Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.

Telomere length is a quantitative trait important for many cellular functions. Failure to regulate telomere length contributes to genomic instability, cellular senescence, cancer, and apoptosis in humans, but the functional significance of telomere regulation in plants is much less well understood. To gain a better understanding of telomere biology in plants, we used quantitative trait locus (QTL) mapping to identify genetic elements that control telomere length variation in maize (Zea mays L.). For this purpose, we measured the median and mean telomere lengths from 178 recombinant inbred lines of the IBM mapping population and found multiple regions that collectively accounted for 33–38% of the variation in telomere length. Two-way analysis of variance revealed interaction between the quantitative trait loci at genetic bin positions 2.09 and 5.04. Candidate genes within these and other significant QTL intervals, along with select genes known a priori to regulate telomere length, were tested for correlations between expression levels and telomere length in the IBM population and diverse inbred lines by quantitative real-time PCR. A slight but significant positive correlation between expression levels and telomere length was observed for many of the candidate genes...

Prognosis and therapeutic management of dogs with cutaneous mast cell tumors (MCTs) depend on clinical stage and histological grade. However, the prognostic value of this latter is still questionable. In the present study, MCT transcriptome was analyzed to identify a set of candidate genes potentially useful for predicting the biological behavior of MCTs. Fifty-one canine MCT biopsies were analyzed. Isolated and purified total RNAs were individually hybridized to the Agilent Canine V2 4x44k DNA microarray. The comparison of reference differentiated and undifferentiated MCT transcriptome revealed a total of 597 differentially expressed genes (147 down-regulated and 450 up-regulated). The functional analysis of this set of genes provided evidence that they were mainly involved in cell cycle, DNA replication, p53 signaling pathway, nucleotide excision repair and pyrimidine metabolism. Class prediction analysis identified 13 transcripts providing the greatest accuracy of class prediction and divided samples into two categories (differentiated and undifferentiated), harboring a different prognosis. The Principal Component Analysis of all samples, made by using the selected 13 markers, confirmed MCT classification. The first three components accounted for 99.924% of the total variance. This molecular classification significantly correlated with survival time (p = 0.0026). Furthermore...

While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods – SKAT and a previously proposed method based on functional linear models (FLM)...

[Purpose] The purpose of this study was to understand factors present at baseline that affect outcome and healthcare utilization post-stroke. We investigated the association between the Charlson Comorbidity Index (CCI) score and functional outcome (length of stay) after hemorrhagic and ischemic stroke. [Subjects and Methods] Data from the Korean National Hospital Discharge In-depth Injury Survey for 6 years, from 2005 to 2010, were used. The t-test and analysis of variance were carried out to compare average differences in the length of stay with the general characteristics in accordance with CCI. Multiple regression analysis was carried out using dummy variables to look at factors affecting stroke patients’ length of stay. [Results] Independent variables with significant relationships with the log-transformed length of stay included gender, type of insurance, the size of city of residence, the number of beds in the hospital, the location of the medical institution, hospitalization path, receipt of physical therapy, treatment involving brain surgery, death, the type of stroke, and CCI. [Conclusion] The results of the present study suggests that CCI independently influences the length of stay after ischemic and hemorrhagic stroke and that variables with significant relationships with the log-transformed length of stay need to be continuously managed.

Plant growth analysis presents difficulties related to statistical comparison of growth rates, and the analysis of variance of primary data could guide the interpretation of results. The objective of this work was to evaluate the analysis of variance of data from distinct harvests of an experiment, focusing especially on the homogeneity of variances and the choice of an adequate ANOVA model. Data from five experiments covering different crops and growth conditions were used. From the total number of variables, 19% were originally homoscedastic, 60% became homoscedastic after logarithmic transformation, and 21% remained heteroscedastic after transformation. Data transformation did not affect the F test in one experiment, whereas in the other experiments transformation modified the F test usually reducing the number of significant effects. Even when transformation has not altered the F test, mean comparisons led to divergent interpretations. The mixed ANOVA model, considering harvest as a random effect, reduced the number of significant effects of every factor which had the F test modified by this model. Examples illustrated that analysis of variance of primary variables provides a tool for identifying significant differences in growth rates. The analysis of variance imposes restrictions to experimental design thereby eliminating some advantages of the functional growth analysis.; 2003

