932 resultados para combinatorial protocol in multiple linear regressions


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The emergence of mass spectrometry-based proteomics has revolutionized the study of proteins and their abundances, functions, interactions, and modifications. However, in a multicellular organism, it is difficult to monitor dynamic changes in protein synthesis in a specific cell type within its native environment. In this thesis, we describe methods that enable the metabolic labeling, purification, and analysis of proteins in specific cell types and during defined periods in live animals. We first engineered a eukaryotic phenylalanyl-tRNA synthetase (PheRS) to selectively recognize the unnatural L-phenylalanine analog p-azido-L-phenylalanine (Azf). Using Caenorhabditis elegans, we expressed the engineered PheRS in a cell type of choice (i.e. body wall muscles, intestinal epithelial cells, neurons, pharyngeal muscles), permitting proteins in those cells -- and only those cells -- to be labeled with azides. Labeled proteins are therefore subject to "click" conjugation to cyclooctyne-functionalized affnity probes, separation from the rest of the protein pool and identification by mass spectrometry. By coupling our methodology with heavy isotopic labeling, we successfully identified proteins -- including proteins with previously unknown expression patterns -- expressed in targeted subsets of cells. While cell types like body wall or pharyngeal muscles can be targeted with a single promoter, many cells cannot; spatiotemporal selectivity typically results from the combinatorial action of multiple regulators. To enhance spatiotemporal selectivity, we next developed a two-component system to drive overlapping -- but not identical -- patterns of expression of engineered PheRS, restricting labeling to cells that express both elements. Specifically, we developed a split-intein-based split-PheRS system for highly efficient PheRS-reconstitution through protein splicing. Together, these tools represent a powerful approach for unbiased discovery of proteins uniquely expressed in a subset of cells at specific developmental stages.

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The purpose of the study was to determine the degree of relationships among GRE scores, undergraduate GPA (UGPA), and success in graduate school, as measured by first year graduate GPA (FGPA), cumulative graduate GPA, and degree attainment status. A second aim of the study was to determine whether the relationships between the composite predictor (GRE scores and UGPA) and the three success measures differed by race/ethnicity and sex. A total of 7,367 graduate student records (masters, 5,990; doctoral: 1,377) from 2000 to 2010 were used to evaluate the relationships among GRE scores, UGPA and the three success measures. Pearson’s correlation, multiple linear and logistic regression, and hierarchical multiple linear and logistic regression analyses were performed to answer the research questions. The results of the correlational analyses differed by degree level. For master’s students, the ETS proposed prediction that GRE scores are valid predictors of first year graduate GPA was supported by the findings from the present study; however, for doctoral students, the proposed prediction was only partially supported. Regression and correlational analyses indicated that UGPA was the variable that consistently predicted all three success measures for both degree levels. The hierarchical multiple linear and logistic regression analyses indicated that at master’s degree level, White students with higher GRE Quantitative Reasoning Test scores were more likely to attain a degree than Asian Americans, while International students with higher UGPA were more likely to attain a degree than White students. The relationships between the three predictors and the three success measures were not significantly different between men and women for either degree level. Findings have implications both for practice and research. They will provide graduate school administrators with institution-specific validity data for UGPA and the GRE scores, which can be referenced in making admission decisions, while they will provide empirical and professionally defensible evidence to support the current practice of using UGPA and GRE scores for admission considerations. In addition, new evidence relating to differential predictions will be useful as a resource reference for future GRE validation researchers.

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The high cost of maize in Kenya is basically driven by East African regional commodity demand forces and agricultural drought. The production of maize, which is a common staple food in Kenya, is greatly affected by agricultural drought. However, calculations of drought risk and impact on maize production in Kenya is limited by the scarcity of reliable rainfall data. The objective of this study was to apply a novel hyperspectral remote sensing method to modelling temporal fluctuations of maize production and prices in five markets in Kenya. SPOT-VEGETATION NDVI time series were corrected for seasonal effects by computing the standardized NDVI anomalies. The maize residual price time series was further related to the NDVI seasonal anomalies using a multiple linear regression modelling approach. The result shows a moderately strong positive relationship (0.67) between residual price series and global maize prices. Maize prices were high during drought periods (i.e. negative NDVI anomalies) and low during wet seasons (i.e. positive NDVI anomalies). This study concludes that NDVI is a good index for monitoring the evolution of maize prices and food security emergency planning in Kenya. To obtain a very strong correlation for the relationship between the wholesale maize price and the global maize price, future research could consider adding other price-driving factors into the regression models.

