978 resultados para General expression


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In this paper we consider the problem of scheduling expression trees on delayed-load architectures. The problem tackled here takes root from the one considered in [Proceedings of the ACM SIGPLAN '91 Conf. on Programming Language Design and Implementation, 1991. p. 256] in which the leaves of the expression trees all refer to memory locations. A generalization of this involves the situation in which the trees may contain register variables, with the registers being used only at the leaves. Solutions to this generalization are given in [ACM Trans. Prog. Lang. Syst. 17 (1995) 740, Microproc. Microprog. 40 (1994) 577]. This paper considers the most general case in which the registers are reusable. This problem is tackled in [Comput. Lang, 21 (1995) 49] which gives an approximate solution to the problem under certain assumptions about the contiguity of the evaluation order: Here we propose an optimal solution (which may involve even a non-contiguous evaluation of the tree). The schedule generated by the algorithm given in this paper is optimal in the sense that it is an interlock-free schedule which uses the minimum number of registers required. An extension to the algorithm incorporates spilling. The problem as stated in this paper is an instruction scheduling problem. However, the problem could also be rephrased as an operations research problem with a difference in terminology. (C) 2002 Elsevier Science B.V. All rights reserved.

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Estrogen signalling is critical for ovarian differentiation in reptiles with temperature-dependent sex determination (TSD). To elucidate the involvement of estrogen in this process, adrenal-kidney-gonadal (AKG) expression of estrogen receptor (ER alpha) was studied at female-producing temperature (FPT) in the developing embryos of the lizard, Calotes versicolor which exhibits a distinct pattern of TSD. The eggs of this lizard were incubated at 31.5 +/- 0.5 degrees C (100% FPT). The torso of embryos containing adrenal-kidney-gonadal complex (AKG) was collected during different stages of development and subjected to Western blotting and immunohistochemistry analysis. The ER alpha, antibody recognized two protein bands with apparent molecular weight similar to 55 and similar to 45 kDa in the total protein extracts of embryonic AKG complex of C. versicolor. The observed results suggest the occurrence of isoforms of ER alpha. The differential expression of two different protein isoforms may reveal their distinct role in cell proliferation during gonadal differentiation. This is the first report to reveal two isoforms of the ER alpha in a reptile during development. Immunohistochemical studies reveal a weak, but specific, cytoplasmic ER alpha immunostaining exclusively in the AKG during late thermo-sensitive period suggesting the responsiveness of AKG to estrogens before gonadal differentiation at FPT. Further, cytoplasmic as well as nuclear expression of ER alpha in the medulla and in oogonia of the cortex (faint activity) at gonadal differentiation stage suggests that the onset of gonadal estrogen activity coincides with sexual differentiation of gonad. Intensity and pattern of the immunoreactions of ER alpha in the medullary region at FPT suggest endogenous production of estrogen which may act in a paracrine fashion to induce neighboring cells into ovarian differentiation pathway. (C) 2014 Elsevier Inc. All rights reserved.

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We derive a relationship between the initial unloading slope, contact depth, and the instantaneous relaxation modulus for indentation in linear viscoelastic solids by a rigid indenter with an arbitrary axisymmetric smooth profile. Although the same expression is well known for indentation in elastic and in elastic-plastic solids, we show that it is also true for indentation in linear viscoelastic solids, provided that the unloading rate is sufficiently fast. Furthermore, the same expression holds true for both fast loading and unloading. These results should provide a sound basis for using the relationship for determining properties of viscoelastic solids using indentation techniques.

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Numerous transcription factors self-assemble into different order oligomeric species in a way that is actively regulated by the cell. Until now, no general functional role has been identified for this widespread process. Here, we capture the effects of modulated self-assembly in gene expression with a novel quantitative framework. We show that this mechanism provides precision and flexibility, two seemingly antagonistic properties, to the sensing of diverse cellular signals by systems that share common elements present in transcription factors like p53, NF-kappa B, STATs, Oct and RXR. Applied to the nuclear hormone receptor RXR, this framework accurately reproduces a broad range of classical, previously unexplained, sets of gene expression data and corroborates the existence of a precise functional regime with flexible properties that can be controlled both at a genome-wide scale and at the individual promoter level.

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Analytical expression of signal bandwidth of general straight and tapered N x N multimode interference (MMI) couplers is presented. The signal bandwidth is characterized as a function of mode relative energy, mode propagation delay time, and mode pulse broadening in the multimode section of MMI coupler. The model is used to evaluate the signal bandwidth of specific couplers. Results indicate that the signal bandwidth decreases seriously with the increase of channel number and channel guide space. Compared with the straight MMI coupler, the tapered MMI coupler has an improved signal bandwidth.

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We generalize the Faddeev-Jackiw canonical path integral quantization for the scenario of a Jacobian with J=1 to that for the general scenario of non-unit Jacobian, give the representation of the quantum transition amplitude with symplectic variables and obtain the generating functionals of the Green function and connected Green function. We deduce the unified expression of the symplectic field variable functions in terms of the Green function or the connected Green function with external sources. Furthermore, we generally get generating functionals of the general proper vertices of any n-points cases under the conditions of considering and not considering Grassmann variables, respectively; they are regular and are the simplest forms relative to the usual field theory.

