71 resultados para Analysis of Algorithms and Problem Complexity
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Contralesional brain connectivity plasticity was previously reported after stroke. This study aims at disentangling the biological mechanisms underlying connectivity plasticity in the uninjured motor network after an ischemic lesion. In particular, we measured generalized fractional anisotropy (GFA) and magnetization transfer ratio (MTR) to assess whether poststroke connectivity remodeling depends on axonal and/or myelin changes. Diffusion-spectrum imaging and magnetization transfer MRI at 3T were performed in 10 patients in acute phase, at 1 and 6 months after stroke, which was affecting motor cortical and/or subcortical areas. Ten age- and gender-matched healthy volunteers were scanned 1 month apart for longitudinal comparison. Clinical assessment was also performed in patients prior to magnetic resonance imaging (MRI). In the contralesional hemisphere, average measures and tract-based quantitative analysis of GFA and MTR were performed to assess axonal integrity and myelination along motor connections as well as their variations in time. Mean and tract-based measures of MTR and GFA showed significant changes in a number of contralesional motor connections, confirming both axonal and myelin plasticity in our cohort of patients. Moreover, density-derived features (peak height, standard deviation, and skewness) of GFA and MTR along the tracts showed additional correlation with clinical scores than mean values. These findings reveal the interplay between contralateral myelin and axonal remodeling after stroke.
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Ipilimumab and tremelimumab are human monoclonal antibodies (Abs) against cytotoxic T-lymphocyte antigen-4 (CTLA-4). Ipilimumab was the first agent to show a statistically significant benefit in overall survival in advanced melanoma patients. Currently, there is no proven association between the BRAFV600 mutation and the disease control rate in response to ipilimumab. This analysis was carried out to assess if BRAFV600 and NRAS mutation status affects the clinical outcome of anti-CTLA-4-treated melanoma patients. This is a retrospective multi-center analysis of 101 patients, with confirmed BRAF and NRAS mutation status, treated with anti-CTLA-4 antibodies from December 2006 until August 2012. The median overall survival, defined from the treatment start date with the anti-CTLA-4. Abs-treatment to death or till last follow up, of BRAFV600 or NRAS mutant patients (n = 62) was 10.12 months (95% CI 6.78-13.2) compared to 8.26 months (95% CI 6.02-19.9) in BRAFV600/NRASwt subpopulation (n = 39) (p = 0.67). The median OS of NRAS mutated patients (n = 24) was 12.1 months and although was prolonged compared to the median OS of BRAF mutated patients (n = 38, mOS = 8.03 months) or BRAFV600/NRASwt patients (n = 39, mOS = 8.26 months) the difference didn't reach statistical significance (p = 0.56). 69 patients were able to complete 4 cycles of anti-CTLA-4 treatment. Of the 24 patients treated with selected BRAF- or MEK-inhibitors, 16 patients received anti-CTLA 4 Abs following either a BRAF or MEK inhibitor with only 8 of them being able to finish 4 cycles of treatment. Based on our results, there is no difference in the median OS in patients treated with anti-CTLA-4 Abs implying that the BRAF/NRAS mutation status alone is not sufficient to predict the outcome of patients treated with anti-CTLA-4 Abs.
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OBJECTIVES: To investigate the frequency of interim analyses, stopping rules, and data safety and monitoring boards (DSMBs) in protocols of randomized controlled trials (RCTs); to examine these features across different reasons for trial discontinuation; and to identify discrepancies in reporting between protocols and publications. STUDY DESIGN AND SETTING: We used data from a cohort of RCT protocols approved between 2000 and 2003 by six research ethics committees in Switzerland, Germany, and Canada. RESULTS: Of 894 RCT protocols, 289 prespecified interim analyses (32.3%), 153 stopping rules (17.1%), and 257 DSMBs (28.7%). Overall, 249 of 894 RCTs (27.9%) were prematurely discontinued; mostly due to reasons such as poor recruitment, administrative reasons, or unexpected harm. Forty-six of 249 RCTs (18.4%) were discontinued due to early benefit or futility; of those, 37 (80.4%) were stopped outside a formal interim analysis or stopping rule. Of 515 published RCTs, there were discrepancies between protocols and publications for interim analyses (21.1%), stopping rules (14.4%), and DSMBs (19.6%). CONCLUSION: Two-thirds of RCT protocols did not consider interim analyses, stopping rules, or DSMBs. Most RCTs discontinued for early benefit or futility were stopped without a prespecified mechanism. When assessing trial manuscripts, journals should require access to the protocol.