This paper reports on changes in mandibular condylar growth in sheep fitted with experimental functional appliances. The paper also addresses the similarities of mandibular condylar growth in sheep and humans. Experimental functional appliances were developed, constructed and applied to four, four-month old, male sheep. Another four sheep served as matched controls. All animals received fluorochrome bone labels during the study and their weight gain also was recorded. Fifteen weeks later, all animals were sacrificed and each temporo-mandibular joint and left metacarpus were removed. Undecalcified mid-sagittal sections of the joint and metacarpus were prepared for fluorescence microscopy. The mandibular condylar growth vector in sheep was found to be in a postero-superior direction. Condylar growth in the control sheep during the experimental period varied from 8.8 to 11.9 mm, with the mean being 10.6 mm, which is quantitatively similar to two years of condylar growth in human adolescents. In the experimental sheep, the condylar growth varied from 8.5 to 13.3 mm, with the mean being 11.4 mm. When metacarpal growth and weight gain were taken into consideration using multivariant analysis, the coefficients for growth in the postero-superior and posterior direction were found to be high...

Purpose: Organic cation transporter-1 (OCT-1) activity (OA), a measure of the OCT-1–mediated influx of imatinib into CML mononuclear cells (MNCs), is predictive of major molecular response (MMR) at 12 and 24 months in patients with untreated CML. We now report the impact of OA on loss of response, disease transformation, and survival after 5 years of imatinib. Patients and Methods: OA is defined as the difference in intracellular concentration of carbon-14–imatinib with and without OCT-1 inhibition. OA was measured in blood from 56 patients with untreated chronic-phase CML. Results: More patients who had high OA (ie, > median OA value) achieved MMR by 60 months compared with patients who had low OA (89% v 55%; P = .007). A low OA was associated with a significantly lower overall survival (87% v 96%; P = .028) and event-free survival (EFS; 48% v 74%; P = .03) as well as a higher kinase domain mutation rate (21% v 4%; P = .047). These differences were highly significant in patients who averaged less than 600 mg/d of imatinib in the first 12 months but were not significant in patients averaging ≥ 600 mg/d. Patients with very low OA (ie, quartile 1) were the only group who developed leukemic transformation (21% in quartile 1 v 0% in all other quartiles; P = .002). Conclusion: Measurement of OA pretherapy is a predictor for the long-term risk of resistance and transformation in patients with imatinib-treated CML. Early dose-intensity may reduce the negative prognostic impact of low OA. We propose that OA could be used to individualize dosage strategies for patients with CML to maximize molecular response and optimize long-term outcome.; Deborah L. White...

[Abstract] Background: Pairwise association between neurons is a key feature in understanding neural coding. Statistical neuroscience provides tools to estimate and assess these associations. In the mammalian brain, activating ascending pathways arise from neuronal nuclei located at the brainstem and at the basal forebrain that regulate the transition between sleep and awake neuronal firing modes in extensive regions of the cerebral cortex, including the primary visual cortex, where neurons are known to be selective for the orientation of a given stimulus. In this paper, the estimation of neural synchrony as a function of time is studied in data obtained from anesthetized cats. A functional data analysis of variance model is proposed. Bootstrap statistical tests are introduced in this context; they are useful tools for the study of differences in synchrony strength regarding 1) transition between different states (anesthesia and awake), and 2) affinity given by orientation selectivity. Results: An analysis of variance model for functional data is proposed for neural synchrony curves, estimated with a cross-correlation based method. Dependence arising from the experimental setting needs to be accounted for. Bootstrap tests allow the identification of differences between experimental conditions (modes of activity) and between pairs of neurons formed by cells with different affinities given by their preferred orientations. In our test case...