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This study is aimed at observing the apoptosis and Bcl-2/Bax gene expression of mammalian cells following heavy-ion and X-ray irradiations. Exponentially growing human hepatoma SMMC-7721 cells cultured in vitro were irradiated with a C-12 ion beam of 50 MeV/u (corresponding to a LET value of 44.56 keV/mu m) from Heavy Ion Research Facility in Lanzhou (HIRFL) at doses varying from 0 to 3 Gy. The X-ray irradiation (8 MV) was performed in the therapy unit of the General Hospital of the Lanzhou Military Area. Survival fractions of irradiated cells at various doses were measured by means of MTT assay. Apoptotic cells after irradiation were analyzed with fluorescence microscope and flow cytometer (FCM). Immuno-histological assay were applied to detect the expression of Bcl-2/Bax genes in the irradiated cells. The survival fraction of SMMC-7721 cells decreased gradually (vs. control p<0.05) with increasing the dose of the carbon ion beam more obviously than X-ray irradiation, and the carbon ion irradiation efficiently induced cell apoptosis and significantly promoted the expression of Bax gene while Bcl-2 gene expression was restrained. High-LET heavy ion beam would induce cell apoptosis effectively than low-LET X-ray, and the apoptosis rate is correlated with the transcription of Bcl-2/Bax and the ratio of Bcl-2/Bax in human hepatoma SMMC-7721 cells after irradiation to heavy ion beam.

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Diane Rowland, Griping, Bitching and Speaking Your Mind: Defamation and Free Expression on the Internet, Pennsylvania State Law Review Symposium Issue 110, no. 3 (2006): 519?538; RAE2008

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Transcription from morbillivirus genomes commences at a single promoter in the 3' non-coding terminus, with the six genes being transcribed sequentially. The 3' and 5' untranslated regions (UTRs) of the genes (mRNA sense), together with the intergenic trinucleotide spacer, comprise the non-coding sequences (NCS) of the virus and contain the conserved gene end and gene start signals, respectively. Bicistronic minigenomes containing transcription units (TUs) encoding autofluorescent reporter proteins separated by measles virus (MV) NCS were used to give a direct estimation of gene expression in single, living cells by assessing the relative amounts of each fluorescent protein in each cell. Initially, five minigenomes containing each of the MV NCS were generated. Assays were developed to determine the amount of each fluorescent protein in cells at both cell population and single-cell levels. This revealed significant variations in gene expression between cells expressing the same NCS-containing minigenome. The minigenome containing the M/F NCS produced significantly lower amounts of fluorescent protein from the second TU (TU2), compared with the other minigenomes. A minigenome with a truncated F 5' UTR had increased expression from TU2. This UTR is 524 nt longer than the other MV 5' UTRs. Insertions into the 5' UTR of the enhanced green fluorescent protein gene in the minigenome containing the N/P NCS showed that specific sequences, rather than just the additional length of F 5' UTR, govern this decreased expression from TU2.

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BACKGROUND: MicroRNAs (miRNAs) are oligoribonucleotides with an important role in regulation of gene expression at the level of translation. Despite imperfect target complementarity, they can also significantly reduce mRNA levels. The validity of miRNA target gene predictions is difficult to assess at the protein level. We sought, therefore, to determine whether a general lowering of predicted target gene mRNA expression by endogenous miRNAs was detectable within microarray gene expression profiles. RESULTS: The target gene sets predicted for each miRNA were mapped onto known gene expression data from a range of tissues. Whether considering mean absolute target gene expression, rank sum tests or 'ranked ratios', many miRNAs with significantly reduced target gene expression corresponded to those known to be expressed in the cognate tissue. Expression levels of miRNAs with reduced target mRNA levels were higher than those of miRNAs with no detectable effect on mRNA expression. Analysis of microarray data gathered after artificial perturbation of expression of a specific miRNA confirmed the predicted increase or decrease in influence of the altered miRNA upon mRNA levels. Strongest associations were observed with targets predicted by TargetScan. CONCLUSION: We have demonstrated that the effect of a miRNA on its target mRNAs' levels can be measured within a single gene expression profile. This emphasizes the extent of this mode of regulation in vivo and confirms that many of the predicted miRNA-mRNA interactions are correct. The success of this approach has revealed the vast potential for extracting information about miRNA function from gene expression profiles.

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

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One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

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Patterns of glycosylation are important in cancer, but the molecular mechanisms that drive changes are often poorly understood. The androgen receptor drives prostate cancer (PCa) development and progression to lethal metastatic castration-resistant disease. Here we used RNA-Seq coupled with bioinformatic analyses of androgen-receptor (AR) binding sites and clinical PCa expression array data to identify ST6GalNAc1 as a direct and rapidly activated target gene of the AR in PCa cells. ST6GalNAc1 encodes a sialytransferase that catalyses formation of the cancer-associated sialyl-Tn antigen (sTn), which we find is also induced by androgen exposure. Androgens induce expression of a novel splice variant of the ST6GalNAc1 protein in PCa cells. This splice variant encodes a shorter protein isoform that is still fully functional as a sialyltransferase and able to induce expression of the sTn-antigen. Surprisingly, given its high expression in tumours, stable expression of ST6GalNAc1 in PCa cells reduced formation of stable tumours in mice, reduced cell adhesion and induced a switch towards a more mesenchymal-like cell phenotype in vitro. ST6GalNAc1 has a dynamic expression pattern in clinical datasets, beingsignificantly up-regulated in primary prostate carcinoma but relatively down-regulated in established metastatic tissue. ST6GalNAc1 is frequently upregulated concurrently with another important glycosylation enzyme GCNT1 previously associated with prostate cancer progression and implicated in Sialyl Lewis X antigen synthesis. Together our data establishes an androgen-dependent mechanism for sTn antigen expression in PCa, and are consistent with a general role for the androgen receptor in driving important coordinate changes to the glycoproteome during PCa progression.