997 resultados para Multiple-trip Bias
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Sphingomonas paucimobilis B90A is able to degrade the alpha-, beta-, gamma-, and delta-isomers of hexachlorocyclohexane (HCH). It contains the genes linA, linB, linC, linD, linE, and linR, which have been implicated in HCH degradation. In this study, dynamic expression of the lin genes was measured in chemostat-grown S. paucimobilis B90A by RNA dot blot hybridization and real-time reverse transcriptase PCR upon exposure to a pulse of different HCH isomers. Irrespective of the addition of HCH, linA, linB, and linC were all expressed constitutively. In contrast, linD and linE were induced with alpha-HCH (2 mg/liter) and gamma-HCH (7 mg/liter). A sharp increase in mRNA levels for linD and linE was observed from 10 to 45 min after the addition of alpha- or gamma-HCH. Induction of linD and linE was not detectable upon the addition of 0.7 mg of gamma-HCH per liter, although the compound was degraded by the cells. The addition of beta-HCH (5 mg/liter) or delta-HCH (20 mg/liter) did not lead to linE and linD induction, despite the fact that 50% of the compounds were degraded. This suggests that degradation of beta- and delta-HCH proceeds by a different pathway than that of alpha- and gamma-HCH.
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Peer-reviewed
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The ability to obtain gene expression profiles from human disease specimens provides an opportunity to identify relevant gene pathways, but is limited by the absence of data sets spanning a broad range of conditions. Here, we analyzed publicly available microarray data from 16 diverse skin conditions in order to gain insight into disease pathogenesis. Unsupervised hierarchical clustering separated samples by disease as well as common cellular and molecular pathways. Disease-specific signatures were leveraged to build a multi-disease classifier, which predicted the diagnosis of publicly and prospectively collected expression profiles with 93% accuracy. In one sample, the molecular classifier differed from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinical presentation evolved. Finally, integration of IFN-regulated gene programs with the skin database revealed a significant inverse correlation between IFN-β and IFN-γ programs across all conditions. Our study provides an integrative approach to the study of gene signatures from multiple skin conditions, elucidating mechanisms of disease pathogenesis. In addition, these studies provide a framework for developing tools for personalized medicine toward the precise prediction, prevention, and treatment of disease on an individual level.
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We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.
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Animals can compete for resources by displaying various acoustic signals that may differentially affect the outcome of competition. We propose the hypothesis that the most efficient signal to deter opponents should be the one that most honestly reveals motivation to compete. We tested this hypothesis in the barn owl (Tyto alba) in which nestlings produce more calls of longer duration than siblings to compete for priority access to the indivisible prey item their parents will deliver next. Because nestlings increase call rate to a larger extent than call duration when they become hungrier, call rate would signal more accurately hunger level. This leads us to propose three predictions. First, a high number of calls should be more efficient in deterring siblings to compete than long calls. Second, the rate at which an individual calls should be more sensitive to variation in the intensity of the sibling vocal competition than the duration of its calls. Third, call rate should influence competitors' vocalization for a longer period of time than call duration. To test these three predictions we performed playback experiments by broadcasting to singleton nestlings calls of varying durations and at different rates. According to the first prediction, singleton nestlings became less vocal to a larger extent when we broadcasted more calls compared to longer calls. In line with the second prediction, nestlings reduced vocalization rate to a larger extent than call duration when we broadcasted more or longer calls. Finally, call rate had a longer influence on opponent's vocal behavior than call duration. Young animals thus actively and differentially use multiple signaling components to compete with their siblings over parental resources.
