combinatorial information. In this paper, we deepen, extend and exemplify this study from the viewpoint of underlying mathematical modelling. This modelling consists in evaluating DNA-microarray measurements as the basis of anticipatory prediction, in the choice of a smooth model given by differential equations, in an approach of the right-hand side with parametric matrices, and in a discrete approximation which is a least squares optimization problem. We give a mathematical and biological discussion, and pay attention to the special case of a linear system, where the matrices do not depend on the state of expressions. Here, we present first numerical examples.

Gene expression patterns in CD4+ peripheral blood cells in healthy subjects and stage IV melanoma patients.

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Felts, Sara J; Van Keulen, Virginia P; Scheid, Adam D; Allen, Kathleen S; Bradshaw, Renee K; Jen, Jin; Peikert, Tobias; Middha, Sumit; Zhang, Yuji; Block, Matthew S; Markovic, Svetomir N; Pease, Larry R

2015-11-01

Melanoma patients exhibit changes in immune responsiveness in the local tumor environment, draining lymph nodes, and peripheral blood. Immune-targeting therapies are revolutionizing melanoma patient care increasingly, and studies show that patients derive clinical benefit from these newer agents. Nonetheless, predicting which patients will benefit from these costly therapies remains a challenge. In an effort to capture individual differences in immune responsiveness, we are analyzing patterns of gene expression in human peripheral blood cells using RNAseq. Focusing on CD4+ peripheral blood cells, we describe multiple categories of immune regulating genes, which are expressed in highly ordered patterns shared by cohorts of healthy subjects and stage IV melanoma patients. Despite displaying conservation in overall transcriptome structure, CD4+ peripheral blood cells from melanoma patients differ quantitatively from healthy subjects in the expression of more than 2000 genes. Moreover, 1300 differentially expressed genes are found in transcript response patterns following activation of CD4+ cells ex vivo, suggesting that widespread functional discrepancies differentiate the immune systems of healthy subjects and melanoma patients. While our analysis reveals that the transcriptome architecture characteristic of healthy subjects is maintained in cancer patients, the genes expressed differentially among individuals and across cohorts provide opportunities for understanding variable immune states as well as response potentials, thus establishing a foundation for predicting individual responses to stimuli such as immunotherapeutic agents.

Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes

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Paules Richard S

2007-11-01

Full Text Available Abstract Background A common observation in the analysis of gene expression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressed genes a challenge. We developed a novel method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes, designated as EPIG. The approach utilizes the underlying structure of gene expression data to extract patterns and identify co-expressed genes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressed genes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressed genes revealed underlying

Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumor.

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Vasselli, James R; Shih, Joanna H; Iyengar, Shuba R; Maranchie, Jodi; Riss, Joseph; Worrell, Robert; Torres-Cabala, Carlos; Tabios, Ray; Mariotti, Andra; Stearman, Robert; Merino, Maria; Walther, McClellan M; Simon, Richard; Klausner, Richard D; Linehan, W Marston

2003-06-10

To identify potential molecular determinants of tumor biology and possible clinical outcomes, global gene-expression patterns were analyzed in the primary tumors of patients with metastatic renal cell cancer by using cDNA microarrays. We used grossly dissected tumor masses that included tumor, blood vessels, connective tissue, and infiltrating immune cells to obtain a gene-expression "profile" from each primary tumor. Two patterns of gene expression were found within this uniformly staged patient population, which correlated with a significant difference in overall survival between the two patient groups. Subsets of genes most significantly associated with survival were defined, and vascular cell adhesion molecule-1 (VCAM-1) was the gene most predictive for survival. Therefore, despite the complex biological nature of metastatic cancer, basic clinical behavior as defined by survival may be determined by the gene-expression patterns expressed within the compilation of primary gross tumor cells. We conclude that survival in patients with metastatic renal cell cancer can be correlated with the expression of various genes based solely on the expression profile in the primary kidney tumor.

Divergent and nonuniform gene expression patterns in mouse brain

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Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

2010-01-01

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series

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Madeira Sara C

2009-06-01

Full Text Available Abstract Background The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using gene expression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters. Methods In this work, we propose e-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series gene expression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters. Results We present results in real data showing the effectiveness of e-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of

Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

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Yu-Chun Chang

2018-05-01

overall survival and cumulative risk in AD patients. Discussion Here we report HKG expression patterns may be an effective tool for evaluation of lung cancer states. For example, the differential expression pattern of 70 HKGs alone can separate normal lung tissue from various lung cancers while a panel of 106 HKGs was a capable class predictor of subtypes of non-small cell carcinomas. We also reported that HKGs have significantly lower variance compared to traditional cancer markers across samples, highlighting the robustness of a panel of genes over any one specific biomarker. Using RNA-seq data, we showed that the expression pattern of 13 HKGs is a significant, independent predictor of overall survival for AD patients. This reinforces the predictive power of a HKG panel across different gene expression measurement platforms. Thus, we propose the expression patterns of HKGs alone may be sufficient for the diagnosis and prognosis of individuals with lung cancer.

White matter tract covariance patterns predict age-declining cognitive abilities.

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Gazes, Yunglin; Bowman, F DuBois; Razlighi, Qolamreza R; O'Shea, Deirdre; Stern, Yaakov; Habeck, Christian

2016-01-15

Previous studies investigating the relationship of white matter (WM) integrity to cognitive abilities and aging have either focused on a global measure or a few selected WM tracts. Ideally, contribution from all of the WM tracts should be evaluated at the same time. However, the high collinearity among WM tracts precludes systematic examination of WM tracts simultaneously without sacrificing statistical power due to stringent multiple-comparison corrections. Multivariate covariance techniques enable comprehensive simultaneous examination of all WM tracts without being penalized for high collinearity among observations. In this study, Scaled Subprofile Modeling (SSM) was applied to the mean integrity of 18 major WM tracts to extract covariance patterns that optimally predicted four cognitive abilities (perceptual speed, episodic memory, fluid reasoning, and vocabulary) in 346 participants across ages 20 to 79years old. Using expression of the covariance patterns, age-independent effects of white matter integrity on cognition and the indirect effect of WM integrity on age-related differences in cognition were tested separately, but inferences from the indirect analyses were cautiously made given that cross-sectional data set was used in the analysis. A separate covariance pattern was identified that significantly predicted each cognitive ability after controlling for age except for vocabulary, but the age by WM covariance pattern interaction was not significant for any of the three abilities. Furthermore, each of the patterns mediated the effect of age on the respective cognitive ability. A distinct set of WM tracts was most influential in each of the three patterns. The WM covariance pattern accounting for fluid reasoning showed the most number of influential WM tracts whereas the episodic memory pattern showed the least number. Specific patterns of WM tracts make significant contributions to the age-related differences in perceptual speed, episodic memory, and

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

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Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

A gene expression study of dorso-ventrally restricted pigment pattern in adult fins of Neolamprologus meeli, an African cichlid species

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Ehsan Pashay Ahi

2017-01-01

Full Text Available Fish color patterns are among the most diverse phenotypic traits found in the animal kingdom. Understanding the molecular and cellular mechanisms that control in chromatophore distribution and pigmentation underlying this diversity is a major goal in developmental and evolutionary biology, which has predominantly been pursued in the zebrafish model system. Here, we apply results from zebrafish work to study a naturally occurring color pattern phenotype in the fins of an African cichlid species from Lake Tanganyika. The cichlid fish Neolamprologus meeli displays a distinct dorsal color pattern, with black and white stripes along the edges of the dorsal fin and of the dorsal half of the caudal fin, corresponding with differences in melanophore density. To elucidate the molecular mechanisms controlling the differences in dorsal and ventral color patterning in the fins, we quantitatively assessed the expression of 15 candidate target genes involved in adult zebrafish pigmentation and stripe formation. For reference gene validation, we screened the expression stability of seven widely expressed genes across the investigated tissue samples and identified tbp as appropriate reference. Relative expression levels of the candidate target genes were compared between the dorsal, striped fin regions and the corresponding uniform, grey-colored regions in the anal and ventral caudal fin. Dorso-ventral expression differences, with elevated levels in both white and black stripes, were observed in two genes, the melanosome protein coding gene pmel and in igsf11, which affects melanophore adhesion, migration and survival. Next, we predicted potential shared upstream regulators of pmel and igsf11. Testing the expression patterns of six predicted transcriptions factors revealed dorso-ventral expression difference of irf1 and significant, negative expression correlation of irf1 with both pmel and igsf11. Based on these results, we propose pmel, igsf11 and irf1 as

Adrenal-kidney-gonad complex measurements may not predict gonad-specific changes in gene expression patterns during temperature-dependent sex determination in the red-eared slider turtle (Trachemys scripta elegans).

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Ramsey, Mary; Crews, David

2007-08-01

Many turtles, including the red-eared slider turtle (Trachemys scripta elegans) have temperature-dependent sex determination in which gonadal sex is determined by temperature during the middle third of incubation. The gonad develops as part of a heterogenous tissue complex that comprises the developing adrenal, kidney, and gonad (AKG complex). Owing to the difficulty in excising the gonad from the adjacent tissues, the AKG complex is often used as tissue source in assays examining gene expression in the developing gonad. However, the gonad is a relatively small component of the AKG, and gene expression in the adrenal-kidney (AK) compartment may interfere with the detection of gonad-specific changes in gene expression, particularly during early key phases of gonadal development and sex determination. In this study, we examine transcript levels as measured by quantitative real-time polymerase chain reaction for five genes important in slider turtle sex determination and differentiation (AR, ERalpha, ERbeta, aromatase, and Sf1) in AKG, AK, and isolated gonad tissues. In all cases, gonad-specific gene expression patterns were attenuated in AKG versus gonad tissue. All five genes were expressed in the AK in addition to the gonad at all stages/temperatures. Inclusion of the AK compartment masked important changes in gonadal gene expression. In addition, AK and gonad expression patterns are not additive, and gonadal gene expression cannot be predicted from intact AKG measurements. (c) 2007 Wiley-Liss, Inc.

Small regulatory RNAs may sharpen spatial expression patterns.

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Erel Levine

2007-11-01

Full Text Available The precise establishment of gene expression patterns is a crucial step in development. Formation of a sharp boundary between high and low spatial expression domains requires a genetic mechanism that exhibits sensitivity, yet is robust to fluctuations, a demand that may not be easily achieved by morphogens alone. Recently, it has been demonstrated that small RNAs (and, in particular, microRNAs play many roles in embryonic development. Whereas some RNAs are essential for embryogenesis, others are limited to fine-tuning a predetermined gene expression pattern. Here, we explore the possibility that small RNAs participate in sharpening a gene expression profile that was crudely established by a morphogen. To this end, we study a model in which small RNAs interact with a target gene and diffusively move from cell to cell. Though diffusion generally smoothens spatial expression patterns, we find that intercellular mobility of small RNAs is actually critical in sharpening the interface between target expression domains in a robust manner. This sharpening occurs as small RNAs diffuse into regions of low mRNA expression and eliminate target molecules therein, but cannot affect regions of high mRNA levels. We discuss the applicability of our results, as examples, to the case of leaf polarity establishment in maize and Hox patterning in the early Drosophila embryo. Our findings point out the functional significance of some mechanistic properties, such as mobility of small RNAs and the irreversibility of their interactions. These properties are yet to be established directly for most classes of small RNAs. An indirect yet simple experimental test of the proposed mechanism is suggested in some detail.

Increased Expression of microRNA-17 Predicts Poor Prognosis in Human Glioma

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Shengkui Lu

2012-01-01

Full Text Available Aim. To investigate the clinical significance of microRNA-17 (miR-17 expression in human gliomas. Methods. Quantitative real-time polymerase chain reaction (qRT-PCR analysis was used to characterize the expression patterns of miR-17 in 108 glioma and 20 normal brain tissues. The associations of miR-17 expression with clinicopathological factors and prognosis of glioma patients were also statistically analyzed. Results. Compared with normal brain tissues, miR-17 expression was significantly higher in glioma tissues (P<0.001. In addition, the increased expression of miR-17 in glioma was significantly associated with advanced pathological grade (P=0.006 and low Karnofsky performance score (KPS, P=0.01. Moreover, Kaplan-Meier survival and Cox regression analyses showed that miR-17 overexpression (P=0.008 and advanced pathological grade (P=0.02 were independent factors predicting poor prognosis for gliomas. Furthermore, subgroup analyses showed that miR-17 expression was significantly associated with poor overall survival in glioma patients with high pathological grades (for grade III~IV: P<0.001. Conclusions. Our data offer the convinced evidence that the increased expression of miR-17 may have potential value for predicting poor prognosis in glioma patients with high pathological grades, indicating that miR-17 may contribute to glioma progression and be a candidate therapeutic target for this disease.

The effects of MicroRNA transfections on global patterns of gene expression in ovarian cancer cells are functionally coordinated

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Shahab Shubin W

2012-08-01

Full Text Available Abstract Background MicroRNAs (miRNAs are a class of small RNAs that have been linked to a number of diseases including cancer. The potential application of miRNAs in the diagnostics and therapeutics of ovarian and other cancers is an area of intense interest. A current challenge is the inability to accurately predict the functional consequences of exogenous modulations in the levels of potentially therapeutic miRNAs. Methods In an initial effort to systematically address this issue, we conducted miRNA transfection experiments using two miRNAs (miR-7, miR-128. We monitored the consequent changes in global patterns of gene expression by microarray and quantitative (real-time polymerase chain reaction. Network analysis of the expression data was used to predict the consequence of each transfection on cellular function and these predictions were experimentally tested. Results While ~20% of the changes in expression patterns of hundreds to thousands of genes could be attributed to direct miRNA-mRNA interactions, the majority of the changes are indirect, involving the downstream consequences of miRNA-mediated changes in regulatory gene expression. The changes in gene expression induced by individual miRNAs are functionally coordinated but distinct between the two miRNAs. MiR-7 transfection into ovarian cancer cells induces changes in cell adhesion and other developmental networks previously associated with epithelial-mesenchymal transitions (EMT and other processes linked with metastasis. In contrast, miR-128 transfection induces changes in cell cycle control and other processes commonly linked with cellular replication. Conclusions The functionally coordinated patterns of gene expression displayed by different families of miRNAs have the potential to provide clinicians with a strategy to treat cancers from a systems rather than a single gene perspective.

Spatiotemporal patterns and predictability of cyberattacks.

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Yu-Zhong Chen

Full Text Available A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Whole-body gene expression pattern registration in Platynereis larvae.

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Asadulina, Albina; Panzera, Aurora; Verasztó, Csaba; Liebig, Christian; Jékely, Gáspár

2012-12-03

Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the

Whole-body gene expression pattern registration in Platynereis larvae

Directory of Open Access Journals (Sweden)

Asadulina Albina

2012-12-01

Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different gene expression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of gene expression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in gene expression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered gene expression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body gene expression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer.

Science.gov (United States)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC. Copyright © 2013 Elsevier Inc. All rights reserved.

Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

Science.gov (United States)

Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

2018-01-01

It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

Neuron-Enriched Gene Expression Patterns are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain.

Science.gov (United States)

Tan, Powell Patrick Cheng; French, Leon; Pavlidis, Paul

2013-01-01

An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia to neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain.

Macaques can predict social outcomes from facial expressions.

Science.gov (United States)

Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

2016-09-01

There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present.

Using excitation patterns to predict auditory masking

NARCIS (Netherlands)

Heijden, van der M.L.; Kohlrausch, A.G.

1992-01-01

We investigated how well auditory masking can be predicted from excitation patterns. For this purpose, a quantitative model proposed by Moore and Glasberg (1987) and Glasberg and Moore (1990) was used to calculate excitation patterns evoked by stationary sounds. We performed simulations of a number

A method for predicting monthly rainfall patterns

International Nuclear Information System (INIS)

Njau, E.C.

1987-11-01

A brief survey is made of previous methods that have been used to predict rainfall trends or drought spells in different parts of the earth. The basic methodologies or theoretical strategies used in these methods are compared with contents of a recent theory of Sun-Weather/Climate links (Njau, 1985a; 1985b; 1986; 1987a; 1987b; 1987c) which point towards the possibility of practical climatic predictions. It is shown that not only is the theoretical basis of each of these methodologies or strategies fully incorporated into the above-named theory, but also this theory may be used to develop a technique by which future monthly rainfall patterns can be predicted in further and finer details. We describe the latter technique and then illustrate its workability by means of predictions made on monthly rainfall patterns in some East African meteorological stations. (author). 43 refs, 11 figs, 2 tabs

Distinct RNA transcriptome patterns are potentially associated with angiogenesis in Tie2-expressing monocytes.

Science.gov (United States)

Wang, Xinjing; Dai, Zhiyuan; Wu, Xiaoli; Wang, Kai; Wang, Xipeng

2016-04-10

Tie2-expressing Monocytes (TEMs) were previously identified as a novel subset of monocytes and were believed to have prominent pro-angiogenesis activities in human tumors. While the molecular mechanism of the angiogenesis promoting capacity of TEMs remains unclear. RNA transcriptome pattern, including non-coding RNAs as microRNA (miRNA) and long non-coding RNA (lncRNA), plays important role in cell differentiation and functions. However, little is known about the transcriptome patterns of TEMs, including those non-coding RNAs. We explore the transcriptome of TEMs and the matched monocytes that do not express Tie2 (Tie2(-)monocytes) isolated from peripheral blood of healthy adults employing the Agilent Human miRNA(8*60K,Design ID: 046064)microarray and the Agilent lncRNA Gene Expression(4*180K, Design ID: 042818)microarray. A total of 141 mRNAs, 142 lncRNAs and 75 miRNAs were found dysregulated in TEMs compared to Tie2(-)monocytes. TEMs have the distinct RNA transcriptome patterns according to the Hierarchical clustering and then the gene expression patterns were confirmed by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Functional annotation by Gene Ontology (GO) analyses showed that the up-regulated mRNAs in TEMs were associated to blood vessel remodeling and positive regulation of epithelial cell proliferation, and the up-regulated insulin like growth factor 1(IGF1) mRNA was involved in both pathways. For functional analysis of those dysregulated non-coding RNAs, target genes of the miRNAs were predicted and cis/trans-regulation analysis of the lncRNAs were performed. Copyright © 2016 Elsevier B.V. All rights reserved.

Solution Patterns Predicting Pythagorean Triples

Science.gov (United States)

Ezenweani, Ugwunna Louis

2013-01-01

Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

MirZ: an integrated microRNA expression atlas and target prediction resource.

Science.gov (United States)

Hausser, Jean; Berninger, Philipp; Rodak, Christoph; Jantscher, Yvonne; Wirth, Stefan; Zavolan, Mihaela

2009-07-01

MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens.

Differential expression pattern of UBX family genes in Caenorhabditis elegans

International Nuclear Information System (INIS)

Yamauchi, Seiji; Sasagawa, Yohei; Ogura, Teru; Yamanaka, Kunitoshi

2007-01-01

UBX (ubiquitin regulatory X)-containing proteins belong to an evolutionary conserved protein family and determine the specificity of p97/VCP/Cdc48p function by binding as its adaptors. Caenorhabditis elegans was found to possess six UBX-containing proteins, named UBXN-1 to -6. However, no general or specific function of them has been revealed. During the course of understanding not only their function but also specified function of p97, we investigated spatial and temporal expression patterns of six ubxn genes in this study. Transcript analyses showed that the expression pattern of each ubxn gene was different throughout worm's development and may show potential developmental dynamics in their function, especially ubxn-5 was expressed specifically in the spermatogenic germline, suggesting a crucial role in spermatogenesis. In addition, as ubxn-4 expression was induced by ER stress, it would function as an ERAD factor in C. elegans. In vivo expression analysis by using GFP translational fusion constructs revealed that six ubxn genes show distinct expression patterns. These results altogether demonstrate that the expression of all six ubxn genes of C. elegans is differently regulated

Comparison of gene expression patterns between porcine cumulus ...

African Journals Online (AJOL)

These results suggest that the aberrant of gene expression patterns detected in the oocytes of NOs compared with COCs explains their reduced quality in terms of development and maturation. In conclusion, these differentially expressed mRNAs may be involved in cellular interactions between oocytes and cumulus cells ...

Different protein-protein interface patterns predicted by different machine learning methods.

Science.gov (United States)

Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

2017-11-22

Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

HLA-G Expression Pattern: Reliable Assessment for Pregnancy Outcome Prediction

Science.gov (United States)

Mosaferi, Elnaz; Majidi, Jafar; Mohammadian, Mojdeh; Babaloo, Zohreh; Monfaredan, Amir; Baradaran, Behzad

2013-01-01

Because mothers and fathers are more or less dissimilar at multiple HLA loci, mother considers her fetus as a semi-allograft. Mother's immune system may recognize paternal HLA as foreign antigen and may develop anti-paternal HLA antibodies and cytotoxic T lymphocyte. There are some mechanisms that modulate maternal immune responses during pregnancy, in order to make uterus an immune privileged site. This immunosuppression is believed to be mediated, at least partly, by HLA-G, non-classical class I human leukocyte antigen (HLA) molecule that is strongly expressed in cytotrophoblast and placenta. The major HLA-G function is its ability to inhibit T and B lymphocytes, NK cells and antigen-presenting cells (APC).Since HLA-G is expressed strongly at the maternofetal interface and has an essential role in immunosuppression, HLA-G polymorphism and altered expression of HLA-G seems to be associated with some complications of pregnancy, such as pre-eclampsia, recurrent misscariage and failure in IVF.This perspective discusses recent findings about HLA-G genetics, function, expression and polymorphism; and focus on HLA-G role in the etiology of recurrent miscarriage. PMID:24312875

HLA-G Expression Pattern: Reliable Assessment for Pregnancy Outcome Prediction

Directory of Open Access Journals (Sweden)

Elnaz Mosaferi

2013-08-01

Full Text Available Because mothers and fathers are more or less dissimilar at multiple HLA loci, mother considers her fetus as a semi-allograft. Mother's immune system may recognize paternal HLA as foreign antigen and may develop anti-paternal HLA antibodies and cytotoxic T lymphocyte. There are some mechanisms that modulate maternal immune responses during pregnancy, in order to make uterus an immune privileged site. This immunosuppression is believed to be mediated, at least partly, by HLA-G, non-classical class I human leukocyte antigen (HLA molecule that is strongly expressed in cytotrophoblast and placenta. The major HLA-G function is its ability to inhibit T and B lymphocytes, NK cells and antigen-presenting cells (APC.Since HLA-G is expressed strongly at the maternofetal interface and has an essential role in immunosuppression, HLA-G polymorphism and altered expression of HLA-G seems to be associated with some complications of pregnancy, such as pre-eclampsia, recurrent misscariage and failure in IVF.This perspective discusses recent findings about HLA-G genetics, function, expression and polymorphism; and focus on HLA-G role in the etiology of recurrent miscarriage.

G-cimp status prediction of glioblastoma samples using mRNA expression data.

Science.gov (United States)

Baysan, Mehmet; Bozdag, Serdar; Cam, Margaret C; Kotliarova, Svetlana; Ahn, Susie; Walling, Jennifer; Killian, Jonathan K; Stevenson, Holly; Meltzer, Paul; Fine, Howard A

2012-01-01

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

Clinicopathologic and gene expression parameters predict liver cancer prognosis

International Nuclear Information System (INIS)

Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

2011-01-01

The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

Expression of nerve growth factor and heme oxygenase-1 predict poor survival of breast carcinoma patients

International Nuclear Information System (INIS)

Noh, Sang Jae; Chung, Myoung Ja; Moon, Woo Sung; Kang, Myoung Jae; Jang, Kyu Yun; Bae, Jun Sang; Jamiyandorj, Urangoo; Park, Ho Sung; Kwon, Keun Sang; Jung, Sung Hoo; Youn, Hyun Jo; Lee, Ho; Park, Byung-Hyun

2013-01-01

Nerve growth factor (NGF) is a neurotrophin and has been suggested to induce heme oxygenase-1 (HO1) expression. Although the role of HO1 in tumorigenesis remains controversial, recent evidence suggests NGF and HO1 as tumor-progressing factors. However, the correlative role of NGF and HO1 and their prognostic impact in breast carcinoma is unknown. We investigated the expression and prognostic significance of the expression of NGF and HO1 in 145 cases of breast carcinoma. Immunohistochemical expression of NGF and HO1 was observed in 31% and 49% of breast carcinoma, respectively. The expression of NGF and HO1 significantly associated with each other, and both have a significant association with histologic grade, HER2 expression, and latent distant metastasis. The expression of NGF and HO1 predicted shorter overall survival of breast carcinoma by univariate and multivariate analysis. NGF expression was an independent prognostic indicator for relapse-free survival by multivariate analysis. The combined expression pattern of NGF and HO1 was also an independent prognostic indicator of overall survival and relapse-free survival. The patients with tumors expressing NGF had the shortest survival and the patients with tumor, which did not express NGF or HO1 showed the longest survival time. This study has demonstrated that individual expression of NGF or HO1, and the combined NGF/HO1 expression pattern could be prognostic indicators for breast carcinoma patients

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

Energy Technology Data Exchange (ETDEWEB)

Pandi, Narayanan Sathiya, E-mail: sathiyapandi@gmail.com; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-10-04

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC.

In silico analysis of stomach lineage specific gene set expression pattern in gastric cancer

International Nuclear Information System (INIS)

Pandi, Narayanan Sathiya; Suganya, Sivagurunathan; Rajendran, Suriliyandi

2013-01-01

Highlights: •Identified stomach lineage specific gene set (SLSGS) was found to be under expressed in gastric tumors. •Elevated expression of SLSGS in gastric tumor is a molecular predictor of metabolic type gastric cancer. •In silico pathway scanning identified estrogen-α signaling is a putative regulator of SLSGS in gastric cancer. •Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. -- Abstract: Stomach lineage specific gene products act as a protective barrier in the normal stomach and their expression maintains the normal physiological processes, cellular integrity and morphology of the gastric wall. However, the regulation of stomach lineage specific genes in gastric cancer (GC) is far less clear. In the present study, we sought to investigate the role and regulation of stomach lineage specific gene set (SLSGS) in GC. SLSGS was identified by comparing the mRNA expression profiles of normal stomach tissue with other organ tissue. The obtained SLSGS was found to be under expressed in gastric tumors. Functional annotation analysis revealed that the SLSGS was enriched for digestive function and gastric epithelial maintenance. Employing a single sample prediction method across GC mRNA expression profiles identified the under expression of SLSGS in proliferative type and invasive type gastric tumors compared to the metabolic type gastric tumors. Integrative pathway activation prediction analysis revealed a close association between estrogen-α signaling and SLSGS expression pattern in GC. Elevated expression of SLSGS in GC is associated with an overall increase in the survival of GC patients. In conclusion, our results highlight that estrogen mediated regulation of SLSGS in gastric tumor is a molecular predictor of metabolic type GC and prognostic factor in GC

G-cimp status prediction of glioblastoma samples using mRNA expression data.

Directory of Open Access Journals (Sweden)

Mehmet Baysan

Full Text Available Glioblastoma Multiforme (GBM is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

Exploring the significance of human mobility patterns in social link prediction

KAUST Repository

Alharbi, Basma Mohammed

2014-01-01

Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper explores the effect of in-depth mobility patterns. Specifically, we study individuals\\' movement behavior, and quantify mobility on the basis of trip frequency, travel purpose and transportation mode. Our hybrid link prediction model is composed of two modules. The first module extracts mobility patterns, including travel purpose and mode, from raw trajectory data. The second module employs the extracted patterns for link prediction. We evaluate our method on two real data sets, GeoLife [15] and Reality Mining [5]. Experimental results show that our hybrid model significantly improves the accuracy of social link prediction, when comparing to primary topology-based solutions. Copyright 2014 ACM.

An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

Directory of Open Access Journals (Sweden)

Liang Yu

2008-12-01

smokers, if combined with cytopathology of the cells, yielded 89–90% sensitivity of lung cancer detection and 87–90% negative predictive value to non-cancer patients. Conclusion This study focuses on predicted targets of three lung-enriched miRNAs, compares their expression patterns in lung cancer by their GO terms, and identifies a minimal set of genes differentially expressed in AD and SCC, followed by validating this gene signature in multiple published datasets. Expression of this gene signature in bronchial epithelial cells of cigarette smokers also has a great sensitivity to predict the patients having lung cancer if combined with cytopathology of the cells.

MicroRNA (miR)-203 and miR-205 expression patterns identify subgroups of prognosis in cutaneous squamous cell carcinoma.

Science.gov (United States)

Cañueto, J; Cardeñoso-Álvarez, E; García-Hernández, J L; Galindo-Villardón, P; Vicente-Galindo, P; Vicente-Villardón, J L; Alonso-López, D; De Las Rivas, J; Valero, J; Moyano-Sanz, E; Fernández-López, E; Mao, J H; Castellanos-Martín, A; Román-Curto, C; Pérez-Losada, J

2017-07-01

Cutaneous squamous cell carcinoma (CSCC) is the second most widespread cancer in humans and its incidence is rising. These tumours can evolve as diseases of poor prognosis, and therefore it is important to identify new markers to better predict its clinical evolution. We aimed to identify the expression pattern of microRNAs (miRNAs or miRs) at different stages of skin cancer progression in a panel of murine skin cancer cell lines. Owing to the increasing importance of miRNAs in the pathogenesis of cancer, we considered the possibility that miRNAs could help to define the prognosis of CSCC and aimed to evaluate the potential use of miR-203 and miR-205 as biomarkers of prognosis in human tumours. Seventy-nine human primary CSCCs were collected at the University Hospital of Salamanca in Spain. We identified differential miRNA expression patterns at different stages of CSCC progression in a well-established panel of murine skin cancer cell lines, and then selected miR-205 and miR-203 to evaluate their association with the clinical prognosis and evolution of human CSCC. miR-205 was expressed in tumours with pathological features recognized as indicators of poor prognosis such as desmoplasia, perineural invasion and infiltrative growth pattern. miR-205 was mainly expressed in undifferentiated areas and in the invasion front, and was associated with both local recurrence and the development of general clinical events of poor evolution. miR-205 expression was an independent variable selected to predict events of poor clinical evolution using the multinomial logistic regression model described in this study. In contrast, miR-203 was mainly expressed in tumours exhibiting the characteristics associated with a good prognosis, was mainly present in well-differentiated zones, and rarely expressed in the invasion front. Therefore, the expression and associations of miR-205 and miR-203 were mostly mutually exclusive. Finally, using a logistic biplot we identified three clusters

The predictive nature of transcript expression levels on protein expression in adult human brain.

Science.gov (United States)

Bauernfeind, Amy L; Babbitt, Courtney C

2017-04-24

Next generation sequencing methods are the gold standard for evaluating expression of the transcriptome. When determining the biological implications of such studies, the assumption is often made that transcript expression levels correspond to protein levels in a meaningful way. However, the strength of the overall correlation between transcript and protein expression is inconsistent, particularly in brain samples. Following high-throughput transcriptomic (RNA-Seq) and proteomic (liquid chromatography coupled with tandem mass spectrometry) analyses of adult human brain samples, we compared the correlation in the expression of transcripts and proteins that support various biological processes, molecular functions, and that are located in different areas of the cell. Although most categories of transcripts have extremely weak predictive value for the expression of their associated proteins (R 2 values of < 10%), transcripts coding for protein kinases and membrane-associated proteins, including those that are part of receptors or ion transporters, are among those that are most predictive of downstream protein expression levels. The predictive value of transcript expression for corresponding proteins is variable in human brain samples, reflecting the complex regulation of protein expression. However, we found that transcriptomic analyses are appropriate for assessing the expression levels of certain classes of proteins, including those that modify proteins, such as kinases and phosphatases, regulate metabolic and synaptic activity, or are associated with a cellular membrane. These findings can be used to guide the interpretation of gene expression results from primate brain samples.

Rhythmic diel pattern of gene expression in juvenile maize leaf.

Directory of Open Access Journals (Sweden)

Maciej Jończyk

Full Text Available BACKGROUND: Numerous biochemical and physiological parameters of living organisms follow a circadian rhythm. Although such rhythmic behavior is particularly pronounced in plants, which are strictly dependent on the daily photoperiod, data on the molecular aspects of the diurnal cycle in plants is scarce and mostly concerns the model species Arabidopsis thaliana. Here we studied the leaf transcriptome in seedlings of maize, an important C4 crop only distantly related to A. thaliana, throughout a cycle of 10 h darkness and 14 h light to look for rhythmic patterns of gene expression. RESULTS: Using DNA microarrays comprising ca. 43,000 maize-specific probes we found that ca. 12% of all genes showed clear-cut diel rhythms of expression. Cluster analysis identified 35 groups containing from four to ca. 1,000 genes, each comprising genes of similar expression patterns. Perhaps unexpectedly, the most pronounced and most common (concerning the highest number of genes expression maxima were observed towards and during the dark phase. Using Gene Ontology classification several meaningful functional associations were found among genes showing similar diel expression patterns, including massive induction of expression of genes related to gene expression, translation, protein modification and folding at dusk and night. Additionally, we found a clear-cut tendency among genes belonging to individual clusters to share defined transcription factor-binding sequences. CONCLUSIONS: Co-expressed genes belonging to individual clusters are likely to be regulated by common mechanisms. The nocturnal phase of the diurnal cycle involves gross induction of fundamental biochemical processes and should be studied more thoroughly than was appreciated in most earlier physiological studies. Although some general mechanisms responsible for the diel regulation of gene expression might be shared among plants, details of the diurnal regulation of gene expression seem to differ

Prediction of Human Activity by Discovering Temporal Sequence Patterns.

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Li, Kang; Fu, Yun

2014-08-01

Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

Predicting fragmentation sizing profiles for different blasting patterns

International Nuclear Information System (INIS)

Sheikh, A.M.; Chung, S.H.

1987-01-01

This paper evaluates the efficiency of blasting in a large scale underground heap leaching operation. The prediction model is based on the dynamic tensile breaking strength of rock formation, the detonation characteristics of the explosives and the drill hole pattern. The modelling includes crack pattern development and fragmentation computation fitted by the Rosin-Rammler distribution equation

Cytokeratin 19 Expression Patterns of Dentigerous Cysts and Odontogenic Keratocysts

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Kamath, KP; Vidya, M

2015-01-01

Background: Although numerous investigators have studied the pattern of keratin expression in different odontogenic cysts, the results have been variable. Aim: The present study was conducted to determine the pattern of expression of cytokeratin 19 (CK 19) in the epithelial lining of odontogenic keratocysts and dentigerous cysts. Materials and Methods: The epithelial layers showing expression of the epithelial marker CK 19 was determined by immunohistochemical methods in 15 tissue specimens each of histopathologically confirmed cases of dentigerous cysts and odontogenic keratocysts. Statistical analysis was done to compare the CK 19 expression between dentigerous cyst and odontogenic keratocyst using the Chi-square test. P keratocysts, 40% (6/15) of the specimens were negative for CK 19, 40% (6/15) of the specimens showed expression only in a single layer of the epithelium, and 20% (3/15) of the specimens showed expression in more than one layer, but not the entire thickness of the epithelium. The observed differences in CK 19 expression by the two lesions were statistically significant (P < 0.01). Conclusion: The differences in CK 19 expression by these cysts may be utilized as a diagnostic tool in differentiating between these two lesions. PMID:25861531

Genomic expression patterns of cardiac tissues from dogs with dilated cardiomyopathy.

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Oyama, Mark A; Chittur, Sridar

2005-07-01

To evaluate global genome expression patterns of left ventricular tissues from dogs with dilated cardiomyopathy (DCM). Tissues obtained from the left ventricle of 2 Doberman Pinschers with end-stage DCM and 5 healthy control dogs. Transcriptional activities of 23,851 canine DNA sequences were determined by use of an oligonucleotide microarray. Genome expression patterns of DCM tissue were evaluated by measuring the relative amount of complementary RNA hybridization to the microarray probes and comparing it with gene expression for tissues from 5 healthy control dogs. 478 transcripts were differentially expressed (> or = 2.5-fold change). In DCM tissue, expression of 173 transcripts was upregulated and expression of 305 transcripts was downregulated, compared with expression for control tissues. Of the 478 transcripts, 167 genes could be specifically identified. These genes were grouped into 1 of 8 categories on the basis of their primary physiologic function. Grouping revealed that pathways involving cellular energy production, signaling and communication, and cell structure were generally downregulated, whereas pathways involving cellular defense and stress responses were upregulated. Many previously unreported genes that may contribute to the pathophysiologic aspects of heart disease were identified. Evaluation of global expression patterns provides a molecular portrait of heart failure, yields insights into the pathophysiologic aspects of DCM, and identifies intriguing genes and pathways for further study.

Acute ischaemic stroke prediction from physiological time series patterns

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Qing Zhang,

2013-05-01

Full Text Available BackgroundStroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.AimsWe examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after 3 months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient’s stroke experience.Method We applied regression-based machine learning techniques to build a prediction algorithm that can forecast 3-month outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but also we adopted trend patterns of time series data as new key features.ResultsWe tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.ConclusionWe demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.

Imbalanced target prediction with pattern discovery on clinical data repositories.

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Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

2017-04-20

Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

Prediction of male-pattern baldness from genotypes

NARCIS (Netherlands)

F. Liu (Fan); M.A. Hamer (Merel); S. Heilmann (S.); C. Herold (Christine); S. Moebus (Susanne); A. Hofman (Albert); A.G. Uitterlinden (André); M.M. Nöthen (Markus); C.M. van Duijn (Cornelia); T.E.C. Nijsten (Tamar); M.H. Kayser (Manfred)

2016-01-01

textabstractThe global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide

Predicting patterns of glioma recurrence using diffusion tensor imaging

International Nuclear Information System (INIS)

Price, Stephen J.; Pickard, John D.; Jena, Rajesh; Burnet, Neil G.; Carpenter, T.A.; Gillard, Jonathan H.

2007-01-01

Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T 2 -weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

Predicting patterns of glioma recurrence using diffusion tensor imaging

Energy Technology Data Exchange (ETDEWEB)

Price, Stephen J.; Pickard, John D. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Academic Neurosurgery Unit (United Kingdom); University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Jena, Rajesh; Burnet, Neil G. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Oncology (United Kingdom); Carpenter, T.A. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Gillard, Jonathan H. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Radiology (United Kingdom)

2007-07-15

Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T{sub 2}-weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

Increased neutrophil expression of pattern recognition receptors during COPD exacerbations

NARCIS (Netherlands)

Pouwels, Simon D.; Van Geffen, Wouter H.; Jonker, Marnix R.; Kerstjens, Huib A. M.; Nawijn, Martijn C.; Heijink, Irene H.

Previously, we observed increased serum levels of damage-associated molecular patterns (DAMPs) during COPD exacerbations. Here, gene expression of DAMP receptors was measured in peripheral blood neutrophils of COPD patients during stable disease and severe acute exacerbation. The expression of

Size-based predictions of food web patterns

DEFF Research Database (Denmark)

Zhang, Lai; Hartvig, Martin; Knudsen, Kim

2014-01-01

We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

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Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

2014-07-01

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Expression profiling to predict the clinical behaviour of ovarian cancer fails independent evaluation

International Nuclear Information System (INIS)

Gevaert, Olivier; De Smet, Frank; Van Gorp, Toon; Pochet, Nathalie; Engelen, Kristof; Amant, Frederic; De Moor, Bart; Timmerman, Dirk; Vergote, Ignace

2008-01-01

In a previously published pilot study we explored the performance of microarrays in predicting clinical behaviour of ovarian tumours. For this purpose we performed microarray analysis on 20 patients and estimated that we could predict advanced stage disease with 100% accuracy and the response to platin-based chemotherapy with 76.92% accuracy using leave-one-out cross validation techniques in combination with Least Squares Support Vector Machines (LS-SVMs). In the current study we evaluate whether tumour characteristics in an independent set of 49 patients can be predicted using the pilot data set with principal component analysis or LS-SVMs. The results of the principal component analysis suggest that the gene expression data from stage I, platin-sensitive advanced stage and platin-resistant advanced stage tumours in the independent data set did not correspond to their respective classes in the pilot study. Additionally, LS-SVM models built using the data from the pilot study – although they only misclassified one of four stage I tumours and correctly classified all 45 advanced stage tumours – were not able to predict resistance to platin-based chemotherapy. Furthermore, models based on the pilot data and on previously published gene sets related to ovarian cancer outcomes, did not perform significantly better than our models. We discuss possible reasons for failure of the model for predicting response to platin-based chemotherapy and conclude that existing results based on gene expression patterns of ovarian tumours need to be thoroughly scrutinized before these results can be accepted to reflect the true performance of microarray technology

BRCA1 and BRCA2 expression patterns and prognostic significance in digestive system cancers.

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Wang, Gui-Hua; Zhao, Chun-Mei; Huang, Ying; Wang, Wei; Zhang, Shu; Wang, Xudong

2018-01-01

The role of BRCA1 and BRCA2 genes is mainly to maintain genome integrity in response to DNA damage through different mechanisms. Deregulation of BRCA1 and BRCA2 is associated with the development of tumor and altered sensitivity to chemotherapeutic agents. In this study, we determined protein expression of BRCA1 and BRCA2 in 4 digestive system cancers (gastric cancer, colorectal cancer, hepatocellular carcinoma, and pancreatic cancer) by immunohistochemistry on tissue microarrays. A total of 1546 samples of 4 types of cancer tissues, their matched adjacent nontumor tissues, and corresponding benign tissues were studied, respectively. Immunohistochemistry expression patterns of the 2 proteins and their correlation with patients' clinical parameters and overall survival were analyzed. The results showed that low expression of cytoplasmic BRCA1 and BRCA2 was commonly associated with advanced tumor-lymph node-metastasis stage, whereas high expression of nuclear BRCA1 was generally correlated with advanced tumor stages in these cancers. High expression of cytoplasmic BRCA1 and BRCA2 had significantly favorable overall survival in digestive system cancers; in contrast, BRCA1 nuclear expression usually predicted poor outcomes. We conclude that BRCA1 and BRCA2 could be used as clinicopathological biomarkers to evaluate the prognosis of digestive system cancers. Copyright © 2017 Elsevier Inc. All rights reserved.

Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

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Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

2016-01-23

Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

Disruption of an Evolutionarily Novel Synaptic Expression Pattern in Autism.

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Xiling Liu

2016-09-01

Full Text Available Cognitive defects in autism spectrum disorder (ASD include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans.

Disruption of an Evolutionarily Novel Synaptic Expression Pattern in Autism

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Jiang, Xi; Hu, Haiyang; Guijarro, Patricia; Mitchell, Amanda; Ely, John J.; Sherwood, Chet C.; Hof, Patrick R.; Qiu, Zilong; Pääbo, Svante; Akbarian, Schahram; Khaitovich, Philipp

2016-01-01

Cognitive defects in autism spectrum disorder (ASD) include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR) transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans. PMID:27685936

The Genomic Pattern of tDNA Operon Expression in E. coli.

Directory of Open Access Journals (Sweden)

2005-06-01

Full Text Available In fast-growing microorganisms, a tRNA concentration profile enriched in major isoacceptors selects for the biased usage of cognate codons. This optimizes translational rate for the least mass invested in the translational apparatus. Such translational streamlining is thought to be growth-regulated, but its genetic basis is poorly understood. First, we found in reanalysis of the E. coli tRNA profile that the degree to which it is translationally streamlined is nearly invariant with growth rate. Then, using least squares multiple regression, we partitioned tRNA isoacceptor pools to predicted tDNA operons from the E. coli K12 genome. Co-expression of tDNAs in operons explains the tRNA profile significantly better than tDNA gene dosage alone. Also, operon expression increases significantly with proximity to the origin of replication, oriC, at all growth rates. Genome location explains about 15% of expression variation in a form, at a given growth rate, that is consistent with replication-dependent gene concentration effects. Yet the change in the tRNA profile with growth rate is less than would be expected from such effects. We estimated per-copy expression rates for all tDNA operons that were consistent with independent estimates for rDNA operons. We also found that tDNA operon location, and the location dependence of expression, were significantly different in the leading and lagging strands. The operonic organization and genomic location of tDNA operons are significant factors influencing their expression. Nonrandom patterns of location and strandedness shown by tDNA operons in E. coli suggest that their genomic architecture may be under selection to satisfy physiological demand for tRNA expression at high growth rates.

Embryo quality predictive models based on cumulus cells gene expression

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Devjak R

2016-06-01

Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs

Directory of Open Access Journals (Sweden)

Sungjun Lee

2016-01-01

Full Text Available Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user’s next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user’s past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user’s next places than the previous approaches considered in most cases.

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural.

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van Prooijen, Jan-Willem; Douglas, Karen M; De Inocencio, Clara

2018-04-01

A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs.

Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural

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Douglas, Karen M.; De Inocencio, Clara

2017-01-01

Abstract A common assumption is that belief in conspiracy theories and supernatural phenomena are grounded in illusory pattern perception. In the present research we systematically tested this assumption. Study 1 revealed that such irrational beliefs are related to perceiving patterns in randomly generated coin toss outcomes. In Study 2, pattern search instructions exerted an indirect effect on irrational beliefs through pattern perception. Study 3 revealed that perceiving patterns in chaotic but not in structured paintings predicted irrational beliefs. In Study 4, we found that agreement with texts supporting paranormal phenomena or conspiracy theories predicted pattern perception. In Study 5, we manipulated belief in a specific conspiracy theory. This manipulation influenced the extent to which people perceive patterns in world events, which in turn predicted unrelated irrational beliefs. We conclude that illusory pattern perception is a central cognitive mechanism accounting for conspiracy theories and supernatural beliefs. PMID:29695889

Transcriptome profiling in conifers and the PiceaGenExpress database show patterns of diversification within gene families and interspecific conservation in vascular gene expression

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Raherison Elie

2012-08-01

Full Text Available Abstract Background Conifers have very large genomes (13 to 30 Gigabases that are mostly uncharacterized although extensive cDNA resources have recently become available. This report presents a global overview of transcriptome variation in a conifer tree and documents conservation and diversity of gene expression patterns among major vegetative tissues. Results An oligonucleotide microarray was developed from Picea glauca and P. sitchensis cDNA datasets. It represents 23,853 unique genes and was shown to be suitable for transcriptome profiling in several species. A comparison of secondary xylem and phelloderm tissues showed that preferential expression in these vascular tissues was highly conserved among Picea spp. RNA-Sequencing strongly confirmed tissue preferential expression and provided a robust validation of the microarray design. A small database of transcription profiles called PiceaGenExpress was developed from over 150 hybridizations spanning eight major tissue types. In total, transcripts were detected for 92% of the genes on the microarray, in at least one tissue. Non-annotated genes were predominantly expressed at low levels in fewer tissues than genes of known or predicted function. Diversity of expression within gene families may be rapidly assessed from PiceaGenExpress. In conifer trees, dehydrins and late embryogenesis abundant (LEA osmotic regulation proteins occur in large gene families compared to angiosperms. Strong contrasts and low diversity was observed in the dehydrin family, while diverse patterns suggested a greater degree of diversification among LEAs. Conclusion Together, the oligonucleotide microarray and the PiceaGenExpress database represent the first resource of this kind for gymnosperm plants. The spruce transcriptome analysis reported here is expected to accelerate genetic studies in the large and important group comprised of conifer trees.

Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

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Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

2014-07-28

Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

Expression Pattern of Fatty Acid Binding Proteins in Celiac Disease Enteropathy

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Natalia M. Bottasso Arias

2015-01-01

Full Text Available Celiac disease (CD is an immune-mediated enteropathy that develops in genetically susceptible individuals following exposure to dietary gluten. Severe changes at the intestinal mucosa observed in untreated CD patients are linked to changes in the level and in the pattern of expression of different genes. Fully differentiated epithelial cells express two isoforms of fatty acid binding proteins (FABPs: intestinal and liver, IFABP and LFABP, respectively. These proteins bind and transport long chain fatty acids and also have other important biological roles in signaling pathways, particularly those related to PPARγ and inflammatory processes. Herein, we analyze the serum levels of IFABP and characterize the expression of both FABPs at protein and mRNA level in small intestinal mucosa in severe enteropathy and normal tissue. As a result, we observed higher levels of circulating IFABP in untreated CD patients compared with controls and patients on gluten-free diet. In duodenal mucosa a differential FABPs expression pattern was observed with a reduction in mRNA levels compared to controls explained by the epithelium loss in severe enteropathy. In conclusion, we report changes in FABPs’ expression pattern in severe enteropathy. Consequently, there might be alterations in lipid metabolism and the inflammatory process in the small intestinal mucosa.

Integrating circadian activity and gene expression profiles to predict chronotoxicity of Drosophila suzukii response to insecticides.

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Hamby, Kelly A; Kwok, Rosanna S; Zalom, Frank G; Chiu, Joanna C

2013-01-01

Native to Southeast Asia, Drosophila suzukii (Matsumura) is a recent invader that infests intact ripe and ripening fruit, leading to significant crop losses in the U.S., Canada, and Europe. Since current D. suzukii management strategies rely heavily on insecticide usage and insecticide detoxification gene expression is under circadian regulation in the closely related Drosophila melanogaster, we set out to determine if integrative analysis of daily activity patterns and detoxification gene expression can predict chronotoxicity of D. suzukii to insecticides. Locomotor assays were performed under conditions that approximate a typical summer or winter day in Watsonville, California, where D. suzukii was first detected in North America. As expected, daily activity patterns of D. suzukii appeared quite different between 'summer' and 'winter' conditions due to differences in photoperiod and temperature. In the 'summer', D. suzukii assumed a more bimodal activity pattern, with maximum activity occurring at dawn and dusk. In the 'winter', activity was unimodal and restricted to the warmest part of the circadian cycle. Expression analysis of six detoxification genes and acute contact bioassays were performed at multiple circadian times, but only in conditions approximating Watsonville summer, the cropping season, when most insecticide applications occur. Five of the genes tested exhibited rhythmic expression, with the majority showing peak expression at dawn (ZT0, 6am). We observed significant differences in the chronotoxicity of D. suzukii towards malathion, with highest susceptibility at ZT0 (6am), corresponding to peak expression of cytochrome P450s that may be involved in bioactivation of malathion. High activity levels were not found to correlate with high insecticide susceptibility as initially hypothesized. Chronobiology and chronotoxicity of D. suzukii provide valuable insights for monitoring and control efforts, because insect activity as well as insecticide timing

"Eyeball test" of thermographic patterns for predicting a successful lateral infraclavicular block.

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Andreasen, Asger M; Linnet, Karen E; Asghar, Semera; Rothe, Christian; Rosenstock, Charlotte V; Lange, Kai H W; Lundstrøm, Lars H

2017-11-01

Increased distal skin temperature can be used to predict the success of lateral infraclavicular (LIC) block. We hypothesized that an "eyeball test" of specific infrared thermographic patterns after LIC block could be used to determine block success. In this observational study, five observers trained in four distinct thermographic patterns independently evaluated thermographic images of the hands of 40 patients at baseline and at one-minute intervals for 30 min after a LIC block. Sensitivity, specificity, and predictive values of a positive and a negative test were estimated to evaluate the validity of specific thermographic patterns for predicting a successful block. Sensory and motor block of the musculocutaneous, radial, ulnar, and median nerves defined block success. Fleiss' kappa statistics of multiple interobserver agreements were used to evaluate reliability. As a diagnostic test, the defined specific thermographic patterns of the hand predicted a successful block with increasing accuracy over the 30-min observation period. Block success was predicted with a sensitivity of 92.4% (95% confidence interval [CI], 86.8 to 96.2) and with a specificity of 84.0% (95% CI, 70.3 to 92.4) at min 30. The Fleiss' kappa for the five observers was 0.87 (95% CI, 0.77 to 0.96). We conclude that visual evaluation by an eyeball test of specific thermographic patterns of the blocked hands may be useful as a valid and reliable diagnostic test for predicting a successful LIC block.

F-spondin/spon1b expression patterns in developing and adult zebrafish.

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Veronica Akle

Full Text Available F-spondin, an extracellular matrix protein, is an important player in embryonic morphogenesis and CNS development, but its presence and role later in life remains largely unknown. We generated a transgenic zebrafish in which GFP is expressed under the control of the F-spondin (spon1b promoter, and used it in combination with complementary techniques to undertake a detailed characterization of the expression patterns of F-spondin in developing and adult brain and periphery. We found that F-spondin is often associated with structures forming long neuronal tracts, including retinal ganglion cells, the olfactory bulb, the habenula, and the nucleus of the medial longitudinal fasciculus (nMLF. F-spondin expression coincides with zones of adult neurogenesis and is abundant in CSF-contacting secretory neurons, especially those in the hypothalamus. Use of this new transgenic model also revealed F-spondin expression patterns in the peripheral CNS, notably in enteric neurons, and in peripheral tissues involved in active patterning or proliferation in adults, including the endoskeleton of zebrafish fins and the continuously regenerating pharyngeal teeth. Moreover, patterning of the regenerating caudal fin following fin amputation in adult zebrafish was associated with F-spondin expression in the blastema, a proliferative region critical for tissue reconstitution. Together, these findings suggest major roles for F-spondin in the CNS and periphery of the developing and adult vertebrate.

Glyoxalase I expression pattern in Hevea brasiliensis seedlings ...

African Journals Online (AJOL)

Glyoxalase I expression pattern in Hevea brasiliensis seedlings under varied stress conditions. MVP Siraj, A Thulaseedharan, Anu Augustine. Abstract. Drought is one of the most important stress factors which adversely affect plants' growth and productivity. Global climate change may make this situation more serious in the ...

Multiple Suboptimal Solutions for Prediction Rules in Gene Expression Data

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Osamu Komori

2013-01-01

Full Text Available This paper discusses mathematical and statistical aspects in analysis methods applied to microarray gene expressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray gene expression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence.

Defining global neuroendocrine gene expression patterns associated with reproductive seasonality in fish.

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Dapeng Zhang

Full Text Available BACKGROUND: Many vertebrates, including the goldfish, exhibit seasonal reproductive rhythms, which are a result of interactions between external environmental stimuli and internal endocrine systems in the hypothalamo-pituitary-gonadal axis. While it is long believed that differential expression of neuroendocrine genes contributes to establishing seasonal reproductive rhythms, no systems-level investigation has yet been conducted. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, by analyzing multiple female goldfish brain microarray datasets, we have characterized global gene expression patterns for a seasonal cycle. A core set of genes (873 genes in the hypothalamus were identified to be differentially expressed between May, August and December, which correspond to physiologically distinct stages that are sexually mature (prespawning, sexual regression, and early gonadal redevelopment, respectively. Expression changes of these genes are also shared by another brain region, the telencephalon, as revealed by multivariate analysis. More importantly, by examining one dataset obtained from fish in October who were kept under long-daylength photoperiod (16 h typical of the springtime breeding season (May, we observed that the expression of identified genes appears regulated by photoperiod, a major factor controlling vertebrate reproductive cyclicity. Gene ontology analysis revealed that hormone genes and genes functionally involved in G-protein coupled receptor signaling pathway and transmission of nerve impulses are significantly enriched in an expression pattern, whose transition is located between prespawning and sexually regressed stages. The existence of seasonal expression patterns was verified for several genes including isotocin, ependymin II, GABA(A gamma2 receptor, calmodulin, and aromatase b by independent samplings of goldfish brains from six seasonal time points and real-time PCR assays. CONCLUSIONS/SIGNIFICANCE: Using both

Patterns of Emotion Experiences as Predictors of Facial Expressions of Emotion.

Science.gov (United States)

Blumberg, Samuel H.; Izard, Carroll E.

1991-01-01

Examined the relations between emotion and facial expressions of emotion in 8- to 12-year-old male psychiatric patients. Results indicated that patterns or combinations of emotion experiences had an impact on facial expressions of emotion. (Author/BB)

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

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Zeng, Tao; Li, Rongjian; Mukkamala, Ravi; Ye, Jieping; Ji, Shuiwang

2015-05-07

Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D in situ hybridization (ISH) gene expression patterns in multiple developing stages of the mouse brain. Currently, the ISH images are annotated with anatomical terms manually. In this paper, we propose a computational approach to annotate gene expression pattern images in the mouse brain at various structural levels over the course of development. We applied deep convolutional neural network that was trained on a large set of natural images to extract features from the ISH images of developing mouse brain. As a baseline representation, we applied invariant image feature descriptors to capture local statistics from ISH images and used the bag-of-words approach to build image-level representations. Both types of features from multiple ISH image sections of the entire brain were then combined to build 3-D, brain-wide gene expression representations. We employed regularized learning methods for discriminating gene expression patterns in different brain structures. Results show that our approach of using convolutional model as feature extractors achieved superior performance in annotating gene expression patterns at multiple levels of brain structures throughout four developing ages. Overall, we achieved average AUC of 0.894 ± 0.014, as compared with 0.820 ± 0.046 yielded by the bag-of-words approach. Deep convolutional neural network model trained on natural image sets and applied to gene expression pattern annotation tasks yielded superior performance, demonstrating its transfer learning property is applicable to such biological image sets.

Energy prediction using spatiotemporal pattern networks

Energy Technology Data Exchange (ETDEWEB)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

2017-11-01

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

Characterization and expression patterns of a membrane-bound trehalase from Spodoptera exigua

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Xu Weihua

2008-05-01

Full Text Available Abstract Background The chitin biosynthesis pathway starts with trehalose in insects and the main functions of trehalases are hydrolysis of trehalose to glucose. Although insects possess two types, soluble trehalase (Tre-1 and membrane-bound trehalase (Tre-2, very little is known about Tre-2 and the difference in function between Tre-1 and Tre-2. Results To gain an insight into trehalase functions in insects, we investigated a putative membrane-bound trehalase from Spodoptera exigua (SeTre-2 cloned from the fat body. The deduced amino acid sequence of SeTre-2 contains 645 residues and has a predicted molecular weight of ~74 kDa and pI of 6.01. Alignment of SeTre-2 with other insect trehalases showed that it contains two trehalase signature motifs and a putative transmembrane domain, which is an important characteristic of Tre-2. Comparison of the genomic DNA and cDNA sequences demonstrated that SeTre-2 comprises 13 exons and 12 introns. Southern blot analysis revealed that S. exigua has two trehalase genes and that SeTre-2 is a single-copy gene. Northern blot analyses showed that the SeTre-2 transcript is expressed not only in the midgut, as previously reported for Bombyx mori, but also in the fat body and Malpighian tubules, although expression patterns differed between the midgut and fat body. SeTre-2 transcripts were detected in the midgut of feeding stage larvae, but not in pupae, whereas SeTre-2 mRNA was detected in the fat body of fifth instar larvae and pupae. Conclusion These findings provide new data on the tissue distribution, expression patterns and potential function of membrane-bound trehalase. The results suggest that the SeTre-2 gene may have different functions in the midgut and fat body.

Pattern-oriented modelling: a 'multi-scope' for predictive systems ecology.

Science.gov (United States)

Grimm, Volker; Railsback, Steven F

2012-01-19

Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.

Prediction of highly expressed genes in microbes based on chromatin accessibility

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Ussery David W

2007-02-01

Full Text Available Abstract Background It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed genes in microbial genomes. We compare these predictions with those based on codon adaptation index (CAI values, and also with experimental data for 6 different microbial genomes, with a particular interest in experimental data from Escherichia coli. Moreover, position preference is examined further in 328 sequenced microbial genomes. Results We find that absolute gene expression levels are correlated with the position preference in many microbial genomes. It is postulated that in these regions, the DNA may be more accessible to the transcriptional machinery. Moreover, ribosomal proteins and ribosomal RNA are encoded by DNA having significantly lower position preference values than other genes in fast-replicating microbes. Conclusion This insight into DNA structure-dependent gene expression in microbes may be exploited for predicting the expression of non-translated genes such as non-coding RNAs that may not be predicted by any of the conventional codon usage bias approaches.

Gene expression patterns of oxidative phosphorylation complex I subunits are organized in clusters.

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Yael Garbian

Full Text Available After the radiation of eukaryotes, the NUO operon, controlling the transcription of the NADH dehydrogenase complex of the oxidative phosphorylation system (OXPHOS complex I, was broken down and genes encoding this protein complex were dispersed across the nuclear genome. Seven genes, however, were retained in the genome of the mitochondrion, the ancient symbiote of eukaryotes. This division, in combination with the three-fold increase in subunit number from bacteria (N = approximately 14 to man (N = 45, renders the transcription regulation of OXPHOS complex I a challenge. Recently bioinformatics analysis of the promoter regions of all OXPHOS genes in mammals supported patterns of co-regulation, suggesting that natural selection favored a mechanism facilitating the transcriptional regulatory control of genes encoding subunits of these large protein complexes. Here, using real time PCR of mitochondrial (mtDNA- and nuclear DNA (nDNA-encoded transcripts in a panel of 13 different human tissues, we show that the expression pattern of OXPHOS complex I genes is regulated in several clusters. Firstly, all mtDNA-encoded complex I subunits (N = 7 share a similar expression pattern, distinct from all tested nDNA-encoded subunits (N = 10. Secondly, two sub-clusters of nDNA-encoded transcripts with significantly different expression patterns were observed. Thirdly, the expression patterns of two nDNA-encoded genes, NDUFA4 and NDUFA5, notably diverged from the rest of the nDNA-encoded subunits, suggesting a certain degree of tissue specificity. Finally, the expression pattern of the mtDNA-encoded ND4L gene diverged from the rest of the tested mtDNA-encoded transcripts that are regulated by the same promoter, consistent with post-transcriptional regulation. These findings suggest, for the first time, that the regulation of complex I subunits expression in humans is complex rather than reflecting global co-regulation.

Expression patterns of the aquaporin gene family during renal development: influence of genetic variability.

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Parreira, Kleber S; Debaix, Huguette; Cnops, Yvette; Geffers, Lars; Devuyst, Olivier

2009-08-01

High-throughput analyses have shown that aquaporins (AQPs) belong to a cluster of genes that are differentially expressed during kidney organogenesis. However, the spatiotemporal expression patterns of the AQP gene family during tubular maturation and the potential influence of genetic variation on these patterns and on water handling remain unknown. We investigated the expression patterns of all AQP isoforms in fetal (E13.5 to E18.5), postnatal (P1 to P28), and adult (9 weeks) kidneys of inbred (C57BL/6J) and outbred (CD-1) mice. Using quantitative polymerase chain reaction (PCR), we evidenced two mRNA patterns during tubular maturation in C57 mice. The AQPs 1-7-11 showed an early (from E14.5) and progressive increase to adult levels, similar to the mRNA pattern observed for proximal tubule markers (Megalin, NaPi-IIa, OAT1) and reflecting the continuous increase in renal cortical structures during development. By contrast, AQPs 2-3-4 showed a later (E15.5) and more abrupt increase, with transient postnatal overexpression. Most AQP genes were expressed earlier and/or stronger in maturing CD-1 kidneys. Furthermore, adult CD-1 kidneys expressed more AQP2 in the collecting ducts, which was reflected by a significant delay in excreting a water load. The expression patterns of proximal vs. distal AQPs and the earlier expression in the CD-1 strain were confirmed by immunoblotting and immunostaining. These data (1) substantiate the clustering of important genes during tubular maturation and (2) demonstrate that genetic variability influences the regulation of the AQP gene family during tubular maturation and water handling by the mature kidney.

Systematic analysis of gene expression pattern in has-miR-197 over-expressed human uterine leiomyoma cells.

Science.gov (United States)

Ling, Jing; Wu, Xiaoli; Fu, Ziyi; Tan, Jie; Xu, Qing

2015-10-01

, FBLN2, C10orf35, HOXD12, CACNG7, and LOC100134279. Our study explored gene expression patterns after miR-197 overexpression and confirmed 17 dominantly dys-regulated genes, which could expand the insights into the function of miR-197 and the molecular mechanisms during the development and progression of uterine leiomyomas. This study might afford new clues for understanding the pathogenesis of uterine leiomyomas, and it could likely provide a unique method for diagnosing or predicting prognosis in the clinical treatment of leiomyoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Cyclooxygenase-2 expression in the normal human eye and its expression pattern in selected eye tumours

DEFF Research Database (Denmark)

Wang, Jinmei; Wu, Yazhen; Heegaard, Steffen

2011-01-01

Purpose: Cyclooxygenase-2 (COX-2) is an enzyme involved in neoplastic processes. The purpose of the present study is to investigate COX-2 expression in the normal human eye and the expression pattern in selected eye tumours involving COX-2 expressing cells. Methods: Immunohistochemical staining...... using antibodies against COX-2 was performed on paraffin sections of normal human eyes and selected eye tumours arising from cells expressing COX-2. Results: Cyclooxygenase-2 expression was found in various structures of the normal eye. Abundant expression was seen in the cornea, iris, ciliary body...... and retina. The COX-2 expression was less in tumours deriving from the ciliary epithelium and also in retinoblastoma. Conclusion: Cyclooxygenase-2 is constitutively expressed in normal human eyes. The expression of COX-2 is much lower in selected eye tumours involving COX-2 expressing cells....

Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

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Zhang, Tuantuan; Huang, Bohua; Yang, Song; Laohalertchai, Charoon

2018-06-01

The seasonal dependence of the prediction skill of 850-hPa monthly zonal wind over the tropical Indo-Pacific domain is examined using the ensemble reforecasts for 1983-2010 from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis and Reforecast (CFSRR) project. According to a maximum signal-to-noise empirical orthogonal function analysis, the most predictable patterns of atmospheric low-level circulation are associated with the developing and maturing phases of El Niño-Southern Oscillation (ENSO). The CFSv2 is capable of predicting these ENSO-related patterns up to 9-months in advance for all months, except for May-June when the effect of the spring barrier is strong. The other predictable climate processes associated with the low-level atmospheric circulation are more seasonally dependent. For winter and spring, the second most predictable patterns are associated with the ENSO decaying phase. Within these seasons, the monthly evolution of the predictable patterns is characterized by a southward shift of westerly wind anomalies, generated by the interaction between the annual cycle and the ENSO signals (i.e., the combination-mode). In general, the CFSv2 hindcast well predicts these patterns at least 5 months in advance for spring, while shows much lower skills for winter months. In summer, the second predictable patterns are associated with the western North Pacific (WNP) monsoon (i.e., the WNP anticyclone/cyclone) in short leads while associated with ENSO in longer leads (after 4-month lead). The second predictable patterns in fall are mainly associated with tropical Indian Ocean Dipole, which can be predicted 3 months in advance.

A strategy for full interrogation of prognostic gene expression patterns: exploring the biology of diffuse large B cell lymphoma.

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Lisa M Rimsza

Full Text Available Gene expression profiling yields quantitative data on gene expression used to create prognostic models that accurately predict patient outcome in diffuse large B cell lymphoma (DLBCL. Often, data are analyzed with genes classified by whether they fall above or below the median expression level. We sought to determine whether examining multiple cut-points might be a more powerful technique to investigate the association of gene expression with outcome.We explored gene expression profiling data using variable cut-point analysis for 36 genes with reported prognostic value in DLBCL. We plotted two-group survival logrank test statistics against corresponding cut-points of the gene expression levels and smooth estimates of the hazard ratio of death versus gene expression levels. To facilitate comparisons we also standardized the expression of each of the genes by the fraction of patients that would be identified by any cut-point. A multiple comparison adjusted permutation p-value identified 3 different patterns of significance: 1 genes with significant cut-point points below the median, whose loss is associated with poor outcome (e.g. HLA-DR; 2 genes with significant cut-points above the median, whose over-expression is associated with poor outcome (e.g. CCND2; and 3 genes with significant cut-points on either side of the median, (e.g. extracellular molecules such as FN1.Variable cut-point analysis with permutation p-value calculation can be used to identify significant genes that would not otherwise be identified with median cut-points and may suggest biological patterns of gene effects.

Expression Patterns and Potential Biological Roles of Dip2a.

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Luqing Zhang

Full Text Available Disconnected (disco-interacting protein 2 homolog A is a member of the DIP2 protein family encoded by Dip2a gene. Dip2a expression pattern has never been systematically studied. Functions of Dip2a in embryonic development and adult are not known. To investigate Dip2a gene expression and function in embryo and adult, a Dip2a-LacZ mouse model was generated by insertion of β-Gal cDNA after Dip2a promoter using CRISPR/Cas9 technology. Dip2a-LacZ mouse was designed to be a lacZ reporter mouse as well as a Dip2a knockout mouse. Heterozygous mice were used to study endogenous Dip2a expression and homozygotes to study DIP2A-associated structure and function. LacZ staining indicated that Dip2a is broadly expressed in neuronal, reproductive and vascular tissues, as well as in heart, kidney, liver and lung. Results demonstrate that Dip2a is expressed in ectoderm-derived tissues in developing embryos. Adult tissues showed rich staining in neurons, mesenchymal, endothelial, smooth muscle cells and cardiomyocytes by cell types. The expression pattern highly overlaps with FSTL1 and supports previous report that DIP2A to be potential receptor of FSTL1 and its protective roles of cardiomyocytes. Broad and intense embryonic and adult expression of Dip2a has implied their multiple structural and physiological roles.

The pattern of cognitive symptoms predicts time to dementia onset.

NARCIS (Netherlands)

Sacuiu, S.; Gustafson, D.; Johansson, B.; Thorvaldsson, V.; Berg, S.; Sjogren, J.M.C.; Guo, X.; Ostling, S.; Skoog, I.

2009-01-01

BACKGROUND: Few studies have examined whether cognitive symptom patterns differ by age and length of time before dementia onset. Our objective was to investigate whether different patterns of cognitive symptoms at ages 70, 75, and 79 years predict short-term (< or =5 years) and long-term (>5 years)

Gene expression patterns in blood leukocytes discriminate patients with acute infections

Science.gov (United States)

Allman, Windy; Chung, Wendy; Mejias, Asuncion; Ardura, Monica; Glaser, Casey; Wittkowski, Knut M.; Piqueras, Bernard; Banchereau, Jacques; Palucka, A. Karolina; Chaussabel, Damien

2007-01-01

Each infectious agent represents a unique combination of pathogen-associated molecular patterns that interact with specific pattern-recognition receptors expressed on immune cells. Therefore, we surmised that the blood immune cells of individuals with different infections might bear discriminative transcriptional signatures. Gene expression profiles were obtained for 131 peripheral blood samples from pediatric patients with acute infections caused by influenza A virus, Gram-negative (Escherichia coli) or Gram-positive (Staphylococcus aureus and Streptococcus pneumoniae) bacteria. Thirty-five genes were identified that best discriminate patients with influenza A virus infection from patients with either E coli or S pneumoniae infection. These genes classified with 95% accuracy (35 of 37 samples) an independent set of patients with either influenza A, E coli, or S pneumoniae infection. A different signature discriminated patients with E coli versus S aureus infections with 85% accuracy (34 of 40). Furthermore, distinctive gene expression patterns were observed in patients presenting with respiratory infections of different etiologies. Thus, microarray analyses of patient peripheral blood leukocytes might assist in the differential diagnosis of infectious diseases. PMID:17105821

Ngram-derived pattern recognition for the detection and prediction of epileptic seizures.

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Amir Eftekhar

Full Text Available This work presents a new method that combines symbol dynamics methodologies with an Ngram algorithm for the detection and prediction of epileptic seizures. The presented approach specifically applies Ngram-based pattern recognition, after data pre-processing, with similarity metrics, including the Hamming distance and Needlman-Wunsch algorithm, for identifying unique patterns within epochs of time. Pattern counts within each epoch are used as measures to determine seizure detection and prediction markers. Using 623 hours of intracranial electrocorticogram recordings from 21 patients containing a total of 87 seizures, the sensitivity and false prediction/detection rates of this method are quantified. Results are quantified using individual seizures within each case for training of thresholds and prediction time windows. The statistical significance of the predictive power is further investigated. We show that the method presented herein, has significant predictive power in up to 100% of temporal lobe cases, with sensitivities of up to 70-100% and low false predictions (dependant on training procedure. The cases of highest false predictions are found in the frontal origin with 0.31-0.61 false predictions per hour and with significance in 18 out of 21 cases. On average, a prediction sensitivity of 93.81% and false prediction rate of approximately 0.06 false predictions per hour are achieved in the best case scenario. This compares to previous work utilising the same data set that has shown sensitivities of up to 40-50% for a false prediction rate of less than 0.15/hour.

Vertebrate Left-Right Asymmetry: What Can Nodal Cascade Gene Expression Patterns Tell Us?

Science.gov (United States)

Schweickert, Axel; Ott, Tim; Kurz, Sabrina; Tingler, Melanie; Maerker, Markus; Fuhl, Franziska; Blum, Martin

2017-12-29

Laterality of inner organs is a wide-spread characteristic of vertebrates and beyond. It is ultimately controlled by the left-asymmetric activation of the Nodal signaling cascade in the lateral plate mesoderm of the neurula stage embryo, which results from a cilia-driven leftward flow of extracellular fluids at the left-right organizer. This scenario is widely accepted for laterality determination in wildtype specimens. Deviations from this norm come in different flavors. At the level of organ morphogenesis, laterality may be inverted (situs inversus) or non-concordant with respect to the main body axis (situs ambiguus or heterotaxia). At the level of Nodal cascade gene activation, expression may be inverted, bilaterally induced, or absent. In a given genetic situation, patterns may be randomized or predominantly lacking laterality (absence or bilateral activation). We propose that the distributions of patterns observed may be indicative of the underlying molecular defects, with randomizations being primarily caused by defects in the flow-generating ciliary set-up, and symmetrical patterns being the result of impaired flow sensing, on the left, the right, or both sides. This prediction, the reasoning of which is detailed in this review, pinpoints functions of genes whose role in laterality determination have remained obscure.

Dynamic expression pattern of kinesin accessory protein in Drosophila

Indian Academy of Sciences (India)

Unknown

terization of the function of the DmKAP gene, we studied its expression pattern at different stages of development using the mRNA in .... region of the developing brain. ..... Kido M and Hirokawa N 1998 Randomization of left-right asymmetry ...

Predicting Expressive Dynamics in Piano Performances using Neural Networks

NARCIS (Netherlands)

van Herwaarden, Sam; Grachten, Maarten; de Haas, W. Bas

2014-01-01

This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data

Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure.

Science.gov (United States)

Ghosh, Shameek; Feng, Mengling; Nguyen, Hung; Li, Jinyan

2016-09-01

Acute hypotension is a significant risk factor for in-hospital mortality at intensive care units. Prolonged hypotension can cause tissue hypoperfusion, leading to cellular dysfunction and severe injuries to multiple organs. Prompt medical interventions are thus extremely important for dealing with acute hypotensive episodes (AHE). Population level prognostic scoring systems for risk stratification of patients are suboptimal in such scenarios. However, the design of an efficient risk prediction system can significantly help in the identification of critical care patients, who are at risk of developing an AHE within a future time span. Toward this objective, a pattern mining algorithm is employed to extract informative sequential contrast patterns from hemodynamic data, for the prediction of hypotensive episodes. The hypotensive and normotensive patient groups are extracted from the MIMIC-II critical care research database, following an appropriate clinical inclusion criteria. The proposed method consists of a data preprocessing step to convert the blood pressure time series into symbolic sequences, using a symbolic aggregate approximation algorithm. Then, distinguishing subsequences are identified using the sequential contrast mining algorithm. These subsequences are used to predict the occurrence of an AHE in a future time window separated by a user-defined gap interval. Results indicate that the method performs well in terms of the prediction performance as well as in the generation of sequential patterns of clinical significance. Hence, the novelty of sequential patterns is in their usefulness as potential physiological biomarkers for building optimal patient risk stratification systems and for further clinical investigation of interesting patterns in critical care patients.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

Science.gov (United States)

Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

VESPUCCI: exploring patterns of gene expression in grapevine

Directory of Open Access Journals (Sweden)

Marco eMoretto

2016-05-01

Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing gene expression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a gene expression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex gene expression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 gene expression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

Patterns, Entropy, and Predictability of Human Mobility and Life

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Qin, Shao-Meng; Verkasalo, Hannu; Mohtaschemi, Mikael; Hartonen, Tuomo; Alava, Mikko

2012-01-01

Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the social context and the related interactions. The picture of human life that emerges shows complexity, which is manifested in such data in properties of the spatiotemporal tracks of individuals. We extract from smartphone-based data for a set of persons important locations such as “home”, “work” and so forth over fixed length time-slots covering the days in the data-set (see also [1], [2]). This set of typical places is heavy-tailed, a power-law distribution with an exponent close to −1.7. To analyze the regularities and stochastic features present, the days are classified for each person into regular, personal patterns. To this are superimposed fluctuations for each day. This randomness is measured by “life” entropy, computed both before and after finding the clustering so as to subtract the contribution of a number of patterns. The main issue that we then address is how predictable individuals are in their mobility. The patterns and entropy are reflected in the predictability of the mobility of the life both individually and on average. We explore the simple approaches to guess the location from the typical behavior, and of exploiting the transition probabilities with time from location or activity A to B. The patterns allow an enhanced predictability, at least up to a few hours into the future from the current location. Such fixed habits are most clearly visible in the working-day length. PMID:23300542

Facial Expressivity at 4 Months: A Context by Expression Analysis.

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Bennett, David S; Bendersky, Margaret; Lewis, Michael

2002-01-01

The specificity predicted by differential emotions theory (DET) for early facial expressions in response to 5 different eliciting situations was studied in a sample of 4-month-old infants (n = 150). Infants were videotaped during tickle, sour taste, jack-in-the-box, arm restraint, and masked-stranger situations and their expressions were coded second by second. Infants showed a variety of facial expressions in each situation; however, more infants exhibited positive (joy and surprise) than negative expressions (anger, disgust, fear, and sadness) across all situations except sour taste. Consistent with DET-predicted specificity, joy expressions were the most common in response to tickling, and were less common in response to other situations. Surprise expressions were the most common in response to the jack-in-the-box, as predicted, but also were the most common in response to the arm restraint and masked-stranger situations, indicating a lack of specificity. No evidence of predicted specificity was found for anger, disgust, fear, and sadness expressions. Evidence of individual differences in expressivity within situations, as well as stability in the pattern across situations, underscores the need to examine both child and contextual factors in studying emotional development. The results provide little support for the DET postulate of situational specificity and suggest that a synthesis of differential emotions and dynamic systems theories of emotional expression should be considered.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

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Richard Danger

2018-01-01

Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Alteration of protein expression pattern of vascular endothelial growth factor (VEGF) from soluble to cell-associated isoform during tumourigenesis

International Nuclear Information System (INIS)

Cressey, Ratchada; Wattananupong, Onusa; Lertprasertsuke, Nirush; Vinitketkumnuen, Usanee

2005-01-01

Vascular endothelial growth factor (VEGF) is a potent mitogen for endothelial cells, and its expression has been correlated with increased tumour angiogenesis. Although numerous publications dealing with the measurement of circulating VEGF for diagnostic and therapeutic monitoring have been published, the relationship between the production of tissue VEGF and its concentration in blood is still unclear. The aims of this study were to determine: 1) The expression pattern of VEGF isoforms at the protein level in colorectal and lung adenocarcinoma in comparison to the pattern in corresponding adjacent normal tissues 2) The relationship between the expression pattern of VEGF and total level of circulating VEGF in the blood to clarify whether the results of measuring circulating VEGF can be used to predict VEGF expression in tumour tissues. Ninety-four tissue samples were obtained from patients, 76 colorectal tumour tissues and 18 lung tumour tissues. VEGF protein expression pattern and total circulating VEGF were examined using western blot and capture ELISA, respectively. Three major protein bands were predominately detected in tumour samples with an apparent molecular mass under reducing conditions of 18, 23 and 26 kDa. The 18 kDa VEGF protein was expressed equally in both normal and colorectal tumour tissues and predominately expressed in normal tissues of lung, whereas the 23 and 26 kDa protein was only detected at higher levels in tumour tissues. The 18, 23 and 26 kDa proteins are believed to represent the VEGF 121 , the VEGF 165 and the VEGF 189 , respectively. There was a significant correlation of the expression of VEGF 165 with a smaller tumour size maximum diameter <5 cm (p < 0.05), and there was a significant correlation of VEGF 189 with advanced clinical stage of colorectal tumours. The measurement of total circulating VEGF in serum revealed that cancer patients significantly (p < 0.001) possessed a higher level of circulating VEGF (1081 ± 652 pg/ml in

Predictable patterns of the May-June rainfall anomaly over East Asia

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Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Emotional facial expressions differentially influence predictions and performance for face recognition.

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Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

2013-01-01

This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

A study on effects of cash flow patterns and auditors’ opinions in predicting financial distress

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Fatemeh Namvar

2013-07-01

Full Text Available Bankruptcy has been one of the most important issues among investors in stock market and there are literally different techniques for predicting bankruptcy. In this paper, we study on effects of cash flow patterns and auditors’ opinions in predicting financial distress on some 80 selected firms traded on Tehran Stock Exchange over the period 2005-2011. In this study, the combination of cash flow patterns represent firm’s resource allocations and operational capabilities interacted with their strategy choices. In additions, predictions about each individual cash flow components, operational, investment, financial, are derived from economic theory, which forms a basis for the life proxy. We use cash flow patterns in the decline stage and compare the results with auditors’ opinions. The results indicate that cash flow patterns could predict financial distress companies in Iran. In addition, the effective cash flow patterns in predicting financial distress is more than auditors’ feedbacks.

Expression profile of the Schistosoma japonicum degradome reveals differential protease expression patterns and potential anti-schistosomal intervention targets.

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Shuai Liu

2014-10-01

Full Text Available Blood fluke proteases play pivotal roles in the processes of invasion, nutrition acquisition, immune evasion, and other host-parasite interactions. Hundreds of genes encoding putative proteases have been identified in the recently published schistosome genomes. However, the expression profiles of these proteases in Schistosoma species have not yet been systematically analyzed. We retrieved and culled the redundant protease sequences of Schistosoma japonicum, Schistosoma mansoni, Echinococcus multilocularis, and Clonorchis sinensis from public databases utilizing bioinformatic approaches. The degradomes of the four parasitic organisms and Homo sapiens were then comparatively analyzed. A total of 262 S. japonicum protease sequences were obtained and the expression profiles generated using whole-genome microarray. Four main clusters of protease genes with different expression patterns were identified: proteases up-regulated in hepatic schistosomula and adult worms, egg-specific or predominantly expressed proteases, cercaria-specific or predominantly expressed proteases, and constantly expressed proteases. A subset of protease genes with different expression patterns were further validated using real-time quantitative PCR. The present study represents the most comprehensive analysis of a degradome in Schistosoma species to date. These results provide a firm foundation for future research on the specific function(s of individual proteases and may help to refine anti-proteolytic strategies in blood flukes.

Data Integration for Spatio-Temporal Patterns of Gene Expression of Zebrafish development: the GEMS database

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Belmamoune Mounia

2008-06-01

Full Text Available The Gene Expression Management System (GEMS is a database system for patterns of gene expression. These patterns result from systematic whole-mount fluorescent in situ hybridization studies on zebrafish embryos. GEMS is an integrative platform that addresses one of the important challenges of developmental biology: how to integrate genetic data that underpin morphological changes during embryogenesis. Our motivation to build this system was by the need to be able to organize and compare multiple patterns of gene expression at tissue level. Integration with other developmental and biomolecular databases will further support our understanding of development. The GEMS operates in concert with a database containing a digital atlas of zebrafish embryo; this digital atlas of zebrafish development has been conceived prior to the expansion of the GEMS. The atlas contains 3D volume models of canonical stages of zebrafish development in which in each volume model element is annotated with an anatomical term. These terms are extracted from a formal anatomical ontology, i.e. the Developmental Anatomy Ontology of Zebrafish (DAOZ. In the GEMS, anatomical terms from this ontology together with terms from the Gene Ontology (GO are also used to annotate patterns of gene expression and in this manner providing mechanisms for integration and retrieval . The annotations are the glue for integration of patterns of gene expression in GEMS as well as in other biomolecular databases. At the one hand, zebrafish anatomy terminology allows gene expression data within GEMS to be integrated with phenotypical data in the 3D atlas of zebrafish development. At the other hand, GO terms extend GEMS expression patterns integration to a wide range of bioinformatics resources.

Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology

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Grimm, Volker; Railsback, Steven F.

2012-01-01

Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions. PMID:22144392

Histone modification profiles are predictive for tissue/cell-type specific expression of both protein-coding and microRNA genes

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Zhang Michael Q

2011-05-01

Full Text Available Abstract Background Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV and TCSR. Results A classifier for differentiating CD4+ T cell-specific genes from housekeeping genes using HMV data was built. We found HMV in both promoter and gene body regions to be predictive of genes which are targets of TCSR. For example, the histone modification types H3K4me3 and H3K27ac were identified as the most predictive for CpG-related promoters, whereas H3K4me3 and H3K79me3 were the most predictive for nonCpG-related promoters. However, genes targeted by TCSR can be predicted using other type of HMVs as well. Such redundancy implies that multiple type of underlying regulatory elements, such as enhancers or intragenic alternative promoters, which can regulate gene expression in a tissue/cell-type specific fashion, may be marked by the HMVs. Finally, we show that the predictive power of HMV for TCSR is not limited to protein-coding genes in CD4+ T cells, as we successfully predicted TCSR targeted genes in muscle cells, as well as microRNA genes with expression specific to CD4+ T cells, by the same classifier which was trained on HMV data of protein-coding genes in CD4+ T cells. Conclusion We have begun to understand the HMV patterns that guide gene expression in both tissue/cell-type specific and ubiquitous manner.

Predictive Modeling of Expressed Emotions in Music Using Pairwise Comparisons

DEFF Research Database (Denmark)

Madsen, Jens; Jensen, Bjørn Sand; Larsen, Jan

2013-01-01

We introduce a two-alternative forced-choice (2AFC) experimental paradigm to quantify expressed emotions in music using the arousal and valence (AV) dimensions. A wide range of well-known audio features are investigated for predicting the expressed emotions in music using learning curves...... and essential baselines. We furthermore investigate the scalability issues of using 2AFC in quantifying emotions expressed in music on large-scale music databases. The possibility of dividing the annotation task between multiple individuals, while pooling individuals’ comparisons is investigated by looking...... comparisons at random by using learning curves. We show that a suitable predictive model of expressed valence in music can be achieved from only 15% of the total number of comparisons when using the Expected Value of Information (EVOI) active learning scheme. For the arousal dimension we require 9...

Depression, self-esteem and anger expression patterns of Korean nursing students.

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Cha, N H; Sok, S R

2014-03-01

According to previous studies, nursing students' anger expression patterns, depression and self-esteem significantly affected the physical and mental well-being of patients. It is of utmost importance that the relationship among them is thoroughly investigated in this study. The purpose of this study was to examine the degrees of anger expression patterns, depression and self-esteem of Korean nursing students and to examine the correlations among them. This was a descriptive cross-sectional study. The subjects consisted of 320 Korean nursing students at colleges in S and G city, Korea. The measurements were based on the Korean standard STAXI (State-Trait Anger Expression Inventory), SCL-90-R (Symptom Checklist-90-Revision) and SLCS-R (Self-Liking/Self-Competence Scale-Revised Version). In the analysis of the degrees of variances, the subjects showed lower anger repression, anger expression, control of anger and depression. The degree of self-esteem revealed a higher than the median value. There were significant correlations among anger expression patterns (anger repression, anger expression and anger control), depression and self-esteem. The study limitations were the degree of representativeness of the setting and sample, and its generalizability. Based on the findings of this study, interventions are needed for Korean nursing students in order to promote anger management and improved self-esteem. The development of an anger control programme for nursing students should focus on lowering depression and enhancing self-esteem. One of the policy issues focused on providing anger management programmes for lowering depression and enhancing self-esteem. This study will enable nursing students to recognize the importance of controlling their anger, enhancing their self-esteem, establishing positive emotions and improving their overall well-being as future professional nurses. © 2013 International Council of Nurses.

cDNA structure, genomic organization and expression patterns of ...

African Journals Online (AJOL)

Visfatin was a newly identified adipocytokine, which was involved in various physiologic and pathologic processes of organisms. The cDNA structure, genomic organization and expression patterns of silver Prussian carp visfatin were described in this report. The silver Prussian carp visfatin cDNA cloned from the liver was ...

Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

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MORARIU, N.

2007-04-01

Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

Architectural patterns of p16 immunohistochemical expression associated with cancer immunity and prognosis of head and neck squamous cell carcinoma.

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Ryu, Hyang Joo; Kim, Eun Kyung; Heo, Su Jin; Cho, Byoung Chul; Kim, Hye Ryun; Yoon, Sun Och

2017-11-01

We evaluated the expression patterns of p16, which is used as a surrogate marker of HPV infection in head and neck squamous cell carcinoma (HNSCC), in regard to their biological and prognostic implications. p16 expression patterns and infiltrated immune cells were analyzed through immunohistochemistry of p16, CD3, CD8, PD-1, FOXP3, and CD163 on surgically resected HNSCCs (n = 393). Patterns of p16 immunoexpression were defined as STRONG (strong, diffuse expression in cytoplasm, and nucleus in >70% of tumor cells), MARGINAL (expression restricted to tumor margins), MOSAIC (ragged, discontinued expression), NUCLEAR (expression in nuclei only), and ABSENT (no expression). The STRONG pattern was more frequent in the oropharynx, and the MARGINAL pattern was noted only in the oral cavity. MOSAIC and NUCLEAR patterns were noted at variable sites. No two patterns of p16 expression showed the same immune cell composition of CD3+ T cells, CD8+ cytotoxic T cells, PD-1+ T cells, FOXP3+ regulatory T cells, and CD163+ macrophages. In overall and disease-free survival analyses, the STRONG pattern showed the most favorable prognosis, while the NUCLEAR pattern had the worst prognosis. HNSCC anatomical sites, tumor-related immune cell components, and patient outcomes were associated with p16 expression patterns. Each architectural pattern of p16 expression may be related to different biological and prognostic phenotypes. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Novel expression patterns of metabotropic glutamate receptor 6 in the zebrafish nervous system.

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Ying-Yu Huang

Full Text Available The metabotropic glutamate receptor 6 (mGluR6 or GRM6 belongs to the class III of the metabotropic glutamate receptor family. It is the only known mGluR that mediates direct synaptic transmission in the nervous system and is thought to mediate the ON-response in the ON-pathway of the vertebrate retina. Phylogenetic and gene structure analysis indicated that the zebrafish genome harbours two mglur6 paralogs, mglur6a and mglur6b. Besides expression in the inner nuclear layer and distinct regions in the brain, both mglur6 paralogs are expressed in ganglion cells of the retina, an expression pattern which can also be observed in the downstream effector molecules gnaoa and gnaob. This unexpected expression pattern is consistent with immunohistological labeling using a peptide antibody specific for the mGluR6b paralog. These expression patterns contradict the existing view that mGluR6 is solely located on ON-bipolar cells where it functions in signal transmission. Consistent with expression in ON-bipolar cells, we report a decreased b-wave amplitude in the electroretinogram after morpholino-based downregulation of mGluR6b, showing a function in the ON response. Our data suggest more widespread functions of mGluR6 mediated signaling in the central nervous system, possibly including sign reversing synapses in the inner retina.

Advantage of the Highly Restricted Odorant Receptor Expression Pattern in Chemosensory Neurons of Drosophila.

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Tharadra, Sana Khalid; Medina, Adriana; Ray, Anandasankar

2013-01-01

A fundamental molecular feature of olfactory systems is that individual neurons express only one receptor from a large odorant receptor gene family. While numerous theories have been proposed, the functional significance and evolutionary advantage of generating a sophisticated one-receptor-per neuron expression pattern is not well understood. Using the genetically tractable Drosophila melanogaster as a model, we demonstrate that the breakdown of this highly restricted expression pattern of an odorant receptor in neurons leads to a deficit in the ability to exploit new food sources. We show that animals with ectopic co-expression of odorant receptors also have a competitive disadvantage in a complex environment with limiting food sources. At the level of the olfactory system, we find changes in both the behavioral and electrophysiological responses to odorants that are detected by endogenous receptors when an olfactory receptor is broadly misexpressed in chemosensory neurons. Taken together these results indicate that restrictive expression patterns and segregation of odorant receptors to individual neuron classes are important for sensitive odor-detection and appropriate olfactory behaviors.

Extracting biologically significant patterns from short time series gene expression data

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McGinnis Thomas

2009-08-01

Full Text Available Abstract Background Time series gene expression data analysis is used widely to study the dynamics of various cell processes. Most of the time series data available today consist of few time points only, thus making the application of standard clustering techniques difficult. Results We developed two new algorithms that are capable of extracting biological patterns from short time point series gene expression data. The two algorithms, ASTRO and MiMeSR, are inspired by the rank order preserving framework and the minimum mean squared residue approach, respectively. However, ASTRO and MiMeSR differ from previous approaches in that they take advantage of the relatively few number of time points in order to reduce the problem from NP-hard to linear. Tested on well-defined short time expression data, we found that our approaches are robust to noise, as well as to random patterns, and that they can correctly detect the temporal expression profile of relevant functional categories. Evaluation of our methods was performed using Gene Ontology (GO annotations and chromatin immunoprecipitation (ChIP-chip data. Conclusion Our approaches generally outperform both standard clustering algorithms and algorithms designed specifically for clustering of short time series gene expression data. Both algorithms are available at http://www.benoslab.pitt.edu/astro/.

A Study of Pattern Prediction in the Monitoring Data of Earthen Ruins with the Internet of Things.

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Xiao, Yun; Wang, Xin; Eshragh, Faezeh; Wang, Xuanhong; Chen, Xiaojiang; Fang, Dingyi

2017-05-11

An understanding of the changes of the rammed earth temperature of earthen ruins is important for protection of such ruins. To predict the rammed earth temperature pattern using the air temperature pattern of the monitoring data of earthen ruins, a pattern prediction method based on interesting pattern mining and correlation, called PPER, is proposed in this paper. PPER first finds the interesting patterns in the air temperature sequence and the rammed earth temperature sequence. To reduce the processing time, two pruning rules and a new data structure based on an R-tree are also proposed. Correlation rules between the air temperature patterns and the rammed earth temperature patterns are then mined. The correlation rules are merged into predictive rules for the rammed earth temperature pattern. Experiments were conducted to show the accuracy of the presented method and the power of the pruning rules. Moreover, the Ming Dynasty Great Wall dataset was used to examine the algorithm, and six predictive rules from the air temperature to rammed earth temperature based on the interesting patterns were obtained, with the average hit rate reaching 89.8%. The PPER and predictive rules will be useful for rammed earth temperature prediction in protection of earthen ruins.

Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients.

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Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G; Hoffman, Eric P; Miller, Frederick W

2016-09-01

To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19(+) B cells and CD68(+) macrophages in responders. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. Published by Oxford University Press on behalf British Society for Rheumatology 2016. This work is written by US Government employees and is in the public domain in the US.

Predictive utility of cyclo-oxygenase-2 expression by colon and rectal cancer.

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Lobo Prabhu, Kristel C; Vu, Lan; Chan, Simon K; Phang, Terry; Gown, Allen; Jones, Steven J; Wiseman, Sam M

2014-05-01

Cyclo-oxygenase-2 (COX-2), an inducible enzyme expressed in areas of inflammation, is a target of interest for colorectal cancer therapy. Currently, the predictive significance of COX-2 in colorectal cancer remains unclear. Tissue microarrays were constructed using 118 colon cancer and 85 rectal cancer specimens; 44 synchronous metastatic colon cancer and 22 rectal cancer lymph nodes were also evaluated. COX-2 expression was assessed by immunohistochemistry. Univariate analysis was used to determine the predictive significance of clinicopathologic variables. Overall survival, disease-specific survival, and disease-free survival were the main outcomes examined. COX-2 was found to be expressed in 93% of colon cancers and 87% of rectal cancers. Decreased COX-2 expression was related to decreased disease-specific survival (P = .016) and decreased disease-free survival (P = .019) in the rectal cancer cohort but not in the colon cancer cohort. COX-2 expression has predictive utility for management of rectal but not colon cancer. Copyright © 2014 Elsevier Inc. All rights reserved.

Expression of an Msx homeobox gene in ascidians: insights into the archetypal chordate expression pattern.

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Ma, L; Swalla, B J; Zhou, J; Dobias, S L; Bell, J R; Chen, J; Maxson, R E; Jeffery, W R

1996-03-01

The Msx homeobox genes are expressed in complex patterns during vertebrate development in conjunction with inductive tissue interactions. As a means of understanding the archetypal role of Msx genes in chordates, we have isolated and characterized an Msx gene in ascidians, protochordates with a relatively simple body plan. The Mocu Msx-a and McMsx-a genes, isolated from the ascidians Molgula oculata and Molgula citrina, respectively, have homeodomains that place them in the msh-like subclass of Msx genes. Therefore, the Molgula Msx-a genes are most closely related to the msh genes previously identified in a number of invertebrates. Southern blot analysis suggests that there are one or two copies of the Msx-a gene in the Molgula genome. Northern blot and RNase protection analysis indicate that Msx-a transcripts are restricted to the developmental stages of the life cycle. In situ hybridization showed that Msx-a mRNA first appears just before gastrulation in the mesoderm (presumptive notochord and muscle) and ectoderm (neural plate) cells. Transcript levels decline in mesoderm cells after the completion of gastrulation, but are enhanced in the folding neural plate during neurulation. Later, Msx-a mRNA is also expressed in the posterior ectoderm and in a subset of the tail muscle cells. The ectoderm and mesoderm cells that express Msx-a are undergoing morphogenetic movements during gastrulation, neurulation, and tail formation. Msx-a expression ceases after these cells stop migrating. The ascidian M. citrina, in which adult tissues and organs begin to develop precociously in the larva, was used to study Msx-a expression during adult development. Msx-a transcripts are expressed in the heart primordium and the rudiments of the ampullae, epidermal protrusions with diverse functions in the juvenile. The heart and ampullae develop in regions where mesenchyme cells interact with endodermal or epidermal epithelia. A comparison of the expression patterns of the Molgula genes

Detection of cytokine expression patterns in the peripheral blood of patients with acute leukemia by antibody microarray analysis.

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Li, Qing; Li, Mei; Wu, Yao-hui; Zhu, Xiao-jian; Zeng, Chen; Zou, Ping; Chen, Zhi-chao

2014-04-01

The cytokines of acute leukemia (AL) patients have certain expression patterns, forming a complex network involved in diagnosis, progression, and prognosis. We collected the serum of different AL patients before and after complete remission (CR) for detection of cytokines by using an antibody chip. The expression patterns of cytokines were determined by using bioinformatics computational analysis. The results showed that there were significant differences in the cytokine expression patterns between AL patients and normal controls, as well as between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). In confirmatory test, ELISA revealed the expression of uPAR in AL. Moreover, the bioinformatic analysis showed that the differentially expressed cytokines among the AL groups were involved in different biological behaviors and were closely related with the development of the disease. It was concluded that the cytokine expression pattern of AL patients is significantly different from that of healthy volunteers. Also, differences of cytokine expression patterns exist between AML and ALL, and between before and after CR in the same subtype of AL, which holds important clinical significance for revealing disease progression.

Distinctive pattern of expression of spermatogenic molecular markers in testes of azoospermic men with non-mosaic Klinefelter syndrome.

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Kleiman, Sandra E; Yogev, Leah; Lehavi, Ofer; Yavetz, Haim; Hauser, Ron

2016-06-01

Mature sperm cells can be found in testicular specimens extracted from azoospermic men with non-mosaic Klinefelter syndrome (KS). The present study evaluates the expression of various known molecular markers of spermatogenesis in a population of men with KS and assesses the ability of those markers to predict spermatogenesis. Two groups of men with non-obstructive azoospermia who underwent testicular sperm-retrieval procedures were included in the study: 31 had non-mosaic KS (KS group) and 91 had normal karyotype (NK group). Each group was subdivided into mixed atrophy (containing some mature sperm cells) or Sertoli cell only syndrome according to testicular histology and cytology observations. Semi-quantitative histological morphometric analysis (interstitial hyperplasia and hyalinization, tubules with cells and abnormal thickness of the basement membrane) and expression of spermatogenetic markers (DAZ, RBM, BOLL, and CDY1) were evaluated and compared among those subgroups. Clear differences in the histological morphometry and spermatogenetic marker expression were noted between the KS and NK groups. There was a significant difference in the expression of spermatogenetic markers between the subgroups of the NK group (as expected), while no difference could be discerned between the two subgroups in the KS group. We conclude that molecular spermatogenetic markers have a pattern of expression in men with KS that is distinctively different from that of men with NK, and that it precludes and limits their use for predicting spermatogenesis in the former. It is suggested that this difference might be due to the specific highly abnormal histological morphometric parameters in KS specimens.

Prediction of highly expressed genes in microbes based on chromatin accessibility

DEFF Research Database (Denmark)

Willenbrock, Hanni; Ussery, David

2007-01-01

BACKGROUND: It is well known that gene expression is dependent on chromatin structure in eukaryotes and it is likely that chromatin can play a role in bacterial gene expression as well. Here, we use a nucleosomal position preference measure of anisotropic DNA flexibility to predict highly expressed...

Prediction of metastasis from low-malignant breast cancer by gene expression profiling

DEFF Research Database (Denmark)

Thomassen, Mads; Tan, Qihua; Eiriksdottir, Freyja

2007-01-01

examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients...... with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.......Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly...

Reprimo tissue-specific expression pattern is conserved between zebrafish and human.

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Ricardo J Figueroa

Full Text Available Reprimo (RPRM, a member of the RPRM gene family, is a tumor-suppressor gene involved in the regulation of the p53-mediated cell cycle arrest at G2/M. RPRM has been associated with malignant tumor progression and proposed as a potential biomarker for early cancer detection. However, the expression and role of RPRM, as well as its family, are poorly understood and their physiology is as yet unstudied. In this scenario, a model system like the zebrafish could serve to dissect the role of the RPRM family members in vivo. Phylogenetic analysis reveals that RPRM and RPRML have been differentially retained by most species throughout vertebrate evolution, yet RPRM3 has been retained only in a small group of distantly related species, including zebrafish. Herein, we characterized the spatiotemporal expression of RPRM (present in zebrafish as an infraclass duplication rprma/rprmb, RPRML and RPRM3 in the zebrafish. By whole-mount in situ hybridization (WISH and fluorescent in situ hybridization (FISH, we demonstrate that rprm (rprma/rprmb and rprml show a similar spatiotemporal expression profile during zebrafish development. At early developmental stages rprmb is expressed in somites. After one day post-fertilization, rprm (rprma/rprmb and rprml are expressed in the notochord, brain, blood vessels and digestive tube. On the other hand, rprm3 shows the most unique expression profile, being expressed only in the central nervous system (CNS. We assessed the expression patterns of RPRM gene transcripts in adult zebrafish and human RPRM protein product in tissue samples by RT-qPCR and immunohistochemistry (IHC staining, respectively. Strikingly, tissue-specific expression patterns of the RPRM transcripts and protein are conserved between zebrafish and humans. We propose the zebrafish as a powerful tool to elucidate the both physiological and pathological roles of the RPRM gene family.

uPAR Expression Pattern in Patients with Urothelial Carcinoma of the Bladder

DEFF Research Database (Denmark)

Dohn, Line Hammer; Pappot, Helle; Iversen, Benedikte Richter

2015-01-01

The objective of the present study was to confirm the expression and localisation pattern of the urokinase-type plasminogen activator receptor (uPAR) focusing on its possible clinical relevance in patients with urothelial neoplasia of the bladder. uPAR is a central molecule in tissue remodelling...... during cancer invasion and metastasis and is an established prognostic marker in various cancer diseases other than bladder cancer. Formalin-fixed and paraffin-embedded tumour-tissue blocks from 186 patients treated with radical cystectomy were analysed. uPAR expression was scored as either negative...... or positive as well as by the actual score. Separate scores were obtained for cancer cells, macrophages and myofibroblasts at the invasive front and in tumour core. We were able to confirm, in an independent patient cohort, the tissue expression and localisation pattern of uPAR as investigated...

Expression patterns of emmprin and monocarboxylate transporter-1 in ovarian epithelial tumors.

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Fukuoka, Miyoko; Hamasaki, Makoto; Koga, Kaori; Hayashi, Hiroyuki; Aoki, Mikiko; Kawarabayashi, Tatsuhiko; Miyamoto, Shingo; Nabeshima, Kazuki

2012-10-01

Emmprin is a transmembrane glycoprotein known as a matrix metalloproteinase inducer and is highly up-regulated in malignant cancer cells. The monocarboxylate transporters (MCTs) are responsible for H(+)-linked transport of monocarboxylates across the cell membrane. It was recently demonstrated that proper plasma membrane localization and activity of MCTs require the presence of emmprin as a chaperone and that MCT-1 also acts as chaperone for emmprin. The objectives of this study were to clarify emmprin and MCT-1 expression patterns in ovarian epithelial tumors and to elucidate the clinicopathological significance of co-localization of the two molecules. Immunohistochemical analysis of 205 epithelial tumors indicated that emmprin is always localized in cell membranes but its distribution differs according to tumor type: in lateral membranes in 89 % of adenomas, in lateral and basal membranes in 76 % of borderline tumors, and in membranes surrounding the entire cell in 98 % of carcinomas. Most carcinomas in situ also showed a lateral and basal expression pattern. In only 21 % of the carcinomas, the cells expressing membranous MCT-1 showed co-localized emmprin expression. Poor co-localization of the two molecules was more frequently found in serous carcinomas. However, the overall survival was not significantly different for the good and poor co-localization carcinoma groups. These findings indicate that the emmprin expression pattern might discriminate between invasive carcinomas and borderline tumors including carcinoma in situ. Moreover, there may be an as yet unidentified regulatory mechanism(s), for localization of MCT-1 and emmprin in cell membranes in vivo.

Domestication rewired gene expression and nucleotide diversity patterns in tomato.

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Sauvage, Christopher; Rau, Andrea; Aichholz, Charlotte; Chadoeuf, Joël; Sarah, Gautier; Ruiz, Manuel; Santoni, Sylvain; Causse, Mathilde; David, Jacques; Glémin, Sylvain

2017-08-01

Plant domestication has led to considerable phenotypic modifications from wild species to modern varieties. However, although changes in key traits have been well documented, less is known about the underlying molecular mechanisms, such as the reduction of molecular diversity or global gene co-expression patterns. In this study, we used a combination of gene expression and population genetics in wild and crop tomato to decipher the footprints of domestication. We found a set of 1729 differentially expressed genes (DEG) between the two genetic groups, belonging to 17 clusters of co-expressed DEG, suggesting that domestication affected not only individual genes but also regulatory networks. Five co-expression clusters were enriched in functional terms involving carbohydrate metabolism or epigenetic regulation of gene expression. We detected differences in nucleotide diversity between the crop and wild groups specific to DEG. Our study provides an extensive profiling of the rewiring of gene co-expression induced by the domestication syndrome in one of the main crop species. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

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Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

2017-09-01

We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predicting cellular growth from gene expression signatures.

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Edoardo M Airoldi

2009-01-01

Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Merlin : microsimulation system for predicting leisure activity-travel patterns

NARCIS (Netherlands)

Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

2004-01-01

Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

Systematic analysis of gene expression patterns associated with postmortem interval in human tissues.

Science.gov (United States)

Zhu, Yizhang; Wang, Likun; Yin, Yuxin; Yang, Ence

2017-07-14

Postmortem mRNA degradation is considered to be the major concern in gene expression research utilizing human postmortem tissues. A key factor in this process is the postmortem interval (PMI), which is defined as the interval between death and sample collection. However, global patterns of postmortem mRNA degradation at individual gene levels across diverse human tissues remain largely unknown. In this study, we performed a systematic analysis of alteration of gene expression associated with PMI in human tissues. From the Genotype-Tissue Expression (GTEx) database, we evaluated gene expression levels of 2,016 high-quality postmortem samples from 316 donors of European descent, with PMI ranging from 1 to 27 hours. We found that PMI-related mRNA degradation is tissue-specific, gene-specific, and even genotype-dependent, thus drawing a more comprehensive picture of PMI-associated gene expression across diverse human tissues. Additionally, we also identified 266 differentially variable (DV) genes, such as DEFB4B and IFNG, whose expression is significantly dispersed between short PMI (S-PMI) and long PMI (L-PMI) groups. In summary, our analyses provide a comprehensive profile of PMI-associated gene expression, which will help interpret gene expression patterns in the evaluation of postmortem tissues.

DEEP--a tool for differential expression effector prediction.

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Degenhardt, Jost; Haubrock, Martin; Dönitz, Jürgen; Wingender, Edgar; Crass, Torsten

2007-07-01

High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH database on signal transduction, to predict additional--and not necessarily differentially expressed--genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules

A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression.

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Ray, Sumanta; Hossain, Sk Md Mosaddek; Khatun, Lutfunnesa; Mukhopadhyay, Anirban

2017-12-20

Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Cell-specific prediction and application of drug-induced gene expression profiles.

Science.gov (United States)

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Does Violence in Adolescence Differentially Predict Offending Patterns in Early Adulthood?

Science.gov (United States)

Cardwell, Stephanie M; Piquero, Alex R

2018-05-01

Previous research is mixed on whether the commission of a violent offense in adolescence is predictive of criminal career characteristics. In the current study, we addressed the following: (a) What factors predict the commission of serious violence in mid-adolescence? and (b) Does involvement in serious violence in mid-adolescence lead to more chronic and/or more heterogeneous patterns of offending in early adulthood? Data were obtained from the Pathways to Desistance Study, a longitudinal study of serious adolescent offenders in Philadelphia, Pennsylvania, and Phoenix, Arizona. Prior arrests, violence exposure, and gang involvement distinguished adolescents who engaged in violence at baseline. A violent offense at baseline was not predictive of a higher frequency of rearrests but was associated with membership in the low offending trajectory. In conclusion, violent offending in adolescence might be a poor predictor of chronic and heterogeneous patterns of offending throughout the life course.

larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster.

Science.gov (United States)

Muenzing, Sascha E A; Strauch, Martin; Truman, James W; Bühler, Katja; Thum, Andreas S; Merhof, Dorit

2018-01-01

The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the registration framework involved in template generation and mapping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expression patterns. All computational methods are available within the larvalign software package: https://github.com/larvalign/larvalign/releases/tag/v1.0.

Towards pattern generation and chaotic series prediction with photonic reservoir computers

Science.gov (United States)

Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

2016-03-01

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

Modeling of gene expression pattern alteration by p,p′-DDE and dieldrin in largemouth bass

Science.gov (United States)

Garcia-Reyero, Natalia; Barber, David; Gross, Timothy; Denslow, Nancy

2006-01-01

In this study, largemouth bass (LMB) were subchronically exposed to p,p′-DDE or dieldrin in their diet to evaluate the effect of exposure on expression of genes involved in reproduction and steroid homeostasis. Using real-time PCR, we detected a different gene expression pattern for each OCP, suggesting that they each affect LMB in a different way. We also detected a different expression pattern among sexes, suggesting that sexes are affected differently by OCPs perhaps reflecting the different adaptive responses of each sex to dysregulation caused by OCP exposure.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

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Diane Heiser

Full Text Available Several individual miRNAs (miRs have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell, our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

Science.gov (United States)

Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

2014-01-01

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Characterizing embryonic gene expression patterns in the mouse using nonredundant sequence-based selection

DEFF Research Database (Denmark)

Sousa-Nunes, Rita; Rana, Amer Ahmed; Kettleborough, Ross

2003-01-01

This article investigates the expression patterns of 160 genes that are expressed during early mouse development. The cDNAs were isolated from 7.5 d postcoitum (dpc) endoderm, a region that comprises visceral endoderm (VE), definitive endoderm, and the node-tissues that are required for the initi...

Gene expression patterns associated with p53 status in breast cancer

International Nuclear Information System (INIS)

Troester, Melissa A; Herschkowitz, Jason I; Oh, Daniel S; He, Xiaping; Hoadley, Katherine A; Barbier, Claire S; Perou, Charles M

2006-01-01

Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes

Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue

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Usadel Björn

2007-05-01

Full Text Available Abstract Background Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper insights into regulatory behavior and cellular responses, as will be discussed for expression data of developing barley endosperm tissue. For that purpose, high-throughput multidimensional scaling (HiT-MDS, a recent method for similarity-preserving data embedding, is substantially refined and used for (a assessing the quality and reliability of centroid gene expression patterns, and for (b derivation of functional relationships of coexpressed genes of endosperm tissue during barley grain development (0–26 days after flowering. Results Temporal expression profiles of 4824 genes at 14 time points are faithfully embedded into two-dimensional displays. Thereby, similar shapes of coexpressed genes get closely grouped by a correlation-based similarity measure. As a main result, by using power transformation of correlation terms, a characteristic cloud of points with bipolar sandglass shape is obtained that is inherently connected to expression patterns of pre-storage, intermediate and storage phase of endosperm development. Conclusion The new HiT-MDS-2 method helps to create global views of expression patterns and to validate centroids obtained from clustering programs. Furthermore, functional gene annotation for developing endosperm barley tissue is successfully mapped to the visualization, making easy localization of major centroids of enriched functional categories possible.

Tissue expression pattern of ABCG transporter indicates functional roles in reproduction of Toxocara canis.

Science.gov (United States)

Luo, Yong-Li; Ma, Guang-Xu; Luo, Yong-Fang; Kuang, Ce-Yan; Jiang, Ai-Yun; Li, Guo-Qing; Zhou, Rong-Qiong

2018-03-01

Toxocara canis is a zoonotic parasite with worldwide distribution. ATP-binding cassette (ABC) transporters are integral membrane proteins which involve in a range of biological processes in various organisms. In present study, the full-length coding sequence of abcg-5 gene of T. canis (Tc-abcg-5) was cloned and characterized. A 633 aa polypeptide containing two conserved Walker A and Walker B motifs was predicted from a continuous 1902 nt open reading frame. Quantitative real-time PCR was employed to determine the transcriptional levels of Tc-abcg-5 gene in adult male and female worms, which indicated high mRNA level of Tc-abcg-5 in the reproductive tract of adult female T. canis. Tc-abcg-5 was expressed to produce rabbit polyclonal antiserum against recombinant TcABCG5. Indirect-fluorescence immunohistochemical assays were carried out to detect the tissue distribution of TcABCG5, which showed predominant distribution of TcABCG5 in the uterus (especially in the germ cells) of adult female T. canis. Tissue transcription and expression pattern of Tc-abcg-5 indicated that Tc-abcg-5 might play essential roles in the reproduction of this parasitic nematode.

Classification, expression pattern and comparative analysis of sugarcane expressed sequences tags (ESTs encoding glycine-rich proteins (GRPs

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Fusaro Adriana

2001-01-01

Full Text Available Since the isolation of the first glycine-rich proteins (GRPs in plants a wealth of new GRPs have been identified. The highly specific but diverse expression pattern of grp genes, taken together with the distinct sub-cellular localization of some GRP groups, clearly indicate that these proteins are involved in several independent physiological processes. Notwithstanding the absence of a clear definition of the role of GRPs in plant cells, studies conducted with these proteins have provided new and interesting insights into the molecular biology and cell biology of plants. Complexly regulated promoters and distinct mechanisms for the regulation of gene expression have been demonstrated and new protein targeting pathways, as well as the exportation of GRPs from different cell types have been discovered. These data show that GRPs can be useful as markers and/or models to understand distinct aspects of plant biology. In this paper, the structural and functional features of these proteins in sugarcane (Saccharum officinarum L. are summarized. Since this is the first description of GRPs in sugarcane, special emphasis has been given to the expression pattern of these GRP genes by studying their abundance and prevalence in the different cDNA-libraries of the Sugarcane Expressed Sequence Tag (SUCEST project . The comparison of sugarcane GRPs with GRPs from other species is also discussed.

Simple regional strain pattern analysis to predict response to cardiac resynchronization therapy

DEFF Research Database (Denmark)

Risum, Niels; Jons, Christian; Olsen, Niels T

2012-01-01

A classical strain pattern of early contraction in one wall and prestretching of the opposing wall followed by late contraction has previously been associated with left bundle branch block (LBBB) activation and short-term response to cardiac resynchronization therapy (CRT). Aims of this study were...... to establish the long-term predictive value of an LBBB-related strain pattern and to identify changes in contraction patterns during short-term and long-term CRT....

Predicting the emotions expressed in music

DEFF Research Database (Denmark)

Madsen, Jens

With the ever-growing popularity and availability of digital music through streaming services and digital download, making sense of the millions of songs, is ever more pertinent. However the traditional approach of creating music systems has treated songs like items in a store, like books...... and movies. However music is special, having origins in a number of evolutionary adaptations. The fundamental needs and goals of a users use of music, was investigated to create the next generation of music systems. People listen to music to regulate their mood and emotions was found to be the most important...... fundamental reason. (Mis)matching peoples mood with the emotions expressed in music was found to be an essential underlying mechanism, people use to regulate their emotions. This formed the basis and overall goal of the thesis, to investigate how to create a predictive model of emotions expressed in music...

Over Expression of a tRNALeu Isoacceptor Changes Charging Pattern of Leucine tRNAs and Reveals New Codon Reading

DEFF Research Database (Denmark)

Sørensen, Michael Askvad; Elf, J.; Bouakaz, E.

2005-01-01

During mRNA translation, synonymous codons for one amino acid are often read by different isoaccepting tRNAs. The theory of selective tRNA charging predicts greatly varying percentages of aminoacylation among isoacceptors in cells starved for their common amino acid. It also predicts major changes...... in tRNA charging patterns upon concentration changes of single isoacceptors, which suggests a novel type of translational control of gene expression. We therefore tested the theory by measuring with Northern blots the charging of Leu-tRNAs in Escherichia coli under Leu limitation in response to over...... postulated a previously unknown common codon for tRNALeu GAG and tRNALeu UAG. Subsequently, we demonstrated that the tRNALeu GAG codon CUU is, in fact, read also by tRNALeu UAG, due to a uridine-5-oxyacetic acid modification....

Expression of DNA Damage Response Molecules PARP1, γH2AX, BRCA1, and BRCA2 Predicts Poor Survival of Breast Carcinoma Patients

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See-Hyoung Park

2015-08-01

Full Text Available BACKGROUND: Poly(ADP-ribose polymerase 1 (PARP1, γH2AX, BRCA1, and BRCA2 are conventional molecular indicators of DNA damage in cells and are often overexpressed in various cancers. In this study, we aimed, using immunohistochemical detection, whether the co-expression of PARP1, γH2AX, BRCA1, and BRCA2 in breast carcinoma (BCA tissue can provide more reliable prediction of survival of BCA patients. MATERIALS AND METHODS: We investigated immunohistochemical expression and prognostic significance of the expression of PARP1, γH2AX, BRCA1, and BRCA2 in 192 cases of BCAs. RESULTS: The expression of these four molecules predicted earlier distant metastatic relapse, shorter overall survival (OS, and relapse-free survival (RFS by univariate analysis. Multivariate analysis revealed the expression of PARP1, γH2AX, and BRCA2 as independent poor prognostic indicators of OS and RFS. In addition, the combined expressional pattern of BRCA1, BRCA2, PARP1, and γH2AX (CSbbph was an additional independent prognostic predictor for OS (P < .001 and RFS (P < .001. The 10-year OS rate was 95% in the CSbbph-low (CSbbph scores 0 and 1 subgroup, but that was only 35% in the CSbbph-high (CSbbph score 4 subgroup. CONCLUSION: This study has demonstrated that the individual and combined expression patterns of PARP1, γH2AX, BRCA1, and BRCA2 could be helpful in determining an accurate prognosis for BCA patients and for the selection of BCA patients who could potentially benefit from anti-PARP1 therapy with a combination of genotoxic chemotherapeutic agents.

Lower MGMT expression predicts better prognosis in proneural-like glioblastoma

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He, Zhi-Cheng; Ping, Yi-Fang; Xu, Sen-Lin; Lin, Yong; Yu, Shi-Cang; Kung, Hsiang-Fu; Bian, Xiu-Wu

2015-01-01

Objective: To investigate the expression and significance of MGMT in different molecular subtypes of glioblastoma (GBM), and to evaluate the important role of MGMT and P53 in predicting the prognosis of GBM patients. Methods: MGMT expression was detected by immunohistochemical staining in 72 cases of GBM which had been classified as three molecular subtypes. The relationship between MGMT and P53, an important molecule for identification of proneural-like GBM, were further analyzed. The association between MGMT and patients’ prognosis was analyzed with Kaplan-Meier method, which was further validated by the data from 513 cases of GBM in the TCGA database. Results: MGMT expression was lower in proneural-like subtype in 72 GBM cases (p < 0.001), and was negatively correlated with P53 (r=-0. 6203, p < 0.001). This results was also verified by a validation group of 87 GBM cases (r=-0. 2950, p < 0.001). Interestingly, low expression of MGMT predicted a better outcome in proneurallike subtype or P53 high-expression group (p < 0.05) but not in non-proneural-like subtype and P53 low-expression group. All of these results were verified by the data from TCGA database. Conclusion: MGMT can be used as an independent prognostic factor and plays an important role in molecular typing and diagnosis of GBM by combination with proneural-like subtype marker P53. PMID:26884942

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

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Caroline Colijn

2009-08-01

Full Text Available Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression, extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB. Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan.

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Elshayeb, Ayman A; Ahmed, Abdelazim A; El Siddig, Marmar A; El Hussien, Adil A

2017-11-14

Enteric fever has persistence of great impact in Sudanese public health especially during rainy season when the causative agent Salmonella enterica serovar Typhi possesses pan endemic patterns in most regions of Sudan - Khartoum. The present study aims to assess the recent state of antibiotics susceptibility of Salmonella Typhi with special concern to multidrug resistance strains and predict the emergence of new resistant patterns and outbreaks. Salmonella Typhi strains were isolated and identified according to the guidelines of the International Standardization Organization and the World Health Organization. The antibiotics susceptibilities were tested using the recommendations of the Clinical Laboratories Standards Institute. Predictions of emerging resistant bacteria patterns and outbreaks in Sudan were done using logistic regression, forecasting linear equations and in silico simulations models. A total of 124 antibiotics resistant Salmonella Typhi strains categorized in 12 average groups were isolated, different patterns of resistance statistically calculated by (y = ax - b). Minimum bactericidal concentration's predication of resistance was given the exponential trend (y = n e x ) and the predictive coefficient R 2  > 0 current antimicrobial drug resistance patterns of community-acquired agents causing outbreaks.

Wnt and TGF-beta expression in the sponge Amphimedon queenslandica and the origin of metazoan embryonic patterning.

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Maja Adamska

2007-10-01

Full Text Available The origin of metazoan development and differentiation was contingent upon the evolution of cell adhesion, communication and cooperation mechanisms. While components of many of the major cell signalling pathways have been identified in a range of sponges (phylum Porifera, their roles in development have not been investigated and remain largely unknown. Here, we take the first steps toward reconstructing the developmental signalling systems used in the last common ancestor to living sponges and eumetazoans by studying the expression of genes encoding Wnt and TGF-beta signalling ligands during the embryonic development of a sponge.Using resources generated in the recent sponge Amphimedon queenslandica (Demospongiae genome project, we have recovered genes encoding Wnt and TGF-beta signalling ligands that are critical in patterning metazoan embryos. Both genes are expressed from the earliest stages of Amphimedon embryonic development in highly dynamic patterns. At the time when the Amphimedon embryos begin to display anterior-posterior polarity, Wnt expression becomes localised to the posterior pole and this expression continues until the swimming larva stage. In contrast, TGF-beta expression is highest at the anterior pole. As in complex animals, sponge Wnt and TGF-beta expression patterns intersect later in development during the patterning of a sub-community of cells that form a simple tissue-like structure, the pigment ring. Throughout development, Wnt and TGF-beta are expressed radially along the anterior-posterior axis.We infer from the expression of Wnt and TGF-beta in Amphimedon that the ancestor that gave rise to sponges, cnidarians and bilaterians had already evolved the capacity to direct the formation of relatively sophisticated body plans, with axes and tissues. The radially symmetrical expression patterns of Wnt and TGF-beta along the anterior-posterior axis of sponge embryos and larvae suggest that these signalling pathways

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

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Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.

Science.gov (United States)

Hall, Benjamin A; Jackson, Ethan; Hajnal, Alex; Fisher, Jasmin

2014-09-06

Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or 'retrodict', compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders.

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David M Mutch

Full Text Available BACKGROUND: The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. METHODOLOGY/PRINCIPAL FINDINGS: The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8-12 kgs weight loss could always be differentiated from non-responders (<4 kgs weight loss. We also assessed whether this differentiation was sufficient for prediction. Using a bottom-up (i.e. black-box approach, standard class prediction algorithms were able to predict dietary responders with up to 61.1%+/-8.1% accuracy. Using a top-down approach (i.e. using differentially expressed genes to build a classifier improved prediction accuracy to 80.9%+/-2.2%. CONCLUSION: Adipose gene expression profiling prior to the consumption of a low-fat diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition.

Pattern Recognition of Gene Expression with Singular Spectrum Analysis

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Hossein Hassani

2014-07-01

Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid gene expression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering gene expression measurements for other applications.

The tailless ortholog nhr-67 regulates patterning of gene expression and morphogenesis in the C. elegans vulva.