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Este estudio de caso busca identificar los elementos del portafolio de política exterior de Trinidad y Tobago que le permitieron promover exitosamente sus intereses en el Protocolo de Kioto. Al hacer esto, este texto analizará las limitaciones de Trinidad y Tobago en términos de vulnerabilidades de localización, burocracia y recursos. Posteriormente, una revisión del portafolio de política exterior de este Estado ilustrará el uso de estrategias de creación de capacidades y de organización como lo son el contacto con actores institucionales y no gubernamentales, la formación de coaliciones y estrategias argumentativas, entre otras. Finalmente, este artículo concluirá que dichas acciones permitieron la promoción de la agenda de política exterior de Trinidad y Tobago a través de la creación de hojas de ruta y la coordinación de la incertidumbre con el Protocolo de Kioto. Para hacer esto, este trabajo se concentrará en examinar conceptos como vulnerabilidad y priorización, asimismo contrastando diferentes artículos académicos en la materia junto con documentos oficiales de Trinidad y Tobago.

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We analysed the viscera of 534 moles (Ta l p a spp.) from 30 of the 47 provinces of peninsular Spain, including 255 individuals of T. europaea from eight provinces, 154 individuals of T. occidentalis from 20 provinces, and 125 unidentified Ta l p a individuals from two provinces. We identified their helminth parasites and determined parasite species richness. We related parasite species richness with sampling effort using both a linear and a logarithmic function. We then performed stepwise linear regressions to predict mole parasite species richness from a small set of selected predictor variables that included sampling effort. We applied the resulting models to forecast T. euro p a e a, T. occidentalis, and Ta l p a spp. parasite species richness in all provinces with recorded host presence, assuming different levels of sampling eff o r t . F i n a l l y, we used partial regression analysis to partition the variation explained by each of the selected variables in the models. We found that mole parasite species richness is strongly conditioned by sampling effort, but that other factors such as cropland area and environmental disturbance have significant independent effects.

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Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

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Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

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The present study extends previous findings by examining whether defense styles, selfobject needs, attachment styles relate to Neediness and Self-Criticism, as maladaptive personality dimensions focused, respectively, on relatedness and self-definition in an Iranian sample. Three hundred and fifty two participants completed a socio-demographic questionnaire as well as the Persian forms of the Depressive Experiences Questionnaire, Experience of Close Relationships-Revised, Defense Style Questionnaire, Beck Depression Inventory–II and Selfobject Needs Inventory. Two Multiple Linear Regression Analyses, entering Self-criticism and Neediness as criterion variables, were computed. According to the results high Attachment anxiety, high Immature defenses, high depressive symptoms, and high need for idealization were related to self-criticism, and explained 47% of its variance. In addition, high attachment anxiety, low mature defenses, high neurotic defenses, high avoidance of mirroring, and low avoidance of idealization/twinship were related to neediness, and explained 40% of its variance. A Principal Component Analysis was performed, entering all the studied variables. Three factors emerged; one describing a maladaptive form of psychological functioning and two describing more mature modes of psychological functioning. The results are discussed in their implications for the understanding of neediness and self-criticism as maladaptive personality dimensions focused, respectively, on relatedness and self-definition.

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The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga

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Adipokines are hormones produced by adipocytes and have been involved in multiple pathologic pathways, including inflammatory and cardiovascular complications in essential hypertension. Arterial stiffness is a frequent vascular complication that represents increased cardiovascular risk in hypertensive patients. Adipokines, such as adiponectin, leptin and resistin, might be implicated in hypertension, as well as in vascular alterations associated with this condition. Arterial stiffness has proven to be a predictor of cardiovascular events. Obesity and target-organ damage such as arterial stiffness are features associated with hypertension. This review aims to update the association between adipokines and arterial stiffness in essential and resistant hypertension (RHTN).

