Predição genômica utilizando painéis de marcadores moleculares com diferentes densidades, em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Home ranges of Guiana dolphins (Sotalia guianensis) (Cetacea: Delphinidae) in the Cananeia estuary, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Biogeographic Distribution Patterns and Their Correlates in the Diverse Frog Fauna of the Atlantic Forest Hotspot

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Utilização de informações genômicas para o melhoramento genético de características da carne em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Comparação entre modelos de análise genômica utilizando dados simulados e dados reais em ovinos

Pós-graduação em Genética e Melhoramento Animal - FCAV

Seleção genômica para características longitudinais de bovinos da raça Holandesa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

SPATIAL VARIABILITY OF THE RAINFALL EROSIVE POTENTIAL IN THE STATE OF MATO GROSSO DO SUL, BRAZIL

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map. Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

A performance based study on gender recognition in large datasets

[EN]Gender recognition has achieved impressive results based on the face appearance in controlled datasets. Its application in the wild and large datasets is still a challenging task for researchers. In this paper, we make use of classical techniques to analyze their performance in controlled and uncontrolled condition respectively with the LFW and MORPH datasets. For both sets the benchmarking protocol follows the 5-fold cross-validation proposed by the BEFIT challenge.

Sea Level Variations from Decades to Millennia: A few Case Studies

The main goals of this Ph.D. study are to investigate the regional and global geophysical components related to present polar ice melting and to provide independent cross validation checks of GIA models using both geophysical data detected by satellite mission, and geological observations from far field sites, in order to determine a lower and upper bound of uncertainty of GIA effect. The subject of this Thesis is the sea level change from decades to millennia scale. Within ice2sea collaboration, we developed a Fortran numerical code to analyze the local short-term sea level change and vertical deformation resulting from the loss of ice mass. This method is used to investigate polar regions: Greenland and Antarctica. We have used mass balance based on ICESat data for Greenland ice sheet and a plausible mass balance for Antarctic ice sheet. We have determined the regional and global fingerprint of sea level variations, vertical deformations of the solid surface of the Earth and variations of shape of the geoid for each ice source mentioned above. The coastal areas are affected by the long wavelength component of GIA process. Hence understanding the response of the Earth to loading is crucial in various contexts. Based on the hypothesis that Earth mantle materials obey to a linear rheology, and that the physical parameters of this rheology can be only characterized by their depth dependence, we investigate the Glacial Isostatic Effect upon the far field sites of Mediterranean area using an improved SELEN program. We presented new and revised observations for archaeological fish tanks located along the Tyrrhenian and Adriatic coast of Italy and new RSL for the SE Tunisia. Spatial and temporal variations of the Holocene sea levels studied in central Italy and Tunisia, provided important constraints on the melting history of the major ice sheets.

Co-frangitura oliva e nocciola: Studio del prodotto

In recent times, the choices of consumers have been more conscious and oriented to foods with health benefits. The present paper deals with the study of oil from crushing of olive and huzelnut with the aim of obtaining a “functional food”. Different samples of oil derived from the crushing of olive (O), olive with 5% of hazelnut (O5N) and olive with 10% of hazelnut (O10N), exposed to different temperatures (28 and 35°C) and times (15 and 30 minutes) of malaxation. The samples of oil were initially subjected to a qualitative assessment by the analysis of peroxide and free acidity. Following further analyses were carried out namely the determination of fatty acids and triglycerides by FAST GC-FID, the determination of tocopherols by HPLC-FLC, the analysis of sterols by GC/MS and the spectroscopic analysis with FT-MIR combined with statistical analysis with PCA and PLS. The results showed that increasing the time and temperature of malaxation there aren’t relevant significant differences (p<0,05) in the composition of fatty acids, triglycerides and tocopherols in the different oils, but there are higher extraction yields. The increase of content of hazelnut in phase of crushing causes the decrease of triglycerides C50 and C52, the increase of the class C54, total tocopherols and of total sterols as well. The samples analysed with FT-MIR spectroscopy have showed, on the contrary to conventional analytical techniques, a good discrimination between different oils despite of the similar chemical composition of olive and hazelnuts. After the PLS models were built from spectra FT-MIR in order to estimate the content of triglycerides C50, C52 and C54 and total tocopherols, with good R2 in full cross validation (R2>0,821).

Applicazione del metodo QDanet_PRO alla classificazione di dati omici

Il presente lavoro di tesi si pone nell'ambito dell'analisi dati attraverso un metodo (QDanet_PRO), elaborato dal Prof. Remondini in collaborazine coi Dott. Levi e Malagoli, basato sull'analisi discriminate a coppie e sulla Teoria dei Network, che ha come obiettivo la classificazione di dati contenuti in dataset dove il numero di campioni è molto ridotto rispetto al numero di variabili. Attraverso questo studio si vogliono identificare delle signature, ovvero un'insieme ridotto di variabili che siano in grado di classificare correttamente i campioni in base al comportamento delle variabili stesse. L'elaborazione dei diversi dataset avviene attraverso diverse fasi; si comincia con una un'analisi discriminante a coppie per identificare le performance di ogni coppia di variabili per poi passare alla ricerca delle coppie più performanti attraverso un processo che combina la Teoria dei Network con la Cross Validation. Una volta ottenuta la signature si conclude l'elaborazione con una validazione per avere un'analisi quantitativa del successo o meno del metodo.

Assessment of total uncertainty in cocaine and benzoylecgonine wastewater load measurements

To check the effectiveness of campaigns preventing drug abuse or indicating local effects of efforts against drug trafficking, it is beneficial to know consumed amounts of substances in a high spatial and temporal resolution. The analysis of drugs of abuse in wastewater (WW) has the potential to provide this information. In this study, the reliability of WW drug consumption estimates is assessed and a novel method presented to calculate the total uncertainty in observed WW cocaine (COC) and benzoylecgonine (BE) loads. Specifically, uncertainties resulting from discharge measurements, chemical analysis and the applied sampling scheme were addressed and three approaches presented. These consist of (i) a generic model-based procedure to investigate the influence of the sampling scheme on the uncertainty of observed or expected drug loads, (ii) a comparative analysis of two analytical methods (high performance liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry), including an extended cross-validation by influent profiling over several days, and (iii) monitoring COC and BE concentrations in WW of the largest Swiss sewage treatment plants. In addition, the COC and BE loads observed in the sewage treatment plant of the city of Berne were used to back-calculate the COC consumption. The estimated mean daily consumed amount was 107 ± 21 g of pure COC, corresponding to 321 g of street-grade COC.