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Jolene S Fernandes

2007-04-01

Full Text Available Regulation of spatio-temporal gene expression in diverse cell and tissue types is a critical aspect of development. Progression through Caenorhabditis elegans vulval development leads to the generation of seven distinct vulval cell types (vulA, vulB1, vulB2, vulC, vulD, vulE, and vulF, each with its own unique gene expression profile. The mechanisms that establish the precise spatial patterning of these mature cell types are largely unknown. Dissection of the gene regulatory networks involved in vulval patterning and differentiation would help us understand how cells generate a spatially defined pattern of cell fates during organogenesis. We disrupted the activity of 508 transcription factors via RNAi and assayed the expression of ceh-2, a marker for vulB fate during the L4 stage. From this screen, we identified the tailless ortholog nhr-67 as a novel regulator of gene expression in multiple vulval cell types. We find that one way in which nhr-67 maintains cell identity is by restricting inappropriate cell fusion events in specific vulval cells, namely vulE and vulF. nhr-67 exhibits a dynamic expression pattern in the vulval cells and interacts with three other transcriptional regulators cog-1 (Nkx6.1/6.2, lin-11 (LIM, and egl-38 (Pax2/5/8 to generate the composite expression patterns of their downstream targets. We provide evidence that egl-38 regulates gene expression in vulB1, vulC, vulD, vulE, as well as vulF cells. We demonstrate that the pairwise interactions between these regulatory genes are complex and vary among the seven cell types. We also discovered a striking regulatory circuit that affects a subset of the vulval lineages: cog-1 and nhr-67 inhibit both one another and themselves. We postulate that the differential levels and combinatorial patterns of lin-11, cog-1, and nhr-67 expression are a part of a regulatory code for the mature vulval cell types.

Patterning of anteroposterior body axis displayed in the expression of Hox genes in sea cucumber Apostichopus japonicus.

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Kikuchi, Mani; Omori, Akihito; Kurokawa, Daisuke; Akasaka, Koji

2015-09-01

The presence of an anteroposterior body axis is a fundamental feature of bilateria. Within this group, echinoderms have secondarily evolved pentameral symmetric body plans. Although all echinoderms present bilaterally symmetric larval stages, they dramatically rearrange their body axis and develop a pentaradial body plan during metamorphosis. Therefore, the location of their anteroposterior body axis in adult forms remains a contentious issue. Unlike other echinoderms, sea cucumbers present an obvious anteroposterior axis not rearranged during metamorphosis, thus representing an interesting group to study their anteroposterior axis patterning. Hox genes are known to play a broadly conserved role in anteroposterior axis patterning in deuterostomes. Here, we report the expression patterns of Hox genes from early development to pentactula stage in sea cucumber. In early larval stages, five Hox genes (AjHox1, AjHox7, AjHox8, AjHox11/13a, and AjHox11/13b) were expressed sequentially along the archenteron, suggesting that the role of anteroposterior patterning of the Hox genes is conserved in bilateral larvae of echinoderms. In doliolaria and pentactula stages, eight Hox genes (AjHox1, AjHox5, AjHox7, AjHox8, AjHox9/10, AjHox11/13a, AjHox11/13b, and AjHox11/13c) were expressed sequentially along the digestive tract, following a similar expression pattern to that found in the visceral mesoderm of other bilateria. Unlike other echinoderms, pentameral expression patterns of AjHox genes were not observed in sea cucumber. Altogether, we concluded that AjHox genes are involved in the patterning of the digestive tract in both larvae and metamorphosis of sea cucumbers. In addition, the anteroposterior axis in sea cucumbers might be patterned like that of other bilateria.

Binary pattern flavored feature extractors for Facial Expression Recognition: An overview

DEFF Research Database (Denmark)

Kristensen, Rasmus Lyngby; Tan, Zheng-Hua; Ma, Zhanyu

2015-01-01

This paper conducts a survey of modern binary pattern flavored feature extractors applied to the Facial Expression Recognition (FER) problem. In total, 26 different feature extractors are included, of which six are selected for in depth description. In addition, the paper unifies important FER...

Spatio-Temporal Expression Patterns of Arabidopsis thaliana and Medicago truncatula Defensin-Like Genes

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Nallu, Sumitha; Wang, Lin; Botanga, Christopher J.; Gomez, S. Karen; Costa, Liliana M.; Harrison, Maria J.; Samac, Deborah A.; Glazebrook, Jane; Katagiri, Fumiaki; Gutierrez-Marcos, Jose F.; VandenBosch, Kathryn A.

2013-01-01

Plant genomes contain several hundred defensin-like (DEFL) genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species. PMID:23527067

Spatio-temporal expression patterns of Arabidopsis thaliana and Medicago truncatula defensin-like genes.

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Mesfin Tesfaye

Full Text Available Plant genomes contain several hundred defensin-like (DEFL genes that encode short cysteine-rich proteins resembling defensins, which are well known antimicrobial polypeptides. Little is known about the expression patterns or functions of many DEFLs because most were discovered recently and hence are not well represented on standard microarrays. We designed a custom Affymetrix chip consisting of probe sets for 317 and 684 DEFLs from Arabidopsis thaliana and Medicago truncatula, respectively for cataloging DEFL expression in a variety of plant organs at different developmental stages and during symbiotic and pathogenic associations. The microarray analysis provided evidence for the transcription of 71% and 90% of the DEFLs identified in Arabidopsis and Medicago, respectively, including many of the recently annotated DEFL genes that previously lacked expression information. Both model plants contain a subset of DEFLs specifically expressed in seeds or fruits. A few DEFLs, including some plant defensins, were significantly up-regulated in Arabidopsis leaves inoculated with Alternaria brassicicola or Pseudomonas syringae pathogens. Among these, some were dependent on jasmonic acid signaling or were associated with specific types of immune responses. There were notable differences in DEFL gene expression patterns between Arabidopsis and Medicago, as the majority of Arabidopsis DEFLs were expressed in inflorescences, while only a few exhibited root-enhanced expression. By contrast, Medicago DEFLs were most prominently expressed in nitrogen-fixing root nodules. Thus, our data document salient differences in DEFL temporal and spatial expression between Arabidopsis and Medicago, suggesting distinct signaling routes and distinct roles for these proteins in the two plant species.

SOX9 Expression Predicts Relapse of Stage II Colon Cancer Patients

DEFF Research Database (Denmark)

Espersen, Maiken Lise Marcker; Linnemann, Dorte; Christensen, Ib Jarle

2016-01-01

The aim of this study was to investigate if the protein expression of Sex-determining region y-box 9 (SOX9) in primary tumors could predict relapse of stage II colon cancer patients.144 patients with stage II primary colon cancer were retrospectively enrolledin the study. SOX9 expression...

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

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Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

Expression pattern of the homeotic gene Bapx1 during early chick gastrointestinal tract development.

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Faure, Sandrine; Georges, Maxime; McKey, Jennifer; Sagnol, Sébastien; de Santa Barbara, Pascal

2013-12-01

Regulation of the Bone Morphogenetic Protein (BMP) signaling pathway is essential for the normal development of vertebrate gastrointestinal (GI) tract, but also for the differentiation of the digestive mesenchymal layer into smooth muscles and submucosal layer. Different studies demonstrated that Bapx1 (for bagpipe homeobox homolog 1) negatively regulates the BMP pathway, but its precise expression pattern during the development and the differentiation of the GI tract mesenchyme actually remains to be examined. Here, we present the spatio-temporal expression profile of Bapx1 in the chick GI tract. We show that Bapx1 is first expressed in the undifferentiated mesenchyme of the gizzard and the colon. After the differentiation of the digestive mesenchyme, we found Bapx1 strongly expressed in the gizzard smooth muscle and in the submucosa layer of the colon. This expression pattern provides new insights into the roles of Bapx1 during the regionalization of the GI tract and the differentiation of the digestive mesenchyme of the colon and the stomach. Copyright © 2013 Elsevier B.V. All rights reserved.

Prevalence of current patterns and predictive trends of multidrug-resistant Salmonella Typhi in Sudan

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Ayman A. Elshayeb

2017-11-01

Full Text Available Abstract Background Enteric fever has persistence of great impact in Sudanese public health especially during rainy season when the causative agent Salmonella enterica serovar Typhi possesses pan endemic patterns in most regions of Sudan - Khartoum. Objectives The present study aims to assess the recent state of antibiotics susceptibility of Salmonella Typhi with special concern to multidrug resistance strains and predict the emergence of new resistant patterns and outbreaks. Methods Salmonella Typhi strains were isolated and identified according to the guidelines of the International Standardization Organization and the World Health Organization. The antibiotics susceptibilities were tested using the recommendations of the Clinical Laboratories Standards Institute. Predictions of emerging resistant bacteria patterns and outbreaks in Sudan were done using logistic regression, forecasting linear equations and in silico simulations models. Results A total of 124 antibiotics resistant Salmonella Typhi strains categorized in 12 average groups were isolated, different patterns of resistance statistically calculated by (y = ax − b. Minimum bactericidal concentration’s predication of resistance was given the exponential trend (y = n ex and the predictive coefficient R2 > 0 < 1 are approximately alike. It was assumed that resistant bacteria occurred with a constant rate of antibiotic doses during the whole experimental period. Thus, the number of sensitive bacteria decreases at the same rate as resistant occur following term to the modified predictive model which solved computationally. Conclusion This study assesses the prediction of multi-drug resistance among S. Typhi isolates by applying low cost materials and simple statistical methods suitable for the most frequently used antibiotics as typhoid empirical therapy. Therefore, bacterial surveillance systems should be implemented to present data on the aetiology and current

Selective modes determine evolutionary rates, gene compactness and expression patterns in Brassica.

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Guo, Yue; Liu, Jing; Zhang, Jiefu; Liu, Shengyi; Du, Jianchang

2017-07-01

It has been well documented that most nuclear protein-coding genes in organisms can be classified into two categories: positively selected genes (PSGs) and negatively selected genes (NSGs). The characteristics and evolutionary fates of different types of genes, however, have been poorly understood. In this study, the rates of nonsynonymous substitution (K a ) and the rates of synonymous substitution (K s ) were investigated by comparing the orthologs between the two sequenced Brassica species, Brassica rapa and Brassica oleracea, and the evolutionary rates, gene structures, expression patterns, and codon bias were compared between PSGs and NSGs. The resulting data show that PSGs have higher protein evolutionary rates, lower synonymous substitution rates, shorter gene length, fewer exons, higher functional specificity, lower expression level, higher tissue-specific expression and stronger codon bias than NSGs. Although the quantities and values are different, the relative features of PSGs and NSGs have been largely verified in the model species Arabidopsis. These data suggest that PSGs and NSGs differ not only under selective pressure (K a /K s ), but also in their evolutionary, structural and functional properties, indicating that selective modes may serve as a determinant factor for measuring evolutionary rates, gene compactness and expression patterns in Brassica. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Exploring the significance of human mobility patterns in social link prediction

KAUST Repository

Alharbi, Basma Mohammed; Zhang, Xiangliang

2014-01-01

Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper

Expression patterns of five polymorphic membrane proteins during the Chlamydia abortus developmental cycle.

Science.gov (United States)

Wheelhouse, Nick; Sait, Michelle; Wilson, Kim; Aitchison, Kevin; McLean, Kevin; Smith, David G E; Longbottom, David

2012-12-07

It has been suggested that polymorphic membrane proteins (Pmps) belonging to the Type V autotransporter protein family play an important role in the pathogenesis of Chlamydia abortus (C. abortus; formerly Chlamydophila abortus) infection. In a previous study we demonstrated the expression of all the pmps at the transcriptional level. The purpose of this study was to measure the number of Pmp positive inclusions throughout the C. abortus developmental cycle to investigate heterogeneity in expression patterns. McCoy cells were infected with C. abortus and analysed for Pmp expression over a 72 h period by fluorescent immunocytochemistry. Pmp18D could be detected at all analysed time points, and could only be accurately quantified from 36 hpi while Pmp10G positive inclusions could be visualised from 36hpi. Expression of Pmps 13G, 16G and 17G could only be visualised later in the cycle and within less than half of visualised inclusions. These results indicate that while expression of specific Pmps is constitutive (Pmp18D), the pattern of expression of other Pmps is more variable. This suggests that different members of the Pmp family may play different roles within the developmental cycle of the organism, with some (Pmps10G and 18D) having roles throughout the cycle, while the heterogeneity of expression of others may aid in antigenic variation. Copyright © 2012 Elsevier B.V. All rights reserved.

Prediction of Associations between microRNAs and Gene Expression in Glioma Biology.

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Stefan Wuchty

Full Text Available Despite progress in the determination of miR interactions, their regulatory role in cancer is only beginning to be unraveled. Utilizing gene expression data from 27 glioblastoma samples we found that the mere knowledge of physical interactions between specific mRNAs and miRs can be used to determine associated regulatory interactions, allowing us to identify 626 associated interactions, involving 128 miRs that putatively modulate the expression of 246 mRNAs. Experimentally determining the expression of miRs, we found an over-representation of over(under-expressed miRs with various predicted mRNA target sequences. Such significantly associated miRs that putatively bind over-expressed genes strongly tend to have binding sites nearby the 3'UTR of the corresponding mRNAs, suggesting that the presence of the miRs near the translation stop site may be a factor in their regulatory ability. Our analysis predicted a significant association between miR-128 and the protein kinase WEE1, which we subsequently validated experimentally by showing that the over-expression of the naturally under-expressed miR-128 in glioma cells resulted in the inhibition of WEE1 in glioblastoma cells.

Towards Predicting Expressed Emotion in Music from Pairwise Comparisons

DEFF Research Database (Denmark)

Madsen, Jens; Jensen, Bjørn Sand; Larsen, Jan

2012-01-01

We introduce five regression models for the modeling of expressed emotion in music using data obtained in a two alternative forced choice listening experiment. The predictive performance of the proposed models is compared using learning curves, showing that all models converge to produce a similar...

Analysis of allelic expression patterns in clonal somatic cells by single-cell RNA-seq.

Science.gov (United States)

Reinius, Björn; Mold, Jeff E; Ramsköld, Daniel; Deng, Qiaolin; Johnsson, Per; Michaëlsson, Jakob; Frisén, Jonas; Sandberg, Rickard

2016-11-01

Cellular heterogeneity can emerge from the expression of only one parental allele. However, it has remained controversial whether, or to what degree, random monoallelic expression of autosomal genes (aRME) is mitotically inherited (clonal) or stochastic (dynamic) in somatic cells, particularly in vivo. Here we used allele-sensitive single-cell RNA-seq on clonal primary mouse fibroblasts and freshly isolated human CD8 + T cells to dissect clonal and dynamic monoallelic expression patterns. Dynamic aRME affected a considerable portion of the cells' transcriptomes, with levels dependent on the cells' transcriptional activity. Notably, clonal aRME was detected, but it was surprisingly scarce (aRME occurs transiently within individual cells, and patterns of aRME are thus primarily scattered throughout somatic cell populations rather than, as previously hypothesized, confined to patches of clonally related cells.

Gender and Age Patterns in Emotional Expression, Body Image, and Self-Esteem: A Qualitative Analysis.

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Polce-Lynch, Mary; Myers, Barbara J.; Kilmartin, Christopher T.; Forssmann-Falck, Renate; Kliewer, Wendy

1998-01-01

Used written narratives to examine gender and age patterns in body image, emotional expression, and self-esteem for 209 students in grades 5, 8, and 12. Results indicate that boys restrict emotional expression in adolescence, whereas girls increase emotional expression in the same period. Girls also are more influenced by body image. (SLD)

Facial expression recognition based on improved local ternary pattern and stacked auto-encoder

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Wu, Yao; Qiu, Weigen

2017-08-01

In order to enhance the robustness of facial expression recognition, we propose a method of facial expression recognition based on improved Local Ternary Pattern (LTP) combined with Stacked Auto-Encoder (SAE). This method uses the improved LTP extraction feature, and then uses the improved depth belief network as the detector and classifier to extract the LTP feature. The combination of LTP and improved deep belief network is realized in facial expression recognition. The recognition rate on CK+ databases has improved significantly.

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

OpenAIRE

Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Abstract Background Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori assumptions about the interactions, which all simulate the observed patterns. It is important to analyze the properties of the circuits. Findings We have analyzed the simulated gene expression ...

c-Fos expression predicts long-term social memory retrieval in mice.

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Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

2016-10-15

The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Expression of Eag1 K+ channel and ErbBs in human pituitary adenomas: cytoskeleton arrangement patterns in cultured cells.

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del Pliego, Margarita González; Aguirre-Benítez, Elsa; Paisano-Cerón, Karina; Valdovinos-Ramírez, Irene; Rangel-Morales, Carlos; Rodríguez-Mata, Verónica; Solano-Agama, Carmen; Martín-Tapia, Dolores; de la Vega, María Teresa; Saldoval-Balanzario, Miguel; Camacho, Javier; Mendoza-Garrido, María Eugenia

2013-01-01

Pituitary adenomas can invade surrounded tissue, but the mechanism remains elusive. Ether à go-go-1 (Eag1) potassium channel and epidermal growth factor receptors (ErbB1 and ErbB2) have been associated to invasive phenotypes or poor prognosis in cancer patients. However, cells arrange their cytoskeleton in order to acquire a successful migration pattern. We have studied ErbBs and Eag1 expression, and cytoskeleton arrangements in 11 human pituitary adenomas. Eag1, ErbB1 and ErbB2 expression were studied by immunochemistry in tissue and cultured cells. The cytoskeleton arrangement was analyzed in cultured cells by immunofluorescence. Normal pituitary tissue showed ErbB2 expression and Eag1 only in few cells. However, Eag1 and ErbB2 were expressed in all the tumors analyzed. ErbB1 expression was observed variable and did not show specificity for a tumor characteristic. Cultured cells from micro- and macro-adenomas clinically functional organize their cytoskeleton suggesting a mesenchymal pattern, and a round leucocyte/amoeboid pattern from invasive clinically silent adenoma. Pituitary tumors over-express EGF receptors and the ErbB2 repeated expression suggests is a characteristic of adenomas. Eag 1 was express, in different extent, and could be a therapeutic target. The cytoskeleton arrangements observed suggest that pituitary tumor cells acquire different patterns: mesenchymal, and leucocyte/amoeboid, the last observed in the invasive adenomas. Amoeboid migration pattern has been associated with high invasion capacity.

Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.

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Piccolo, Stephen R; Andrulis, Irene L; Cohen, Adam L; Conner, Thomas; Moos, Philip J; Spira, Avrum E; Buys, Saundra S; Johnson, W Evan; Bild, Andrea H

2015-11-04

Women with a family history of breast cancer face considerable uncertainty about whether to pursue standard screening, intensive screening, or prophylactic surgery. Accurate and individualized risk-estimation approaches may help these women make more informed decisions. Although highly penetrant genetic variants have been associated with familial breast cancer (FBC) risk, many individuals do not carry these variants, and many carriers never develop breast cancer. Common risk variants have a relatively modest effect on risk and show limited potential for predicting FBC development. As an alternative, we hypothesized that additional genomic data types, such as gene-expression levels, which can reflect genetic and epigenetic variation, could contribute to classifying a person's risk status. Specifically, we aimed to identify common patterns in gene-expression levels across individuals who develop FBC. We profiled peripheral blood mononuclear cells from women with a family history of breast cancer (with or without a germline BRCA1/2 variant) and from controls. We used the support vector machines algorithm to differentiate between patients who developed FBC and those who did not. Our study used two independent datasets, a training set of 124 women from Utah (USA) and an external validation (test) set from Ontario (Canada) of 73 women (197 total). We controlled for expression variation associated with clinical, demographic, and treatment variables as well as lymphocyte markers. Our multigene biomarker provided accurate, individual-level estimates of FBC occurrence for the Utah cohort (AUC = 0.76 [0.67-84]) . Even at their lower confidence bounds, these accuracy estimates meet or exceed estimates from alternative approaches. Our Ontario cohort resulted in similarly high levels of accuracy (AUC = 0.73 [0.59-0.86]), thus providing external validation of our findings. Individuals deemed to have "high" risk by our model would have an estimated 2.4 times greater odds of

Quantitative expression patterns of peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) protein in mice

International Nuclear Information System (INIS)

Girroir, Elizabeth E.; Hollingshead, Holly E.; He Pengfei; Zhu Bokai; Perdew, Gary H.; Peters, Jeffrey M.

2008-01-01

The expression patterns of PPARβ/δ have been described, but the majority of these data are based on mRNA data. To date, there are no reports that have quantitatively examined the expression of PPARβ/δ protein in mouse tissues. In the present study, a highly specific PPARβ/δ antibody was developed, characterized, and used to examine tissue expression patterns of PPARβ/δ. As compared to commercially available anti-PPARβ/δ antibodies, one of six polyclonal anti-PPARβ/δ antibodies developed was significantly more effective for immunoprecipitation of in vitro-translated PPARβ/δ. This antibody was used for quantitative Western blot analysis using radioactive detection methods. Expression of PPARβ/δ was highest in colon, small intestine, liver, and keratinocytes as compared to other tissues including heart, spleen, skeletal muscle, lung, brain, and thymus. Interestingly, PPARβ/δ expression was localized in the nucleus and RXRα can be co-immunoprecipitated with nuclear PPARβ/δ. Results from these studies demonstrate that PPARβ/δ expression is highest in intestinal epithelium, liver, and keratinocytes, consistent with significant biological roles in these tissues

MLH1 expression predicts the response to preoperative therapy and is associated with PD-L1 expression in esophageal cancer.

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Momose, Kota; Yamasaki, Makoto; Tanaka, Koji; Miyazaki, Yasuhiro; Makino, Tomoki; Takahashi, Tsuyoshi; Kurokawa, Yukinori; Nakajima, Kiyokazu; Takiguchi, Shuji; Mori, Masaki; Doki, Yuichiro

2017-07-01

Programmed death-ligand 1 (PD-1/PD-L1) inhibition therapy demonstrates potential as a future treatment for esophageal cancer. Mismatch repair status and tumor PD-L1 expression are the candidate predictive biomarkers for response to this therapy. In colorectal cancer, mismatch repair-deficient tumors are associated with improved survival, although they are not sensitive to 5-fluorouracil-based chemotherapy. The purpose of the present study was to investigate the association between MutL homolog 1 (MLH1) expression and prognosis, response to therapy and PD-L1 expression in esophageal cancer. Immunohistochemistry was used to evaluate MLH1 and PD-L1 expression in 251 resected specimens. Of the specimens, 30.3% exhibited low MLH1 expression and 15.5% exhibited high PD-L1 expression. The 5-year overall survival rates for the high MLH1 expression group and the low MLH1 expression group were 51.3 and 55.6%, respectively (P=0.5260). The responder ratio was 45.7% in the high MLH1 expression group and 15.4% in the low MLH1 expression group (PMLH1 expression group (P=0.0064) and 25.0% in the low MLH1 expression group. MLH1 expression may be a predictive factor for the response to preoperative therapy in esophageal cancer, and esophageal cancer with low MLH1 expression may have a mechanism that assists in promoting tumor PD-L1 expression.

Predictive value of MSH2 gene expression in colorectal cancer treated with capecitabine

DEFF Research Database (Denmark)

Jensen, Lars H; Danenberg, Kathleen D; Danenberg, Peter V

2007-01-01

was associated with a hazard ratio of 0.5 (95% confidence interval, 0.23-1.11; P = 0.083) in survival analysis. CONCLUSION: The higher gene expression of MSH2 in responders and the trend for predicting overall survival indicates a predictive value of this marker in the treatment of advanced CRC with capecitabine.......PURPOSE: The objective of the present study was to evaluate the gene expression of the DNA mismatch repair gene MSH2 as a predictive marker in advanced colorectal cancer (CRC) treated with first-line capecitabine. PATIENTS AND METHODS: Microdissection of paraffin-embedded tumor tissue, RNA...

Expression pattern of salt tolerance-related genes in Aegilops cylindrica.

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Arabbeigi, Mahbube; Arzani, Ahmad; Majidi, Mohammad Mahdi; Sayed-Tabatabaei, Badraldin Ebrahim; Saha, Prasenjit

2018-02-01

Aegilops cylindrica , a salt-tolerant gene pool of wheat, is a useful plant model for understanding mechanism of salt tolerance. A salt-tolerant USL26 and a salt-sensitive K44 genotypes of A. cylindrica , originating from Uremia Salt Lake shores in Northwest Iran and a non-saline Kurdestan province in West Iran, respectively, were identified based on screening evaluation and used for this work. The objective of the current study was to investigate the expression patterns of four genes related to ion homeostasis in this species. Under treatment of 400 mM NaCl, USL26 showed significantly higher root and shoot dry matter levels and K + concentrations, together with lower Na + concentrations than K44 genotype. A. cylindrica HKT1;5 ( AecHKT1;5 ), SOS1 ( AecSOS1 ), NHX1 ( AecNHX1 ) and VP1 ( AecVP1 ) were partially sequenced to design each gene specific primer. Quantitative real-time PCR showed a differential expression pattern of these genes between the two genotypes and between the root and shoot tissues. Expressions of AecHKT1;5 and AecSOS1 was greater in the roots than in the shoots of USL26 while AecNHX1 and AecVP1 were equally expressed in both tissues of USL26 and K44. The higher transcripts of AecHKT1;5 in the roots versus the shoots could explain both the lower Na + in the shoots and the much lower Na + and higher K + concentrations in the roots/shoots of USL26 compared to K44. Therefore, the involvement of AecHKT1;5 in shoot-to-root handover of Na + in possible combination with the exclusion of excessive Na + from the root in the salt-tolerant genotype are suggested.

A novel method for prediction of dynamic smiling expressions after orthodontic treatment: a case report.

Science.gov (United States)

Dai, Fanfan; Li, Yangjing; Chen, Gui; Chen, Si; Xu, Tianmin

2016-02-01

Smile esthetics has become increasingly important for orthodontic patients, thus prediction of post-treatment smile is necessary for a perfect treatment plan. In this study, with a combination of three-dimensional craniofacial data from the cone beam computed tomography and color-encoded structured light system, a novel method for smile prediction was proposed based on facial expression transfer, in which dynamic facial expression was interpreted as a matrix of facial depth changes. Data extracted from the pre-treatment smile expression record were applied to the post-treatment static model to realize expression transfer. Therefore smile esthetics of the patient after treatment could be evaluated in pre-treatment planning procedure. The positive and negative mean values of error for prediction accuracy were 0.9 and - 1.1 mm respectively, with the standard deviation of ± 1.5 mm, which is clinically acceptable. Further studies would be conducted to reduce the prediction error from both the static and dynamic sides as well as to explore automatically combined prediction from the two sides.

Introducing etch kernels for efficient pattern sampling and etch bias prediction

Science.gov (United States)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka

2018-01-01

Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

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Karacali Bilge

2007-10-01

Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

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Julien Becker

Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior.

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Tsoi, Lam C; Qin, Tingting; Slate, Elizabeth H; Zheng, W Jim

2011-11-11

To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets. We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray

Genetic prediction of male pattern baldness.

Science.gov (United States)

Hagenaars, Saskia P; Hill, W David; Harris, Sarah E; Ritchie, Stuart J; Davies, Gail; Liewald, David C; Gale, Catharine R; Porteous, David J; Deary, Ian J; Marioni, Riccardo E

2017-02-01

Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

Graded and discontinuous EphA-ephrinB expression patterns in the developing auditory brainstem.

Science.gov (United States)

Wallace, Matthew M; Harris, J Aaron; Brubaker, Donald Q; Klotz, Caitlyn A; Gabriele, Mark L

2016-05-01

Eph-ephrin interactions guide topographic mapping and pattern formation in a variety of systems. In contrast to other sensory pathways, their precise role in the assembly of central auditory circuits remains poorly understood. The auditory midbrain, or inferior colliculus (IC) is an intriguing structure for exploring guidance of patterned projections as adjacent subdivisions exhibit distinct organizational features. The central nucleus of the IC (CNIC) and deep aspects of its neighboring lateral cortex (LCIC, Layer 3) are tonotopically-organized and receive layered inputs from primarily downstream auditory sources. While less is known about more superficial aspects of the LCIC, its inputs are multimodal, lack a clear tonotopic order, and appear discontinuous, terminating in modular, patch/matrix-like distributions. Here we utilize X-Gal staining approaches in lacZ mutant mice (ephrin-B2, -B3, and EphA4) to reveal EphA-ephrinB expression patterns in the nascent IC during the period of projection shaping that precedes hearing onset. We also report early postnatal protein expression in the cochlear nuclei, the superior olivary complex, the nuclei of the lateral lemniscus, and relevant midline structures. Continuous ephrin-B2 and EphA4 expression gradients exist along frequency axes of the CNIC and LCIC Layer 3. In contrast, more superficial LCIC localization is not graded, but confined to a series of discrete ephrin-B2 and EphA4-positive Layer 2 modules. While heavily expressed in the midline, much of the auditory brainstem is devoid of ephrin-B3, including the CNIC, LCIC Layer 2 modular fields, the dorsal nucleus of the lateral lemniscus (DNLL), as well as much of the superior olivary complex and cochlear nuclei. Ephrin-B3 LCIC expression appears complementary to that of ephrin-B2 and EphA4, with protein most concentrated in presumptive extramodular zones. Described tonotopic gradients and seemingly complementary modular/extramodular patterns suggest Eph

77 FR 7601 - Notice of Segregation of Public Lands for the Pattern Energy Group Ocotillo Express Wind Energy...

Science.gov (United States)

2012-02-13

... LVRWB10B3980] Notice of Segregation of Public Lands for the Pattern Energy Group Ocotillo Express Wind Energy... Acts, for a period of 2 years for the purpose of processing a wind energy right-of-way (ROW... filed by Pattern Energy Group for the Ocotillo Express Wind Project on the above described lands while...

Do proposed facial expressions of contempt, shame, embarrassment, and compassion communicate the predicted emotion?

Science.gov (United States)

Widen, Sherri C; Christy, Anita M; Hewett, Kristen; Russell, James A

2011-08-01

Shame, embarrassment, compassion, and contempt have been considered candidates for the status of basic emotions on the grounds that each has a recognisable facial expression. In two studies (N=88, N=60) on recognition of these four facial expressions, observers showed moderate agreement on the predicted emotion when assessed with forced choice (58%; 42%), but low agreement when assessed with free labelling (18%; 16%). Thus, even though some observers endorsed the predicted emotion when it was presented in a list, over 80% spontaneously interpreted these faces in a way other than the predicted emotion.

Evolution-development congruence in pattern formation dynamics: Bifurcations in gene expression and regulation of networks structures.

Science.gov (United States)

Kohsokabe, Takahiro; Kaneko, Kunihiko

2016-01-01

Search for possible relationships between phylogeny and ontogeny is important in evolutionary-developmental biology. Here we uncover such relationships by numerical evolution and unveil their origin in terms of dynamical systems theory. By representing developmental dynamics of spatially located cells with gene expression dynamics with cell-to-cell interaction under external morphogen gradient, gene regulation networks are evolved under mutation and selection with the fitness to approach a prescribed spatial pattern of expressed genes. For most numerical evolution experiments, evolution of pattern over generations and development of pattern by an evolved network exhibit remarkable congruence. Both in the evolution and development pattern changes consist of several epochs where stripes are formed in a short time, while for other temporal regimes, pattern hardly changes. In evolution, these quasi-stationary regimes are generations needed to hit relevant mutations, while in development, they are due to some gene expression that varies slowly and controls the pattern change. The morphogenesis is regulated by combinations of feedback or feedforward regulations, where the upstream feedforward network reads the external morphogen gradient, and generates a pattern used as a boundary condition for the later patterns. The ordering from up to downstream is common in evolution and development, while the successive epochal changes in development and evolution are represented as common bifurcations in dynamical-systems theory, which lead to the evolution-development congruence. Mechanism of exceptional violation of the congruence is also unveiled. Our results provide a new look on developmental stages, punctuated equilibrium, developmental bottlenecks, and evolutionary acquisition of novelty in morphogenesis. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution Published by Wiley Periodicals, Inc.

Hierarchical clustering of gene expression patterns in the Eomes + lineage of excitatory neurons during early neocortical development

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Cameron David A

2012-08-01

Full Text Available Abstract Background Cortical neurons display dynamic patterns of gene expression during the coincident processes of differentiation and migration through the developing cerebrum. To identify genes selectively expressed by the Eomes + (Tbr2 lineage of excitatory cortical neurons, GFP-expressing cells from Tg(Eomes::eGFP Gsat embryos were isolated to > 99% purity and profiled. Results We report the identification, validation and spatial grouping of genes selectively expressed within the Eomes + cortical excitatory neuron lineage during early cortical development. In these neurons 475 genes were expressed ≥ 3-fold, and 534 genes ≤ 3-fold, compared to the reference population of neuronal precursors. Of the up-regulated genes, 328 were represented at the Genepaint in situ hybridization database and 317 (97% were validated as having spatial expression patterns consistent with the lineage of differentiating excitatory neurons. A novel approach for quantifying in situ hybridization patterns (QISP across the cerebral wall was developed that allowed the hierarchical clustering of genes into putative co-regulated groups. Forty four candidate genes were identified that show spatial expression with Intermediate Precursor Cells, 49 candidate genes show spatial expression with Multipolar Neurons, while the remaining 224 genes achieved peak expression in the developing cortical plate. Conclusions This analysis of differentiating excitatory neurons revealed the expression patterns of 37 transcription factors, many chemotropic signaling molecules (including the Semaphorin, Netrin and Slit signaling pathways, and unexpected evidence for non-canonical neurotransmitter signaling and changes in mechanisms of glucose metabolism. Over half of the 317 identified genes are associated with neuronal disease making these findings a valuable resource for studies of neurological development and disease.

BnDGAT1s Function Similarly in Oil Deposition and Are Expressed with Uniform Patterns in Tissues of Brassica napus

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Cuizhu Zhao

2017-12-01

Full Text Available As an allotetraploid oilcrop, Brassica napus contains four duplicated Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1 genes, which catalyze one of the rate-limiting steps in triacylglycerol (TAG biosynthesis in plants. While all four BnDGAT1s have been expressed functionally in yeast, their expression patterns in different germplasms and tissues and also consequent contribution to seed oil accumulation in planta remain to be elucidated. In this study, the coding regions of the four BnDGAT1s were expressed in an Arabidopsis dgat1 mutant. All four BnDGAT1s showed similar effects on oil content and fatty acid composition, a result which is different from that observed in previous studies of their expression in yeast. Expression patterns of BnDGAT1s were analyzed in developing seeds of 34 B. napus inbred lines and in different tissues of 14 lines. Different expression patterns were observed for the four BnDGAT1s, which suggests that they express independently or randomly in different germplasm sources. Higher expression of BnDGAT1s was correlated with higher seed oil content lines. Tissue-specific analyses showed that the BnDGAT1s were expressed in a uniform pattern in different tissues. Our results suggest that it is important to maintain expression of the four BnDGAT1s for maximum return on oil content.

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Short-range dynamics and prediction of mesoscale flow patterns in the MISTRAL field experiment

Energy Technology Data Exchange (ETDEWEB)

Weber, R.O.; Kaufmann, P.; Talkner, P. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1997-06-01

In a limited area of about 50 km by 50 km with complex topography, wind measurements on a dense network were performed during the MISTRAL field experiment in 1991-1992. From these data the characteristic wind fields were identified by an automated classification method. The dynamics of the resulting twelve typical regional flow patterns is studied. It is discussed how transitions between the flow patterns take place and how well the transition probabilities can be described in the framework of a Markov model. Guided by this discussion, a variety of prediction models were tested which allow a short-term forecast of the flow pattern type. It is found that a prediction model which uses forecast information from the synoptic scale has the best forecast skill. (author) 2 figs., 7 refs.

An interspecific fungal hybrid reveals cross-kingdom rules for allopolyploid gene expression patterns.

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Murray P Cox

2014-03-01

Full Text Available Polyploidy, a state in which the chromosome complement has undergone an increase, is a major force in evolution. Understanding the consequences of polyploidy has received much attention, and allopolyploids, which result from the union of two different parental genomes, are of particular interest because they must overcome a suite of biological responses to this merger, known as "genome shock." A key question is what happens to gene expression of the two gene copies following allopolyploidization, but until recently the tools to answer this question on a genome-wide basis were lacking. Here we utilize high throughput transcriptome sequencing to produce the first genome-wide picture of gene expression response to allopolyploidy in fungi. A novel pipeline for assigning sequence reads to the gene copies was used to quantify their expression in a fungal allopolyploid. We find that the transcriptional response to allopolyploidy is predominantly conservative: both copies of most genes are retained; over half the genes inherit parental gene expression patterns; and parental differential expression is often lost in the allopolyploid. Strikingly, the patterns of gene expression change are highly concordant with the genome-wide expression results of a cotton allopolyploid. The very different nature of these two allopolyploids implies a conserved, eukaryote-wide transcriptional response to genome merger. We provide evidence that the transcriptional responses we observe are mostly driven by intrinsic differences between the regulatory systems in the parent species, and from this propose a mechanistic model in which the cross-kingdom conservation in transcriptional response reflects conservation of the mutational processes underlying eukaryotic gene regulatory evolution. This work provides a platform to develop a universal understanding of gene expression response to allopolyploidy and suggests that allopolyploids are an exceptional system to investigate gene

Realistic prediction of individual facial emotion expressions for craniofacial surgery simulations

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Gladilin, Evgeny; Zachow, Stefan; Deuflhard, Peter; Hege, Hans-Christian

2003-05-01

In addition to the static soft tissue prediction, the estimation of individual facial emotion expressions is an important criterion for the evaluation of the carniofacial surgery planning. In this paper, we present an approach for the estimation of individual facial emotion expressions on the basis of geometrical models of human anatomy derived from tomographic data and the finite element modeling of facial tissue biomechanics.

Construction and evaluation of yeast expression networks by database-guided predictions

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Katharina Papsdorf

2016-05-01

Full Text Available DNA-Microarrays are powerful tools to obtain expression data on the genome-wide scale. We performed microarray experiments to elucidate the transcriptional networks, which are up- or down-regulated in response to the expression of toxic polyglutamine proteins in yeast. Such experiments initially generate hit lists containing differentially expressed genes. To look into transcriptional responses, we constructed networks from these genes. We therefore developed an algorithm, which is capable of dealing with very small numbers of microarrays by clustering the hits based on co-regulatory relationships obtained from the SPELL database. Here, we evaluate this algorithm according to several criteria and further develop its statistical capabilities. Initially, we define how the number of SPELL-derived co-regulated genes and the number of input hits influences the quality of the networks. We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. We find that this approach is useful for our own experimental data sets and also for many other data sets which we tested from the SPELL microarray database. Furthermore, the clusters obtained by the described algorithm greatly improve the assignment to biological processes and transcription factors for the individual clusters. Thus, the described clustering approach, which will be available through the ClusterEx web interface, and the evaluation parameters derived from it represent valuable tools for the fast and informative analysis of yeast microarray data.

The Influence of Gene Expression Time Delays on Gierer–Meinhardt Pattern Formation Systems

KAUST Repository

Seirin Lee, S.

2010-03-23

There are numerous examples of morphogen gradients controlling long range signalling in developmental and cellular systems. The prospect of two such interacting morphogens instigating long range self-organisation in biological systems via a Turing bifurcation has been explored, postulated, or implicated in the context of numerous developmental processes. However, modelling investigations of cellular systems typically neglect the influence of gene expression on such dynamics, even though transcription and translation are observed to be important in morphogenetic systems. In particular, the influence of gene expression on a large class of Turing bifurcation models, namely those with pure kinetics such as the Gierer-Meinhardt system, is unexplored. Our investigations demonstrate that the behaviour of the Gierer-Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen oscillations and radical sensitivities to the duration of gene expression are observed and, at best, severely restrict the possible parameter spaces for feasible biological behaviour. These results also indicate that the behaviour of Turing pattern formation systems on the inclusion of gene expression time delays may provide a means of distinguishing between possible forms of interaction kinetics. Finally, this study also emphasises that sub-cellular and gene expression dynamics should not be simply neglected in models of long range biological pattern formation via morphogens. © 2010 Society for Mathematical Biology.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

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Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

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Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

2012-07-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

CD147 expression predicts biochemical recurrence after prostatectomy independent of histologic and pathologic features.

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Bauman, Tyler M; Ewald, Jonathan A; Huang, Wei; Ricke, William A

2015-07-25

CD147 is an MMP-inducing protein often implicated in cancer progression. The purpose of this study was to investigate the expression of CD147 in prostate cancer (PCa) progression and the prognostic ability of CD147 in predicting biochemical recurrence after prostatectomy. Plasma membrane-localized CD147 protein expression was quantified in patient samples using immunohistochemistry and multispectral imaging, and expression was compared to clinico-pathological features (pathologic stage, Gleason score, tumor volume, preoperative PSA, lymph node status, surgical margins, biochemical recurrence status). CD147 specificity and expression were confirmed with immunoblotting of prostate cell lines, and CD147 mRNA expression was evaluated in public expression microarray datasets of patient prostate tumors. Expression of CD147 protein was significantly decreased in localized tumors (pT2; p = 0.02) and aggressive PCa (≥pT3; p = 0.004), and metastases (p = 0.001) compared to benign prostatic tissue. Decreased CD147 was associated with advanced pathologic stage (p = 0.009) and high Gleason score (p = 0.02), and low CD147 expression predicted biochemical recurrence (HR 0.55; 95 % CI 0.31-0.97; p = 0.04) independent of clinico-pathologic features. Immunoblot bands were detected at 44 kDa and 66 kDa, representing non-glycosylated and glycosylated forms of CD147 protein, and CD147 expression was lower in tumorigenic T10 cells than non-tumorigenic BPH-1 cells (p = 0.02). Decreased CD147 mRNA expression was associated with increased Gleason score and pathologic stage in patient tumors but is not associated with recurrence status. Membrane-associated CD147 expression is significantly decreased in PCa compared to non-malignant prostate tissue and is associated with tumor progression, and low CD147 expression predicts biochemical recurrence after prostatectomy independent of pathologic stage, Gleason score, lymph node status, surgical margins, and tumor volume in multivariable

Genetic prediction of male pattern baldness.

