941 resultados para Statistical Power


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I agree with Costanza and Finkelstein (2015) that it is futile to further invest in the study of generational differences in the work context due to a lack of appropriate theory and methods. The key problem with the generations concept is that splitting continuous variables such as age or time into a few discrete units involves arbitrary cutoffs and atheoretical groupings of individuals (e.g., stating that all people born between the early 1960s and early 1980s belong to Generation X). As noted by methodologists, this procedure leads to a loss of information about individuals and reduced statistical power (MacCallum, Zhang, Preacher, & Rucker, 2002). Due to these conceptual and methodological limitations, I regard it as very difficult if not impossible to develop a “comprehensive theory of generations” (Costanza & Finkelstein, p. 20) and to rigorously examine generational differences at work in empirical studies.

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The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha−1 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.

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Strong statistical evidence was found for differences in tolerance to natural infections of Tobacco streak virus (TSV) in sunflower hybrids. Data from 470 plots involving 23 different sunflower hybrids tested in multiple trials over 5 years in Australia were analysed. Using a Bayesian Hierarchical Logistic Regression model for analysis provided: (i) a rigorous method for investigating the relative effects of hybrid, seasonal rainfall and proximity to inoculum source on the incidence of severe TSV disease; (ii) a natural method for estimating the probability distributions of disease incidence in different hybrids under historical rainfall conditions; and (iii) a method for undertaking all pairwise comparisons of disease incidence between hybrids whilst controlling the familywise error rate without any drastic reduction in statistical power. The tolerance identified in field trials was effective against the main TSV strain associated with disease outbreaks, TSV-parthenium. Glasshouse tests indicate this tolerance to also be effective against the other TSV strain found in central Queensland, TSV-crownbeard. The use of tolerant germplasm is critical to minimise the risk of TSV epidemics in sunflower in this region. We found strong statistical evidence that rainfall during the early growing months of March and April had a negative effect on the incidence of severe infection with greatly reduced disease incidence in years that had high rainfall during this period.

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Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

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O Carcinoma de Pulmão de Células Não Pequenas (NSCLC) é uma doença freqüentemente letal e altamente resistente à terapia oncológica convencional, como por exemplo, o tratamento quimioterápico com cisplatina e paclitaxel. A superexpressão de Ciclooxigenase-2 (COX-2) é constantemente observada em pacientes com NSCLC, estando associada ao prognóstico ruim destes pacientes. Acredita-se que a alta expressão de COX-2 produz efeitos anti-apoptóticos, porém pouco é conhecido sobre os mecanismos de regulação desta enzima. Muitos sinais capazes de ativar COX-2 também induzem a proteína supressora de tumor p53, conhecida pelo seu papel fundamental no controle da proliferação celular e apoptose. Dados recentes indicam que a proteína p53 é um importante regulador da expressão de COX-2. O objetivo desta dissertação foi avaliar os efeitos da quimioterapia na expressão da enzima COX-2 em linhagens celulares com diferente status do gene TP53, e ainda, correlacionar a expressão de COX-2 e o status mutacional de TP53, com as características clínico-patológicas de pacientes com NSCLC. Como ferramentas experimentais foram usadas técnicas de biologia celular e molecular como interferência de RNA, PCR em tempo real, análise mutacional e imuno-histoquímica. Com os resultados obtidos, observamos que as linhagens celulares de câncer de pulmão que apresentam p53 na sua forma selvagem, quando expostas ao tratamento com cisplatina, apresentaram indução da expressão de COX-2 (RNAm e proteína), em adição ao aumento da síntese de Prostaglandina E2 (PGE2). Em contrapartida, a expressão de COX-2 não foi alterada após o tratamento com cisplatina nas linhagens celulares que apresentavam mutação no gene TP53. Ao avaliar o tratamento com paclitaxel, foi observado um aumento da expressão de COX-2 nas linhagens A549 e H460 (linhagens celulares do tipo selvagem para p53), entretanto não foi observada alteração nos níveis de PGE2. Em adição, o tratamento com paclitaxel induziu um aumento da expressão de COX-2 na linhagem com deleção em TP53, ACC LC-319. Em seguida, após silenciamento de p53 na linhagem celular A549, por interferência de RNA, a cisplatina passou a não ser mais capaz de induzir o aumento da expressão de COX-2. No tratamento com paclitaxel, o silenciamento de TP53 não mudou a expressão de COX-2, indicando assim um efeito independente de p53. Dessa maneira, sugerimos que a indução de COX-2, por cisplatina, em linhagens celulares NSCLC é dependente de p53. Na análise dos pacientes NSCLC, os resultados demonstram que 54% dos pacientes apresentam expressão positiva de COX-2. Mutações em TP53 foram observadas em 57% dos pacientes, incluindo 56% de fumantes correntes e 37% de ex-fumantes. Uma associação entre a expressão de COX-2 e o status selvagem de TP53 foi observada, entre os pacientes que apresentaram expressão positiva de COX-2, 80% apresentaram TP53 selvagem. Um número maior de pacientes é necessário para aumentar o poder estatístico e confirmar as tendências observadas nesse estudo

