Aplicação de lógica fuzzy na elaboração de planta de valores genéricos

Pós-graduação em Ciências Cartográficas - FCT

Avaliação dos fatores preditivos dos pólipos endometriais em mulheres na pós-menopausa

Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB

Recovering Streptococcus mutans over restorations by the tray technique: a randomized clinical study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estudo do ultrassom de potência no pré-tratamento do material lignocelulósico de resíduos da bananeira

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização de Híbridos Simples Experimentais de Milho (Zea Mays L.)

Pós-graduação em Agronomia - FEIS

Seleção genômica e estudo de associação em um rebanho experimental da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners

Bertuzzi, R, Bueno, S, Pasqua, LA, Acquesta, FM, Batista, MB, Roschel, H, Kiss, MAPDM, Serrao, JC, Tricoli, V, and Ugrinowitsch, C. Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners. J Strength Cond Res 26(8): 2096-2102, 2012-The purpose of this study was to investigate the main bioenergetics and neuromuscular determinants of the time to exhaustion (T-lim) at the velocity corresponding to maximal oxygen uptake in recreational long-distance runners. Twenty runners performed the following tests on 5 different days: (a) maximal incremental treadmill test, (b) 2 submaximal tests to determine running economy and vertical stiffness, (c) exhaustive test to measured the T-lim, (d) maximum dynamic strength test, and (e) muscle power production test. Aerobic and anaerobic energy contributions during the T-lim test were also estimated. The stepwise multiple regression method selected 3 independent variables to explain T-lim variance. Total energy production explained 84.1% of the shared variance (p = 0.001), whereas peak oxygen uptake ((V) over dotO(2)peak) measured during T-lim and lower limb muscle power ability accounted for the additional 10% of the shared variance (p = 0.014). These data suggest that the total energy production, (V) over dotO(2)peak, and lower limb muscle power ability are the main physiological and neuromuscular determinants of T-lim in recreational long-distance runners.

Landwirtschaftliche Schaderregerprognose mit Hilfe von geographischen Informationssystemen

In der hier vorliegenden Arbeit wurde am Beispiel der Kraut- und Knollenfäule an Kartoffeln Phytophthora infestans und des Kartoffelkäfers Leptinotarsa decemlineata untersucht, ob durch den Einsatz von Geographischen Informationssystemen (GIS) landwirtschaftliche Schader¬reger¬prognosen für jeden beliebigen Kartoffelschlag in Deutschland erstellt werden können. Um dieses Ziel zu erreichen, wurden die Eingangsparameter (Temperatur und relative Luftfeuchte) der Prognosemodelle für die beiden Schaderreger (SIMLEP1, SIMPHYT1, SIMPHYT3 and SIMBLIGHT1) so aufbereitet, dass Wetterdaten flächendeckend für Deutschland zur Verfügung standen. Bevor jedoch interpoliert werden konnte, wurde eine Regionalisierung von Deutschland in Interpolationszonen durchgeführt und somit Naturräume geschaffen, die einen Vergleich und eine Bewertung der in ihnen liegenden Wetterstationen zulassen. Hierzu wurden die Boden-Klima-Regionen von SCHULZKE und KAULE (2000) modifiziert, an das Wetterstationsnetz angepasst und mit 5 bis 10 km breiten Pufferzonen an der Grenze der Interpolationszonen versehen, um die Wetterstationen so häufig wie möglich verwenden zu können. Für die Interpolation der Wetterdaten wurde das Verfahren der multiplen Regression gewählt, weil dieses im Vergleich zu anderen Verfahren die geringsten Abweichungen zwischen interpolierten und gemessenen Daten aufwies und den technischen Anforderungen am besten entsprach. Für 99 % aller Werte konnten bei der Temperaturberechnung Abweichungen in einem Bereich zwischen -2,5 und 2,5 °C erzielt werden. Bei der Berechnung der relativen Luftfeuchte wurden Abweichungen zwischen -12 und 10 % relativer Luftfeuchte erreicht. Die Mittelwerte der Abweichungen lagen bei der Temperatur bei 0,1 °C und bei der relativen Luftfeuchte bei -1,8 %. Zur Überprüfung der Trefferquoten der Modelle beim Betrieb mit interpolierten Wetterdaten wurden Felderhebungsdaten aus den Jahren 2000 bis 2007 zum Erstauftreten der Kraut- und Knollenfäule sowie des Kartoffelkäfers verwendet. Dabei konnten mit interpolierten Wetterdaten die gleichen und auch höhere Trefferquoten erreicht werden, als mit der bisherigen Berechnungsmethode. Beispielsweise erzielte die Berechnung des Erstauftretens von P. infestans durch das Modell SIMBLIGHT1 mit interpolierten Wetterdaten im Schnitt drei Tage geringere Abweichungen im Vergleich zu den Berechnungen ohne GIS. Um die Auswirkungen interpretieren zu können, die durch Abweichungen der Temperatur und der relativen Luftfeuchte entstanden wurde zusätzlich eine Sensitivitätsanalyse zur Temperatur und relativen Luftfeuchte der verwendeten Prognosemodelle durchgeführt. Die Temperatur hatte bei allen Modellen nur einen geringen Einfluss auf das Prognoseergebnis. Veränderungen der relativen Luftfeuchte haben sich dagegen deutlich stärker ausgewirkt. So lag bei SIMBLIGHT1 die Abweichung durch eine stündliche Veränderung der relativen Luftfeuchte (± 6 %) bei maximal 27 Tagen, wogegen stündliche Veränderungen der Temperatur (± 2 °C) eine Abweichung von maximal 10 Tagen ausmachten. Die Ergebnisse dieser Arbeit zeigen, dass durch die Verwendung von GIS mindestens die gleichen und auch höhere Trefferquoten bei Schaderregerprognosen erzielt werden als mit der bisherigen Verwendung von Daten einer nahegelegenen Wetterstation. Die Ergebnisse stellen einen wesentlichen Fortschritt für die landwirtschaftlichen Schaderregerprognosen dar. Erstmals ist es möglich, bundesweite Prognosen für jeden beliebigen Kartoffelschlag zur Bekämpfung von Schädlingen in der Landwirtschaft bereit zu stellen.