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Saskia P Hagenaars

2017-02-01

Full Text Available Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8. By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82% those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

Prediction of ion-exchange column breakthrough curves by constant-pattern wave approach.

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Lee, I-Hsien; Kuan, Yu-Chung; Chern, Jia-Ming

2008-03-21

The release of heavy metals from industrial wastewaters represents one of major threats to environment. Compared with chemical precipitation method, fixed-bed ion-exchange process can effectively remove heavy metals from wastewaters and generate no hazardous sludge. In order to design and operate fixed-bed ion-exchange processes successfully, it is very important to understand the column dynamics. In this study, the column experiments for Cu2+/H+, Zn2+/H+, and Cd2+/H+ systems using Amberlite IR-120 were performed to measure the breakthrough curves under varying operating conditions. The experimental results showed that total cation concentration in the mobile-phase played a key role on the breakthrough curves; a higher feed concentration resulted in an earlier breakthrough. Furthermore, the column dynamics was also predicted by self-sharpening and constant-pattern wave models. The self-sharpening wave model assuming local ion-exchange equilibrium could provide a simple and quick estimation for the breakthrough volume, but the predicted breakthrough curves did not match the experimental data very well. On the contrary, the constant-pattern wave model using a constant driving force model for finite ion-exchange rate provided a better fit to the experimental data. The obtained liquid-phase mass transfer coefficient was correlated to the flow velocity and other operating parameters; the breakthrough curves under varying operating conditions could thus be predicted by the constant-pattern wave model using the correlation.

Personality patterns predict the risk of antisocial behavior in Spanish-speaking adolescents.

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Alcázar-Córcoles, Miguel A; Verdejo-García, Antonio; Bouso-Sáiz, José C; Revuelta-Menéndez, Javier; Ramírez-Lira, Ezequiel

2017-05-01

There is a renewed interest in incorporating personality variables in criminology theories in order to build models able to integrate personality variables and biological factors with psychosocial and sociocultural factors. The aim of this article is the assessment of personality dimensions that contribute to the prediction of antisocial behavior in adolescents. For this purpose, a sample of adolescents from El Salvador, Mexico, and Spain was obtained. The sample consisted of 1035 participants with a mean age of 16.2. There were 450 adolescents from a forensic population (those who committed a crime) and 585 adolescents from the normal population (no crime committed). All of participants answered personality tests about neuroticism, extraversion, psychoticism, sensation seeking, impulsivity, and violence risk. Principal component analysis of the data identified two independent factors: (i) the disinhibited behavior pattern (PDC), formed by the dimensions of neuroticism, psychoticism, impulsivity and risk of violence; and (ii) the extrovert behavior pattern (PEC), formed by the dimensions of sensation risk and extraversion. Both patterns significantly contributed to the prediction of adolescent antisocial behavior in a logistic regression model which properly classifies a global percentage of 81.9%, 86.8% for non-offense and 72.5% for offense behavior. The classification power of regression equations allows making very satisfactory predictions about adolescent offense commission. Educational level has been classified as a protective factor, while age and gender (male) have been classified as risk factors.

Dynamical prediction and pattern mapping in short-term load forecasting

Energy Technology Data Exchange (ETDEWEB)

Aguirre, Luis Antonio; Rodrigues, Daniela D.; Lima, Silvio T. [Departamento de Engenharia Eletronica, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil); Martinez, Carlos Barreira [Departamento de Engenharia Hidraulica e Recursos Hidricos, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, 31270-901 Belo Horizonte, MG (Brazil)

2008-01-15

This work will not put forward yet another scheme for short-term load forecasting but rather will provide evidences that may improve our understanding about fundamental issues which underlay load forecasting problems. In particular, load forecasting will be decomposed into two main problems, namely dynamical prediction and pattern mapping. It is argued that whereas the latter is essentially static and becomes nonlinear when weekly features in the data are taken into account, the former might not be deterministic at all. In such cases there is no determinism (serial correlations) in the data apart from the average cycle and the best a model can do is to perform pattern mapping. Moreover, when there is determinism in addition to the average cycle, the underlying dynamics are sometimes linear, in which case there is no need to resort to nonlinear models to perform dynamical prediction. Such conclusions were confirmed using real load data and surrogate data analysis. In a sense, the paper details and organizes some general beliefs found in the literature on load forecasting. This sheds some light on real model-building and forecasting problems and helps understand some apparently conflicting results reported in the literature. (author)

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

Science.gov (United States)

Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

2017-09-01

Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

Pattern of somatostatin receptors expression in normal and bladder cancer tissue samples.

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Karavitakis, Markos; Msaouel, Pavlos; Michalopoulos, Vassilis; Koutsilieris, Michael

2014-06-01

Known risks factors for bladder cancer progression and recurrence are limited regarding their prognostic ability. Therefore identification of molecular determinants of disease progression could provide with more specific prognostic information and could be translated into new approaches for biomarker development. In the present study we evaluated, the expression patterns of somatostatin receptors 1-5 (SSTRs) in normal and tumor bladder tissues. The expression of SSTR1-5 was characterized in 45 normal and bladder cancer tissue samples using reverse transcriptase-polymerase chain reaction (RT-PCR). SSTR1 was expressed in 24 samples, SSTR2 in 15, SSTR3 in 23, SSTR4 in 16 and SSTR5 in all but one sample. Bladder cancer tissue samples expressed lower levels of SSTR3. Co-expression of SSTRs was associated with superficial disease. Our results demonstrate, for the first time, that there is expression of SSTR in normal and bladder cancer urothelium. Further studies are required to evaluate the prognostic and therapeutic significance of these findings. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Evolution‐development congruence in pattern formation dynamics: Bifurcations in gene expression and regulation of networks structures

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Kohsokabe, Takahiro

2016-01-01

ABSTRACT Search for possible relationships between phylogeny and ontogeny is important in evolutionary‐developmental biology. Here we uncover such relationships by numerical evolution and unveil their origin in terms of dynamical systems theory. By representing developmental dynamics of spatially located cells with gene expression dynamics with cell‐to‐cell interaction under external morphogen gradient, gene regulation networks are evolved under mutation and selection with the fitness to approach a prescribed spatial pattern of expressed genes. For most numerical evolution experiments, evolution of pattern over generations and development of pattern by an evolved network exhibit remarkable congruence. Both in the evolution and development pattern changes consist of several epochs where stripes are formed in a short time, while for other temporal regimes, pattern hardly changes. In evolution, these quasi‐stationary regimes are generations needed to hit relevant mutations, while in development, they are due to some gene expression that varies slowly and controls the pattern change. The morphogenesis is regulated by combinations of feedback or feedforward regulations, where the upstream feedforward network reads the external morphogen gradient, and generates a pattern used as a boundary condition for the later patterns. The ordering from up to downstream is common in evolution and development, while the successive epochal changes in development and evolution are represented as common bifurcations in dynamical‐systems theory, which lead to the evolution‐development congruence. Mechanism of exceptional violation of the congruence is also unveiled. Our results provide a new look on developmental stages, punctuated equilibrium, developmental bottlenecks, and evolutionary acquisition of novelty in morphogenesis. J. Exp. Zool. (Mol. Dev. Evol.) 326B:61–84, 2016. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution

Sympatry Predicts Spot Pigmentation Patterns and Female Association Behavior in the Livebearing Fish Poeciliopsis baenschi

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Roth-Monzón, Andrea J.; Scott, Laura E.; Camargo, Ashley A.; Clark, Eliza I.; Schott, Eric E.; Johnson, Jerald B.

2017-01-01

In this study, we explored the possibility that differences in pigmentation patterns among populations of the fish Poeciliopsis baenschi were associated with the presence or absence of the closely related species P. turneri. If reproductive character displacement is responsible, spotting patterns in these two species should diverge in sympatry, but not allopatry. We predicted that female P. baenschi from sympatric sites should show a preference for associating with conspecifics vs. heterospecific males, but females from allopatric sites should show no such preferences. To evaluate these predictions, we compared spotting patterns and female association behaviors in populations of P. baenschi from Central Mexico. We found that both of our predictions were supported. Poeciliopsis baenschi that co-occured with P. turneri had spotting patterns significantly different than their counterparts from allopatric sites. Using a simultaneous choice test of video presentations of males, we also found that female P. baenschi from populations that co-occured with P. turneri spent significantly more time with males of their own species than with P. turneri males. In contrast, females from allopatric populations of P. baenschi showed no differences in the amount of time they spent with either conspecific or heterospecific males. Together, our results are consistent with the hypothesis that reproductive character displacement may be responsible for behavioral and spotting pattern differences in these populations of P. baenschi. PMID:28107407

Expression of estrogen-related gene markers in breast cancer tissue predicts aromatase inhibitor responsiveness.

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Irene Moy

Full Text Available Aromatase inhibitors (AIs are the most effective class of drugs in the endocrine treatment of breast cancer, with an approximate 50% treatment response rate. Our objective was to determine whether intratumoral expression levels of estrogen-related genes are predictive of AI responsiveness in postmenopausal women with breast cancer. Primary breast carcinomas were obtained from 112 women who received AI therapy after failing adjuvant tamoxifen therapy and developing recurrent breast cancer. Tumor ERα and PR protein expression were analyzed by immunohistochemistry (IHC. Messenger RNA (mRNA levels of 5 estrogen-related genes-AKR1C3, aromatase, ERα, and 2 estradiol/ERα target genes, BRCA1 and PR-were measured by real-time PCR. Tumor protein and mRNA levels were compared with breast cancer progression rates to determine predictive accuracy. Responsiveness to AI therapy-defined as the combined complete response, partial response, and stable disease rates for at least 6 months-was 51%; rates were 56% in ERα-IHC-positive and 14% in ERα-IHC-negative tumors. Levels of ERα, PR, or BRCA1 mRNA were independently predictive for responsiveness to AI. In cross-validated analyses, a combined measurement of tumor ERα and PR mRNA levels yielded a more superior specificity (36% and identical sensitivity (96% to the current clinical practice (ERα/PR-IHC. In patients with ERα/PR-IHC-negative tumors, analysis of mRNA expression revealed either non-significant trends or statistically significant positive predictive values for AI responsiveness. In conclusion, expression levels of estrogen-related mRNAs are predictive for AI responsiveness in postmenopausal women with breast cancer, and mRNA expression analysis may improve patient selection.

The expression pattern of microRNAs in granulosa cells of subordinate and dominant follicles during the early luteal phase of the bovine estrous cycle.

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Dessie Salilew-Wondim

Full Text Available This study aimed to investigate the miRNA expression patterns in granulosa cells of subordinate (SF and dominant follicle (DF during the early luteal phase of the bovine estrous cycle. For this, miRNA enriched total RNA isolated from granulosa cells of SF and DF obtained from heifers slaughtered at day 3 and day 7 of the estrous cycle was used for miRNAs deep sequencing. The results revealed that including 17 candidate novel miRNAs, several known miRNAs (n = 291-318 were detected in SF and DF at days 3 and 7 of the estrous cycle of which 244 miRNAs were common to all follicle groups. The let-7 families, bta-miR-10b, bta-miR-26a, bta-miR-99b and bta-miR-27b were among abundantly expressed miRNAs in both SF and DF at both days of the estrous cycle. Further analysis revealed that the expression patterns of 16 miRNAs including bta-miR-449a, bta-miR-449c and bta-miR-222 were differentially expressed between the granulosa cells of SF and DF at day 3 of the estrous cycle. However, at day 7 of the estrous cycle, 108 miRNAs including bta-miR-409a, bta-miR-383 and bta-miR-184 were differentially expressed between the two groups of granulosa cell revealing the presence of distinct miRNA expression profile changes between the two follicular stages at day 7 than day 3 of the estrous cycle. In addition, unlike the SF, marked temporal miRNA expression dynamics was observed in DF groups between day 3 and 7 of the estrous cycle. Target gene prediction and pathway analysis revealed that major signaling associated with follicular development including Wnt signaling, TGF-beta signaling, oocyte meiosis and GnRH signaling were affected by differentially expressed miRNAs. Thus, this study highlights the miRNA expression patterns of granulosa cells in subordinate and dominant follicles that could be associated with follicular recruitment, selection and dominance during the early luteal phase of the bovine estrous cycle.

Differential expression patterns of metastasis suppressor proteins in basal cell carcinoma.

Science.gov (United States)

Bozdogan, Onder; Yulug, Isik G; Vargel, Ibrahim; Cavusoglu, Tarik; Karabulut, Ayse A; Karahan, Gurbet; Sayar, Nilufer

2015-08-01

Basal cell carcinomas (BCCs) are common malignant skin tumors. Despite having a significant invasion capacity, they metastasize only rarely. Our aim in this study was to detect the expression patterns of the NM23-H1, NDRG1, E-cadherin, RHOGDI2, CD82/KAI1, MKK4, and AKAP12 metastasis suppressor proteins in BCCs. A total of 96 BCC and 10 normal skin samples were included for the immunohistochemical study. Eleven frozen BCC samples were also studied by quantitative real time polymerase chain reaction (qRT-PCR) to detect the gene expression profile. NM23-H1 was strongly and diffusely expressed in all types of BCC. Significant cytoplasmic expression of NDRG1 and E-cadherin was also detected. However, AKAP12 and CD82/KAI1 expression was significantly decreased. The expressions of the other proteins were somewhere between the two extremes. Similarly, qRT-PCR analysis showed down-regulation of AKAP12 and up-regulation of NM23-H1 and NDRG1 in BCC. Morphologically aggressive BCCs showed significantly higher cytoplasmic NDRG1 expression scores and lower CD82/KAI1 scores than non-aggressive BCCs. The relatively preserved levels of NM23-H1, NDRG1, and E-cadherin proteins may have a positive effect on the non-metastasizing features of these tumors. © 2014 The International Society of Dermatology.

A comparative analysis of primary and secondary Gleason pattern predictive ability for positive surgical margins after radical prostatectomy.

Science.gov (United States)

Sfoungaristos, S; Kavouras, A; Kanatas, P; Polimeros, N; Perimenis, P

2011-01-01

To compare the predictive ability of primary and secondary Gleason pattern for positive surgical margins in patients with clinically localized prostate cancer and a preoperative Gleason score ≤ 6. A retrospective analysis of the medical records of patients undergone a radical prostatectomy between January 2005 and October 2010 was conducted. Patients' age, prostate volume, preoperative PSA, biopsy Gleason score, the 1st and 2nd Gleason pattern were entered a univariate and multivariate analysis. The 1st and 2nd pattern were tested for their ability to predict positive surgical margins using receiver operating characteristic curves. Positive surgical margins were noticed in 56 cases (38.1%) out of 147 studied patients. The 2nd pattern was significantly greater in those with positive surgical margins while the 1st pattern was not significantly different between the 2 groups of patients. ROC analysis revealed that area under the curve was 0.53 (p=0.538) for the 1st pattern and 0.60 (p=0.048) for the 2nd pattern. Concerning the cases with PSA <10 ng/ml, it was also found that only the 2nd pattern had a predictive ability (p=0.050). When multiple logistic regression analysis was conducted it was found that the 2nd pattern was the only independent predictor. The second Gleason pattern was found to be of higher value than the 1st one for the prediction of positive surgical margins in patients with preoperative Gleason score ≤ 6 and this should be considered especially when a neurovascular bundle sparing radical prostatectomy is planned, in order not to harm the oncological outcome.

Aberrant membranous expression of β-catenin predicts poor prognosis in patients with craniopharyngioma.

Science.gov (United States)

Li, Zongping; Xu, Jianguo; Huang, Siqing; You, Chao

2015-12-01

The objective of this study is to investigate β-catenin expression in craniopharyngioma patients and determine its significance in predicting the prognosis of this disease. Fifty craniopharyngioma patients were enrolled in this study. Expression of β-catenin in tumor specimens collected from these patients was examined through immunostaining. In addition, mutation of exon 3 in the β-catenin gene, CTNNB1, was analyzed using polymerase chain reaction, denaturing high-pressure liquid chromatography, and DNA sequencing. Based on these results, we explored the association between membranous β-catenin expression, clinical and pathologic characteristics, and prognoses in these patients. Of all craniopharyngioma specimens, 31 (62.0%) had preserved membranous β-catenin expression, whereas the remaining 19 specimens (38.0%) displayed aberrant expression. Statistical analysis showed a significant correlation between aberrant membranous β-catenin expression and CTNNB1 exon 3 mutation, as well as between aberrant membranous β-catenin expression and the histopathologic type of craniopharyngioma and type of resection in our patient population. Furthermore, aberrant membranous β-catenin expression was found to be associated with poor patient survival. Results of Kaplan-Meier survival analysis and Cox regression analysis further confirmed this finding. In conclusion, our study demonstrated that aberrant membranous β-catenin expression was significantly correlated with poor survival in patients with craniopharyngioma. This raises the possibility for use of aberrant membranous β-catenin expression as an independent risk factor in predicting the prognosis of this disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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Teng Shaolei

2013-01-01

Full Text Available Abstract Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs and Support Vector Machines (SVMs were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression.

Could the outcome of the 2016 US elections have been predicted from past voting patterns?

CSIR Research Space (South Africa)

Schmitz, Peter MU

2017-07-01

Full Text Available In South Africa, a team of analysts has for some years been using statistical techniques to predict election outcomes during election nights in South Africa. The prediction method involves using statistical clusters based on past voting patterns...

Inducible defenses stay up late: temporal patterns of immune gene expression in Tenebrio molitor.

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Johnston, Paul R; Makarova, Olga; Rolff, Jens

2013-12-06

The course of microbial infection in insects is shaped by a two-stage process of immune defense. Constitutive defenses, such as engulfment and melanization, act immediately and are followed by inducible defenses, archetypically the production of antimicrobial peptides, which eliminate or suppress the remaining microbes. By applying RNAseq across a 7-day time course, we sought to characterize the long-lasting immune response to bacterial challenge in the mealworm beetle Tenebrio molitor, a model for the biochemistry of insect immunity and persistent bacterial infection. By annotating a hybrid de novo assembly of RNAseq data, we were able to identify putative orthologs for the majority of components of the conserved insect immune system. Compared with Tribolium castaneum, the most closely related species with a reference genome sequence and a manually curated immune system annotation, the T. molitor immune gene count was lower, with lineage-specific expansions of genes encoding serine proteases and their countervailing inhibitors accounting for the majority of the deficit. Quantitative mapping of RNAseq reads to the reference assembly showed that expression of genes with predicted functions in cellular immunity, wound healing, melanization, and the production of reactive oxygen species was transiently induced immediately after immune challenge. In contrast, expression of genes encoding antimicrobial peptides or components of the Toll signaling pathway and iron sequestration response remained elevated for at least 7 days. Numerous genes involved in metabolism and nutrient storage were repressed, indicating a possible cost of immune induction. Strikingly, the expression of almost all antibacterial peptides followed the same pattern of long-lasting induction, regardless of their spectra of activity, signaling possible interactive roles in vivo. Copyright © 2014 Johnston et al.

Differential expression patterns and clinical significance of estrogen receptor-α and β in papillary thyroid carcinoma

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Huang, Yanhong; Dong, Wenwu; Li, Jing; Zhang, Hao; Shan, Zhongyan; Teng, Weiping

2014-01-01

The incidence of papillary thyroid cancer (PTC) is markedly higher in women than men during the reproductive years. In vitro studies have suggested that estrogen may play an important role in the development and progression of PTC through estrogen receptors (ERs). This study aimed to investigate the expression patterns of the two main ER subtypes, α and β1 (wild-type ERβ), in PTC tissue and their clinical significance. Immunohistochemical staining of thyroid tissue sections was performed to detect ER expression in female patients with PTC (n = 89) and nodular thyroid goiter (NTG; n = 30) using the Elivision™ plus two-step system. The relationships between ER subtype expression and clinicopathological/biological factors were further analyzed. The positive percentage and expression levels of ERα were significantly higher in female PTC patients of reproductive age (18–45 years old; n = 50) than age-matched female NTG patients (n = 30), while ERβ1 exhibited the opposite pattern. There was no difference in ERα or ERβ1 expression between female PTC patients of reproductive age and those of advanced reproductive age (>45 years old; n = 39). In the female PTC patients of reproductive age, ERα expression level was positively correlated with that of Ki-67, while ERβ1 was negatively correlated with mutant P53. Furthermore, more patients with exclusively nuclear ERα expression had extrathyroidal extension (ETE) as compared with those with extranuclear ERα localization. VEGF expression was significantly decreased in female PTC patients of reproductive age with only nuclear ERβ1 expression when compared with those with extranuclear ERβ1 localization. In PTC patients of advanced reproductive age, neither ERα nor ERβ1 expression showed any correlation with that of Ki-67, mutant P53, VEGF, tumor size, TNM stage, ETE, or lymph node metastases. The differential expression patterns of the two ER subtypes between PTC and NTG indicate that ERα may be a useful

Response-predictive gene expression profiling of glioma progenitor cells in vitro.

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Sylvia Moeckel

Full Text Available High-grade gliomas are amongst the most deadly human tumors. Treatment results are disappointing. Still, in several trials around 20% of patients respond to therapy. To date, diagnostic strategies to identify patients that will profit from a specific therapy do not exist.In this study, we used serum-free short-term treated in vitro cell cultures to predict treatment response in vitro. This approach allowed us (a to enrich specimens for brain tumor initiating cells and (b to confront cells with a therapeutic agent before expression profiling.As a proof of principle we analyzed gene expression in 18 short-term serum-free cultures of high-grade gliomas enhanced for brain tumor initiating cells (BTIC before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed to predict therapy-induced impairment of proliferation in vitro.For the tyrosine kinase inhibitor Sunitinib used in this dataset, the approach revealed additional predictive information in comparison to the evaluation of classical signaling analysis.

The distribution pattern of ERα expression, ESR1 genetic variation and expression of growth factor receptors: association with breast cancer prognosis in Russian patients treated with adjuvant tamoxifen.

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Babyshkina, Nataliya; Vtorushin, Sergey; Zavyalova, Marina; Patalyak, Stanislav; Dronova, Tatyana; Litviakov, Nikolay; Slonimskaya, Elena; Kzhyshkowska, Julia; Cherdyntseva, Nadejda; Choynzonov, Evgeny

2017-08-01

Identification of additional biomarkers associated with ER genomic and nongenomic pathways could be very useful to distinguish patients who will benefit from tamoxifen treatment. The aim of this study was to analyze the prognostic significance of the distribution pattern of ERα expression, ESR1 gene single-nucleotide polymorphisms and expression levels of growth factor receptors in Russian hormone receptor-positive breast cancer patients treated with adjuvant tamoxifen. Formalin-fixed paraffin-embedded tumor tissue samples from 97 patients were examined for the distribution pattern of ERα expression, as well as for EGFR and TGF-βR1 expression by immunohistochemistry. Genotypes for ESR1 +30T>C (rs2077647) and ESR1 2014G>A (rs2228480) were analyzed using a TaqMan assay. Progression-free survival (PFS) was used as an endpoint for the survival analyses. We found that patients with the heterogeneous distribution of ERα expression had poor prognosis on tamoxifen treatment (P = 0.021). We identified a high EGFR expression in patients who developed distant metastasis or recurrence during tamoxifen treatment (a tamoxifen-resistant group-TR) in contrast to the distant metastasis-free patients (a tamoxifen-sensitive group-TS) (80.0 vs. 41.9 %, respectively, P = 0.009). Carriers of the ESR12014A mutant allele were more prevalent among the TR patients compared to the TS patients (26.3 vs. 8.0 %, respectively, P = 0.009). EGFR expression and the distribution pattern of ERα expression were associated with the response to tamoxifen by both univariate and multivariate logistic regression analyses. The presence of these markers either alone or in combination was correlated with the worse PFS for all patients. Analysis of the distribution pattern of ERα expression and the EGFR status in tumor tissue may be valuable for patient selection for tamoxifen adjuvant therapy.

AP-2α and AP-2β cooperatively orchestrate homeobox gene expression during branchial arch patterning.

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Van Otterloo, Eric; Li, Hong; Jones, Kenneth L; Williams, Trevor

2018-01-25

The evolution of a hinged moveable jaw with variable morphology is considered a major factor behind the successful expansion of the vertebrates. DLX homeobox transcription factors are crucial for establishing the positional code that patterns the mandible, maxilla and intervening hinge domain, but how the genes encoding these proteins are regulated remains unclear. Herein, we demonstrate that the concerted action of the AP-2α and AP-2β transcription factors within the mouse neural crest is essential for jaw patterning. In the absence of these two proteins, the hinge domain is lost and there are alterations in the size and patterning of the jaws correlating with dysregulation of homeobox gene expression, with reduced levels of Emx, Msx and Dlx paralogs accompanied by an expansion of Six1 expression. Moreover, detailed analysis of morphological features and gene expression changes indicate significant overlap with various compound Dlx gene mutants. Together, these findings reveal that the AP-2 genes have a major function in mammalian neural crest development, influencing patterning of the craniofacial skeleton via the DLX code, an effect that has implications for vertebrate facial evolution, as well as for human craniofacial disorders. © 2018. Published by The Company of Biologists Ltd.

Pattern-Recognition Receptor Signaling Regulator mRNA Expression in Humans and Mice, and in Transient Inflammation or Progressive Fibrosis

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Günthner, Roman; Kumar, Vankayala Ramaiah Santhosh; Lorenz, Georg; Anders, Hans-Joachim; Lech, Maciej

2013-01-01

The cell type-, organ-, and species-specific expression of the pattern-recognition receptors (PRRs) are well described but little is known about the respective expression profiles of their negative regulators. We therefore determined the mRNA expression levels of A20, CYLD, DUBA, ST2, CD180, SIGIRR, TANK, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, SHP1, SHP2, TOLLIP, IRF4, SIKE, NLRX1, ERBIN, CENTB1, and Clec4a2 in human and mouse solid organs. Humans and mice displayed significant differences between their respective mRNA expression patterns of these factors. Additionally, we characterized their expression profiles in mononuclear blood cells upon bacterial endotoxin, which showed a consistent induction of A20, SOCS3, IRAK-M, and Clec4a2 in human and murine cells. Furthermore, we studied the expression pattern in transient kidney ischemia-reperfusion injury versus post-ischemic atrophy and fibrosis in mice. A20, CD180, ST2, SOCS1, SOCS3, SHIP, IRAK-M, DOK1, DOK2, IRF4, CENTB1, and Clec4a2 were all induced, albeit at different times of injury and repair. Progressive fibrosis was associated with a persistent induction of these factors. Thus, the organ- and species-specific expression patterns need to be considered in the design and interpretation of studies related to PRR-mediated innate immunity, which seems to be involved in tissue injury, tissue regeneration and in progressive tissue scarring. PMID:24009023

Gene expression pattern at different time points following ALA-PDT

International Nuclear Information System (INIS)

Verwanger, T.; Sanovic, R.; Ruhdorfer, S.; Aberger, F.; Frischauf, A.; Krammer, B.

2003-01-01

Full text: The photo sensitizer protoporphyrin IX, endogenously accumulated from the precursor aminolevulinic acid (ALA), is a successful agent in photodynamic tumor therapy. In spite of encouraging clinical results, the basic mechanisms leading to cell death are not fully understood. We therefore set out to analyze the alteration of the gene expression pattern in the squamous cell carcinoma cell line A-431 at different time points after photodynamic treatment with endogenous protoporphyrin IX by cDNA-array technique. Cells were incubated for 16 hours with 100 μg/ml ALA and irradiated with a fluence of 3.5 J/cm 2 resulting in 50 % survival until 8 hours post treatment. RNA was isolated at 1.5, 3, 5 and 8 hours post treatment as well as of 3 controls (untreated, light only and dark), radioactively labelled by reverse transcription with 33P-dCTP and hybridized onto macroarray PCR filters containing PCR products of 2135 genes, which were selected for relevance in tumors, stress response and signal transduction. Verification of observed expression changes was carried out by real time PCR. We found a strong induction of expression of immediate early genes like c-fos as well as decreased expression of genes involved in proliferation like myc and the proliferating cell nuclear antigen (PCNA). (author)

Predicting vehicle fuel consumption patterns using floating vehicle data.

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Du, Yiman; Wu, Jianping; Yang, Senyan; Zhou, Liutong

2017-09-01

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers' information and vehicles' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model. Copyright © 2017. Published by Elsevier B.V.

MRI features can predict EGFR expression in lower grade gliomas. A voxel-based radiomic analysis

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Li, Yiming; Liu, Xing; Qian, Zenghui; Fan, Xing; Li, Shaowu; Jiang, Tao [Capital Medical University, Beijing Neurosurgical Institute, Beijing (China); Xu, Kaibin [Chinese Academy of Sciences, Institute of Automation, Beijing (China); Wang, Kai [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Wang, Yinyan [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Beijing Tiantan Hospital, Capital Medical University, Department of Neurosurgery, Beijing (China)

2018-01-15

To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis. 270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set. A signature of 41 MRI features achieved accuracies of 82.5% (area under the curve [AUC] = 0.90) in the training set and 90.0% (AUC = 0.95) in the validation set. This radiomic signature consisted of 25 first-order statistics or related wavelet features (including range, standard deviation, uniformity, variance), one shape and size-based feature (spherical disproportion), and 15 textural features or related wavelet features (including sum variance, sum entropy, run percentage). A radiomic signature allowing for the prediction of the EGFR expression level in patients with lower grade glioma was identified, suggesting that using tumour-derived radiological features for predicting genomic information is feasible. (orig.)

Klf8 regulates left-right asymmetric patterning through modulation of Kupffer's vesicle morphogenesis and spaw expression.

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Lin, Che-Yi; Tsai, Ming-Yuan; Liu, Yu-Hsiu; Lu, Yu-Fen; Chen, Yi-Chung; Lai, Yun-Ren; Liao, Hsin-Chi; Lien, Huang-Wei; Yang, Chung-Hsiang; Huang, Chang-Jen; Hwang, Sheng-Ping L

2017-07-17

Although vertebrates are bilaterally symmetric organisms, their internal organs are distributed asymmetrically along a left-right axis. Disruption of left-right axis asymmetric patterning often occurs in human genetic disorders. In zebrafish embryos, Kupffer's vesicle, like the mouse node, breaks symmetry by inducing asymmetric expression of the Nodal-related gene, spaw, in the left lateral plate mesoderm (LPM). Spaw then stimulates transcription of itself and downstream genes, including lft1, lft2, and pitx2, specifically in the left side of the diencephalon, heart and LPM. This developmental step is essential to establish subsequent asymmetric organ positioning. In this study, we evaluated the role of krüppel-like factor 8 (klf8) in regulating left-right asymmetric patterning in zebrafish embryos. Zebrafish klf8 expression was disrupted by both morpholino antisense oligomer-mediated knockdown and a CRISPR-Cas9 system. Whole-mount in situ hybridization was conducted to evaluate gene expression patterns of Nodal signalling components and the positions of heart and visceral organs. Dorsal forerunner cell number was evaluated in Tg(sox17:gfp) embryos and the length and number of cilia in Kupffer's vesicle were analyzed by immunocytochemistry using an acetylated tubulin antibody. Heart jogging, looping and visceral organ positioning were all defective in zebrafish klf8 morphants. At the 18-22 s stages, klf8 morphants showed reduced expression of genes encoding Nodal signalling components (spaw, lft1, lft2, and pitx2) in the left LPM, diencephalon, and heart. Co-injection of klf8 mRNA with klf8 morpholino partially rescued spaw expression. Furthermore, klf8 but not klf8△zf overexpressing embryos showed dysregulated bilateral expression of Nodal signalling components at late somite stages. At the 10s stage, klf8 morphants exhibited reductions in length and number of cilia in Kupffer's vesicle, while at 75% epiboly, fewer dorsal forerunner cells were observed

Women's gender role orientation predicts their drinking patterns: a follow-up study of Czech women.

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Kubicka, Ludek; Csémy, Ladislav

2008-06-01

Evaluation of the hypothesis that women's non-traditional gender role orientation contributes to drinking patterns typical for men. A two-wave prospective study with data collected in 1992 and 1997. The data reflect Czech women's changing gender role orientation and their drinking patterns during a historical period of post-totalitarian societal transformation. A representative cohort of 497 Prague women aged 30-59 years in 1997. Face-to-face interview data on drinking patterns and individually collected original questionnaire on gender role orientation. An analysis of the principal components of the gender role orientation questionnaire has led to four components, designated as egalitarianism, liberalism, feminism and hedonism. Constructed role orientation scales had Cronbachs's alpha reliabilities ranging from 0.57 to 0.74. With possible confounders controlled (thanks mainly to the prospective design), non-traditional gender role orientation components assessed in 1992 predicted the usual quantities of alcohol women have consumed per occasion in 1997, as well as three hazardous drinking patterns (occasional use of > or = 96 g alcohol, usual use of > or = 48 g and daily intake of > or = 40 g). Specifically, women's usual quantity per occasion and occasional use of > or = 96 g were predicted by egalitarianism and hedonism, and hedonism predicted usual use of > or = 48 g as well as average daily intake of > or = 40 g ethanol. Women's gender role orientation can be associated with their drinking patterns with non-traditional gender role identification being associated with greater likelihood of hazardous drinking.

CD147 expression predicts biochemical recurrence after prostatectomy independent of histologic and pathologic features

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Bauman, Tyler M.; Ewald, Jonathan A.; Huang, Wei; Ricke, William A.

2015-01-01

CD147 is an MMP-inducing protein often implicated in cancer progression. The purpose of this study was to investigate the expression of CD147 in prostate cancer (PCa) progression and the prognostic ability of CD147 in predicting biochemical recurrence after prostatectomy. Plasma membrane-localized CD147 protein expression was quantified in patient samples using immunohistochemistry and multispectral imaging, and expression was compared to clinico-pathological features (pathologic stage, Gleason score, tumor volume, preoperative PSA, lymph node status, surgical margins, biochemical recurrence status). CD147 specificity and expression were confirmed with immunoblotting of prostate cell lines, and CD147 mRNA expression was evaluated in public expression microarray datasets of patient prostate tumors. Expression of CD147 protein was significantly decreased in localized tumors (pT2; p = 0.02) and aggressive PCa (≥pT3; p = 0.004), and metastases (p = 0.001) compared to benign prostatic tissue. Decreased CD147 was associated with advanced pathologic stage (p = 0.009) and high Gleason score (p = 0.02), and low CD147 expression predicted biochemical recurrence (HR 0.55; 95 % CI 0.31–0.97; p = 0.04) independent of clinico-pathologic features. Immunoblot bands were detected at 44 kDa and 66 kDa, representing non-glycosylated and glycosylated forms of CD147 protein, and CD147 expression was lower in tumorigenic T10 cells than non-tumorigenic BPH-1 cells (p = 0.02). Decreased CD147 mRNA expression was associated with increased Gleason score and pathologic stage in patient tumors but is not associated with recurrence status. Membrane-associated CD147 expression is significantly decreased in PCa compared to non-malignant prostate tissue and is associated with tumor progression, and low CD147 expression predicts biochemical recurrence after prostatectomy independent of pathologic stage, Gleason score, lymph node status, surgical margins, and tumor volume in multivariable

A theoty of fast search for feul loading pattern in lWRs

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Suo Changan

1990-01-01

In order to fast search for fuel loading pattern without trial and error, a theory for predicting in-core reactivity distribution, according to power necessity and available assemblies, has been developed on basis of the fast computing nodal method and two group diffusion theory. In that, the fast group flux distribution can be predicted from power necessity and the approximation of fast group constants to be independent of nodes. Then, the thermal group fluxes are expressed by both known powers and predicted fast fluxes. After replacing thermal flux, the thermal diffusion equations turn into some equations that have only unknown group constants. The unknown constants are expressed approximately by making use of some expansions of infinite multiplication factors of available assemblies. In such a way, the non-linear reactivity equations are developed and then solved, where node reactivities are the only unknown physical quantities, Finally, the loading pattern is obtained by setting some of available assemblies at each node location where corresponds to a closest reactivity of between laid assembly and node. A computer code LOADMP based on the theory has been made. The theory has been tested numerically on IAEA benchmark problem, and gives an accurate prediction of reactivity distribution and loading pattern. The CPU-time for making a loading pattern search is saved very much, about one second on the CYPER-825/170 machine

Strengths and weaknesses of EST-based prediction of tissue-specific alternative splicing

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Vingron Martin

2004-09-01

Full Text Available Abstract Background Alternative splicing contributes significantly to the complexity of the human transcriptome and proteome. Computational prediction of alternative splice isoforms are usually based on EST sequences that also allow to approximate the expression pattern of the related transcripts. However, the limited number of tissues represented in the EST data as well as the different cDNA construction protocols may influence the predictive capacity of ESTs to unravel tissue-specifically expressed transcripts. Methods We predict tissue and tumor specific splice isoforms based on the genomic mapping (SpliceNest of the EST consensus sequences and library annotation provided in the GeneNest database. We further ascertain the potentially rare tissue specific transcripts as the ones represented only by ESTs derived from normalized libraries. A subset of the predicted tissue and tumor specific isoforms are then validated via RT-PCR experiments over a spectrum of 40 tissue types. Results Our strategy revealed 427 genes with at least one tissue specific transcript as well as 1120 genes showing tumor specific isoforms. While our experimental evaluation of computationally predicted tissue-specific isoforms revealed a high success rate in confirming the expression of these isoforms in the respective tissue, the strategy frequently failed to detect the expected restricted expression pattern. The analysis of putative lowly expressed transcripts using normalized cDNA libraries suggests that our ability to detect tissue-specific isoforms strongly depends on the expression level of the respective transcript as well as on the sensitivity of the experimental methods. Especially splice isoforms predicted to be disease-specific tend to represent transcripts that are expressed in a set of healthy tissues rather than novel isoforms. Conclusions We propose to combine the computational prediction of alternative splice isoforms with experimental validation for

Gene expression signatures that predict radiation exposure in mice and humans.

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Holly K Dressman

2007-04-01

Full Text Available The capacity to assess environmental inputs to biological phenotypes is limited by methods that can accurately and quantitatively measure these contributions. One such example can be seen in the context of exposure to ionizing radiation.We have made use of gene expression analysis of peripheral blood (PB mononuclear cells to develop expression profiles that accurately reflect prior radiation exposure. We demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1,000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from nonirradiated samples with an accuracy of 90%, sensitivity of 85%, and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and nonirradiated human patients with an accuracy of 77%, sensitivity of 82%, and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated that are highly predictive of different levels of radiation exposure in mice and humans.We suggest that this approach, with additional refinement, could provide a method to assess the effects of various environmental inputs into biological phenotypes as well as providing a more practical application of a rapid molecular screening test for the diagnosis of radiation exposure.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

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Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Expression of Ku70 predicts results of radiotherapy in prostate cancer

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Hasegawa, Tomokazu; Someya, Masanori; Hori, Masakazu; Nakata, Kensei; Kitagawa, Mio; Tsuchiya, Takaaki; Sakata, Koh-ichi [Sapporo Medical University School of medicine, Department of Radiology, Chuo-ku, Sapporo, Hokkaido (Japan); Matsumoto, Yoshihisa [Research Laboratory for Nuclear Reactors, Tokyo Institute of Technology, Meguro-ku, Tokyo (Japan); Nojima, Masanori [The University of Tokyo, The Institute of Medical Science Hospital, Minatoku, Tokyo (Japan); Masumori, Naoya [Sapporo Medical University School of medicine, Department of Urology, Chuo-ku, Sapporo, Hokkaido (Japan); Hasegawa, Tadashi [Sapporo Medical University School of medicine, Department of Surgical Pathology, Chuo-ku, Sapporo, Hokkaido (Japan)

2017-01-15

Therapeutic strategy for prostate cancer is decided according to T stage, Gleason score, and prostate-specific antigen (PSA) level. These clinical factors are not accurate enough to predict individual risk of local failure of prostate cancer after radiotherapy. Parameters involved with radiosensitivity are required to improve the predictive capability for local relapse. We analyzed 58 patients with localized adenocarcinoma of the prostate between August 2007 and October 2010 treated with 76 Gy of intensity-modulated radiotherapy (IMRT) as a discovery cohort and 42 patients between March 2001 and May 2007 treated with three-dimensional conformal radiotherapy (3D-CRT) as a validation cohort. Immunohistochemical examination for proteins involved in nonhomologous end-joining was performed using biopsy specimens. Ku70 expression was not correlated with various clinical parameters, such as the Gleason score and D'amico risk classification, indicating that Ku70 expression was an independent prognostic factor. The predictive value for PSA relapse was markedly improved after the combination of Gleason score and Ku70 expression, as compared with Gleason score alone. In patients treated with radiotherapy and androgen deprivation therapy (ADT), no relapses were observed in patients with Gleason score ≤7 or low Ku70 expression. In contrast, patients with Gleason score ≥8 and high Ku70 expression had high PSA relapse rates. In the validation cohort, similar results were obtained. Treatment with 76 Gy and ADT can be effective for patients with Gleason score ≤7 or low Ku70 expression, but is not enough for patients with Gleason score ≥8 and high Ku70 expression and, thus, require other treatment approaches. (orig.) [German] Die Behandlung beim Prostatakarzinom ist abhaengig von T-Stadium, Gleason-Score und prostataspezifischem Antigen (PSA). Diese klinischen Faktoren sind jedoch zu ungenau, um das individuelle Lokalrezidivrisiko beim Prostatakarzinom nach

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

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Borlawsky Tara B

2010-10-01

Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

Clustering gene expression data based on predicted differential effects of GV interaction.

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Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

The combined expression patterns of Ikaros isoforms characterize different hematological tumor subtypes.