A number of mucopolysaccharidosis type VII (MPS VII) mouse models with different levels of residual enzyme activity have been created replicating the range of clinical phenotypes observed in human MPS VII patients. In this study, a lentivirus encoding murine β-glucuronidase was administered intravenously at birth to both the severe (Gus(mps/mps) strain) and attenuated (Gus(tm(L175F)Sly) strain) mouse models of MPS VII. Circulating enzyme levels were normalized in the Gus(mps/mps) mice and were 3.5-fold higher than normal in the Gus(tm(L175F)Sly) mouse 12 and 18 months after administration. Tissue β-glucuronidase activity increased over untreated levels in all tissues evaluated in both strains at 12 months, and the elevated level was maintained in Gus(tm(L175F)Sly) tissues at 18 months. These elevated enzyme levels reduced glycosaminoglycan storage in the liver, spleen, kidney, and heart in both models. Bone mineral volume decreased toward normal in both models after 12 months of therapy and after 18 months in the Gus(tm(L175F)Sly) mouse. Open-field exploration was improved in 18-month-old treated Gus(tm(L175F)Sly) mice, while spatial learning improved in both 12- and 18-month-old treated Gus(tm(L175F)Sly) mice. Overall, neonatal administration of lentiviral gene therapy resulted in sustained enzyme expression for up to 18 months in murine models of MPS VII. Significant improvements in biochemistry and enzymology as well as functional improvement of bone and behavior deficits in the Gus(tm(L175F)Sly) model were observed. Therapy significantly increased the lifespan of Gus(mps/mps) mice...

BACKGROUND MicroRNAs (miRNAs) are small non-coding RNAs that regulate complex transcriptional networks underpin immune responses. However, little is known about the specific miRNA networks that control differentiation of specific leukocyte subsets. In this study, we profiled miRNA expression during differentiation of eosinophils from bone marrow (BM) progenitors (bmEos), and correlated expression with potential mRNA targets involved in crucial regulatory functions. Profiling was performed on whole BM cultures to document the dynamic changes in miRNA expression in the BM microenvironment over the differentiation period. miRNA for network analysis were identified in BM cultures enriched in differentiating eosinophils, and chosen for their potential ability to target mRNA of factors that are known to play critical roles in eosinophil differentiation pathways or cell identify. METHODOLOGY/PRINCIPAL FINDINGS We identified 68 miRNAs with expression patterns that were up- or down- regulated 5-fold or more during bmEos differentiation. By employing TargetScan and MeSH databases, we identified 348 transcripts involved in 30 canonical pathways as potentially regulated by these miRNAs. Furthermore, by applying miRanda and Ingenuity Pathways Analysis (IPA)...

Apesar da importância que as trepadeiras apresentam em florestas tropicais, estudos sobre a montagem da comunidade de lianas (trepadeiras lenhosas e sublenhosas) que investiguem desde a contribuição dos fatores abióticos e bióticos até fatores intrínsecos (coexistência entre indivíduos) são escassos. O objetivo geral desta tese é pesquisar a estruturação da comunidade das espécies de lianas em uma Floresta Estacional Semidecídua (FES), investigando (1) a importância relativa dos fatores ambientais e espaciais para diferentes espécies de lianas, (2) a estruturação filogenética da comunidade de trepadeiras em diferentes ambientes, e (3) os efeitos diretos ou mediados das árvores e arbustos para o número de espécies e indivíduos de trepadeiras. Mostramos que (1) grande parte da variação na composição de espécies de lianas em uma FES é devido a fatores não investigados (fatores estocásticos) e o espaço (autocorrelação espacial). Portanto, concluímos que os maiores determinantes na variação da composição de espécies de lianas em uma FES é a aleatoriedade (sendo reflexo da variação estocástica das populações) e a limitação por dispersão (demonstrada pela alta autocorrelação espacial). No segundo capítulo (2)...