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Using data collected simultaneously from a trawl and a hydrophone, we found that temporal and spatial trends in densities of juvenile Atlantic croaker (Micropogonias undulatus) in the Neuse River estuary in North Carolina can be identified by monitoring their sound production. Multivariate analysis of covariance (MA NCOVA) revealed that catch per unit of effort (CPUE) of Atlantic croaker had a significant relationship with the dependent variables of sound level and peak frequency of Atlantic croaker calls. Tests of between-subject correspondence failed to detect relationships between CPUE and either of the call parameters, but statistical power was low. Williamson’s index of spatial overlap indicated that call detection rate (expressed by a 0–3 calling index) was correlated in time and space with Atlantic croaker CPUE. The correspondence between acoustic parameters and trawl catch rates varied by month and by habitat. In general, the calling index had a higher degree of overlap with this species’ density than did the received sound level of their calls. Classification and regression tree analysis identified calling index as the strongest correlate of CPUE. Passive acoustics has the potential to be an inexpensive means of identifying spatial and temporal trends in abundance for soniferous fish species.

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Determining patterns of population connectivity is critical to the evaluation of marine reserves as recruitment sources for harvested populations. Mutton snapper (Lutjanus analis) is a good test case because the last known major spawning aggregation in U.S. waters was granted no-take status in the Tortugas South Ecological Reserve (TSER) in 2001. To evaluate the TSER population as a recruitment source, we genotyped mutton snapper from the Dry Tortugas, southeast Florida, and from three locations across the Caribbean at eight microsatellite loci. Both Fstatistics and individual-based Bayesian analyses indicated that genetic substructure was absent across the five populations. Genetic homogeneity of mutton snapper populations is consistent with its pelagic larval duration of 27 to 37 days and adult behavior of annual migrations to large spawning aggregations. Statistical power of future genetic assessments of mutton snapper population connectivity may benefit from more comprehensive geographic sampling, and perhaps from the development of less polymorphic DNA microsatellite loci. Research where alternative methods are used, such as the transgenerational marking of embryonic otoliths with barium stable isotopes, is also needed on this and other species with diverse life history characteristics to further evaluate the TSER as a recruitment source and to define corridors of population connectivity across the Caribbean and Florida.

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[ES] Las aguas residuales domésticas asociadas a los núcleos urbanos se encuentran entre los principales impactos antrópicos que amenazan la biodiversidad de los ecosistemas costeros. El presente trabajo tiene como objetivo evaluar el impacto de aguas residuales provenientes de la población de Bermeo sobre las comunidades intermareales de la parte mas externa de la Reserva de la Biosfera de Urdaibai. Para ello se ha contrastado la estructura de la vegetación bajo la influencia del emisario con la existente en cuatro localidades control en los años 2013 y 2014. Los resultados reflejan diferencias en la composición de la flora intermareal entre la localidad impactada y las localidades no afectadas por la contaminación. La localidad impactada queda caracterizada por la proliferación de algas filamentosas (Bachelotia antillarum) y clorófitos (Ulva intestinalis), así como de rodofíceas cespitosas con corticación simple (Gellidium pusillum, Gellidium pulchellum y Caulacanthus ustulatus). Por el contrario, en las localidades control son abundantes las especies perennes de gran porte y morfología compleja (Bifurcaria bifurcata, Cystoseira tamariscifolia, Halopteris spp. y Gelidium corneum). La calcárea Coralina elongata, estaba presente tanto en las localidades control como en la localidad impactada. Por otra parte, los análisis de la varianza realizados detectaron una elevada variabilidad espacio-temporal en la composición multivariable de la vegetación intermareal de las estaciones control, lo cual restó poder estadístico para detectar las diferencias entre la localidad impactada y los controles. Este resultado pone de manifiesto la dificultad e importancia de elegir controles apropiados para detectar impactos ambientales. Este estudio ha proporcionado la información necesaria sobre el estado ecológico de las comunidades en la situación pre-operacional de la EDAR de Lamiaran (Bermeo), lo cual permitirá evaluar en un futuro la eficacia del tratamiento de las aguas en términos de recuperación biológica.

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Perhaps the most difficult job of the ecotoxicologist is extrapolating data calculated from laboratory experiments with high precision and accuracy into the real world of highly-dynamics aquatic environments. The establishment of baseline laboratory toxicity testing data for individual compounds and ecologically important and field studies serve as a precursor to ecosystem level studies needed for ecological risk assessment. The first stage in the field portion of risk assessment is the determination of actual environmental concentrations of the contaminant being studied and matching those concentrations with laboratory toxicity tests. Risk estimates can be produced via risk quotients that would determine the probability that adverse effects may occur. In this first stage of risk assessment, environmental realism is often not achieved. This is due, in part, to the fact that single-species laboratory toxicity tests, while highly controlled, do not account for the complex interactions (Chemical, physical, and biological) that take place in the natural environment. By controlling as many variables in the laboratory as possible, an experiment can be produced in such a fashion that real effects from a compound can be determined for a particular test organism. This type of approach obviously makes comparison with real world data most difficult. Conversely, field oriented studies fall short in the interpretation of ecological risk assessment because of low statistical power, lack of adequate replicaiton, and the enormous amount of time and money needed to perform such studies. Unlike a controlled laboratory bioassay, many other stressors other than the chemical compound in question affect organisms in the environment. These stressors range from natural occurrences (such as changes in temperature, salinity, and community interactions) to other confounding anthropogenic inputs. Therefore, an improved aquatic toxicity test that will enhance environmental realism and increase the accuracy of future ecotoxicological risk assessments is needed.