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Orozco, Carlos A; Acevedo, Andrés; Cortina, Lazaro; Cuellar, Gina E; Duarte, Mónica; Martín, Liliana; Mesa, Néstor M; Muñoz, Javier; Portilla, Carlos A; Quijano, Sandra M; Quintero, Guillermo; Rodriguez, Miriam; Saavedra, Carlos E; Groot, Helena; Torres, María M; López-Segura, Valeriano

2013-01-01

A variety of genetic alterations are considered hallmarks of cancer development and progression. The Ikaros gene family, encoding for key transcription factors in hematopoietic development, provides several examples as genetic defects in these genes are associated with the development of different types of leukemia. However, the complex patterns of expression of isoforms in Ikaros family genes has prevented their use as clinical markers. In this study, we propose the use of the expression profiles of the Ikaros isoforms to classify various hematological tumor diseases. We have standardized a quantitative PCR protocol to estimate the expression levels of the Ikaros gene exons. Our analysis reveals that these levels are associated with specific types of leukemia and we have found differences in the levels of expression relative to five interexonic Ikaros regions for all diseases studied. In conclusion, our method has allowed us to precisely discriminate between B-ALL, CLL and MM cases. Differences between the groups of lymphoid and myeloid pathologies were also identified in the same way.

Differential gene expression patterns between smokers and non‐smokers: cause or consequence?

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Jansen, Rick; Brooks, Andy; Willemsen, Gonneke; van Grootheest, Gerard; de Geus, Eco; Smit, Jan H.; Penninx, Brenda W.; Boomsma, Dorret I.

2015-01-01

Abstract The molecular mechanisms causing smoking‐induced health decline are largely unknown. To elucidate the molecular pathways involved in cause and consequences of smoking behavior, we conducted a genome‐wide gene expression study in peripheral blood samples targeting 18 238 genes. Data of 743 smokers, 1686 never smokers and 890 ex‐smokers were available from two population‐based cohorts from the Netherlands. In addition, data of 56 monozygotic twin pairs discordant for ever smoking were used. One hundred thirty‐two genes were differentially expressed between current smokers and never smokers (P smokers into account, expression of these 132 genes was classified into reversible (94 genes), slowly reversible (31 genes), irreversible (6 genes) or inconclusive (1 gene). Expression of 6 of the 132 genes (three reversible and three slowly reversible) was confirmed to be reactive to smoking as they were differentially expressed in monozygotic pairs discordant for smoking. Cis‐expression quantitative trait loci for GPR56 and RARRES3 (downregulated in smokers) were associated with increased number of cigarettes smoked per day in a large genome‐wide association meta‐analysis, suggesting a causative effect of GPR56 and RARRES3 expression on smoking behavior. In conclusion, differential gene expression patterns in smokers are extensive and cluster in several underlying disease pathways. Gene expression differences seem mainly direct consequences of smoking, and largely reversible after smoking cessation. However, we also identified DNA variants that may influence smoking behavior via the mediating gene expression. PMID:26594007

Rootstock-regulated gene expression patterns associated with fire blight resistance in apple

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Jensen Philip J

2012-01-01

Full Text Available Abstract Background Desirable apple varieties are clonally propagated by grafting vegetative scions onto rootstocks. Rootstocks influence many phenotypic traits of the scion, including resistance to pathogens such as Erwinia amylovora, which causes fire blight, the most serious bacterial disease of apple. The purpose of the present study was to quantify rootstock-mediated differences in scion fire blight susceptibility and to identify transcripts in the scion whose expression levels correlated with this response. Results Rootstock influence on scion fire blight resistance was quantified by inoculating three-year old, orchard-grown apple trees, consisting of 'Gala' scions grafted to a range of rootstocks, with E. amylovora. Disease severity was measured by the extent of shoot necrosis over time. 'Gala' scions grafted to G.30 or MM.111 rootstocks showed the lowest rates of necrosis, while 'Gala' on M.27 and B.9 showed the highest rates of necrosis. 'Gala' scions on M.7, S.4 or M.9F56 had intermediate necrosis rates. Using an apple DNA microarray representing 55,230 unique transcripts, gene expression patterns were compared in healthy, un-inoculated, greenhouse-grown 'Gala' scions on the same series of rootstocks. We identified 690 transcripts whose steady-state expression levels correlated with the degree of fire blight susceptibility of the scion/rootstock combinations. Transcripts known to be differentially expressed during E. amylovora infection were disproportionately represented among these transcripts. A second-generation apple microarray representing 26,000 transcripts was developed and was used to test these correlations in an orchard-grown population of trees segregating for fire blight resistance. Of the 690 transcripts originally identified using the first-generation array, 39 had expression levels that correlated with fire blight resistance in the breeding population. Conclusions Rootstocks had significant effects on the fire blight

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

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Mohammad Manir Hossain Mollah

Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

Reduced glucocorticoid receptor expression predicts bladder tumor recurrence and progression.

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Ishiguro, Hitoshi; Kawahara, Takashi; Zheng, Yichun; Netto, George J; Miyamoto, Hiroshi

2014-08-01

To assess the levels of glucocorticoid receptor (GR) expression in bladder tumors because the status and its prognostic value remain largely unknown. We immunohistochemically stained for GR in bladder tumor and matched non-neoplastic bladder tissue specimens. Overall, GR was positive in 129 (87%) of 149 urothelial tumors, which was significantly (P=.026) lower than in non-neoplastic urothelium (90 [96%] of 94). Forty-two (79%) of 53 low-grade tumors vs 45 (47%) of 96 high-grade carcinomas (Pcancer-specific survival of MI tumors (P=.067). Multivariate analysis identified low GR expression as a strong predictor for recurrence of NMI tumors (P=.034). GR expression was downregulated in bladder tumors compared with nonneoplastic bladder tumors and in high-grade/MI tumors compared with low-grade/NMI tumors. Decreased expression of GR, as an independent prognosticator, predicted recurrence of NMI tumors. These results support experimental evidence suggesting an inhibitory role of GR signals in bladder cancer outgrowth. Copyright© by the American Society for Clinical Pathology.

Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity.

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Costa, Rui Ponte; Padamsey, Zahid; D'Amour, James A; Emptage, Nigel J; Froemke, Robert C; Vogels, Tim P

2017-09-27

Long-term modifications of neuronal connections are critical for reliable memory storage in the brain. However, their locus of expression-pre- or postsynaptic-is highly variable. Here we introduce a theoretical framework in which long-term plasticity performs an optimization of the postsynaptic response statistics toward a given mean with minimal variance. Consequently, the state of the synapse at the time of plasticity induction determines the ratio of pre- and postsynaptic modifications. Our theory explains the experimentally observed expression loci of the hippocampal and neocortical synaptic potentiation studies we examined. Moreover, the theory predicts presynaptic expression of long-term depression, consistent with experimental observations. At inhibitory synapses, the theory suggests a statistically efficient excitatory-inhibitory balance in which changes in inhibitory postsynaptic response statistics specifically target the mean excitation. Our results provide a unifying theory for understanding the expression mechanisms and functions of long-term synaptic transmission plasticity. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP CFS

Energy Technology Data Exchange (ETDEWEB)

Liang, Jianyin [CMA Institute of Tropical and Marine Meteorology, Guangzhou, Guangdong (China); Yang, Song; Kumar, Arun [NOAA/NWS/NCEP Climate Prediction Center, Camp Springs, MD (United States); Hu, Zeng-Zhen [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Huang, Bohua [George Mason University, Department of Climate Dynamics, Fairfax, VA (United States); Zhang, Zuqiang [CMA National Climate Center, Beijing (China)

2009-06-15

The predictable patterns of the Asian and Indo-Pacific summer precipitation in the NCEP climate forecast system (CFS) are depicted by applying a maximized signal-to-noise empirical orthogonal function analysis. The CFS captures the two most dominant modes of observed climate patterns. The first most dominant mode is characterized by the climate features of the onset years of El Nino-Southern Oscillation (ENSO), with strong precipitation signals over the tropical eastern Indian and western Pacific oceans, Southeast Asia, and tropical Asian monsoon regions including the Bay of Bengal and the South China Sea. The second most dominant mode is characterized by the climate features of the decay years of ENSO, with weakening signals over the western-central Pacific and strengthening signals over the Indian Ocean. The CFS is capable of predicting the most dominant modes several months in advance. It is also highly skillful in capturing the air-sea interaction processes associated with the precipitation features, as demonstrated in sea surface temperature and wind patterns. (orig.)

Time course of gene expression during mouse skeletal muscle hypertrophy.

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Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

2013-10-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

Prediction of male-pattern baldness from genotypes.

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Liu, Fan; Hamer, Merel A; Heilmann, Stefanie; Herold, Christine; Moebus, Susanne; Hofman, Albert; Uitterlinden, André G; Nöthen, Markus M; van Duijn, Cornelia M; Nijsten, Tamar Ec; Kayser, Manfred

2016-06-01

The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.

Emotion expression in body action and posture.

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Dael, Nele; Mortillaro, Marcello; Scherer, Klaus R

2012-10-01

Emotion communication research strongly focuses on the face and voice as expressive modalities, leaving the rest of the body relatively understudied. Contrary to the early assumption that body movement only indicates emotional intensity, recent studies have shown that body movement and posture also conveys emotion specific information. However, a deeper understanding of the underlying mechanisms is hampered by a lack of production studies informed by a theoretical framework. In this research we adopted the Body Action and Posture (BAP) coding system to examine the types and patterns of body movement that are employed by 10 professional actors to portray a set of 12 emotions. We investigated to what extent these expression patterns support explicit or implicit predictions from basic emotion theory, bidimensional theory, and componential appraisal theory. The overall results showed partial support for the different theoretical approaches. They revealed that several patterns of body movement systematically occur in portrayals of specific emotions, allowing emotion differentiation. Although a few emotions were prototypically expressed by one particular pattern, most emotions were variably expressed by multiple patterns, many of which can be explained as reflecting functional components of emotion such as modes of appraisal and action readiness. It is concluded that further work in this largely underdeveloped area should be guided by an appropriate theoretical framework to allow a more systematic design of experiments and clear hypothesis testing.

The herpes simplex virus-induced demise of keratinocytes is associated with a dysregulated pattern of p63 expression.

Science.gov (United States)

Megyeri, Klára; Orosz, László; Kormos, Bernadett; Pásztor, Katalin; Seprényi, György; Ocsovszki, Imre; Mándi, Yvette; Bata-Csörgo, Zsuzsanna; Kemény, Lajos

2009-01-01

p63 plays a pivotal role in the development and maintenance of stratified epithelial tissues. In an effort to gain insight into the pathogenic mechanisms of skin infections caused by HSV-1 and HSV-2, we determined the patterns of p63 expression in primary keratinocytes and in the HaCaT cell line. The levels of DeltaNp63alpha and a 50kDa p73 isoform were decreased, Bax-alpha remained unaffected, while the expressions of the Bax-beta, TAp63gamma and a 44.5kDa p73 isoform were highly increased in both HSV-1-infected HaCaT cells and primary keratinocytes. In contrast, in response to HSV-2 infection the levels of DeltaNp63alpha, a 50kDa p73 isoform and a 44.5kDa p73 protein were decreased, Bax-alpha and TAp63gamma remained unaffected, while the expression of Bax-beta was slightly increased. The knockdown of TAp63 expression enhanced the viability of HSV-1-infected cells. Thus, HSV-1 and HSV-2 modulate the patterns of p63 and Bax expression in a serotype-specific manner. The dysregulated pattern of p63 expression observed in HSV-infected keratinocytes may comprise part of a mechanism by which these viruses perturb the functions of keratinocytes and lead to their demise.

Ethnicity prediction and classification from iris texture patterns: A survey on recent advances

CSIR Research Space (South Africa)

Mabuza-Hocquet, Gugulethu

2017-03-01

Full Text Available The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research...

Gender perceptions predict sex differences in growth patterns of indigenous Guatemalan infants and young children.

Science.gov (United States)

Tumilowicz, Alison; Habicht, Jean-Pierre; Pelto, Gretel; Pelletier, David L

2015-11-01

Nearly one-half of Guatemalan children experience growth faltering, more so in indigenous than in nonindigenous children. On the basis of ethnographic interviews in Totonicapán, Guatemala, which revealed differences in maternal perceptions about food needs in infant girls and boys, we predicted a cumulative sex difference in favor of girls that occurred at ∼6 mo of age and diminished markedly thereafter. We examined whether the predicted differences in age-sex patterns were observed in the village, replicated the examination nationally for indigenous children, and examined whether the pattern in nonindigenous children was different. Ethnographic interviews (n = 24) in an indigenous village were conducted. Anthropometric measurements of the village children aged 0-35 mo (n = 119) were obtained. National-level growth patterns were analyzed for indigenous (n = 969) and nonindigenous (n = 1374) children aged 0-35 mo with the use of Demographic and Health Survey (DHS) data. Mothers reported that, compared with female infants, male infants were hungrier, were not as satisfied with breastfeeding alone, and required earlier complementary feeding. An anthropometric analysis confirmed the prediction of healthier growth in indigenous girls than in indigenous boys throughout the first year of life, which resulted in a 2.98-cm height-for-age difference (HAD) between sexes in the village and a 1.61-cm HAD (P differences diminished in the second year of life (P differences in the HAD that first favor girls and then favor boys in the indigenous growth patterns are due to feeding patterns on the basis of gendered cultural perceptions. Circumstances that result in differential sex growth patterns need to be elucidated, in particular the favorable growth in girls in the first year of life. © 2015 American Society for Nutrition.

Of mice and men: divergence of gene expression patterns in kidney.

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Lydie Cheval

Full Text Available Since the development of methods for homologous gene recombination, mouse models have played a central role in research in renal pathophysiology. However, many published and unpublished results show that mice with genetic changes mimicking human pathogenic mutations do not display the human phenotype. These functional differences may stem from differences in gene expression between mouse and human kidneys. However, large scale comparison of gene expression networks revealed conservation of gene expression among a large panel of human and mouse tissues including kidneys. Because renal functions result from the spatial integration of elementary processes originating in the glomerulus and the successive segments constituting the nephron, we hypothesized that differences in gene expression profiles along the human and mouse nephron might account for different behaviors. Analysis of SAGE libraries generated from the glomerulus and seven anatomically defined nephron segments from human and mouse kidneys allowed us to identify 4644 pairs of gene orthologs expressed in either one or both species. Quantitative analysis shows that many transcripts are present at different levels in the two species. It also shows poor conservation of gene expression profiles, with less than 10% of the 4644 gene orthologs displaying a higher conservation of expression profiles than the neutral expectation (p<0.05. Accordingly, hierarchical clustering reveals a higher degree of conservation of gene expression patterns between functionally unrelated kidney structures within a given species than between cognate structures from the two species. Similar findings were obtained for sub-groups of genes with either kidney-specific or housekeeping functions. Conservation of gene expression at the scale of the whole organ and divergence at the level of its constituting sub-structures likely account for the fact that although kidneys assume the same global function in the two species

Expression pattern of matrix metalloproteinases in human gynecological cancer cell lines

International Nuclear Information System (INIS)

Schröpfer, Andrea; Kammerer, Ulrike; Kapp, Michaela; Dietl, Johannes; Feix, Sonja; Anacker, Jelena

2010-01-01

Matrix metalloproteinases (MMPs) are involved in the degradation of protein components of the extracellular matrix and thus play an important role in tumor invasion and metastasis. Their expression is related to the progression of gynecological cancers (e.g. endometrial, cervical or ovarian carcinoma). In this study we investigated the expression pattern of the 23 MMPs, currently known in humans, in different gynecological cancer cell lines. In total, cell lines from three endometrium carcinomas (Ishikawa, HEC-1-A, AN3 CA), three cervical carcinomas (HeLa, Caski, SiHa), three chorioncarcinomas (JEG, JAR, BeWo), two ovarian cancers (BG-1, OAW-42) and one teratocarcinoma (PA-1) were examined. The expression of MMPs was analyzed by RT-PCR, Western blot and gelatin zymography. We demonstrated that the cell lines examined can constitutively express a wide variety of MMPs on mRNA and protein level. While MMP-2, -11, -14 and -24 were widely expressed, no expression was seen for MMP-12, -16, -20, -25, -26, -27 in any of the cell lines. A broad range of 16 MMPs could be found in the PA1 cells and thus this cell line could be used as a positive control for general MMP experiments. While the three cervical cancer cell lines expressed 10-14 different MMPs, the median expression in endometrial and choriocarcinoma cells was 7 different enzymes. The two investigated ovarian cancer cell lines showed a distinctive difference in the number of expressed MMPs (2 vs. 10). Ishikawa, Caski, OAW-42 and BeWo cell lines could be the best choice for all future experiments on MMP regulation and their role in endometrial, cervical, ovarian or choriocarcinoma development, whereas the teratocarcinoma cell line PA1 could be used as a positive control for general MMP experiments

The expression pattern of the C-terminal kinesin gene kifc1 during the spermatogenesis of Sepiella maindroni.

Science.gov (United States)

Tan, Fu-Qing; Ma, Xiao-Xin; Zhu, Jun-Quan; Yang, Wan-Xi

2013-12-10

In this study, we investigated the gene sequence and characteristic of kifc1 in Sepiella maindroni through PCR and RACE technology. Our research aimed particularly at the spatio-temporal expression pattern of kifc1 in the developmental testis through in situ hybridization. The particular role of kifc1 in the spermatogenesis of S. maindroni was our particular interest. Based on multiple protein sequence alignments of KIFC1 homologues, kifc1 gene from the testis of S. maindroni was identified, which consisted of 2432bp including a 2109 in-frame ORF corresponding to 703 continuous amino acids. The encoded polypeptide shared highest similarity with Octopus tankahkeei. Through the prediction of the secondary and tertiary structures, the motor domain of KIFC1 was conserved at the C-terminal, having putative ATP-binding and microtubule-binding motifs, while the N-terminal was more specific to bind various cargoes for cellular events. The stalk domain connecting between the C-terminal and N-terminal determined the direction of movement. According to RT-PCR results, the kifc1 gene is not tissue-specific, commonly detected in different tissues, for example, the testis, liver, stomach, muscle, caecum and gills. Through an in situ hybridization method, the expression pattern of KIFC1 protein mimics in the spermatogenesis of S. maindroni. During the primary stage of the spermatogenesis, the kifc1 mRNA signal was barely detectable. At the early spermatids, the signal started to be present. With the elongation of spermatids, the signals increased substantially. It peaked and gathered around the acrosome area when the spermatids began to transform to spindle shape. As the spermatids developed into mature sperm, the signal vanished. In summary, the expression of kfic1 at specific stages during spermiogenesis and its distribution shed light on the potential functions of this motor in major cytological transformations. The KIFC1 homologue may provide a direct shaping force to the

A genome-wide study of DNA methylation patterns and gene expression levels in multiple human and chimpanzee tissues.

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Athma A Pai

2011-02-01

Full Text Available The modification of DNA by methylation is an important epigenetic mechanism that affects the spatial and temporal regulation of gene expression. Methylation patterns have been described in many contexts within and across a range of species. However, the extent to which changes in methylation might underlie inter-species differences in gene regulation, in particular between humans and other primates, has not yet been studied. To this end, we studied DNA methylation patterns in livers, hearts, and kidneys from multiple humans and chimpanzees, using tissue samples for which genome-wide gene expression data were also available. Using the multi-species gene expression and methylation data for 7,723 genes, we were able to study the role of promoter DNA methylation in the evolution of gene regulation across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. However, we also found a large number of gene expression differences between species that might be explained, at least in part, by corresponding differences in methylation levels. In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%-18% of differences in gene expression levels between humans and chimpanzees.

Higher resting heart rate variability predicts skill in expressing some emotions.

Science.gov (United States)

Tuck, Natalie L; Grant, Rosemary C I; Sollers, John J; Booth, Roger J; Consedine, Nathan S

2016-12-01

Vagally mediated heart rate variability (vmHRV) is a measure of cardiac vagal tone, and is widely viewed as a physiological index of the capacity to regulate emotions. However, studies have not directly tested whether vmHRV is associated with the ability to facially express emotions. In extending prior work, the current report tested links between resting vmHRV and the objectively assessed ability to facially express emotions, hypothesizing that higher vmHRV would predict greater expressive skill. Eighty healthy women completed self-reported measures, before attending a laboratory session in which vmHRV and the ability to express six emotions in the face were assessed. A repeated measures analysis of variance revealed a marginal main effect for vmHRV on skill overall; individuals with higher resting vmHRV were only better able to deliberately facially express anger and interest. Findings suggest that differences in resting vmHRV are associated with the objectively assessed ability to facially express some, but not all, emotions, with potential implications for health and well-being. © 2016 Society for Psychophysiological Research.

Branchial Expression Patterns of Claudin Isoforms in Atlantic Salmon During Seawater Acclimation and Smoltification

DEFF Research Database (Denmark)

Tipsmark, Christian K; Kiilerich, Pia; Nilsen, Tom O

2008-01-01

in epithelia. We identified Atlantic salmon genes belonging to the claudin family by screening expressed sequence tag libraries available at NCBI and classification was performed with aid of maximum likelihood and neighbour-joining analysis. In gill libraries, five isoforms (10e, 27a, 28a, 28b and 30) were...... present and QPCR analysis confirmed tissue-specific expression in gill when compared to kidney, intestine, heart, muscle, brain and liver. Expression patterns during acclimation of freshwater salmon to seawater (SW) and during the smoltification process were examined. Acclimation to SW reduced...... induced no significant changes in expression of the other isoforms. This study demonstrates the expression of an array of salmon claudin isoforms and shows that SW acclimation involves inverse regulation, in the gill, of claudin 10e versus claudin 27a and 30. It is possible, that claudin 10e...

Gene expression prediction by soft integration and the elastic net-best performance of the DREAM3 gene expression challenge.

Directory of Open Access Journals (Sweden)

Mika Gustafsson

Full Text Available BACKGROUND: To predict gene expressions is an important endeavour within computational systems biology. It can both be a way to explore how drugs affect the system, as well as providing a framework for finding which genes are interrelated in a certain process. A practical problem, however, is how to assess and discriminate among the various algorithms which have been developed for this purpose. Therefore, the DREAM project invited the year 2008 to a challenge for predicting gene expression values, and here we present the algorithm with best performance. METHODOLOGY/PRINCIPAL FINDINGS: We develop an algorithm by exploring various regression schemes with different model selection procedures. It turns out that the most effective scheme is based on least squares, with a penalty term of a recently developed form called the "elastic net". Key components in the algorithm are the integration of expression data from other experimental conditions than those presented for the challenge and the utilization of transcription factor binding data for guiding the inference process towards known interactions. Of importance is also a cross-validation procedure where each form of external data is used only to the extent it increases the expected performance. CONCLUSIONS/SIGNIFICANCE: Our algorithm proves both the possibility to extract information from large-scale expression data concerning prediction of gene levels, as well as the benefits of integrating different data sources for improving the inference. We believe the former is an important message to those still hesitating on the possibilities for computational approaches, while the latter is part of an important way forward for the future development of the field of computational systems biology.

Expression patterns of nicotinamide phosphoribosyltransferase and nicotinic acid phosphoribosyltransferase in human malignant lymphomas.

Science.gov (United States)

Olesen, Uffe Høgh; Hastrup, Nina; Sehested, Maxwell

2011-04-01

The purpose of the study was to determine in human malignant lymphomas the expression patterns of nicotinamide phosphoribosyltransferase (NAMPT) and nicotinic acid phosphoribosyltransferase (NAPRT), the primary, rate-limiting enzymes in the synthesis of NAD+. NAMPT is a potential biomarker for sensitivity to NAMPT inhibitors and NAPRT is a biomarker for the use of nicotinic acid as a chemoprotectant in treatment with NAMPT inhibitors. The NAMPT inhibitor, APO866, is currently in clinical phase II trials in lymphomas. The expression of NAMPT and NAPRT was investigated in 53 samples of malignant lymphomas (diffuse large B-cell lymphoma, follicular B-cell lymphoma, Hodgkin's lymphoma and peripheral T-cell lymphoma). The expression of NAMPT was generally high in the more aggressive malignant lymphomas, with >80% strong expression, whereas the expression in the more indolent follicular lymphoma (FL) was significantly lower (>75% moderate or low expression, p = 0.0002). NAMPT was very highly expressed in Hodgkin Reed-Sternberg cells in Hodgkin's lymphoma. NAPRT expression was more varied (p > 0.0001) with 30-50% low expression except for Hodgkin's lymphoma where 85% displayed low expression (p = 0.0024). In conclusion, FL are a promising target for NAMPT inhibitors whereas substantial subsets of malignant lymphomas especially in Hodgkin lymphoma may be suitable for a combination treatment with nicotinic acid and NAMPT inhibitors. © 2011 The Authors. APMIS © 2011 APMIS.

The SOD gene family in tomato: identification, phylogenetic relationships and expression patterns

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kun feng

2016-08-01

Full Text Available Superoxide dismutases (SODs are critical antioxidant enzymes that protect organisms from reactive oxygen species (ROS caused by adverse conditions, and have been widely found in the cytoplasm, chloroplasts, and mitochondria of eukaryotic and prokaryotic cells. Tomato (Solanum lycopersicum L. is an important economic crop and is cultivated worldwide. However, abiotic and biotic stresses severely hinder growth and development of the plant, which affects the production and quality of the crop. To reveal the potential roles of SOD genes under various stresses, we performed a systematic analysis of the tomato SOD gene family and analyzed the expression patterns of SlSOD genes in response to abiotic stresses at the whole-genome level. The characteristics of the SlSOD gene family were determined by analyzing gene structure, conserved motifs, chromosomal distribution, phylogenetic relationships, and expression patterns. We determined that there are at least nine SOD genes in tomato, including four Cu/ZnSODs, three FeSODs, and one MnSOD, and they are unevenly distributed on 12 chromosomes. Phylogenetic analyses of SOD genes from tomato and other plant species were separated into two groups with a high bootstrap value, indicating that these SOD genes were present before the monocot-dicot split. Additionally, many cis-elements that respond to different stresses were found in the promoters of nine SlSOD genes. Gene expression analysis based on RNA-seq data showed that most genes were expressed in all tested tissues, with the exception of SlSOD6 and SlSOD8, which were only expressed in young fruits. Microarray data analysis showed that most members of the SlSOD gene family were altered under salt- and drought-stress conditions. This genome-wide analysis of SlSOD genes helps to clarify the function of SlSOD genes under different stress conditions and provides information to aid in further understanding the evolutionary relationships of SOD genes in plants.

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-05-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

KAUST Repository

Othoum, Ghofran K

2013-01-01

Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

The combined expression patterns of Ikaros isoforms characterize different hematological tumor subtypes.

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Carlos A Orozco

Full Text Available A variety of genetic alterations are considered hallmarks of cancer development and progression. The Ikaros gene family, encoding for key transcription factors in hematopoietic development, provides several examples as genetic defects in these genes are associated with the development of different types of leukemia. However, the complex patterns of expression of isoforms in Ikaros family genes has prevented their use as clinical markers. In this study, we propose the use of the expression profiles of the Ikaros isoforms to classify various hematological tumor diseases. We have standardized a quantitative PCR protocol to estimate the expression levels of the Ikaros gene exons. Our analysis reveals that these levels are associated with specific types of leukemia and we have found differences in the levels of expression relative to five interexonic Ikaros regions for all diseases studied. In conclusion, our method has allowed us to precisely discriminate between B-ALL, CLL and MM cases. Differences between the groups of lymphoid and myeloid pathologies were also identified in the same way.

Single cell analysis of gene expression patterns of competence development and initiation of sporulation in Bacillus subtilis grown on chemically defined media

NARCIS (Netherlands)

Veening, J. -W.; Smits, W. K.; Hamoen, L. W.; Kuipers, O. P.

Aim: Understanding the basis for the heterogeneous (or bistable) expression patterns of competence development and sporulation in Bacillus subtilis. Methods and Results: Using flow cytometric analyses of various promoter-GFP fusions, we have determined the single-cell gene expression patterns of

Low expression of c-Myc protein predicts poor outcomes in patients with hepatocellular carcinoma after resection.

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Ji, Fei; Zhang, Zhi-Heng; Zhang, Yi; Shen, Shun-Li; Cao, Qing-Hua; Zhang, Long-Juan; Li, Shao-Qiang; Peng, Bao-Gang; Liang, Li-Jian; Hua, Yun-Peng

2018-04-24

Embryonic Liver Fodrin (ELF) is an adaptor protein of transforming growth factor (TGF-β) signaling cascade. Disruption of ELF results in mislocalization of Smad3 and Smad4, leading to compromised TGF-β signaling. c-Myc is an important oncogenic transcription factor, and the disruption of TGF-β signaling promotes c-Myc-induced hepatocellular carcinoma (HCC) carcinogenesis. However, the prognostic significance of c-Myc in HCC is less understood METHODS: The expression of c-Myc protein and mRNA were measured by immunohistochemistry (IHC) and qRT- PCR, respectively. IHC was performed to detect TGF-β1 and ELF expression in HCC tissues. Their relationship with clinicopathological factors and overall survival (OS) and disease free survival (DFS) were examined. The expression of c-Myc protein and mRNA in HCC tissues were significantly higher in HCC area than those in normal liver tissues. However, the expression were low compared with those adjacent to HCC area. c-Myc protein was independently predictive of DFS and OS, and it was negatively correlated with tumor size (P = 0.031), tumor number (P = 0.038), and recurrence (P = 0.001). Low c-Myc expression was associated with short-term recurrence and poor prognosis. The predictive value of c-Myc combined with TGF-β1 or/and ELF was higher than that of any other single marker. Low c-Myc, high TGF-β1 or/and low ELF expression was associated with the worst DFS and OS. Low expression of c-Myc protein predicts poor outcomes in patients with HCC with hepatectomy. The combination of the expression of c-Myc, TGF-β1, and ELF can be used to accurately predict outcomes of patients with HCC.

A Novel Gli3 Enhancer Controls the Gli3 Spatiotemporal Expression Pattern through a TALE Homeodomain Protein Binding Site ▿‡

OpenAIRE

Coy, Sarah; Caamaño, Jorge H.; Carvajal, Jaime; Cleary, Michael L.; Borycki, Anne-Gaëlle

2011-01-01

The zinc finger transcription factor Gli3 is an essential mediator of hedgehog signaling. Gli3 has a dynamic expression pattern during embryonic development. In the neural tube, Gli3 transcripts are patterned along the anteroposterior and dorsoventral axes such that the initial broad expression in the posterior neural tube becomes dorsally restricted as neurogenesis takes place. Little is known about the molecular mechanisms that regulate this dynamic expression. Here, we report on a phylogen...

Expression patterns of Passiflora edulis APETALA1/FRUITFULL homologues shed light onto tendril and corona identities

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Livia C. T. Scorza

2017-02-01

Full Text Available Abstract Background Passiflora (passionflowers makes an excellent model for studying plant evolutionary development. They are mostly perennial climbers that display axillary tendrils, which are believed to be modifications of the inflorescence. Passionflowers are also recognized by their unique flower features, such as the extra whorls of floral organs composed of corona filaments and membranes enclosing the nectary. Although some work on Passiflora organ ontogeny has been done, the developmental identity of both Passiflora tendrils and the corona is still controversial. Here, we combined ultrastructural analysis and expression patterns of the flower meristem and floral organ identity genes of the MADS-box AP1/FUL clade to reveal a possible role for these genes in the generation of evolutionary novelties in Passiflora. Results We followed the development of structures arising from the axillary meristem from juvenile to adult phase in P. edulis. We further assessed the expression pattern of P. edulis AP1/FUL homologues (PeAP1 and PeFUL, by RT-qPCR and in situ hybridization in several tissues, correlating it with the developmental stages of P. edulis. PeAP1 is expressed only in the reproductive stage, and it is highly expressed in tendrils and in flower meristems from the onset of their development. PeAP1 is also expressed in sepals, petals and in corona filaments, suggesting a novel role for PeAP1 in floral organ diversification. PeFUL presented a broad expression pattern in both vegetative and reproductive tissues, and it is also expressed in fruits. Conclusions Our results provide new molecular insights into the morphological diversity in the genus Passiflora. Here, we bring new evidence that tendrils are part of the Passiflora inflorescence. This points to the convergence of similar developmental processes involving the recruitment of genes related to flower identity in the origin of tendrils in different plant families. The data obtained also

Amygdala nuclei critical for emotional learning exhibit unique gene expression patterns.

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Partin, Alexander C; Hosek, Matthew P; Luong, Jonathan A; Lella, Srihari K; Sharma, Sachein A R; Ploski, Jonathan E

2013-09-01

The amygdala is a heterogeneous, medial temporal lobe structure that has been implicated in the formation, expression and extinction of emotional memories. This structure is composed of numerous nuclei that vary in cytoarchitectonics and neural connections. In particular the lateral nucleus of the amygdala (LA), central nucleus of the amygdala (CeA), and the basal (B) nucleus contribute an essential role to emotional learning. However, to date it is still unclear to what extent these nuclei differ at the molecular level. Therefore we have performed whole genome gene expression analysis on these nuclei to gain a better understanding of the molecular differences and similarities among these nuclei. Specifically the LA, CeA and B nuclei were laser microdissected from the rat brain, and total RNA was isolated from these nuclei and subjected to RNA amplification. Amplified RNA was analyzed by whole genome microarray analysis which revealed that 129 genes are differentially expressed among these nuclei. Notably gene expression patterns differed between the CeA nucleus and the LA and B nuclei. However gene expression differences were not considerably different between the LA and B nuclei. Secondary confirmation of numerous genes was performed by in situ hybridization to validate the microarray findings, which also revealed that for many genes, expression differences among these nuclei were consistent with the embryological origins of these nuclei. Knowing the stable gene expression differences among these nuclei will provide novel avenues of investigation into how these nuclei contribute to emotional arousal and emotional learning, and potentially offer new genetic targets to manipulate emotional learning and memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Attitudes to emotional expression and personality in predicting post-traumatic stress disorder.

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Nightingale, J; Williams, R M

2000-09-01

To test hypotheses derived from a suggestion of Williams (1989) that negative attitudes towards emotional expression act as a predisposing or maintaining factor for post-traumatic stress reactions following a traumatic event. The study employed a prospective design in which attitudes to emotional expression, the 'Big Five' personality factors (Costa & McCrae, 1992a) and initial symptoms and injury severity within 1 week of a road traffic accident were used to predict the development of post-traumatic stress disorder 6 weeks post-accident. Sixty victims of road traffic accidents randomly selected from attenders at a large A&E department were assessed by questionnaire and interview. Measures comprised a 4-item scale relating to emotional expression, standardized scales for intrusion and avoidance features of traumatic experiences, and for anxiety and depression and the NEO-FFI Five Factor Personality Inventory. Forty-five of these participants responded to a postal questionnaire follow-up. In this survey the battery was repeated and also included a self-report diagnostic measure of post-traumatic stress disorder (PTSD). The percentage of the sample meeting DSM-IV diagnostic criteria for PTSD at 6 weeks post-trauma was 30.8%. A small but significant relationship was found for negative attitudes to emotional expression at 1 week to predict intrusive symptoms and diagnosis at 6 weeks, over and above the independent relationships of initial symptoms, initial injury severity, personality and coping. The emotional expression measure was largely stable between the two points of measurement. More negative attitudes to emotional expression were related to less openness, extraversion and agreeableness personality domains. Some support for the hypotheses was found in relation to the development of PTSD and for the status of attitudes to emotion as a stable trait related to personality factors. The potential importance of attitudes to emotional expression in therapy and other

Characterization and expression patterns of small RNAs in synthesized Brassica hexaploids.

Science.gov (United States)

Shen, Yanyue; Zhao, Qin; Zou, Jun; Wang, Wenliang; Gao, Yi; Meng, Jinling; Wang, Jianbo

2014-06-01

Polyploidy has played an important role in promoting plant evolution through genomic merging and doubling. We used high-throughput sequencing to compare miRNA expression profiles between Brassica hexaploid and its parents. A total of 613, 784 and 742 known miRNAs were identified in Brassica rapa, Brassica carinata, and Brassica hexaploid, respectively. We detected 618 miRNAs were differentially expressed (log(2)Ratio ≥ 1, P ≤ 0.05) between Brassica hexaploid and its parents, and 425 miRNAs were non-additively expressed in Brassica hexaploid, which suggest a trend of non-additive miRNA regulation following hybridization and polyploidization. Remarkably, majority of the non-additively expressed miRNAs in the Brassica hexaploid are repressed, and there was a bias toward repression of B. rapa miRNAs, which is consistent with the progenitor-biased gene repression in the synthetic allopolyploids. In addition, we identified 653 novel mature miRNAs in Brassica hexaploid and its parents. Finally, we found that almost all the non-additive accumulation of siRNA clusters exhibited a low-parent pattern in Brassica hexaploid. Non-additive small RNA regulation is involved in a range of biological pathways, probably providing a driving force for variation and adaptation in allopolyploids.

A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

Science.gov (United States)

2017-02-01

affecting the function of Fanconi Anemia (FA) genes ( FANCA /B/C/D2/E/F/G/I/J/L/M, PALB2) or DNA damage response genes involved in HR 5 (ATM, ATR...Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...To) 15 July 2010 – 2 Nov.2016 4. TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP

Distinctive expression pattern of OCT4 variants in different types of breast cancer.

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Soheili, Saamaaneh; Asadi, Malek Hossein; Farsinejad, Alireza

2017-01-01

OCT4 is a key regulator of self-renewal and pluripotency in embryonic stem cells which can potentially encode three spliced variants designated OCT4A, OCT4B and OCT4B1. Based on cancer stem cell concept, it is suggested that the stemness factors misexpressed in cancer cells and potentially is involved in tumorigenesis. Accordingly, in this study, we investigated the potential expression of OCT4 variants in breast cancer tissues. A total of 94 tumoral and peritumoral breast specimens were evaluated with respect to the expression of OCT4 variants using quantitative RT-PCR and immunohistochemical (IHC) analysis. We detected the expression of OCT4 variants in breast tumor tissues with no or very low levels of expression in peritumoral samples of the same patients. While OCT4B was highly expressed in lobular type of breast cancer, OCT4A and OCTB1 variants are highly expressed in low grade (I and II) ductal tumors. Furthermore, the results of this study revealed a considerable association between the expression level of OCT4 variants and the expression of ER, PR, Her2 and P53 factors. All data demonstrated a distinctive expression pattern of OCT4 spliced variants in different types of breast cancer and provide further evidence for the involvement of embryonic genes in carcinogenesis.

Similar patterns of neural activity predict memory function during encoding and retrieval.

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Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

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Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

aeGEPUCI: a database of gene expression in the dengue vector mosquito, Aedes aegypti

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James Anthony A

2010-10-01

Full Text Available Abstract Background Aedes aegypti is the principal vector of dengue and yellow fever viruses. The availability of the sequenced and annotated genome enables genome-wide analyses of gene expression in this mosquito. The large amount of data resulting from these analyses requires efficient cataloguing before it becomes useful as the basis for new insights into gene expression patterns and studies of the underlying molecular mechanisms for generating these patterns. Findings We provide a publicly-accessible database and data-mining tool, aeGEPUCI, that integrates 1 microarray analyses of sex- and stage-specific gene expression in Ae. aegypti, 2 functional gene annotation, 3 genomic sequence data, and 4 computational sequence analysis tools. The database can be used to identify genes expressed in particular stages and patterns of interest, and to analyze putative cis-regulatory elements (CREs that may play a role in coordinating these patterns. The database is accessible from the address http://www.aegep.bio.uci.edu. Conclusions The combination of gene expression, function and sequence data coupled with integrated sequence analysis tools allows for identification of expression patterns and streamlines the development of CRE predictions and experiments to assess how patterns of expression are coordinated at the molecular level.

A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

International Nuclear Information System (INIS)

Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

2015-01-01

Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

A comparative study of cell cycle mediator protein expression patterns in anaplastic and papillary thyroid carcinoma.

Science.gov (United States)

Evans, Juanita J; Crist, Henry S; Durvesh, Saima; Bruggeman, Richard D; Goldenberg, David

2012-07-01

Anaplastic thyroid carcinoma (ATC) is an extremely aggressive and rapidly fatal neoplasm. The aim of this study was to identify a limited cell cycle associated protein expression pattern unique to ATC and to correlate that pattern with clinical outcome. This represents one of the largest tissue micro-array projects comparing the cell cycle protein expression data of ATC to other well-differentiated tumors in the literature. Tissue microarrays were created from 21 patients with ATC and an age and gender matched cohort of patients with papillary thyroid carcinoma (PTC). Expression of epidermal growth factor receptor, cyclin D1, cyclin E, p53, p21, p16, aurora kinase A, opioid growth factor (OGF), OGF-receptor, thyroglobulin and Ki-67 was evaluated in a semi-quantitative fashion. Differences in protein expression between the cohorts were evaluated using chi-square tests with Bonferroni adjustments. Survival time and presence of metastasis at presentation were collected. The ATC cohort showed a statistically significant decrease (p cycle with aberrant expression of multiple protein markers suggesting increased proliferative activity and loss of control of cell cycle progression to G₁ phase. These findings support the assertion that ATC may represent the furthest end of a continuum of thyroid carcinoma dedifferentiation.

Inferring regulatory networks from expression data using tree-based methods.

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Vân Anh Huynh-Thu

2010-09-01

Full Text Available One of the pressing open problems of computational systems biology is the elucidation of the topology of genetic regulatory networks (GRNs using high throughput genomic data, in particular microarray gene expression data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM challenge aims to evaluate the success of GRN inference algorithms on benchmarks of simulated data. In this article, we present GENIE3, a new algorithm for the inference of GRNs that was best performer in the DREAM4 In Silico Multifactorial challenge. GENIE3 decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene is predicted from the expression patterns of all the other genes (input genes, using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link. Putative regulatory links are then aggregated over all genes to provide a ranking of interactions from which the whole network is reconstructed. In addition to performing well on the DREAM4 In Silico Multifactorial challenge simulated data, we show that GENIE3 compares favorably with existing algorithms to decipher the genetic regulatory network of Escherichia coli. It doesn't make any assumption about the nature of gene regulation, can deal with combinatorial and non-linear interactions, produces directed GRNs, and is fast and scalable. In conclusion, we propose a new algorithm for GRN inference that performs well on both synthetic and real gene expression data. The algorithm, based on feature selection with tree-based ensemble methods, is simple and generic, making it adaptable to other types of genomic data and interactions.