OBJECTIVE: To correlate functional ability and quality of life of elderly women with knee osteoarthritis. METHODS: Cross-sectional study composed of 40 elderly women with knee osteoarthritis. We used the following instruments: identification questionnaire, Western Ontario and McMaster Universities Arthritis Index (WOMAC), and World Health Organization Quality of Life Questionnaire-OLD (WHOQOL-OLD). The significance level was 0.05 (5%), and confidence intervals were 95%. For statistical analysis we used parametric statistical tests, descriptive analysis, test for equality of two proportions, Pearson's correlation, correlation test, and analysis of variance. RESULTS: The mean age (± standard deviation) was 74.1 (±6.7) years, and 47.5% of patients had osteoarthritis in both knees. Moderate pain was reported by 45% of patients when they walked on a flat plane and 40% when they were seated or lying down; 55% had severe or very severe pain when climbing or descending stairs; 50% reported moderate joint stiffness after sitting, lying, or resting; and 65% reported moderate or little stiffness after waking. In physical function, 60% of patients had moderate or severe difficulty in descending stairs and 67.5%, when climbing stairs; 60% reported severe or very severe difficulty in getting in and out of the car...

This paper presents new results on Functional Analysis of Variance for fixed effect models with correlated Hilbert-valued Gaussian error components. The geometry of the Reproducing Kernel Hilbert Space (RKHS) of the error term is considered in the computation of the total sum of squares, the residual sum of squares, and the sum of squares due to the regression. Under suitable linear transformation of the correlated functional data, the distributional characteristics of these statistics, their moment generating and characteristic functions, are derived. Fixed effect linear hypothesis testing is finally formulated in the Hilbert-valued multivariate Gaussian context considered.

In several modern applications, ranging from genetics to genomics and neuroimaging, there is a need to compare observations across different populations, such as groups of healthy and diseased individuals. The interest is in detecting a group effect. When the observations are vectorial, real-valued and follow a multivariate Normal distribution, multivariate analysis of variance (MANOVA) tests are routinely applied. However, such traditional procedures are not suitable when dealing with more complex data structures such as functional (e.g. curves) or graph-structured (e.g. trees and networks) objects, where the required distributional assumptions may be violated. In this paper we discuss a distance-based MANOVA-like approach, the DBF test, for detecting differences between groups for a wider range of data types. The test statistic, analogously to other distance-based statistics, only relies on a suitably chosen distance measure that captures the pairwise dissimilarity among all available samples. An approximate null probability distribution of the DBF statistic is proposed thus allowing inferences to be drawn without the need for costly permutation procedures. Through extensive simulations we provide evidence that the proposed methodology works well for a range of data types and distances...

This article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time-warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability. The focus is on single-random-factor models but the approach can be easily generalized to more complex ANOVA models. The behavior of the estimators is studied by simulation, and an application to the analysis of growth curves of flour beetles is presented. Although the model assumes a smooth latent process behind the observed trajectories, smoothness of the observed data is not required; the method can be applied to the sparsely observed data that is often encountered in longitudinal studies.

Kaminski, Thomas W.; Context: More than 7 million students are involved in high school sports annually in the United States. Disturbances in postures as result of fatigue have been postulated to effect male and female interscholastic athletes differently. It is important that this population be studied, and the mechanism by which these injuries are produced be determined. Objective: The purpose of this study was to determine the effects gender and fatigue have on postural control in a group of healthy high school athletes as measured by modified version of the Star Excursion Balance Test (SEBT). Design: Within groups, pre-test/post-test study. Setting: A climate controlled, research center. Participants: A total of 30 healthy varsity high school athletes, 15 male (age= 17.1±1yrs; height=175.8cm±9.2; mass=70.1±8.5kg) and 15 female (age= 16.4±1; height=166cm±8.2; mass=60.6±7kg) participated in this study. Interventions: The subject’s dynamic postural control was tested using the modified SEBT before and after completing a functional fatigue protocol. Main Outcome Measures: The normalized component reach directions including anterior (ANT), posteromedial (PM), and posterolateral (PL) and the composite reach distance scores for both the right and left side were used as dependant measures for analysis in this study. A univariate...