Recipients' Satisfaction with Locally Procured Food Aid Rations: Comparative Evidence from a Three Country Matched Survey

Using survey data from natural experiments in three countries that simultaneously received food aid sourced locally and from the United States, we test the hypothesis that locally-sourced commodities are more culturally appropriate and thus preferred over traditional food aid commodities sourced from the donor country. We use a semi-nonparametric regression method to estimate recipients' satisfaction with these commodities across a range of criteria. We establish that recipients of locally procured rations are generally more satisfied with the commodities they receive than are recipients of US-sourced foods. This pattern is especially pronounced among less-well-off recipients. (C) 2013 Elsevier Ltd. All rights reserved.

Testing the structural and cross-cultural validity of the KIDSCREEN-27 quality of life questionnaire

OBJECTIVES: The aim of this study is to assess the structural and cross-cultural validity of the KIDSCREEN-27 questionnaire. METHODS: The 27-item version of the KIDSCREEN instrument was derived from a longer 52-item version and was administered to young people aged 8-18 years in 13 European countries in a cross-sectional survey. Structural and cross-cultural validity were tested using multitrait multi-item analysis, exploratory and confirmatory factor analysis, and Rasch analyses. Zumbo's logistic regression method was applied to assess differential item functioning (DIF) across countries. Reliability was assessed using Cronbach's alpha. RESULTS: Responses were obtained from n = 22,827 respondents (response rate 68.9%). For the combined sample from all countries, exploratory factor analysis with procrustean rotations revealed a five-factor structure which explained 56.9% of the variance. Confirmatory factor analysis indicated an acceptable model fit (RMSEA = 0.068, CFI = 0.960). The unidimensionality of all dimensions was confirmed (INFIT: 0.81-1.15). Differential item functioning (DIF) results across the 13 countries showed that 5 items presented uniform DIF whereas 10 displayed non-uniform DIF. Reliability was acceptable (Cronbach's alpha = 0.78-0.84 for individual dimensions). CONCLUSIONS: There was substantial evidence for the cross-cultural equivalence of the KIDSCREEN-27 across the countries studied and the factor structure was highly replicable in individual countries. Further research is needed to correct scores based on DIF results. The KIDSCREEN-27 is a new short and promising tool for use in clinical and epidemiological studies.