Novel expression patterns of carotenoid pathway-related gene in citrus leaves and maturing fruits

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Carotenoids are abundant in citrus fruits and vary among cultivars and species. In the present study, HPLC and real-time PCR were used to investigate the expression patterns of 23 carotenoid biosynthesis gene family members and their possible relation with carotenoid accumulation in flavedo, juice s...

Expression of a gymnosperm PIN homologous gene correlates with auxin immunolocalization pattern at cotyledon formation and in demarcation of the procambium during Picea abies somatic embryo development and in seedling tissues.

Science.gov (United States)

Palovaara, Joakim; Hallberg, Henrik; Stasolla, Claudio; Luit, Bert; Hakman, Inger

2010-04-01

In seed plants, the body organization is established during embryogenesis and is uniform across gymnosperms and angiosperms, despite differences during early embryogeny. Evidence from angiosperms implicates the plant hormone auxin and its polar transport, mainly established by the PIN family of auxin efflux transporters, in the patterning of embryos. Here, PaPIN1 from Norway spruce (Picea abies [L.] Karst.), a gene widely expressed in conifer tissues and organs, was characterized and its expression and localization patterns were determined with reverse transcription polymerase chain reaction and in situ hybridization during somatic embryo development and in seedlings. PaPIN1 shares the predicted structure of other PIN proteins, but its central hydrophilic loop is longer than most PINs. In phylogenetic analyses, PaPIN1 clusters with Arabidopsis thaliana (L.) Heynh. PIN3, PIN4 and PIN7, but its expression pattern also suggests similarity to PIN1. The PaPIN1 expression signal was high in the protoderm of pre-cotyledonary embryos, but not if embryos were pre-treated with the auxin transport inhibitor N-1-naphthylphthalamic acid (NPA). This, together with a high auxin immunolocalization signal in this cell layer, suggests a role of PaPIN1 during cotyledon formation. At later stages, high PaPIN1 expression was observed in differentiating procambium, running from the tip of incipient cotyledons down through the embryo axis and to the root apical meristem (RAM), although the mode of RAM specification in conifer embryos differs from that of most angiosperms. Also, the PaPIN1 in situ signal was high in seedling root tips including root cap columella cells. The results thus suggest that PaPIN1 provides an ancient function associated with auxin transport and embryo pattern formation prior to the separation of angiosperms and gymnosperms, in spite of some morphological differences.

Morphological diversity of the avian foot is related with the pattern of msx gene expression in the developing autopod.

Science.gov (United States)

Gañan, Y; Macias, D; Basco, R D; Merino, R; Hurle, J M

1998-04-01

The formation of the digits in amniota embryos is accompanied by apoptotic cell death of the interdigital mesoderm triggered through BMP signaling. Differences in the intensity of this apoptotic process account for the establishment of the different morphological types of feet observed in amniota (i.e., free-digits, webbed digits, lobulated digits). The molecular basis accounting for the differential pattern of interdigital cell death remains uncertain since the reduction of cell death in species with webbed digits is not accompanied by a parallel reduction in the pattern of expression of bmp genes in the interdigital regions. In this study we show that the duck interdigital web mesoderm exhibits an attenuated response to both BMP-induced apoptosis and TGFbeta-induced chondrogenesis in comparison with species with free digits. The attenuated response to these signals is accompanied by a reduced pattern of expression of msx-1 and msx-2 genes. Local application of FGF in the duck interdigit expands the domain of msx-2 expression but not the domain of msx-1 expression. This change in the expression of msx-2 is followed by a parallel increase in spontaneous and exogenous BMP-induced interdigital cell death, while the chondrogenic response to TGFbetas is unchanged. The regression of AER, as deduced by the pattern of extinction of fgf-8 expression, takes place in a similar fashion in the chick and duck regardless of the differences in interdigital cell death and msx gene expression. Implantation of BMP-beads in the distal limb mesoderm induces AER regression in both the chick and duck. This finding suggests an additional role for BMPs in the physiological regression of the AER. It is proposed that the formation of webbed vs free-digit feet in amniota results from a premature differentiation of the interdigital mesoderm into connective tissue caused by a reduced expression of msx genes in the developing autopod. Copyright 1998 Academic Press.

Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging

Science.gov (United States)

Prasetiyowati, S. S.; Sibaroni, Y.

2018-03-01

Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.

Divergent Expression Patterns and Function Implications of Four nanos Genes in a Hermaphroditic Fish, Epinephelus coioides.

Science.gov (United States)

Sun, Zhi-Hui; Wang, Yang; Lu, Wei-Jia; Li, Zhi; Liu, Xiao-Chun; Li, Shui-Sheng; Zhou, Li; Gui, Jian-Fang

2017-03-23

Multiple nanos genes have been characterized in several fishes, but the functional implications of their various expression patterns remain unclear. In this study, we identified and characterized four nanos genes from a hermaphroditic fish orange-spotted grouper, Epinephelus coioides . Ecnanos1a and Ecnanos1b show divergent expression patterns, and the dynamic expression change of Ecnanos1a in pituitaries during sex change is associated with testis differentiation and spermatogenesis. Ecnanos2 and Ecnanos3 might be germline stem cells (GSCs) and primordial germ cells (PGCs)-specific markers, respectively. Significantly, Ecnanos3 3'-untranslated region (UTR) is necessary for PGC specific expression, where a non-canonical "GCACGTTT" sequence is required for miR-430-mediated repression of Ecnanos3 RNA. Furthermore, grouper Dead end (Dnd) can relieve miR-430 repression in PGCs by associating with a 23 bp U-rich region (URR) in Ecnanos3 3'-UTR. The current study revealed the functional association of multiple nanos genes with PGC formation and germ cell development in orange-spotted grouper, and opened up new possibilities for developing biotechnologies through utilizing the associations between Ecnanos3 and PGCs or between Ecnanos2 and GSCs in the hermaphroditic fish.

Complementary striped expression patterns of NK homeobox genes during segment formation in the annelid Platynereis.

Science.gov (United States)

Saudemont, Alexandra; Dray, Nicolas; Hudry, Bruno; Le Gouar, Martine; Vervoort, Michel; Balavoine, Guillaume

2008-05-15

NK genes are related pan-metazoan homeobox genes. In the fruitfly, NK genes are clustered and involved in patterning various mesodermal derivatives during embryogenesis. It was therefore suggested that the NK cluster emerged in evolution as an ancestral mesodermal patterning cluster. To test this hypothesis, we cloned and analysed the expression patterns of the homologues of NK cluster genes Msx, NK4, NK3, Lbx, Tlx, NK1 and NK5 in the marine annelid Platynereis dumerilii, a representative of trochozoans, the third great branch of bilaterian animals alongside deuterostomes and ecdysozoans. We found that most of these genes are involved, as they are in the fly, in the specification of distinct mesodermal derivatives, notably subsets of muscle precursors. The expression of the homologue of NK4/tinman in the pulsatile dorsal vessel of Platynereis strongly supports the hypothesis that the vertebrate heart derived from a dorsal vessel relocated to a ventral position by D/V axis inversion in a chordate ancestor. Additionally and more surprisingly, NK4, Lbx, Msx, Tlx and NK1 orthologues are expressed in complementary sets of stripes in the ectoderm and/or mesoderm of forming segments, suggesting an involvement in the segment formation process. A potentially ancient role of the NK cluster genes in segment formation, unsuspected from vertebrate and fruitfly studies so far, now deserves to be investigated in other bilaterian species, especially non-insect arthropods and onychophorans.

Prediction of lymphatic metastasis based on gene expression profile analysis after brachytherapy for early-stage oral tongue carcinoma

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Mogushi, Kaoru; Miura, Masahiko; Yoshimura, Ryo-ichi; Kurabayashi, Tohru; Shibuya, Hitoshi; Tanaka, Hiroshi; Noda, Shuhei; Iwakawa, Mayumi; Imai, Takashi

2008-01-01

Background and purpose: The management of lymphatic metastasis of early-stage oral tongue carcinoma patients is crucial for its prognosis. The purpose of this study was to evaluate the predictive ability of lymphatic metastasis after brachytherapy (BRT) for early-stage tongue carcinoma based on gene expression profiling. Patients and methods: Pre-therapeutic biopsies from 39 patients with T1 or T2 tongue cancer were analyzed for gene expression signatures using Codelink Uniset Human 20K Bioarray. All patients were treated with low dose-rate BRT for their primary lesions and underwent strict follow-up under a wait-and-see policy for cervical lymphatic metastasis. Candidate genes were selected for predicting lymph-node status in the reference group by the permutation test. Predictive accuracy was further evaluated by the prediction strength (PS) scoring system using an independent validation group. Results: We selected a set of 19 genes whose expression differed significantly between classes with or without lymphatic metastasis in the reference group. The lymph-node status in the validation group was predicted by the PS scoring system with an accuracy of 76%. Conclusions: Gene expression profiling using 19 genes in primary tumor tissues may allow prediction of lymphatic metastasis after BRT for early-stage oral tongue carcinoma

Cross-study analysis of gene expression data for intermediate neuroblastoma identifies two biological subtypes

International Nuclear Information System (INIS)

Warnat, Patrick; Oberthuer, André; Fischer, Matthias; Westermann, Frank; Eils, Roland; Brors, Benedikt

2007-01-01

Neuroblastoma patients show heterogeneous clinical courses ranging from life-threatening progression to spontaneous regression. Recently, gene expression profiles of neuroblastoma tumours were associated with clinically different phenotypes. However, such data is still rare for important patient subgroups, such as patients with MYCN non-amplified advanced stage disease. Prediction of the individual course of disease and optimal therapy selection in this cohort is challenging. Additional research effort is needed to describe the patterns of gene expression in this cohort and to identify reliable prognostic markers for this subset of patients. We combined gene expression data from two studies in a meta-analysis in order to investigate differences in gene expression of advanced stage (3 or 4) tumours without MYCN amplification that show contrasting outcomes (alive or dead) at five years after initial diagnosis. In addition, a predictive model for outcome was generated. Gene expression profiles from 66 patients were included from two studies using different microarray platforms. In the combined data set, 72 genes were identified as differentially expressed by meta-analysis at a false discovery rate (FDR) of 8.33%. Meta-analysis detected 34 differentially expressed genes that were not found as significant in either single study. Outcome prediction based on data of both studies resulted in a predictive accuracy of 77%. Moreover, the genes that were differentially expressed in subgroups of advanced stage patients without MYCN amplification accurately separated MYCN amplified tumours from low stage tumours without MYCN amplification. Our findings support the hypothesis that neuroblastoma consists of two biologically distinct subgroups that differ by characteristic gene expression patterns, which are associated with divergent clinical outcome

Genes expressed in specific areas of the human fetal cerebral cortex display distinct patterns of evolution.

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Nelle Lambert

2011-03-01

Full Text Available The developmental mechanisms through which the cerebral cortex increased in size and complexity during primate evolution are essentially unknown. To uncover genetic networks active in the developing cerebral cortex, we combined three-dimensional reconstruction of human fetal brains at midgestation and whole genome expression profiling. This novel approach enabled transcriptional characterization of neurons from accurately defined cortical regions containing presumptive Broca and Wernicke language areas, as well as surrounding associative areas. We identified hundreds of genes displaying differential expression between the two regions, but no significant difference in gene expression between left and right hemispheres. Validation by qRTPCR and in situ hybridization confirmed the robustness of our approach and revealed novel patterns of area- and layer-specific expression throughout the developing cortex. Genes differentially expressed between cortical areas were significantly associated with fast-evolving non-coding sequences harboring human-specific substitutions that could lead to divergence in their repertoires of transcription factor binding sites. Strikingly, while some of these sequences were accelerated in the human lineage only, many others were accelerated in chimpanzee and/or mouse lineages, indicating that genes important for cortical development may be particularly prone to changes in transcriptional regulation across mammals. Genes differentially expressed between cortical regions were also enriched for transcriptional targets of FoxP2, a key gene for the acquisition of language abilities in humans. Our findings point to a subset of genes with a unique combination of cortical areal expression and evolutionary patterns, suggesting that they play important roles in the transcriptional network underlying human-specific neural traits.

Characterization, expression patterns and functional analysis of the MAPK and MAPKK genes in watermelon (Citrullus lanatus).

Science.gov (United States)

Song, Qiuming; Li, Dayong; Dai, Yi; Liu, Shixia; Huang, Lei; Hong, Yongbo; Zhang, Huijuan; Song, Fengming

2015-12-23

Mitogen-activated protein kinase (MAPK) cascades, which consist of three functionally associated protein kinases, namely MEKKs, MKKs and MPKs, are universal signaling modules in all eukaryotes and have been shown to play critical roles in many physiological and biochemical processes in plants. However, little or nothing is known about the MPK and MKK families in watermelon. In the present study, we performed a systematic characterization of the ClMPK and ClMKK families including the identification and nomenclature, chromosomal localization, phylogenetic relationships, ClMPK-ClMKK interactions, expression patterns in different tissues and in response to abiotic and biotic stress and transient expression-based functional analysis for their roles in disease resistance. Genome-wide survey identified fifteen ClMPK and six ClMKK genes in watermelon genome and phylogenetic analysis revealed that both of the ClMPK and ClMKK families can be classified into four distinct groups. Yeast two-hybrid assays demonstrated significant interactions between members of the ClMPK and ClMKK families, defining putative ClMKK2-1/ClMKK6-ClMPK4-1/ClMPK4-2/ClMPK13 and ClMKK5-ClMPK6 cascades. Most of the members in the ClMPK and ClMKK families showed differential expression patterns in different tissues and in response to abiotic (e.g. drought, salt, cold and heat treatments) and biotic (e.g. infection of Fusarium oxysporum f. sp. niveum) stresses. Transient expression of ClMPK1, ClMPK4-2 and ClMPK7 in Nicotiana benthamiana resulted in enhanced resistance to Botrytis cinerea and upregulated expression of defense genes while transient expression of ClMPK6 and ClMKK2-2 led to increased susceptibility to B. cinerea. Furthermore, transient expression of ClMPK7 also led to hypersensitive response (HR)-like cell death and significant accumulation of H2O2 in N. benthamiana. We identified fifteen ClMPK and six ClMKK genes from watermelon and analyzed their phylogenetic relationships, expression

Instrumentality, Expressivity, and Relational Qualities in the Same-Sex Friendships of College Women and Men

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Frey, Lisa L.; Beesley, Denise; Hurst, Rebecca; Saldana, Star; Licuanan, Brian

2016-01-01

Using the relational-cultural model (Jordan, Kaplan, Miller, Stiver, & Surrey, 1991), the authors hypothesized that instrumentality, expressivity, and the individual affective experience of same-sex friendships would predict increased relationship mutuality, with college women and men showing different predictive patterns. Overall, results…

Predicting the effect of fire on large-scale vegetation patterns in North America.

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Donald McKenzie; David L. Peterson; Ernesto. Alvarado

1996-01-01

Changes in fire regimes are expected across North America in response to anticipated global climatic changes. Potential changes in large-scale vegetation patterns are predicted as a result of altered fire frequencies. A new vegetation classification was developed by condensing Kuchler potential natural vegetation types into aggregated types that are relatively...

Spatio-temporal patterns and predictions of phytoplankton assemblages in a subtropical river delta system

DEFF Research Database (Denmark)

Wang, Chao; Li, Xinhui; Wang, Xiangxiu

2016-01-01

Spatial and seasonal sampling within a subtropical river delta system, the Pearl River Delta (China), provided data to determine seasonal phytoplankton patterns and develop prediction models. The high nutrient levels and frequent water exchanges resulted in a phytoplankton community with greatest...

Predicting clinical symptoms of attention deficit hyperactivity disorder based on temporal patterns between and within intrinsic connectivity networks.

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Wang, Xun-Heng; Jiao, Yun; Li, Lihua

2017-10-24

Attention deficit hyperactivity disorder (ADHD) is a common brain disorder with high prevalence in school-age children. Previously developed machine learning-based methods have discriminated patients with ADHD from normal controls by providing label information of the disease for individuals. Inattention and impulsivity are the two most significant clinical symptoms of ADHD. However, predicting clinical symptoms (i.e., inattention and impulsivity) is a challenging task based on neuroimaging data. The goal of this study is twofold: to build predictive models for clinical symptoms of ADHD based on resting-state fMRI and to mine brain networks for predictive patterns of inattention and impulsivity. To achieve this goal, a cohort of 74 boys with ADHD and a cohort of 69 age-matched normal controls were recruited from the ADHD-200 Consortium. Both structural and resting-state fMRI images were obtained for each participant. Temporal patterns between and within intrinsic connectivity networks (ICNs) were applied as raw features in the predictive models. Specifically, sample entropy was taken asan intra-ICN feature, and phase synchronization (PS) was used asan inter-ICN feature. The predictive models were based on the least absolute shrinkage and selectionator operator (LASSO) algorithm. The performance of the predictive model for inattention is r=0.79 (p<10 -8 ), and the performance of the predictive model for impulsivity is r=0.48 (p<10 -8 ). The ICN-related predictive patterns may provide valuable information for investigating the brain network mechanisms of ADHD. In summary, the predictive models for clinical symptoms could be beneficial for personalizing ADHD medications. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

A fingertip force prediction model for grasp patterns characterised from the chaotic behaviour of EEG.

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Roy, Rinku; Sikdar, Debdeep; Mahadevappa, Manjunatha; Kumar, C S

2018-05-19

A stable grasp is attained through appropriate hand preshaping and precise fingertip forces. Here, we have proposed a method to decode grasp patterns from motor imagery and subsequent fingertip force estimation model with a slippage avoidance strategy. We have developed a feature-based classification of electroencephalography (EEG) associated with imagination of the grasping postures. Chaotic behaviour of EEG for different grasping patterns has been utilised to capture the dynamics of associated motor activities. We have computed correlation dimension (CD) as the feature and classified with "one against one" multiclass support vector machine (SVM) to discriminate between different grasping patterns. The result of the analysis showed varying classification accuracies at different subband levels. Broad categories of grasping patterns, namely, power grasp and precision grasp, were classified at a 96.0% accuracy rate in the alpha subband. Furthermore, power grasp subtypes were classified with an accuracy of 97.2% in the upper beta subband, whereas precision grasp subtypes showed relatively lower 75.0% accuracy in the alpha subband. Following assessment of fingertip force distributions while grasping, a nonlinear autoregressive (NAR) model with proper prediction of fingertip forces was proposed for each grasp pattern. A slippage detection strategy has been incorporated with automatic recalibration of the regripping force. Intention of each grasp pattern associated with corresponding fingertip force model was virtualised in this work. This integrated system can be utilised as the control strategy for prosthetic hand in the future. The model to virtualise motor imagery based fingertip force prediction with inherent slippage correction for different grasp types ᅟ.

Can superconductivity be predicted with the aid of pattern recognition techniques

International Nuclear Information System (INIS)

Pijpers, F.W.

1982-01-01

Pattern recognition techniques were employed in order to investigate the possibility to find features of the elements of the periodic system that may be relevant for the description of their behaviour with respect to superconductivity. Learning machines were constructed using those elements of the periodic system whose superconducting properties have been well studied. Relevant features appear to be the electronic work function and the number of valence electrons as given by Miedema, the specific heat, the heat of melting, the heat of sublimation, the melting point and the atomic radius. The learning machines have a predicting capability of the order of 90%. The predictive power of these machines concerning the superconducting behaviour of the alkali and alkaline-earth metals belonging to a given test set, however, appears to be less convincing

Temporal expression and localization patterns of variant surface antigens in clinical Plasmodium falciparum isolates during erythrocyte schizogony.

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Anna Bachmann

Full Text Available Avoidance of antibody-mediated immune recognition allows parasites to establish chronic infections and enhances opportunities for transmission. The human malaria parasite Plasmodium falciparum possesses a number of multi-copy gene families, including var, rif, stevor and pfmc-2tm, which encode variant antigens believed to be expressed on the surfaces of infected erythrocytes. However, most studies of these antigens are based on in vitro analyses of culture-adapted isolates, most commonly the laboratory strain 3D7, and thus may not be representative of the unique challenges encountered by P. falciparum in the human host. To investigate the expression of the var, rif-A, rif-B, stevor and pfmc-2tm family genes under conditions that mimic more closely the natural course of infection, ex vivo clinical P. falciparum isolates were analyzed using a novel quantitative real-time PCR approach. Expression patterns in the clinical isolates at various time points during the first intraerythrocytic developmental cycle in vitro were compared to those of strain 3D7. In the clinical isolates, in contrast to strain 3D7, there was a peak of expression of the multi-copy gene families rif-A, stevor and pfmc-2tm at the young ring stage, in addition to the already known expression peak in trophozoites. Furthermore, most of the variant surface antigen families were overexpressed in the clinical isolates relative to 3D7, with the exception of the pfmc-2tm family, expression of which was higher in 3D7 parasites. Immunofluorescence analyses performed in parallel revealed two stage-dependent localization patterns of RIFIN, STEVOR and PfMC-2TM. Proteins were exported into the infected erythrocyte at the young trophozoite stage, whereas they remained inside the parasite membrane during schizont stage and were subsequently observed in different compartments in the merozoite. These results reveal a complex pattern of expression of P. falciparum multi-copy gene families during

MicroRNAs show mutually exclusive expression patterns in the brain of adult male rats

DEFF Research Database (Denmark)

Olsen, Line; Klausen, Mikkel; Helboe, Lone

2009-01-01

BACKGROUND: The brain is a major site of microRNA (miRNA) gene expression, but the spatial expression patterns of miRNAs within the brain have not yet been fully covered. METHODOLOGY/PRINCIPAL FINDINGS: We have characterized the regional expression profiles of miRNAs in five distinct regions...... of the adult rat brain: amygdala, cerebellum, hippocampus, hypothalamus and substantia nigra. Microarray profiling uncovered 48 miRNAs displaying more than three-fold enrichment between two or more brain regions. Notably, we found reciprocal expression profiles for a subset of the miRNAs predominantly found...... (> ten times) in either the cerebellum (miR-206 and miR-497) or the forebrain regions (miR-132, miR-212, miR-221 and miR-222). CONCLUSIONS/SIGNIFICANCE: The results indicate that some miRNAs could be important for area-specific functions in the brain. Our data, combined with previous studies in mice...

Predictable patterns in microtext as seen in educational applications using MXit in South Africa

CSIR Research Space (South Africa)

Butgereit, LL

2013-09-01

Full Text Available in a country of approximately fifty million people. In order to analyze MXit lingo for educational purposes, it was necessary to first determine whether or not there were any predictable patterns when people chatted using MXit lingo. This paper presents...

Effects of intense magnetic fields on sedimentation pattern and gene expression profile in budding yeast

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Ikehata, Masateru; Iwasaka, Masakazu; Miyakoshi, Junji; Ueno, Shoogo; Koana, Takao

2003-05-01

Effects of magnetic fields (MFs) on biological systems are usually investigated using biological indices such as gene expression profiles. However, to precisely evaluate the biological effects of MF, the effects of intense MFs on systematic material transport processes including experimental environment must be seriously taken into consideration. In this study, a culture of the budding yeast, Saccharomyces cerevisiae, was used as a model for an in vitro biological test system. After exposure to 5 T static vertical MF, we found a difference in the sedimentation pattern of cells depending on the location of the dish in the magnet bore. Sedimented cells were localized in the center of the dish when they were placed in the lower part of the magnet bore while the sedimentation of the cells was uniform in dishes placed in the upper part of the bore because of the diamagnetic force. Genome wide gene expression profile of the yeast cells after exposure to 5 T static MF for 2 h suggested that the MF did not affect the expression level of any gene in yeast cells although the sedimentation pattern was altered. In addition, exposure to 10 T for 1 h and 5 T for 24 h also did not affect the gene expression. On the other hand, a slight change in expressions of several genes which are related to respiration was observed by exposure to a 14 T static MF for 24 h. The necessity of estimating the indirect effects of MFs on a study of its biological effect of MF in vitro will be discussed.

Association between gene expression profile of the primary tumor and chemotherapy response of metastatic breast cancer

NARCIS (Netherlands)

Savci-Heijink, Cemile Dilara; Halfwerk, Hans; Koster, Jan; van de Vijver, Marc Joan

2017-01-01

Background: To better predict the likelihood of response to chemotherapy, we have conducted a study comparing the gene expression patterns of primary tumours with their corresponding response to systemic chemotherapy in the metastatic setting. Methods: mRNA expression profiles of breast carcinomas

Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

Science.gov (United States)

Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

2015-07-01

Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

Patterns of gene expression in a scleractinian coral undergoing natural bleaching.

Science.gov (United States)

Seneca, Francois O; Forêt, Sylvain; Ball, Eldon E; Smith-Keune, Carolyn; Miller, David J; van Oppen, Madeleine J H

2010-10-01

Coral bleaching is a major threat to coral reefs worldwide and is predicted to intensify with increasing global temperature. This study represents the first investigation of gene expression in an Indo-Pacific coral species undergoing natural bleaching which involved the loss of algal symbionts. Quantitative real-time polymerase chain reaction experiments were conducted to select and evaluate coral internal control genes (ICGs), and to investigate selected coral genes of interest (GOIs) for changes in gene expression in nine colonies of the scleractinian coral Acropora millepora undergoing bleaching at Magnetic Island, Great Barrier Reef, Australia. Among the six ICGs tested, glyceraldehyde 3-phosphate dehydrogenase and the ribosomal protein genes S7 and L9 exhibited the most constant expression levels between samples from healthy-looking colonies and samples from the same colonies when severely bleached a year later. These ICGs were therefore utilised for normalisation of expression data for seven selected GOIs. Of the seven GOIs, homologues of catalase, C-type lectin and chromoprotein genes were significantly up-regulated as a result of bleaching by factors of 1.81, 1.46 and 1.61 (linear mixed models analysis of variance, P coral bleaching response genes. In contrast, three genes, including one putative ICG, showed highly variable levels of expression between coral colonies. Potential variation in microhabitat, gene function unrelated to the stress response and individualised stress responses may influence such differences between colonies and need to be better understood when designing and interpreting future studies of gene expression in natural coral populations.

Allele specific expression in worker reproduction genes in the bumblebee Bombus terrestris

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Harindra E. Amarasinghe

2015-07-01

Full Text Available Methylation has previously been associated with allele specific expression in ants. Recently, we found methylation is important in worker reproduction in the bumblebee Bombus terrestris. Here we searched for allele specific expression in twelve genes associated with worker reproduction in bees. We found allele specific expression in Ecdysone 20 monooxygenase and IMP-L2-like. Although we were unable to confirm a genetic or epigenetic cause for this allele specific expression, the expression patterns of the two genes match those predicted for imprinted genes.

Theories of Person Perception Predict Patterns of Neural Activity During Mentalizing.

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Thornton, Mark A; Mitchell, Jason P

2017-08-22

Social life requires making inferences about other people. What information do perceivers spontaneously draw upon to make such inferences? Here, we test 4 major theories of person perception, and 1 synthetic theory that combines their features, to determine whether the dimensions of such theories can serve as bases for describing patterns of neural activity during mentalizing. While undergoing functional magnetic resonance imaging, participants made social judgments about well-known public figures. Patterns of brain activity were then predicted using feature encoding models that represented target people's positions on theoretical dimensions such as warmth and competence. All 5 theories of person perception proved highly accurate at reconstructing activity patterns, indicating that each could describe the informational basis of mentalizing. Cross-validation indicated that the theories robustly generalized across both targets and participants. The synthetic theory consistently attained the best performance-approximately two-thirds of noise ceiling accuracy--indicating that, in combination, the theories considered here can account for much of the neural representation of other people. Moreover, encoding models trained on the present data could reconstruct patterns of activity associated with mental state representations in independent data, suggesting the use of a common neural code to represent others' traits and states. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Synergistic interactions of biotic and abiotic environmental stressors on gene expression.

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Altshuler, Ianina; McLeod, Anne M; Colbourne, John K; Yan, Norman D; Cristescu, Melania E

2015-03-01

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

A modified consumer inkjet for spatiotemporal control of gene expression.

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Daniel J Cohen

Full Text Available This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 microm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer and glucose (inhibitor, can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity.

Expression and distribution of voltage-gated ion channels in ferret sinoatrial node.

Science.gov (United States)

Brahmajothi, Mulugu V; Morales, Michael J; Campbell, Donald L; Steenbergen, Charles; Strauss, Harold C

2010-10-01

Spontaneous diastolic depolarization in the sinoatrial (SA) node enables it to serve as pacemaker of the heart. The variable cell morphology within the SA node predicts that ion channel expression would be heterogeneous and different from that in the atrium. To evaluate ion channel heterogeneity within the SA node, we used fluorescent in situ hybridization to examine ion channel expression in the ferret SA node region and atrial appendage. SA nodal cells were distinguished from surrounding cardiac myocytes by expression of the slow (SA node) and cardiac (surrounding tissue) forms of troponin I. Nerve cells in the sections were identified by detection of GAP-43 and cytoskeletal middle neurofilament. Transcript expression was characterized for the 4 hyperpolarization-activated cation channels, 6 voltage-gated Na(+) channels, 3 voltage-gated Ca(2+) channels, 24 voltage-gated K(+) channel α-subunits, and 3 ancillary subunits. To ensure that transcript expression was representative of protein expression, immunofluorescence was used to verify localization patterns of voltage-dependent K(+) channels. Colocalizations were performed to observe any preferential patterns. Some overlapping and nonoverlapping binding patterns were observed. Measurement of different cation channel transcripts showed heterogeneous expression with many different patterns of expression, attesting to the complexity of electrical activity in the SA node. This study provides insight into the possible role ion channel heterogeneity plays in SA node pacemaker activity.

Efficient Spatio-Temporal Local Binary Patterns for Spontaneous Facial Micro-Expression Recognition

Science.gov (United States)

Wang, Yandan; See, John; Phan, Raphael C.-W.; Oh, Yee-Hui

2015-01-01

Micro-expression recognition is still in the preliminary stage, owing much to the numerous difficulties faced in the development of datasets. Since micro-expression is an important affective clue for clinical diagnosis and deceit analysis, much effort has gone into the creation of these datasets for research purposes. There are currently two publicly available spontaneous micro-expression datasets—SMIC and CASME II, both with baseline results released using the widely used dynamic texture descriptor LBP-TOP for feature extraction. Although LBP-TOP is popular and widely used, it is still not compact enough. In this paper, we draw further inspiration from the concept of LBP-TOP that considers three orthogonal planes by proposing two efficient approaches for feature extraction. The compact robust form described by the proposed LBP-Six Intersection Points (SIP) and a super-compact LBP-Three Mean Orthogonal Planes (MOP) not only preserves the essential patterns, but also reduces the redundancy that affects the discriminality of the encoded features. Through a comprehensive set of experiments, we demonstrate the strengths of our approaches in terms of recognition accuracy and efficiency. PMID:25993498

Clinically Relevant Subsets Identified by Gene Expression Patterns Support a Revised Ontogenic Model of Wilms Tumor: A Children's Oncology Group Study

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Samantha Gadd

2012-08-01

Full Text Available Wilms tumors (WT have provided broad insights into the interface between development and tumorigenesis. Further understanding is confounded by their genetic, histologic, and clinical heterogeneity, the basis of which remains largely unknown. We evaluated 224 WT for global gene expression patterns; WT1, CTNNB1, and WTX mutation; and 11p15 copy number and methylation patterns. Five subsets were identified showing distinct differences in their pathologic and clinical features: these findings were validated in 100 additional WT. The gene expression pattern of each subset was compared with published gene expression profiles during normal renal development. A novel subset of epithelial WT in infants lacked WT1, CTNNB1, and WTX mutations and nephrogenic rests and displayed a gene expression pattern of the postinduction nephron, and none recurred. Three subsets were characterized by a low expression of WT1 and intralobar nephrogenic rests. These differed in their frequency of WT1 and CTNNB1 mutations, in their age, in their relapse rate, and in their expression similarities with the intermediate mesoderm versus the metanephric mesenchyme. The largest subset was characterized by biallelic methylation of the imprint control region 1, a gene expression profile of the metanephric mesenchyme, and both interlunar and perilobar nephrogenic rests. These data provide a biologic explanation for the clinical and pathologic heterogeneity seen within WT and enable the future development of subset-specific therapeutic strategies. Further, these data support a revision of the current model of WT ontogeny, which allows for an interplay between the type of initiating event and the developmental stage in which it occurs.

Population genetic variation in gene expression is associated withphenotypic variation in Saccharomyces cerevisiae

Energy Technology Data Exchange (ETDEWEB)

Fay, Justin C.; McCullough, Heather L.; Sniegowski, Paul D.; Eisen, Michael B.

2004-02-25

The relationship between genetic variation in gene expression and phenotypic variation observable in nature is not well understood. Identifying how many phenotypes are associated with differences in gene expression and how many gene-expression differences are associated with a phenotype is important to understanding the molecular basis and evolution of complex traits. Results: We compared levels of gene expression among nine natural isolates of Saccharomyces cerevisiae grown either in the presence or absence of copper sulfate. Of the nine strains, two show a reduced growth rate and two others are rust colored in the presence of copper sulfate. We identified 633 genes that show significant differences in expression among strains. Of these genes,20 were correlated with resistance to copper sulfate and 24 were correlated with rust coloration. The function of these genes in combination with their expression pattern suggests the presence of both correlative and causative expression differences. But the majority of differentially expressed genes were not correlated with either phenotype and showed the same expression pattern both in the presence and absence of copper sulfate. To determine whether these expression differences may contribute to phenotypic variation under other environmental conditions, we examined one phenotype, freeze tolerance, predicted by the differential expression of the aquaporin gene AQY2. We found freeze tolerance is associated with the expression of AQY2. Conclusions: Gene expression differences provide substantial insight into the molecular basis of naturally occurring traits and can be used to predict environment dependent phenotypic variation.

Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.

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Guilloux, Jean-Philippe; Bassi, Sabrina; Ding, Ying; Walsh, Chris; Turecki, Gustavo; Tseng, George; Cyranowski, Jill M; Sibille, Etienne

2015-02-01

Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

Expression changes in the stroma of prostate cancer predict subsequent relapse.

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Zhenyu Jia

Full Text Available Biomarkers are needed to address overtreatment that occurs for the majority of prostate cancer patients that would not die of the disease but receive radical treatment. A possible barrier to biomarker discovery may be the polyclonal/multifocal nature of prostate tumors as well as cell-type heterogeneity between patient samples. Tumor-adjacent stroma (tumor microenvironment is less affected by genetic alteration and might therefore yield more consistent biomarkers in response to tumor aggressiveness. To this end we compared Affymetrix gene expression profiles in stroma near tumor and identified a set of 115 probe sets for which the expression levels were significantly correlated with time-to-relapse. We also compared patients that chemically relapsed shortly after prostatectomy (<1 year, and patients that did not relapse in the first four years after prostatectomy. We identified 131 differentially expressed microarray probe sets between these two categories. 19 probe sets (15 genes overlapped between the two gene lists with p<0.0001. We developed a PAM-based classifier by training on samples containing stroma near tumor: 9 rapid relapse patient samples and 9 indolent patient samples. We then tested the classifier on 47 different samples, containing 90% or more stroma. The classifier predicted the risk status of patients with an average accuracy of 87%. This is the first general tumor microenvironment-based prognostic classifier. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for predicting outcomes for patients.

Patterns of Expression of Vaginal T-Cell Activation Markers during Estrogen-Maintained Vaginal Candidiasis

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Al-Sadeq Ameera

2008-12-01

Full Text Available The immunosuppressive activity of estrogen was further investigated by assessing the pattern of expression of CD25, CD28, CD69, and CD152 on vaginal T cells during estrogen-maintained vaginal candidiasis. A precipitous and significant decrease in vaginal fungal burden toward the end of week 3 postinfection was concurrent with a significant increase in vaginal lymphocyte numbers. During this period, the percentage of CD3+, CD3+CD4+, CD152+, and CD28+ vaginal T cells gradually and significantly increased. The percentage of CD3+ and CD3+CD4+ cells increased from 43% and 15% at day 0 to 77% and 40% at day 28 postinfection. Compared with 29% CD152+ vaginal T cells in naive mice, > 70% of vaginal T cells were CD152+ at day 28 postinfection. In conclusion, estrogen-maintained vaginal candidiasis results in postinfection time-dependent changes in the pattern of expression of CD152, CD28, and other T-cell markers, suggesting that T cells are subject to mixed suppression and activation signals.

Working Memory and Auditory Imagery Predict Sensorimotor Synchronization with Expressively Timed Music.

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Colley, Ian D; Keller, Peter E; Halpern, Andrea R

2017-08-11

Sensorimotor synchronization (SMS) is prevalent and readily studied in musical settings, as most people are able to perceive and synchronize with a beat (e.g. by finger tapping). We took an individual differences approach to understanding SMS to real music characterized by expressive timing (i.e. fluctuating beat regularity). Given the dynamic nature of SMS, we hypothesized that individual differences in working memory and auditory imagery-both fluid cognitive processes-would predict SMS at two levels: 1) mean absolute asynchrony (a measure of synchronization error), and 2) anticipatory timing (i.e. predicting, rather than reacting to beat intervals). In Experiment 1, participants completed two working memory tasks, four auditory imagery tasks, and an SMS-tapping task. Hierarchical regression models were used to predict SMS performance, with results showing dissociations among imagery types in relation to mean absolute asynchrony, and evidence of a role for working memory in anticipatory timing. In Experiment 2, a new sample of participants completed an expressive timing perception task to examine the role of imagery in perception without action. Results suggest that imagery vividness is important for perceiving and control is important for synchronizing with, irregular but ecologically valid musical time series. Working memory is implicated in synchronizing by anticipating events in the series.

High endothelin-converting enzyme-1 expression independently predicts poor survival of patients with esophageal squamous cell carcinoma.

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Wu, Ching-Fang; Lee, Ching-Tai; Kuo, Yao-Hung; Chen, Tzu-Haw; Chang, Chi-Yang; Chang, I-Wei; Wang, Wen-Lun

2017-09-01

Patients with esophageal squamous cell carcinoma have poor survival and high recurrence rate, thus an effective prognostic biomarker is needed. Endothelin-converting enzyme-1 is responsible for biosynthesis of endothelin-1, which promotes growth and invasion of human cancers. The role of endothelin-converting enzyme-1 in esophageal squamous cell carcinoma is still unknown. Therefore, this study investigated the significance of endothelin-converting enzyme-1 expression in esophageal squamous cell carcinoma clinically. We enrolled patients with esophageal squamous cell carcinoma who provided pretreated tumor tissues. Tumor endothelin-converting enzyme-1 expression was evaluated by immunohistochemistry and was defined as either low or high expression. Then we evaluated whether tumor endothelin-converting enzyme-1 expression had any association with clinicopathological findings or predicted survival of patients with esophageal squamous cell carcinoma. Overall, 54 of 99 patients with esophageal squamous cell carcinoma had high tumor endothelin-converting enzyme-1 expression, which was significantly associated with lymph node metastasis ( p = 0.04). In addition, tumor endothelin-converting enzyme-1 expression independently predicted survival of patients with esophageal squamous cell carcinoma, and the 5-year survival was poorer in patients with high tumor endothelin-converting enzyme-1 expression ( p = 0.016). Among patients with locally advanced and potentially resectable esophageal squamous cell carcinoma (stage II and III), 5-year survival was poorer with high tumor endothelin-converting enzyme-1 expression ( p = 0.003). High tumor endothelin-converting enzyme-1 expression also significantly predicted poorer survival of patients in this population. In patients with esophageal squamous cell carcinoma, high tumor endothelin-converting enzyme-1 expression might indicate high tumor invasive property. Therefore, tumor endothelin-converting enzyme-1 expression

Ancestral and derived attributes of the dlx gene repertoire, cluster structure and expression patterns in an African cichlid fish

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Renz Adina J

2011-01-01

Full Text Available Abstract Background Cichlid fishes have undergone rapid, expansive evolutionary radiations that are manifested in the diversification of their trophic morphologies, tooth patterning and coloration. Understanding the molecular mechanisms that underlie the cichlids' unique patterns of evolution requires a thorough examination of genes that pattern the neural crest, from which these diverse phenotypes are derived. Among those genes, the homeobox-containing Dlx gene family is of particular interest since it is involved in the patterning of the brain, jaws and teeth. Results In this study, we characterized the dlx genes of an African cichlid fish, Astatotilapia burtoni, to provide a baseline to later allow cross-species comparison within Cichlidae. We identified seven dlx paralogs (dlx1a, -2a, -4a, -3b, -4b, -5a and -6a, whose orthologies were validated with molecular phylogenetic trees. The intergenic regions of three dlx gene clusters (dlx1a-2a, dlx3b-4b, and dlx5a-6a were amplified with long PCR. Intensive cross-species comparison revealed a number of conserved non-coding elements (CNEs that are shared with other percomorph fishes. This analysis highlighted additional lineage-specific gains/losses of CNEs in different teleost fish lineages and a novel CNE that had previously not been identified. Our gene expression analyses revealed overlapping but distinct expression of dlx orthologs in the developing brain and pharyngeal arches. Notably, four of the seven A. burtoni dlx genes, dlx2a, dlx3b, dlx4a and dlx5a, were expressed in the developing pharyngeal teeth. Conclusion This comparative study of the dlx genes of A. burtoni has deepened our knowledge of the diversity of the Dlx gene family, in terms of gene repertoire, expression patterns and non-coding elements. We have identified possible cichlid lineage-specific changes, including losses of a subset of dlx expression domains in the pharyngeal teeth, which will be the targets of future functional

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

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Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

2007-01-01

Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

Patterns of transposable element expression and insertion in cancer

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Evan A Clayton

2016-11-01

Full Text Available Human transposable element (TE activity in somatic tissues causes mutations that can contribute to tumorigenesis. Indeed, TE insertion mutations have been implicated in the etiology of a number of different cancer types. Nevertheless, the full extent of somatic TE activity, along with its relationship to tumorigenesis, have yet to be fully explored. Recent developments in bioinformatics software make it possible to analyze TE expression levels and TE insertional activity directly from transcriptome (RNA-seq and whole genome (DNA-seq next-generation sequence data. We applied these new sequence analysis techniques to matched normal and primary tumor patient samples from the Cancer Genome Atlas (TCGA in order to analyze the patterns of TE expression and insertion for three cancer types: breast invasive carcinoma, head and neck squamous cell carcinoma, and lung adenocarcinoma. Our analysis focused on the three most abundant families of active human TEs: Alu, SVA and L1. We found evidence for high levels of somatic TE activity for these three families in normal and cancer samples across diverse tissue types. Abundant transcripts for all three TE families were detected in both normal and cancer tissues along with an average of ~80 unique TE insertions per individual patient/tissue. We observed an increase in L1 transcript expression and L1 insertional activity in primary tumor samples for all three cancer types. Tumor-specific TE insertions are enriched for private mutations, consistent with a potentially causal role in tumorigenesis. We used genome feature analysis to investigate two specific cases of putative cancer-causing TE mutations in further detail. An Alu insertion in an upstream enhancer of the CBL tumor suppressor gene is associated with down-regulation of the gene in a single breast cancer patient, and an L1 insertion in the first exon of the BAALC gene also disrupts its expression in head and neck squamous cell carcinoma. Our results are

Perturbation of B Cell Gene Expression Persists in HIV-Infected Children Despite Effective Antiretroviral Therapy and Predicts H1N1 Response.