Lee, Jong-Soo; Cervical cancer has been one of the most common cancers among women, especially in the developing countries. Our research group has built a new medical device which uses fluorescence spectroscopy for early detection of cervical cancer. The output of the device belongs to the functional data. My role in the project is to determine if the factor of room light is statistically significant using the data setting from the experiment. It is impossible to use traditional statistical method for large functional data because the number of dimensions is much larger than the number of observations. The thesis comes up with some ideas of dimension reduction techniques including PCA and EDA. Based upon the thoughts of Adaptively Truncated Hotelling T-Square Test, this thesis extends the method to more than two groups which we call it Adaptively Truncated MANOVA. Simulations are made on the three test statistics of Adaptively Truncated MANOVA. However, whether we can apply the Adaptively Truncated MANOVA to the real data still needs more work in the future.; University of Delaware, Department of Statistics; M.S.

OBJETIVO: Traduzir para o português e validar o questionário de qualidade de vida Functional Assessment of Cancer Therapy - Bone Marrow Transplantation (FACT-BMT) em pacientes transplantados de medula óssea. OBJETIVO: O estudo foi realizado em Ribeirão Preto, SP, em 2005. O FACT-BMT (versão 3) traduzido e a versão em português do Short Form-36 Health Survey (SF-36) foram aplicados simultaneamente em 55 pacientes consecutivos com leucemia, submetidos ao transplante e em seguimento. Dois parâmetros clínicos foram utilizados para testar a sensibilidade do questionário: tempo decorrido do transplante e presença ou não de doença do enxerto contra o hospedeiro. Foi utilizada a análise de variância (ANOVA) com o teste post hoc de Tukey. Aplicou-se o coeficiente alfa de Cronbach, padronizado para todas as questões, escore final e domínios. RESULTADOS: A média de idade dos pacientes foi 34,8±8,1 anos, com escolaridade média de 10,8±4,7 anos, sendo 78,1% do sexo feminino. A duração média de tempo pós-transplante foi de 29,8±32,19 meses. Nenhuma alteração do formato original do questionário foi observada no final do processo de tradução e adaptação cultural. A consistência interna foi alta (0...

O envelhecimento é um processo progressivo e natural e a atividade física vem sendo apontada como uma possibilidade de minimizar o seu impacto e, especialmente, manter a capacidade funcional do idoso por mais tempo. O objetivo do presente estudo foi analisar as modificações do Índice de Aptidão Funcional Geral (IAFG) de idosos participan-tes de um programa de atividades físicas no decorrer de 10 meses, associando aos diferentes estratos etários, tempo de participação no programa e modificações nas capacidades físicas avaliadas. O estudo foi realizado com 225 idosos, média de idade de 69,26 anos (dp=5,685), participantes do programa de Atividade Física e Dança Folclórica para a Terceira Idade do Centro de Desportes/Universidade Federal de Santa Catarina. Para a análise dos dados foi utilizada a estatística descritiva, o teste t de Student e análise de variância (ANOVA). De março a dezembro de 2005, verificou-se diferença estatisticamente significante (p< 0,01) do IAFG e nas variáveis agilidade/equilíbrio e coordenação (p< 0,01). As capacidades físicas força (p=0,323), resistência (p= 0,946) e flexibilidade (p=0,722) não tiveram diferença sig-nificante no período analisado. Verificou-se também que o grupo que praticava atividades físicas há mais de 10 anos e com faixa etária acima de 80 anos de idade...