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The objective of this work was to determine the efficiency of the Papadakis method on the quality evaluation of experiments with multiple-harvest oleraceous crops, and on the estimate of the covariate and the ideal plot size. Data from nine uniformity trials (five with bean pod, two with zucchini, and two with sweet pepper) and from one experiment with treatments (with sweet pepper) were used. Through the uniformity trials, the best way to calculate the covariate was defined and the optimal plot size was calculated. In the experiment with treatments, analyses of variance and covariance were performed, in which the covariate was calculated by the Papadakis method, and experimental precision was evaluated based on four statistics. The use of analysis of covariance with the covariate obtained by the Papadakis method increases the quality of experiments with multiple-harvest oleraceous crops and allows the use of smaller plot sizes. The best covariate is the one that considers a neighboring plot of each side of the reference plot.
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This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.
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PURPOSE: To investigate the mechanism(s) of resistance to the RAF-inhibitor vemurafenib, we conducted a comprehensive analysis of the genetic alterations occurring in metastatic lesions from a patient with a BRAF(V600E)-mutant cutaneous melanoma who, after a first response, underwent subsequent rechallenge with this drug. EXPERIMENTAL DESIGN: We obtained blood and tissue samples from a patient diagnosed with a BRAF(V600E)-mutant cutaneous melanoma that was treated with vemurafenib and achieved a near-complete response. At progression, he received additional lines of chemo/immunotherapy and was successfully rechallenged with vemurafenib. Exome and RNA sequencing were conducted on a pretreatment tumor and two subcutaneous resistant metastases, one that was present at baseline and previously responded to vemurafenib (PV1) and one that occurred de novo after reintroduction of the drug (PV2). A culture established from PV1 was also analyzed. RESULTS: We identified two NRAS-activating somatic mutations, Q61R and Q61K, affecting two main subpopulations in the metastasis PV1 and a BRAF alternative splicing, involving exons 4-10, in the metastasis PV2. These alterations, known to confer resistance to RAF inhibitors, were tumor-specific, mutually exclusive, and were not detected in pretreatment tumor samples. In addition, the oncogenic PIK3CA(H1047R) mutation was detected in a subpopulation of PV1, but this mutation did not seem to play a major role in vemurafenib resistance in this metastasis. CONCLUSIONS: This work describes the coexistence within the same patient of different molecular mechanisms of resistance to vemurafenib affecting different metastatic sites. These findings have direct implications for the clinical management of BRAF-mutant melanoma. Clin Cancer Res; 19(20); 5749-57. ©2013 AACR.
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BACKGROUND AND AIMS: Black cherry (Prunus serotina) is a North American tree that is rapidly invading European forests. This species was introduced first as an ornamental plant, then it was massively planted by foresters in many countries, but its origins and the process of invasion remain poorly documented. Based on a genetic survey of both native and invasive ranges, the invasion history of black cherry was investigated by identifying putative source populations and then assessing the importance of multiple introductions on the maintenance of gene diversity. METHODS: Genetic variability and structure of 23 populations from the invasive range and 22 populations from the native range were analysed using eight nuclear microsatellite loci and five chloroplast DNA regions. KEY RESULTS: Chloroplast DNA diversity suggests there were multiple introductions from a single geographic region (the north-eastern United States). A low reduction of genetic diversity was observed in the invasive range for both nuclear and plastid genomes. High propagule pressure including both the size and number of introductions shaped the genetic structure in Europe and boosted genetic diversity. Populations from Denmark, The Netherlands, Belgium and Germany showed high genetic diversity and low differentiation among populations, supporting the hypothesis that numerous introduction events, including multiple individuals and exchanges between sites, have taken place during two centuries of plantation. CONCLUSIONS: This study postulates that the invasive black cherry has originated from east of the Appalachian Mountains (mainly the Allegheny plateau) and its invasiveness in north-western Europe is mainly due to multiple introductions containing high numbers of individuals.