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Cotugno, Nicola; De Armas, Lesley; Pallikkuth, Suresh; Rinaldi, Stefano; Issac, Biju; Cagigi, Alberto; Rossi, Paolo; Palma, Paolo; Pahwa, Savita

2017-01-01

Despite effective antiretroviral therapy (ART), HIV-infected individuals with apparently similar clinical and immunological characteristics can vary in responsiveness to vaccinations. However, molecular mechanisms responsible for such impairment, as well as biomarkers able to predict vaccine responsiveness in HIV-infected children, remain unknown. Following the hypothesis that a B cell qualitative impairment persists in HIV-infected children (HIV) despite effective ART and phenotypic B cell immune reconstitution, the aim of the current study was to investigate B cell gene expression of HIV compared to age-matched healthy controls (HCs) and to determine whether distinct gene expression patterns could predict the ability to respond to influenza vaccine. To do so, we analyzed prevaccination transcriptional levels of a 96-gene panel in equal numbers of sort-purified B cell subsets (SPBS) isolated from peripheral blood mononuclear cells using multiplexed RT-PCR. Immune responses to H1N1 antigen were determined by hemaglutination inhibition and memory B cell ELISpot assays following trivalent-inactivated influenza vaccination (TIV) for all study participants. Although there were no differences in terms of cell frequencies of SPBS between HIV and HC, the groups were distinguishable based upon gene expression analyses. Indeed, a 28-gene signature, characterized by higher expression of genes involved in the inflammatory response and immune activation was observed in activated memory B cells (CD27 + CD21 - ) from HIV when compared to HC despite long-term viral control (>24 months). Further analysis, taking into account H1N1 responses after TIV in HIV participants, revealed that a 25-gene signature in resting memory (RM) B cells (CD27 + CD21 + ) was able to distinguish vaccine responders from non-responders (NR). In fact, prevaccination RM B cells of responders showed a higher expression of gene sets involved in B cell adaptive immune responses ( APRIL, BTK, BLIMP1 ) and

Transcription-based prediction of response to IFNbeta using supervised computational methods.

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Sergio E Baranzini

2005-01-01

Full Text Available Changes in cellular functions in response to drug therapy are mediated by specific transcriptional profiles resulting from the induction or repression in the activity of a number of genes, thereby modifying the preexisting gene activity pattern of the drug-targeted cell(s. Recombinant human interferon beta (rIFNbeta is routinely used to control exacerbations in multiple sclerosis patients with only partial success, mainly because of adverse effects and a relatively large proportion of nonresponders. We applied advanced data-mining and predictive modeling tools to a longitudinal 70-gene expression dataset generated by kinetic reverse-transcription PCR from 52 multiple sclerosis patients treated with rIFNbeta to discover higher-order predictive patterns associated with treatment outcome and to define the molecular footprint that rIFNbeta engraves on peripheral blood mononuclear cells. We identified nine sets of gene triplets whose expression, when tested before the initiation of therapy, can predict the response to interferon beta with up to 86% accuracy. In addition, time-series analysis revealed potential key players involved in a good or poor response to interferon beta. Statistical testing of a random outcome class and tolerance to noise was carried out to establish the robustness of the predictive models. Large-scale kinetic reverse-transcription PCR, coupled with advanced data-mining efforts, can effectively reveal preexisting and drug-induced gene expression signatures associated with therapeutic effects.

Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles

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Lee Yun-Shien

2008-03-01

Full Text Available Abstract Background The hierarchical clustering tree (HCT with a dendrogram 1 and the singular value decomposition (SVD with a dimension-reduced representative map 2 are popular methods for two-way sorting the gene-by-array matrix map employed in gene expression profiling. While HCT dendrograms tend to optimize local coherent clustering patterns, SVD leading eigenvectors usually identify better global grouping and transitional structures. Results This study proposes a flipping mechanism for a conventional agglomerative HCT using a rank-two ellipse (R2E, an improved SVD algorithm for sorting purpose seriation by Chen 3 as an external reference. While HCTs always produce permutations with good local behaviour, the rank-two ellipse seriation gives the best global grouping patterns and smooth transitional trends. The resulting algorithm automatically integrates the desirable properties of each method so that users have access to a clustering and visualization environment for gene expression profiles that preserves coherent local clusters and identifies global grouping trends. Conclusion We demonstrate, through four examples, that the proposed method not only possesses better numerical and statistical properties, it also provides more meaningful biomedical insights than other sorting algorithms. We suggest that sorted proximity matrices for genes and arrays, in addition to the gene-by-array expression matrix, can greatly aid in the search for comprehensive understanding of gene expression structures. Software for the proposed methods can be obtained at http://gap.stat.sinica.edu.tw/Software/GAP.

Expression pattern of neuronal intermediate filament α-internexin in anterior pituitary gland and related tumors.

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Schult, D; Hölsken, A; Buchfelder, M; Schlaffer, S-M; Siegel, S; Kreitschmann-Andermahr, I; Fahlbusch, R; Buslei, R

2015-08-01

α-Internexin (INA) is a class IV neuronal intermediate filament protein that maintains the morphogenesis of neurons. It is expressed in developing neuroblasts and represents the major component of the cytoskeleton in cerebellar granule cells of adult central nervous system tissue. Data concerning INA expression in the human frontal pituitary lobe and related adenomas (PA) is missing. Using immunohistochemistry we examined the distribution pattern of INA in a large cohort of 152 PA, 11 atypical PA, 4 pituitary carcinomas and 20 normal pituitaries (overall n = 187). Quantity of INA protein expression was semi-quantitatively evaluated and grouped into five categories (0 = 0%; 1 = >0-5%; 2 = >5-35%; 3 = >35-80%; 4 = >80% of cells). Cellular staining intensity of INA appeared significantly higher in gonadotropinomas (Go, n = 62), null cell adenomas (NC, n = 7) and thyrotropinomas (TSHomas, n = 7) compared to the other tumor subtypes (p ≤ 0.001). Furthermore, Go and NC showed a peculiar pseudorosette-like staining pattern surrounding blood vessels in 85.5% (59/69) of cases. Interestingly, areas exhibiting homogenous INA staining were often associated with oncocytic cell changes and decreased immunohistochemically detectable hormone expression. Only 8.5% (8/94) of other PA showed a comparable INA distribution (p ≤ 0.001). Go, NC as well as TSHomas exhibit high levels of intracellular INA protein indicating neuronal transdifferentiation. A possible impact on pathogenesis and endocrine activity needs further investigation.

Molecular characterization of cDNAs encoding G protein alpha and beta subunits and study of their temporal and spatial expression patterns in Nicotiana plumbaginifolia Viv.

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Kaydamov, C; Tewes, A; Adler, K; Manteuffel, R

2000-04-25

We have isolated cDNA sequences encoding alpha and beta subunits of potential G proteins from a cDNA library prepared from somatic embryos of Nicotiana plumbaginifolia Viv. at early developmental stages. The predicted NPGPA1 and NPGPB1 gene products are 75-98% identical to the known respective plant alpha and beta subunits. Southern hybridizations indicate that NPGPA1 is probably a single-copy gene, whereas at least two copies of NPGPB1 exist in the N. plumbaginifolia genome. Northern analyses reveal that both NPGPA1 and NPGPB1 mRNA are expressed in all embryogenic stages and plant tissues examined and their expression is obviously regulated by the plant hormone auxin. Immunohistological localization of NPGPalpha1 and NPGPbeta1 preferentially on plasma and endoplasmic reticulum membranes and their immunochemical detection exclusively in microsomal cell fractions implicate membrane association of both proteins. The temporal and spatial expression patterns of NPGPA1 and NPGPB1 show conformity as well as differences. This could account for not only cooperative, but also individual activities of both subunits during embryogenesis and plant development.

Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

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Leach, Lindsey J

2014-04-11

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution \\'nullisomic-tetrasomic\\' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

KAUST Repository

Leach, Lindsey J; Belfield, Eric J; Jiang, Caifu; Brown, Carly; Mithani, Aziz; Harberd, Nicholas P

2014-01-01

BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution 'nullisomic-tetrasomic' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

The functional landscape of mouse gene expression

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Zhang Wen

2004-12-01

Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

Computational Prediction of MicroRNAs from Toxoplasma gondii Potentially Regulating the Hosts’ Gene Expression

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Müşerref Duygu Saçar

2014-10-01

Full Text Available MicroRNAs (miRNAs were discovered two decades ago, yet there is still a great need for further studies elucidating their genesis and targeting in different phyla. Since experimental discovery and validation of miRNAs is difficult, computational predictions are indispensable and today most computational approaches employ machine learning. Toxoplasma gondii, a parasite residing within the cells of its hosts like human, uses miRNAs for its post-transcriptional gene regulation. It may also regulate its hosts’ gene expression, which has been shown in brain cancer. Since previous studies have shown that overexpressed miRNAs within the host are causal for disease onset, we hypothesized that T. gondii could export miRNAs into its host cell. We computationally predicted all hairpins from the genome of T. gondii and used mouse and human models to filter possible candidates. These were then further compared to known miRNAs in human and rodents and their expression was examined for T. gondii grown in mouse and human hosts, respectively. We found that among the millions of potential hairpins in T. gondii, only a few thousand pass filtering using a human or mouse model and that even fewer of those are expressed. Since they are expressed and differentially expressed in rodents and human, we suggest that there is a chance that T. gondii may export miRNAs into its hosts for direct regulation.

Conserved regional patterns of GABA-related transcript expression in the neocortex of subjects with schizophrenia.

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Hashimoto, Takanori; Bazmi, H Holly; Mirnics, Karoly; Wu, Qiang; Sampson, Allan R; Lewis, David A

2008-04-01

Individuals with schizophrenia exhibit disturbances in a number of cognitive, affective, sensory, and motor functions that depend on the circuitry of different cortical areas. The cognitive deficits associated with dysfunction of the dorsolateral prefrontal cortex result, at least in part, from abnormalities in GABA neurotransmission, as reflected in a specific pattern of altered expression of GABA-related genes. Consequently, the authors sought to determine whether this pattern of altered gene expression is restricted to the dorsolateral prefrontal cortex or could also contribute to the dysfunction of other cortical areas in subjects with schizophrenia. Real-time quantitative polymerase chain reaction was used to assess the levels of eight GABA-related transcripts in four cortical areas (dorsolateral prefrontal cortex, anterior cingulate cortex, and primary motor and primary visual cortices) of subjects (N=12) with schizophrenia and matched normal comparison subjects. Expression levels of seven transcripts were lower in subjects with schizophrenia, with the magnitude of reduction for each transcript comparable across the four areas. The largest reductions were detected for mRNA encoding somatostatin and parvalbumin, followed by moderate decreases in mRNA expression for the 67-kilodalton isoform of glutamic acid decarboxylase, the GABA membrane transporter GAT-1, and the alpha 1 and delta subunits of GABA(A) receptors. In contrast, the expression of calretinin mRNA did not differ between the subject groups in any of the four areas. Because the areas examined represent the major functional domains (e.g., association, limbic, motor, and sensory) of the cerebral cortex, our findings suggest that a conserved set of molecular alterations affecting GABA neurotransmission contribute to the pathophysiology of different clinical features of schizophrenia.

Patterns of expression of cell wall related genes in sugarcane

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Lima D.U.

2001-01-01

Full Text Available Our search for genes related to cell wall metabolism in the sugarcane expressed sequence tag (SUCEST database (http://sucest.lbi.dcc.unicamp.br resulted in 3,283 reads (1% of the total reads which were grouped into 459 clusters (potential genes with an average of 7.1 reads per cluster. To more clearly display our correlation coefficients, we constructed surface maps which we used to investigate the relationship between cell wall genes and the sugarcane tissues libraries from which they came. The only significant correlations that we found between cell wall genes and/or their expression within particular libraries were neutral or synergetic. Genes related to cellulose biosynthesis were from the CesA family, and were found to be the most abundant cell wall related genes in the SUCEST database. We found that the highest number of CesA reads came from the root and stem libraries. The genes with the greatest number of reads were those involved in cell wall hydrolases (e.g. beta-1,3-glucanases, xyloglucan endo-beta-transglycosylase, beta-glucosidase and endo-beta-mannanase. Correlation analyses by surface mapping revealed that the expression of genes related to biosynthesis seems to be associated with the hydrolysis of hemicelluloses, pectin hydrolases being mainly associated with xyloglucan hydrolases. The patterns of cell wall related gene expression in sugarcane based on the number of reads per cluster reflected quite well the expected physiological characteristics of the tissues. This is the first work to provide a general view on plant cell wall metabolism through the expression of related genes in almost all the tissues of a plant at the same time. For example, developing flowers behaved similarly to both meristematic tissues and leaf-root transition zone tissues. Besides providing a basis for future research on the mechanisms of plant development which involve the cell wall, our findings will provide valuable tools for plant engineering in the

Modelling and predicting biogeographical patterns in river networks

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Sabela Lois

2016-04-01

Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

In situ aromatase expression in primary tumor is associated with estrogen receptor expression but is not predictive of response to endocrine therapy in advanced breast cancer

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Lykkesfeldt, Anne E; Henriksen, Katrine L; Rasmussen, Birgitte B; Sasano, Hironobu; Evans, Dean B; Møller, Susanne; Ejlertsen, Bent; Mouridsen, Henning T

2009-01-01

New, third-generation aromatase inhibitors (AIs) have proven comparable or superior to the anti-estrogen tamoxifen for treatment of estrogen receptor (ER) and/or progesterone receptor (PR) positive breast cancer. AIs suppress total body and intratumoral estrogen levels. It is unclear whether in situ carcinoma cell aromatization is the primary source of estrogen production for tumor growth and whether the aromatase expression is predictive of response to endocrine therapy. Due to methodological difficulties in the determination of the aromatase protein, COX-2, an enzyme involved in the synthesis of aromatase, has been suggested as a surrogate marker for aromatase expression. Primary tumor material was retrospectively collected from 88 patients who participated in a randomized clinical trial comparing the AI letrozole to the anti-estrogen tamoxifen for first-line treatment of advanced breast cancer. Semi-quantitative immunohistochemical (IHC) analysis was performed for ER, PR, COX-2 and aromatase using Tissue Microarrays (TMAs). Aromatase was also analyzed using whole sections (WS). Kappa analysis was applied to compare association of protein expression levels. Univariate Wilcoxon analysis and the Cox-analysis were performed to evaluate time to progression (TTP) in relation to marker expression. Aromatase expression was associated with ER, but not with PR or COX-2 expression in carcinoma cells. Measurements of aromatase in WS were not comparable to results from TMAs. Expression of COX-2 and aromatase did not predict response to endocrine therapy. Aromatase in combination with high PR expression may select letrozole treated patients with a longer TTP. TMAs are not suitable for IHC analysis of in situ aromatase expression and we did not find COX-2 expression in carcinoma cells to be a surrogate marker for aromatase. In situ aromatase expression in tumor cells is associated with ER expression and may thus point towards good prognosis. Aromatase expression in cancer

Dogs Evaluate Threatening Facial Expressions by Their Biological Validity--Evidence from Gazing Patterns.

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Sanni Somppi

Full Text Available Appropriate response to companions' emotional signals is important for all social creatures. The emotional expressions of humans and non-human animals have analogies in their form and function, suggesting shared evolutionary roots, but very little is known about how animals other than primates view and process facial expressions. In primates, threat-related facial expressions evoke exceptional viewing patterns compared with neutral or positive stimuli. Here, we explore if domestic dogs (Canis familiaris have such an attentional bias toward threatening social stimuli and whether observed emotional expressions affect dogs' gaze fixation distribution among the facial features (eyes, midface and mouth. We recorded the voluntary eye gaze of 31 domestic dogs during viewing of facial photographs of humans and dogs with three emotional expressions (threatening, pleasant and neutral. We found that dogs' gaze fixations spread systematically among facial features. The distribution of fixations was altered by the seen expression, but eyes were the most probable targets of the first fixations and gathered longer looking durations than mouth regardless of the viewed expression. The examination of the inner facial features as a whole revealed more pronounced scanning differences among expressions. This suggests that dogs do not base their perception of facial expressions on the viewing of single structures, but the interpretation of the composition formed by eyes, midface and mouth. Dogs evaluated social threat rapidly and this evaluation led to attentional bias, which was dependent on the depicted species: threatening conspecifics' faces evoked heightened attention but threatening human faces instead an avoidance response. We propose that threatening signals carrying differential biological validity are processed via distinctive neurocognitive pathways. Both of these mechanisms may have an adaptive significance for domestic dogs. The findings provide a novel

Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression.

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Thomas P Stricker

2017-03-01

Full Text Available Breast cancer, the second leading cause of cancer death of women worldwide, is a heterogenous disease with multiple different subtypes. These subtypes carry important implications for prognosis and therapy. Interestingly, it is known that these different subtypes not only have different biological behaviors, but also have distinct gene expression profiles. However, it has not been rigorously explored whether particular transcriptional isoforms are also differentially expressed among breast cancer subtypes, or whether transcript isoforms from the same sets of genes can be used to differentiate subtypes. To address these questions, we analyzed the patterns of transcript isoform expression using a small set of RNA-sequencing data for eleven Estrogen Receptor positive (ER+ subtype and fourteen triple negative (TN subtype tumors. We identified specific sets of isoforms that distinguish these tumor subtypes with higher fidelity than standard mRNA expression profiles. We found that alternate promoter usage, alternative splicing, and alternate 3'UTR usage are differentially regulated in breast cancer subtypes. Profiling of isoform expression in a second, independent cohort of 68 tumors confirmed that expression of splice isoforms differentiates breast cancer subtypes. Furthermore, analysis of RNAseq data from 594 cases from the TCGA cohort confirmed the ability of isoform usage to distinguish breast cancer subtypes. Also using our expression data, we identified several RNA processing factors that were differentially expressed between tumor subtypes and/or regulated by estrogen receptor, including YBX1, YBX2, MAGOH, MAGOHB, and PCBP2. RNAi knock-down of these RNA processing factors in MCF7 cells altered isoform expression. These results indicate that global dysregulation of splicing in breast cancer occurs in a subtype-specific and reproducible manner and is driven by specific differentially expressed RNA processing factors.

Predicting the minimum liquid surface tension activity of pseudomonads expressing biosurfactants.

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Mohammed, I U; Deeni, Y; Hapca, S M; McLaughlin, K; Spiers, A J

2015-01-01

Bacteria produce a variety of biosurfactants capable of significantly reducing liquid (aqueous) surface tension (γ) with a range of biological roles and biotechnological uses. To determine the lowest achievable surface tension (γMin ), we tested a diverse collection of Pseudomonas-like isolates from contaminated soil and activated sludge and identified those expressing biosurfactants by drop-collapse assay. Liquid surface tension-reducing ability was quantitatively determined by tensiometry, with 57 isolates found to significantly lower culture supernatant surface tensions to 24·5-49·1 mN m(-1) . Differences in biosurfactant behaviour determined by foaming, emulsion and oil-displacement assays were also observed amongst isolates producing surface tensions of 25-27 mN m(-1) , suggesting that a range of structurally diverse biosurfactants were being expressed. Individual distribution identification (IDI) analysis was used to identify the theoretical probability distribution that best fitted the surface tension data, which predicted a γMin of 24·24 mN m(-1) . This was in agreement with predictions based on earlier work of published mixed bacterial spp. data, suggesting a fundamental limit to the ability of bacterial biosurfactants to reduce surface tensions in aqueous systems. This implies a biological restriction on the synthesis and export of these agents or a physical-chemical restriction on their functioning once produced. Numerous surveys of biosurfactant-producing bacteria have been conducted, but only recently has an attempt been made to predict the minimum liquid surface tension these surface-active agents can achieve. Here, we determine a theoretical minimum of 24 mN m(-1) by statistical analysis of tensiometry data, suggesting a fundamental limit for biosurfactant activity in bacterial cultures incubated under standard growth conditions. This raises a challenge to our understanding of biosurfactant expression, secretion and function, as well as

Expression patterns of nicotinamide phosphoribosyltransferase and nicotinic acid phosphoribosyltransferase in human malignant lymphomas

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Olesen, Uffe Høgh; Hastrup, Nina; Sehested, Maxwell

2011-01-01

The purpose of the study was to determine in human malignant lymphomas the expression patterns of nicotinamide phosphoribosyltransferase (NAMPT) and nicotinic acid phosphoribosyltransferase (NAPRT), the primary, rate-limiting enzymes in the synthesis of NAD+. NAMPT is a potential biomarker...... for sensitivity to NAMPT inhibitors and NAPRT is a biomarker for the use of nicotinic acid as a chemoprotectant in treatment with NAMPT inhibitors. The NAMPT inhibitor, APO866, is currently in clinical phase II trials in lymphomas. The expression of NAMPT and NAPRT was investigated in 53 samples of malignant.......0024). In conclusion, FL are a promising target for NAMPT inhibitors whereas substantial subsets of malignant lymphomas especially in Hodgkin lymphoma may be suitable for a combination treatment with nicotinic acid and NAMPT inhibitors....

Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

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Chen, Yu-Jen; Liu, Chih-Min; Hsu, Yung-Chin; Lo, Yu-Chun; Hwang, Tzung-Jeng; Hwu, Hai-Gwo; Lin, Yi-Tin; Tseng, Wen-Yih Isaac

2018-01-01

A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Spatial and temporal expression patterns of auxin response transcription factors in the syncytium induced by the beet cyst nematode Heterodera schachtii in Arabidopsis.

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Hewezi, Tarek; Piya, Sarbottam; Richard, Geoffrey; Rice, J Hollis

2014-09-01

Plant-parasitic cyst nematodes induce the formation of a multinucleated feeding site in the infected root, termed the syncytium. Recent studies point to key roles of the phytohormone auxin in the regulation of gene expression and establishment of the syncytium. Nevertheless, information about the spatiotemporal expression patterns of the transcription factors that mediate auxin transcriptional responses during syncytium formation is limited. Here, we provide a gene expression map of 22 auxin response factors (ARFs) during the initiation, formation and maintenance stages of the syncytium induced by the cyst nematode Heterodera schachtii in Arabidopsis. We observed distinct and overlapping expression patterns of ARFs throughout syncytium development phases. We identified a set of ARFs whose expression is predominantly located inside the developing syncytium, whereas others are expressed in the neighbouring cells, presumably to initiate specific transcriptional programmes required for their incorporation within the developing syncytium. Our analyses also point to a role of certain ARFs in determining the maximum size of the syncytium. In addition, several ARFs were found to be highly expressed in fully developed syncytia, suggesting a role in maintaining the functional phenotype of mature syncytia. The dynamic distribution and overlapping expression patterns of various ARFs seem to be essential characteristics of ARF activity during syncytium development. © 2014 BSPP AND JOHN WILEY & SONS LTD.

Postmortem mRNA expression patterns in left ventricular myocardial tissues and their implications for forensic diagnosis of sudden cardiac death.

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Son, Gi Hoon; Park, Seong Hwan; Kim, Yunmi; Kim, Ji Yeon; Kim, Jin Wook; Chung, Sooyoung; Kim, Yu-Hoon; Kim, Hyun; Hwang, Juck-Joon; Seo, Joong-Seok

2014-03-01

Sudden cardiac death (SCD), which is primarily caused by lethal heart disorders resulting in structural and arrhythmogenic abnormalities, is one of the prevalent modes of death in most developed countries. Myocardial ischemia, mainly due to coronary artery disease, is the most common type of heart disease leading to SCD. However, postmortem diagnosis of SCD is frequently complicated by obscure histological evidence. Here, we show that certain mRNA species, namely those encoding hemoglobin A1/2 and B (Hba1/2 and Hbb, respectively) as well as pyruvate dehydrogenase kinase 4 (Pdk4), exhibit distinct postmortem expression patterns in the left ventricular free wall of SCD subjects when compared with their expression patterns in the corresponding tissues from control subjects with non-cardiac causes of death. Hba1/2 and Hbb mRNA expression levels were higher in ischemic SCD cases with acute myocardial infarction or ischemic heart disease without recent infarction, and even in cardiac death subjects without apparent pathological signs of heart injuries, than control subjects. By contrast, Pdk4 mRNA was expressed at lower levels in SCD subjects. In conclusion, we found that altered myocardial Hba1/2, Hbb, and Pdk4 mRNA expression patterns can be employed as molecular signatures of fatal cardiac dysfunction to forensically implicate SCD as the primary cause of death.

Ring-enhancement pattern on contrast-enhanced CT predicts adenosquamous carcinoma of the pancreas: a matched case-control study.

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Imaoka, Hiroshi; Shimizu, Yasuhiro; Mizuno, Nobumasa; Hara, Kazuo; Hijioka, Susumu; Tajika, Masahiro; Tanaka, Tsutomu; Ishihara, Makoto; Ogura, Takeshi; Obayashi, Tomohiko; Shinagawa, Akihide; Sakaguchi, Masafumi; Yamaura, Hidekazu; Kato, Mina; Niwa, Yasumasa; Yamao, Kenji

2014-01-01

Adenosquamous carcinoma of the pancreas (ASC) is a rare malignant neoplasm of the pancreas, exhibiting both glandular and squamous differentiation. However, little is known about its imaging features. This study examined the imaging features of pancreatic ASC. We evaluated images of contrast-enhanced computed tomography (CT) and endoscopic ultrasonography (EUS). As controls, solid pancreatic neoplasms matched in a 2:1 ratio to ASC cases for age, sex and tumor location were also evaluated. Twenty-three ASC cases were examined, and 46 solid pancreatic neoplasms (43 pancreatic ductal adenocarcinomas, two pancreatic neuroendocrine tumors and one acinar cell carcinoma) were matched as controls. Univariate analysis demonstrated significant differences in the outline and vascularity of tumors on contrast-enhanced CT in the ASC and control groups (P outline, cystic changes, and the ring-enhancement pattern on contrast-enhanced CT were seen to have significant predictive powers by stepwise forward logistic regression analysis (P = 0.044, P = 0.010, and P = 0.001, respectively). Of the three, the ring-enhancement pattern was the most useful, and its predictive diagnostic sensitivity, specificity, positive predictive value and negative predictive value for diagnosis of ASC were 65.2%, 89.6%, 75.0% and 84.3%, respectively. These results demonstrate that presence of the ring-enhancement pattern on contrast-enhanced CT is the most useful predictive factor for ASC. Copyright © 2014 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Expression patterns of tight junction components induced by CD24 in an oral epithelial cell-culture model correlated to affected periodontal tissues.

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Ye, P; Yu, H; Simonian, M; Hunter, N

2014-04-01

Previously we demonstrated uniformly strong expression of CD24 in the epithelial attachment to the tooth and in the migrating epithelium of the periodontitis lesion. Titers of serum antibodies autoreactive with CD24 peptide correlated with reduced severity of periodontal disease. Ligation of CD24 expressed by oral epithelial cells induced formation of tight junctions that limited paracellular diffusion. In this study, we aimed to reveal that the lack of uniform expression of tight junction components in the pocket epithelium of periodontitis lesions is likely to contribute to increased paracellular permeability to bacterial products. This is proposed as a potential driver of the immunopathology of periodontitis. An epithelial culture model with close correspondence for expression patterns for tight junction components in periodontal epithelia was used. Immunohistochemical staining and confocal laser scanning microscopy were used to analyse patterns of expression of gingival epithelial tight junction components. The minimally inflamed gingival attachment was characterized by uniformly strong staining at cell contacts for the tight junction components zona occludens-1, zona occludens-2, occludin, junction adhesion molecule-A, claudin-4 and claudin-15. In contrast, the pocket epithelium of the periodontal lesion showed scattered, uneven staining for these components. This pattern correlated closely with that of unstimulated oral epithelial cells in culture. Following ligation of CD24 expressed by these cells, the pattern of tight junction component expression of the minimally inflamed gingival attachment developed rapidly. There was evidence for non-uniform and focal expression only of tight junction components in the pocket epithelium. In the cell-culture model, ligation of CD24 induced a tight junction expression profile equivalent to that observed for the minimally inflamed gingival attachment. Ligation of CD24 expressed by gingival epithelial cells by lectin

Effectiveness of gene expression profiling for response prediction of rectal cancer to preoperative radiotherapy

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Ojima, Eiki; Inoue, Yasuhiro; Miki, Chikao; Kusunoki, Masato; Mori, Masaki

2007-01-01

Our aim was to determine whether the expression levels of specific genes could predict clinical radiosensitivity in human colorectal cancer. Radioresistant colorectal cancer cell lines were established by repeated X-ray exposure (total, 100 Gy), and the gene expressions of the parent and radioresistant cell lines were compared in a microarray analysis. To verify the microarray data, we carried out a reverse transcriptase-polymerase chain reaction analysis of identified genes in clinical samples from 30 irradiated rectal cancer patients. A comparison of the intensity data for the parent and three radioresistant cell lines revealed 17 upregulated and 142 downregulated genes in all radioresistant cell lines. Next, we focused on two upregulated genes, PTMA (prothymosin α) and EIF5a2 (eukaryotic translation initiation factor 5A), in the radioresistant cell lines. In clinical samples, the expression of PTMA was significantly higher in the minor effect group than in the major effect group (P=0.004), but there were no significant differences in EIF5a2 expression between the two groups. We identified radiation-related genes in colorectal cancer and demonstrated that PTMA may play an important role in radiosensitivity. Our findings suggest that PTMA may be a novel marker for predicting the effectiveness of radiotherapy in clinical cases. (author)

Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

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Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

2009-01-01

Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

Diversity of Histologic Patterns and Expression of Cytoskeletal Proteins in Canine Skeletal Osteosarcoma.

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Nagamine, E; Hirayama, K; Matsuda, K; Okamoto, M; Ohmachi, T; Kadosawa, T; Taniyama, H

2015-09-01

Osteosarcoma (OS), the most common bone tumor, includes OS of the head (OSH) and appendicular OS (OSA). In dogs, it is classified into 6 histologic subtypes: osteoblastic, chondroblastic, fibroblastic, telangiectatic, giant cell, and poorly differentiated. This study investigated the significance of the histologic classification relevant to clinical outcome and the histologic and immunohistochemical relationships between pleomorphism and expression of cytoskeletal proteins in 60 cases each of OSH and OSA. Most neoplasms exhibited histologic diversity, and 64% of OS contained multiple subtypes. In addition to the above 6 subtypes, myxoid, round cell, and epithelioid subtypes were observed. Although the epithelioid subtypes were observed in only OSH, no significant difference in the frequency of other subtypes was observed. Also, no significant relevance was observed between the clinical outcome and histologic subtypes. Cytokeratin (CK) was expressed in both epithelioid and sarcomatoid tumor cells in various subtypes, and all CK-positive tumor cells also expressed vimentin. Vimentin and α-smooth muscle actin (SMA) were expressed in all subtypes. A few SMA-positive spindle-shaped tumor cells exhibited desmin expression. Glial fibrillary acidic protein-positive tumor cells were observed in many subtypes, and some of these cells showed neurofilament expression. Although OSH exhibited significantly stronger immunoreactivity for SMA than OSA, no significant difference in other cytoskeletal proteins was observed. Some tumor cells had cytoskeletal protein expression compatible with the corresponding histologic subtypes, such as CK in the epithelioid subtype and SMA in the fibroblastic subtype. Thus, canine skeletal OS is composed of pleomorphic and heterogenous tumor cells as is reflected in the diversity of histologic patterns and expression of cytoskeletal proteins. © The Author(s) 2015.

Expression patterns and role of PTEN in rat peripheral nerve development and injury.

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Chen, Hui; Xiang, Jianping; Wu, Junxia; He, Bo; Lin, Tao; Zhu, Qingtang; Liu, Xiaolin; Zheng, Canbin

2018-05-29

Studies have suggested that phosphatase and tensin homolog (PTEN) plays an important role in neuroprotection and neuronal regeneration. To better understand the potential role of PTEN with respect to peripheral nerve development and injury, we investigated the expression pattern of PTEN at different stages of rat peripheral nerve development and injury and subsequently assessed the effect of pharmacological inhibition of PTEN using bpV(pic) on axonal regeneration in a rat sciatic nerve crush injury model. During the early stages of development, PTEN exhibits low expression in neuronal cell bodies and axons. From embryonic day (E) 18.5 and postnatal day (P)5 to adult, PTEN protein becomes more detectable, with high expression in the dorsal root ganglia (DRG) and axons. PTEN expression is inhibited in peripheral nerves, preceding myelination during neuronal development and remyelination after acute nerve injury. Low PTEN expression after nerve injury promotes Akt/mammalian target of rapamycin (mTOR) signaling pathway activity. In vivo pharmacological inhibition of PTEN using bpV(pic) promoted axonal regrowth, increased the number of myelinated nerve fibers, improved locomotive recovery and enhanced the amplitude response and nerve conduction velocity following stimulation in a rat sciatic nerve crush injury model. Thus, we suggest that PTEN may play potential roles in peripheral nerve development and regeneration and that inhibition of PTEN expression is beneficial for nerve regeneration and functional recovery after peripheral nerve injury. Copyright © 2018 Elsevier B.V. All rights reserved.

EMMPRIN co-expressed with matrix metalloproteinases predicts poor prognosis in patients with osteosarcoma.

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Futamura, Naohisa; Nishida, Yoshihiro; Urakawa, Hiroshi; Kozawa, Eiji; Ikuta, Kunihiro; Hamada, Shunsuke; Ishiguro, Naoki

2014-06-01

Several studies have focused on the relationships between the expression of extracellular matrix metalloproteinase inducer (EMMPRIN) and the prognosis of patients with malignant tumors. However, few of these have investigated the expression of EMMPRIN in osteosarcoma. We examined expression levels of EMMPRIN immunohistochemically in 53 cases of high-grade osteosarcoma of the extremities and analyzed the correlation of its expression with patient prognosis. The correlation between matrix metalloproteinases (MMPs) and EMMPRIN expression and the prognostic value of co-expression were also analyzed. Staining positivity for EMMPRIN was negative in 7 cases, low in 17, moderate in 19, and strong in 10. The overall and disease-free survivals (OS and DFS) in patients with higher EMMPRIN expression (strong-moderate) were significantly lower than those in the lower (weak-negative) group (0.037 and 0.024, respectively). In multivariate analysis, age (P=0.004), location (P=0.046), and EMMPRIN expression (P=0.038) were significant prognostic factors for overall survival. EMMPRIN expression (P=0.024) was also a significant prognostic factor for disease-free survival. Co-expression analyses of EMMPRIN and MMPs revealed that strong co-expression of EMMPRIN and membrane-type 1 (MT1)-MMP had a poor prognostic value (P=0.056 for DFS, P=0.006 for OS). EMMPRIN expression and co-expression with MMPs well predict the prognosis of patients with extremity osteosarcoma, making EMMPRIN a possible therapeutic target in these patients.

Improving prediction of Alzheimer’s disease using patterns of cortical thinning and homogenizing images according to disease stage

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Eskildsen, Simon Fristed; Coupé, Pierrick; García-Lorenzo, Daniel

Predicting Alzheimer’s disease (AD) in individuals with some symptoms of cognitive decline may have great influence on treatment choice and guide subject selection in trials on disease modifying drugs. Structural MRI has the potential of revealing early signs of neurodegeneration in the human brain...... and may thus aid in predicting and diagnosing AD. Surface-based cortical thickness measurements from T1-weighted MRI have demonstrated high sensitivity to cortical gray matter changes. In this study, we investigated the possibility of using patterns of cortical thickness measurements for predicting AD...... of conversion from MCI to AD can be improved by learning the atrophy patterns that are specific to the different stages of disease progression. This has the potential to guide the further development of imaging biomarkers in AD....

Combined lineage mapping and gene expression profiling of embryonic brain patterning using ultrashort pulse microscopy and image registration

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Gibbs, Holly C.; Dodson, Colin R.; Bai, Yuqiang; Lekven, Arne C.; Yeh, Alvin T.

2014-12-01

During embryogenesis, presumptive brain compartments are patterned by dynamic networks of gene expression. The spatiotemporal dynamics of these networks, however, have not been characterized with sufficient resolution for us to understand the regulatory logic resulting in morphogenetic cellular behaviors that give the brain its shape. We have developed a new, integrated approach using ultrashort pulse microscopy [a high-resolution, two-photon fluorescence (2PF)-optical coherence microscopy (OCM) platform using 10-fs pulses] and image registration to study brain patterning and morphogenesis in zebrafish embryos. As a demonstration, we used time-lapse 2PF to capture midbrain-hindbrain boundary morphogenesis and a wnt1 lineage map from embryos during brain segmentation. We then performed in situ hybridization to deposit NBT/BCIP, where wnt1 remained actively expressed, and reimaged the embryos with combined 2PF-OCM. When we merged these datasets using morphological landmark registration, we found that the mechanism of boundary formation differs along the dorsoventral axis. Dorsally, boundary sharpening is dominated by changes in gene expression, while ventrally, sharpening may be accomplished by lineage sorting. We conclude that the integrated visualization of lineage reporter and gene expression domains simultaneously with brain morphology will be useful for understanding how changes in gene expression give rise to proper brain compartmentalization and structure.

The grapevine kinome: annotation, classification and expression patterns in developmental processes and stress responses.

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Zhu, Kaikai; Wang, Xiaolong; Liu, Jinyi; Tang, Jun; Cheng, Qunkang; Chen, Jin-Gui; Cheng, Zong-Ming Max

2018-01-01

Protein kinases (PKs) have evolved as the largest family of molecular switches that regulate protein activities associated with almost all essential cellular functions. Only a fraction of plant PKs, however, have been functionally characterized even in model plant species. In the present study, the entire grapevine kinome was identified and annotated using the most recent version of the grapevine genome. A total of 1168 PK-encoding genes were identified and classified into 20 groups and 121 families, with the RLK-Pelle group being the largest, with 872 members. The 1168 kinase genes were unevenly distributed over all 19 chromosomes, and both tandem and segmental duplications contributed to the expansion of the grapevine kinome, especially of the RLK-Pelle group. Ka/Ks values indicated that most of the tandem and segmental duplication events were under purifying selection. The grapevine kinome families exhibited different expression patterns during plant development and in response to various stress treatments, with many being coexpressed. The comprehensive annotation of grapevine kinase genes, their patterns of expression and coexpression, and the related information facilitate a more complete understanding of the roles of various grapevine kinases in growth and development, responses to abiotic stress, and evolutionary history.

uPAR Expression Pattern in Patients with Urothelial Carcinoma of the Bladder--Possible Clinical Implications.

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Line Hammer Dohn

Full Text Available The objective of the present study was to confirm the expression and localisation pattern of the urokinase-type plasminogen activator receptor (uPAR focusing on its possible clinical relevance in patients with urothelial neoplasia of the bladder. uPAR is a central molecule in tissue remodelling during cancer invasion and metastasis and is an established prognostic marker in various cancer diseases other than bladder cancer. Formalin-fixed and paraffin-embedded tumour-tissue blocks from 186 patients treated with radical cystectomy were analysed. uPAR expression was scored as either negative or positive as well as by the actual score. Separate scores were obtained for cancer cells, macrophages and myofibroblasts at the invasive front and in tumour core. We were able to confirm, in an independent patient cohort, the tissue expression and localisation pattern of uPAR as investigated by Immunohistochemistry as well as a significant association between uPAR positivity and increasing tumour stage and tumour grade. This demonstrates the robustness of our previous and current findings. In addition the association between uPAR positive myofibroblasts and poor survival was reproduced. The highest hazard ratios for survival were seen for uPAR positive myofibroblasts both at the invasive front and in tumour core. Evaluating uPAR expression by the actual score showed a significant association between uPAR positive myofibroblasts in tumour core and an increased risk of cancer specific mortality. Our investigations have generated new and valuable biological information about the cell types being involved in tumour invasion and progression through the plasminogen activation system.

Zinc oxide nanoparticle exposure triggers different gene expression patterns in maize shoots and roots

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