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Introduction: Les études GVvA (Genome-wide association ,-studies) ont identifié et confirmé plus de 20 gènes de susceptibilité au DT2 et ont contribué à mieux comprendre sa physiopathologie. L'hyperglycémie à jeun (GJ), et 2 heures après une HGPO (G2h) sont les deux mesures cliniques du diagnostic du DT2. Nous avons identifié récemment la G6P du pancréas (G6PC2) comme déterminant de la variabilité physiologique de la GJ puis Ie récepteur à la mélatonine (MTNRIB) qui de plus lie la régulation du rythme circadien au DT2. Dans ce travail nous avons étudié la génétique de la G2h à l'aide de l'approche GWA. Résultats: Nous avons réalisé une méta-analyse GWA dans le cadre de MAGIC (Meta-Analysis of Glucose and Insulin related traits Consortium) qui a inclus 9 études GWA (N=15'234). La réplication de 29 loci (N=6958-30 121, P < 10-5 ) a confirmé 5 nouveaux loci; 2 étant connus comme associés avec Ie DT2 (TCF7L2, P = 1,6 X 10-10 ) et la GJ (GCKR, p = 5,6 X 10-10 ); alors que GIPR (p= 5,2 X 10-12), VSP13C (p= 3,9 X 10-8) et ADCY5 (p = 1,11 X 10-15 ) sont inédits. GIPR code Ie récepteur au GIP (gastric inhibitory polypeptide) qui est sécrété par les ceIlules intestinales pour stimuler la sécrétion de l'insuline en réponse au glucose (l'effet incrétine). Les porteurs du variant GIPR qui augmente la G2h ont également un indice insulinogénique plus bas, (p= 1,0 X 10-17) mais ils ne présentent aucune modification de leur glycémie suite à une hyperglycémie provoquée par voie veineuse (p= 0,21). Ces résultats soutiennent un effet incrétine du locus GIPR qui expliquerait ~9,6 % de la variance total de ce trait. La biologie de ADCY5 et VPS13C et son lien avec l'homéostasie du glucose restent à élucider. GIPR n'est pas associé avec le risque de DT2 indiquant qu'il influence la variabilité physiologique de la G2h alors que le locus ADCY5 est associé avec le DT2 (OR = 1,11, P = 1,5 X 10-15). Conclusion: Notre étude démontre que l'étude de la G2h est une approche efficace d'une part pour la compréhension de la base génétique de la physiologie de ce trait clinique important et d'autre part pour identifier de nouveaux gènes de susceptibilité au DT2.
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Little is known about the role of the transcription factor peroxisome proliferator-activated receptor (PPAR) beta/delta in liver. Here we set out to better elucidate the function of PPARbeta/delta in liver by comparing the effect of PPARalpha and PPARbeta/delta deletion using whole genome transcriptional profiling and analysis of plasma and liver metabolites. In fed state, the number of genes altered by PPARalpha and PPARbeta/delta deletion was similar, whereas in fasted state the effect of PPARalpha deletion was much more pronounced, consistent with the pattern of gene expression of PPARalpha and PPARbeta/delta. Minor overlap was found between PPARalpha- and PPARbeta/delta-dependent gene regulation in liver. Pathways upregulated by PPARbeta/delta deletion were connected to innate immunity and inflammation. Pathways downregulated by PPARbeta/delta deletion included lipoprotein metabolism and various pathways related to glucose utilization, which correlated with elevated plasma glucose and triglycerides and reduced plasma cholesterol in PPARbeta/delta-/- mice. Downregulated genes that may underlie these metabolic alterations included Pklr, Fbp1, Apoa4, Vldlr, Lipg, and Pcsk9, which may represent novel PPARbeta/delta target genes. In contrast to PPARalpha-/- mice, no changes in plasma free fatty acid, plasma beta-hydroxybutyrate, liver triglycerides, and liver glycogen were observed in PPARbeta/delta-/- mice. Our data indicate that PPARbeta/delta governs glucose utilization and lipoprotein metabolism and has an important anti-inflammatory role in liver. Overall, our analysis reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver.