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The efficacy of the human papillomavirus type 16 (HPV-16)/HPV-18 AS04-adjuvanted vaccine against cervical infections with HPV in the Papilloma Trial against Cancer in Young Adults (PATRICIA) was evaluated using a combination of the broad-spectrum L1-based SPF10 PCR-DNA enzyme immunoassay (DEIA)/line probe assay (LiPA25) system with type-specific PCRs for HPV-16 and -18. Broad-spectrum PCR assays may underestimate the presence of HPV genotypes present at relatively low concentrations in multiple infections, due to competition between genotypes. Therefore, samples were retrospectively reanalyzed using a testing algorithm incorporating the SPF10 PCR-DEIA/LiPA25 plus a novel E6-based multiplex type-specific PCR and reverse hybridization assay (MPTS12 RHA), which permits detection of a panel of nine oncogenic HPV genotypes (types 16, 18, 31, 33, 35, 45, 52, 58, and 59). For the vaccine against HPV types 16 and 18, there was no major impact on estimates of vaccine efficacy (VE) for incident or 6-month or 12-month persistent infections when the MPTS12 RHA was included in the testing algorithm versus estimates with the protocol-specified algorithm. However, the alternative testing algorithm showed greater sensitivity than the protocol-specified algorithm for detection of some nonvaccine oncogenic HPV types. More cases were gained in the control group than in the vaccine group, leading to higher point estimates of VE for 6-month and 12-month persistent infections for the nonvaccine oncogenic types included in the MPTS12 RHA assay (types 31, 33, 35, 45, 52, 58, and 59). This post hoc analysis indicates that the per-protocol testing algorithm used in PATRICIA underestimated the VE against some nonvaccine oncogenic HPV types and that the choice of the HPV DNA testing methodology is important for the evaluation of VE in clinical trials. (This study has been registered at ClinicalTrials.gov under registration no. NCT00122681.).

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The pathological mechanisms underlying cognitive dysfunction in multiple sclerosis (MS) are not yet fully understood and, in addition to demyelinating lesions and gray-matter atrophy, subclinical disease activity may play a role. To evaluate the contribution of asymptomatic gadolinium-enhancing lesions to cognitive dysfunction along with gray-matter damage and callosal atrophy in relapsing-remitting MS (RRMS) patients. Forty-two treated RRMS and 30 controls were evaluated. MRI (3T) variables of interest were brain white-matter and cortical lesion load, cortical and deep gray-matter volumes, corpus callosum volume and presence of gadolinium-enhancing lesions. Outcome variables included EDSS, MS Functional Composite (MSFC) subtests and the Brief Repeatable Battery of Neuropsychological tests. Cognitive dysfunction was classified as deficits in two or more cognitive subtests. Multivariate regression analyses assessed the contribution of MRI metrics to outcomes. Patients with cognitive impairment (45.2%) had more cortical lesions and lower gray-matter and callosal volumes. Patients with subclinical MRI activity (15%) had worse cognitive performance. Clinical disability on MSFC was mainly associated with putaminal atrophy. The main independent predictors for cognitive deficits were high burden of cortical lesions and number of gadolinium-enhancing lesions. Cognitive dysfunction was especially related to high burden of cortical lesions and subclinical disease activity. Cognitive studies in MS should look over subclinical disease activity as a potential contributor to cognitive impairment.

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A common breeding strategy is to carry out basic studies to investigate the hypothesis of a single gene controlling the trait (major gene) with or without polygenes of minor effect. In this study we used Bayesian inference to fit genetic additive-dominance models of inheritance to plant breeding experiments with multiple generations. Normal densities with different means, according to the major gene genotype, were considered in a linear model in which the design matrix of the genetic effects had unknown coefficients (which were estimated in individual basis). An actual data set from an inheritance study of partenocarpy in zucchini (Cucurbita pepo L.) was used for illustration. Model fitting included posterior probabilities for all individual genotypes. Analysis agrees with results in the literature but this approach was far more efficient than previous alternatives assuming that design matrix was known for the generations. Partenocarpy in zucchini is controlled by a major gene with important additive effect and partial dominance.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Universidade Estadual de Campinas . Faculdade de Educação Física