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Reproductive division of labor and the coexistence of distinct castes are hallmarks of insect societies. In social insect species with multiple queens per colony, the fitness of nestmate queens directly depends on the process of caste allocation (i.e., the relative investment in queen, sterile worker and male production). The aim of this study is to investigate the genetic components to the process of caste allocation in a multiple-queen ant species. We conducted controlled crosses in the Argentine ant Linepithema humile and established single-queen colonies to identify maternal and paternal family effects on the relative production of new queens, workers, and males. There were significant effects of parental genetic backgrounds on various aspects of caste allocation: the paternal lineage affected the proportion of queens and workers produced whereas the proportions of queens and males, and females and males were influenced by the interaction between parental lineages. In addition to revealing nonadditive genetic effects on female caste determination in a multiple-queen ant species, this study reveals strong genetic compatibility effects between parental genomes on caste allocation components.
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OBJECTIVE: The aim of this study was to conduct a statistical analysis to determine the outcome of conservative treatment after delivery of a first fetus in multiple pregnancy and thus define new prognostic factors. STUDY DESIGN: Multicentre retrospective study involving 12 centers over a 10-year period. RESULTS: Twenty-eight twin pregnancies and seven triplet pregnancies which were managed conservatively. In twin pregnancies, 79% of the delayed-delivery fetuses survived; only 7% of the first delivered fetuses survived. The mean interval between deliveries was 47 days. No statistical difference was found concerning cerclage, antibiotic therapy, tocolysis and hospitalization. Earlier delivery of the first twin and premature rupture of membranes for the second twin were significantly related to a longer interval between deliveries. CONCLUSION: Delayed delivery in multifetal pregnancies can be successful if there are no contraindications and these pregnancies are managed in a tertiary perinatal center. Publications limited to successful cases have undoubtedly introduced some bias in assessment.
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An experiment was carried out to examine the impact on electrodermal activity of people when approached by groups of one or four virtual characters at varying distances. It was premised on the basis of proxemics theory that the closer the approach of the virtual characters to the participant, the greater the level of physiological arousal. Physiological arousal was measured by the number of skin conductance responses within a short time period after the approach, and the maximum change in skin conductance level 5 s after the approach. The virtual characters were each either female or a cylinder of human size, and one or four characters approached each subject a total of 12 times. Twelve male subjects were recruited for the experiment. The results suggest that the number of skin conductance responses after the approach and the change in skin conductance level increased the closer the virtual characters approached toward the participants. Moreover, these response variables were inversely correlated with the number of visits, showing a typical adaptation effect. There was some evidence to suggest that the number of characters who simultaneously approached (one or four) was positively associated with the responses. Surprisingly there was no evidence of a difference in response between the humanoid characters and cylinders on the basis of this physiological data. It is suggested that the similarity in this quantitative arousal response to virtual characters and virtual objects might mask a profound difference in qualitative response, an interpretation supported by questionnaire and interview results. Overall the experiment supported the premise that people exhibit heightened physiological arousal the closer they are approached by virtual characters.
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BACKGROUND: Selective publication of studies, which is commonly called publication bias, is widely recognized. Over the years a new nomenclature for other types of bias related to non-publication or distortion related to the dissemination of research findings has been developed. However, several of these different biases are often still summarized by the term 'publication bias'. METHODS/DESIGN: As part of the OPEN Project (To Overcome failure to Publish nEgative fiNdings) we will conduct a systematic review with the following objectives:- To systematically review highly cited articles that focus on non-publication of studies and to present the various definitions of biases related to the dissemination of research findings contained in the articles identified.- To develop and discuss a new framework on nomenclature of various aspects of distortion in the dissemination process that leads to public availability of research findings in an international group of experts in the context of the OPEN Project.We will systematically search Web of Knowledge for highly cited articles that provide a definition of biases related to the dissemination of research findings. A specifically designed data extraction form will be developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article.For the development of a new framework we will construct an initial table listing different levels and different hazards en route to making research findings public. An international group of experts will iteratively review the table and reflect on its content until no new insights emerge and consensus has been reached. DISCUSSION: Results are expected to be publicly available in mid-2013. This systematic review together with the results of other systematic reviews of the OPEN project will serve as a basis for the development of future policies and guidelines regarding the assessment and prevention of publication bias.