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BACKGROUND:Blood lipid levels including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) are highly heritable. Genome-wide association is a promising approach to map genetic loci related to these heritable phenotypes.METHODS:In 1087 Framingham Heart Study Offspring cohort participants (mean age 47 years, 52% women), we conducted genome-wide analyses (Affymetrix 100K GeneChip) for fasting blood lipid traits. Total cholesterol, HDL-C, and TG were measured by standard enzymatic methods and LDL-C was calculated using the Friedewald formula. The long-term averages of up to seven measurements of LDL-C, HDL-C, and TG over a ~30 year span were the primary phenotypes. We used generalized estimating equations (GEE), family-based association tests (FBAT) and variance components linkage to investigate the relationships between SNPs (on autosomes, with minor allele frequency [greater than or equal to]10%, genotypic call rate [greater than or equal to]80%, and Hardy-Weinberg equilibrium p [greater than or equal to] 0.001) and multivariable-adjusted residuals. We pursued a three-stage replication strategy of the GEE association results with 287 SNPs (P < 0.001 in Stage I) tested in Stage II (n ~1450 individuals) and 40 SNPs (P < 0.001 in joint analysis of Stages I and II) tested in Stage III (n~6650 individuals).RESULTS:Long-term averages of LDL-C, HDL-C, and TG were highly heritable (h2 = 0.66, 0.69, 0.58, respectively; each P < 0.0001). Of 70,987 tests for each of the phenotypes, two SNPs had p < 10-5 in GEE results for LDL-C, four for HDL-C, and one for TG. For each multivariable-adjusted phenotype, the number of SNPs with association p < 10-4 ranged from 13 to 18 and with p < 10-3, from 94 to 149. Some results confirmed previously reported associations with candidate genes including variation in the lipoprotein lipase gene (LPL) and HDL-C and TG (rs7007797; P = 0.0005 for HDL-C and 0.002 for TG). The full set of GEE, FBAT and linkage results are posted at the database of Genotype and Phenotype (dbGaP). After three stages of replication, there was no convincing statistical evidence for association (i.e., combined P < 10-5 across all three stages) between any of the tested SNPs and lipid phenotypes.CONCLUSION:Using a 100K genome-wide scan, we have generated a set of putative associations for common sequence variants and lipid phenotypes. Validation of selected hypotheses in additional samples did not identify any new loci underlying variability in blood lipids. Lack of replication may be due to inadequate statistical power to detect modest quantitative trait locus effects (i.e., < 1% of trait variance explained) or reduced genomic coverage of the 100K array. GWAS in FHS using a denser genome-wide genotyping platform and a better-powered replication strategy may identify novel loci underlying blood lipids.

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Treatment regimens for solid tumours have been extensively investigated for their physical toxic effects, but far less is known about the potential impairment of cognitive function by anticancer treatment regimens. Here, we review published studies that examined cognitive function in adult patients receiving systemic therapy for solid tumours. Our review suggests that patients can experience cognitive changes related to their treatment. However, several studies had methodological limitations, such as use of a limited sample size, lack of baseline assessment, and lack of control for potential confounding factors. Better designed clinical trials are required so that the difficulties patients face in terms of reduced cognitive function as a result of anticancer treatment can be fully elucidated. These trials should have sufficient statistical power and, importantly, should also be prospective.

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Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

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Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.

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Evidence for climate-correlated low frequency variability of various components of marine ecosystems has accumulated rapidly over the past 2 decades. There has also been a growing recognition that society needs to learn how the fluctuations of these various components are linked, and to predict the likely amplitude and steepness of future changes. Demographic characteristics of marine zooplankton make them especially suitable for examining variability of marine ecosystems at interannual to decadal time scales. Their life cycle duration is short enough that there is little carryover of population membership from year to year, but long enough that variability can be tracked with monthly-to-seasonal sampling. Because zooplankton are rarely fished, comparative analysis of changes in their abundance can greatly enhance our ability to evaluate the importance of and interaction between physical environment, food web, and fishery harvest as causal mechanisms driving ecosystem level changes. A number of valuable within-region analyses of zooplankton time series have been published in the past decade, covering a variety of modes of variability including changes in total biomass, changes in size structure and species composition, changes in spatial distribution, and changes in seasonal timing. But because most zooplankton time series are relatively short compared to the time scales of interest, the statistical power of local analyses is often low, and between-region and between-variable comparisons are also needed. In this paper, we review the results of recent within- and between-region analyses, and suggest some priorities for future work.