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We have taken advantage of the natural milieu of matched pair of azole sensitive (AS) and azole resistant (AR) clinical isolates of Candida glabrata for expressing its major ABC multidrug transporter, CgCdr1p for structure and functional analysis. This was accomplished by tagging a green fluorescent protein (GFP) downstream of ORF of CgCDR1 and integrating the resultant fusion protein at its native chromosomal locus in AS and AR backgrounds. The characterization confirmed that in comparison to AS isolate, CgCdr1p-GFP was over-expressed in AR isolates due to its hyperactive native promoter and the GFP tag did not affect its functionality in either construct. We observed that in addition to Rhodamine 6 G (R6G) and Fluconazole (FLC), a recently identified fluorescent substrate of multidrug transporters Nile Red (NR) could also be expelled by CgCdr1p. Competition assays with these substrates revealed the presence of overlapping multiple drug binding sites in CgCdr1p. Point mutations employing site directed mutagenesis confirmed that the role played by unique amino acid residues critical to ATP catalysis and localization of ABC drug transporter proteins are well conserved in C. glabrata as in other yeasts. This study demonstrates a first in vivo novel system where over-expression of GFP tagged MDR transporter protein can be driven by its own hyperactive promoter of AR isolates. Taken together, this in vivo system can be exploited for the structure and functional analysis of CgCdr1p and similar proteins wherein the artefactual concerns encountered in using heterologous systems are totally excluded.
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PURPOSE OF REVIEW: One of the seven key scientific priorities identified in the road map on HIV cure research is to 'determine the host mechanisms that control HIV replication in the absence of therapy'. This review summarizes the recent work in genomics and in epigenetic control of viral replication that is relevant for this mission. RECENT FINDINGS: New technologies allow the joint analysis of host and viral transcripts. They identify the patterns of antisense transcription of the viral genome and its role in gene regulation. High-throughput studies facilitate the assessment of integration at the genome scale. Integration site, orientation and host genomic context modulate the transcription and should also be assessed at the level of single cells. The various models of latency in primary cells can be followed using dynamic study designs to acquire transcriptome and proteome data of the process of entry, maintenance and reactivation of latency. Dynamic studies can be applied to the study of transcription factors and chromatin modifications in latency and upon reactivation. SUMMARY: The convergence of primary cell models of latency, new high-throughput quantitative technologies applied to the study of time series and the identification of compounds that reactivate viral transcription bring unprecedented precision to the study of viral latency.
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The peroxisome proliferator-activated receptor gamma (PPARgamma) is abundantly expressed in adipocytes, and plays an important role in adipocyte differentiation and fat accretion. It is a heterodimeric partner of the retinoid X receptors alpha, beta and gamma, which are also expressed in the adipose tissue. As lethality of PPARgamma(-/-) and RXRalpha(-/-) mouse fetuses precluded the analysis of PPARgamma and RXRalpha functions in mature adipocytes, we generated RXRalpha(ad-/-) and PPARgamma(ad-/-) mice, in which RXRalpha and PPARgamma are selectively ablated in adult adipocytes, respectively. Even though the adiposity of RXRalpha(ad-/-) mice is similar to that of control mice when fed a regular diet, they are resistant to chemically and dietary-induced obesity. However, mature adipocytes lacking either both RXRalpha and RXRgamma or PPARgamma die, and are replaced by newly formed adipocytes. Thus, in adipocytes, RXRalpha is essential for lipogenesis, but RXRgamma can functionally replace RXRalpha for the adipocyte vital functions exerted by PPARgamma/RXR heterodimers.
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The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.
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MOTIVATION: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.
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The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.
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In this paper we propose a stabilized conforming finite volume element method for the Stokes equations. On stating the convergence of the method, optimal a priori error estimates in different norms are obtained by establishing the adequate connection between the finite volume and stabilized finite element formulations. A superconvergence result is also derived by using a postprocessing projection method. In particular, the stabilization of the continuous lowest equal order pair finite volume element discretization is achieved by enriching the velocity space with local functions that do not necessarily vanish on the element boundaries. Finally, some numerical experiments that confirm the predicted behavior of the method are provided.
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High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy
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Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.
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This paper presents and discusses further aspects of the subjectivist interpretation of probability (also known as the 'personalist' view of probabilities) as initiated in earlier forensic and legal literature. It shows that operational devices to elicit subjective probabilities - in particular the so-called scoring rules - provide additional arguments in support of the standpoint according to which categorical claims of forensic individualisation do not follow from a formal analysis under that view of probability theory.