Effects of Chemical Deicers on Amphibian Communites

Roads and highways present a unique challenge to wildlife as they exhibit substantial impacts on the surrounding ecosystem through the interruption of a number of ecological processes. With new roads added to the national highway system every year, an understanding of these impacts is required for effective mitigation of potential environmental impacts. A major contributor to these negative effects is the deposition of chemicals used in winter deicing activities to nearby surface waters. These chemicals often vary in composition and may affect freshwater species differently. The negative impacts of widespread deposition of sodium chloride (NaCl) have prompted a search for an `environmentally friendly' alternative. However, little research has investigated the potential environmental effects of widespread use of these alternatives. Herein, I detail the results of laboratory tests and field surveys designed to determine the impacts of road salt (NaCl) and other chemical deicers on amphibian communities in Michigan's Upper Peninsula. Using larval amphibians I demonstrate the lethal impacts of a suite of chemical deicers on this sensitive, freshwater species. Larval wood frogs (Lithobates sylvatica) were tolerant of short-term (96 hours) exposure to urea (CH4N2O), sodium chloride (NaCl), and magnesium chloride (MgCl2). However, these larvae were very sensitive to acetate products (C8H12CaMgO8, CH3COOK) and calcium chloride (CaCl2). These differences in tolerance suggest that certain deicers may be more harmful to amphibians than others. Secondly, I expanded this analysis to include an experiment designed to determine the sublethal effects of chronic exposure to environmentally realistic concentrations of NaCl on two unique amphibian species, L. sylvatica and green frogs (L. clamitans). L. sylvatica tend to breed in small, ephemeral wetlands and metamorphose within a single season. However, L. clamitans breed primarily in more permanent wetlands and often remain as tadpoles for one year or more. These species employ different life history strategies in this region which may influence their response to chronic NaCl exposure. Both species demonstrated potentially harmful effects on individual fitness. L. sylvatica larvae had a high incidence of edema suggesting the NaCl exposure was a significant physiologic stressor to these larvae. L. clamitans larvae reduced tail length during their exposure which may affect adult fitness of these individuals. In order to determine the risk local amphibians face when using these roadside pools, I conducted a survey of the spatial distribution of chloride in the three northernmost counties of Michigan. This area receives a relatively low amount of NaCl which is confined to state and federal highways. The chloride concentrations in this region were much lower than those in urban systems; however, amphibians breeding in the local area may encounter harmful chloride levels arising from temporal variations in hydroperiods. Spatial variation of chloride levels suggests the road-effect zone for amphibians may be as large as 1000 m from a salt-treated highway. Lastly, I performed an analysis of the use of specific conductance to predict chloride concentrations in natural surface water bodies. A number of studies have used this regression to predict chloride concentrations from measurements of specific conductance. This method is often chosen in the place of ion chromatography due to budget and time constraints. However, using a regression method to characterize this relationship does not result in accurate chloride ion concentration estimates.

A whole-genome scan for recurrent airway obstruction in Warmblood sport horses indicates two positional candidate regions

Recurrent airway obstruction (RAO), or heaves, is a naturally occurring asthma-like disease that is related to sensitisation and exposure to mouldy hay and has a familial basis with a complex mode of inheritance. A genome-wide scanning approach using two half-sibling families was taken in order to locate the chromosome regions that contribute to the inherited component of this condition in these families. Initially, a panel of 250 microsatellite markers, which were chosen as a well-spaced, polymorphic selection covering the 31 equine autosomes, was used to genotype the two half-sibling families, which comprised in total 239 Warmblood horses. Subsequently, supplementary markers were added for a total of 315 genotyped markers. Each half-sibling family is focused around a severely RAO-affected stallion, and the phenotype of each individual was assessed for RAO and related signs, namely, breathing effort at rest, breathing effort at work, coughing, and nasal discharge, using an owner-based questionnaire. Analysis using a regression method for half-sibling family structures was performed using RAO and each of the composite clinical signs separately; two chromosome regions (on ECA13 and ECA15) showed a genome-wide significant association with RAO at P < 0.05. An additional 11 chromosome regions showed a more modest association. This is the first publication that describes the mapping of genetic loci involved in RAO. Several candidate genes are located in these regions, a number of which are interleukins. These are important signalling molecules that are intricately involved in the control of the immune response and are therefore good positional candidates.

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^