A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

PCJ River Basins` Water Availability Caused by Water Diversion Scenarios to Supply Metropolitan Areas of So Paulo

A dynamic systems simulation model of water resources was developed as a tool to help analyze alternatives to water resources management for the Piracicaba, Capivari and Jundiai River Water Basins (RB-PCJ), and used to run six 50-year simulations from 2004 to 2054. The model estimates water supply and demand, as well as contamination load by several consumers. Six runs were performed using a constant mean precipitation value, changing water supply and demand and different volumes diverted from RB-PCJ to RB-Alto Tiet. For the Business as Usual scenario, the Sustainability Index went from 0.44 in 2004 to 0.20 by 2054. The Water Sustainability Index changed from 74% in 2004 to 131% by 2054. The Falkenmark Index changed from 1,403 m(3) person (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) in 2004 to 734 m(3) person (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) by 2054. We concluded that sanitation is one of the major problems for the PCJ River Basins.

Water Resources Assessment at Piracicaba, Capivari and Jundiai River Basins: A Dynamic Systems Approach

The Piracicaba, Capivari, and Jundiai River Basins (RB-PCJ) are mainly located in the State of So Paulo, Brazil. Using a dynamics systems simulation model (WRM-PCJ) to assess water resources sustainability, five 50-year simulations were run. WRM-PCJ was developed as a tool to aid decision and policy makers on the RB-PCJ Watershed Committee. The model has 254 variables. The model was calibrated and validated using available information from the 80s. Falkenmark Water Stress Index went from 1,403 m(3) person (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) in 2004 to 734 m(3) P (-aEuro parts per thousand 1) year (-aEuro parts per thousand 1) in 2054, and Xu Sustainability Index from 0.44 to 0.20. In 2004, the Keller River Basin Development Phase was Conservation, and by 2054 was Augmentation. The three criteria used to evaluate water resources showed that the watershed is at crucial water resources management turning point. The WRM-PCJ performed well, and it proved to be an excellent tool for decision and policy makers at RB-PCJ.

WATER RESOURCES SITUATION AT PIRACICABA, CAPIVARI AND JUNDIAI WATERSHEDS USING A DYNAMIC SYSTEMS MODEL

Using a dynamic systems model specifically developed for Piracicaba, Capivari and Jundia River Water Basins (BH-PCJ) as a tool to help to analyze water resources management alternatives for policy makers and decision takers, five simulations for 50 years timeframe were performed. The model estimates water supply and demand, as well as wastewater generation from the consumers at BH-PCJ. A run was performed using mean precipitation value constant, and keeping the actual water supply and demand rates, the business as usual scenario. Under these considerations, it is expected an increment of about similar to 76% on water demand, that similar to 39% of available water volume will come from wastewater reuse, and that waste load increases to similar to 91%. Falkenmark Index will change from 1,403 m(3) person(-1) year(-1) in 2004, to 734 m(3) P(-1) year(-1) by 2054, and the Sustainability Index from 0.44 to 0.20. Another four simulations were performed by affecting the annual precipitation by 90 and 110%; considering an ecological flow equal to 30% of the mean daily flow; and keeping the same rates for all other factors except for ecological flow and household water consumption. All of them showed a tendency to a water crisis in the near future at BH-PCJ.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Spatial Modeling of a Soil Fertility Index using Visible-Near-Infrared Spectra and Terrain Attributes

Our objective was to develop a methodology to predict soil fertility using visible near-infrared (vis-NIR) diffuse reflectance spectra and terrain attributes derived from a digital elevation model (DEM). Specifically, our aims were to: (i) assemble a minimum data set to develop a soil fertility index for sugarcane (Sarcharum officinarum L.) (SFI-SC) for biofuel production in tropical soils; (ii) construct a model to predict the SFI-SC using soil vis-NIR spectra and terrain attributes; and (iii) produce a soil fertility map for our study area and assess it by comparing it with a green vegetation index (GVI). The study area was 185 ha located in sao Paulo State, Brazil. In total, 184 soil samples were collected and analyzed for a range of soil chemical and physical properties. Their vis-NIR spectra were collected from 400 to 2500 nm. The Shuttle Radar Topographic Mission 3-arcsec (90-m resolution) DEM of the area was used to derive 17 terrain attributes. A minimum data set of soil properties was selected to develop the SFI-SC. The SFI-SC consisted of three classes: Class 1, the highly fertile soils; Class 2, the fertile soils; and Class 3, the least fertile soils. It was derived heuristically with conditionals and using expert knowledge. The index was modeled with the spectra and terrain data using cross-validated decision trees. The cross-validation of the model correctly predicted Class 1 in 75% of cases, Class 2 in 61%, and Class 3 in 65%. A fertility map was derived for the study area and compared with a map of the GVI. Our approach offers a methodology that incorporates expert knowledge to derive the SFI-SC and uses a versatile spectro-spatial methodology that may be implemented for rapid and accurate determination of soil fertility and better exploration of areas suitable for production.

Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

HFE gene mutations in patients with primary iron overload: Is there a significant improvement in molecular diagnosis yield with HFE sequencing?

Rare HFE variants have been shown to be associated with hereditary hemochromatosis (HH), an iron overload disease. The low frequency of the HFE p.C282Y mutation in HH-affected Brazilian patients may suggest that other HFE-related mutations may also be implicated in the pathogenesis of HH in this population. The main aim was to screen for new HFE mutations in Brazilian individuals with primary iron overload and to investigate their relationship with HH. Fifty Brazilian patients with primary iron overload (transferrin saturation >50% in females and 60% in males) were selected. Subsequent bidirectional sequencing for each HFE exon was performed. The effect of HFE mutations on protein structure were analyzed by molecular dynamics simulation and free binding energy calculations. p.C282Y in homozygosis or in heterozygosis with p.H63D were the most frequent genotypic combinations associated with HH in our sample population (present in 17 individuals, 34%). Thirty-six (72.0%) out of the 50 individuals presented at least one HFE mutation. The most frequent genotype associated with HH was the homozygous p.C282Y mutation (n = 11, 22.0%). One novel mutation (p.V256I) was indentified in heterozygosis with the p.H63D mutation. In silico modeling analysis of protein behavior indicated that the p.V256I mutation does not reduce the binding affinity between HFE and beta 2-microglobulin ((beta 2M) in the same way the p.C282Y mutation does compared with the native HFE protein. In conclusion, screening of HFE through direct sequencing, as compared to p.C282Y/p.H63D genotyping, was not able to increase the molecular diagnosis yield of HH. The novel p.V256I mutation could not be implicated in the molecular basis of the HH phenotype, although its role cannot be completely excluded in HH-phenotype development. Our molecular modeling analysis can help in the analysis of novel, previously undescribed, HFE mutations. (C) 2010 Elsevier Inc. All rights reserved.

Molecular Modeling Suggests Cruzain Specificity for Peptide Primaquine Prodrugs

Chagas` disease, infection caused by the protozoan Trypanosoma cruzi, is an important, social and medical ailment in the Latin America. This disease is endemic in 21 countries, mostly Latin America countries, with more than 300,000 new cases every year and about 16-18 million infected people. Current therapy is not effective in the chronic phase of the disease. Thus, new and better drugs are urgently needed. In this sense, the in vitro activity of primaquine (PQ) was reported. Based on this, peptide prodrugs of primaquine containing dipeptides - lysine-arginine (LysArg), phenylalanine-alanine (PheAla) and phenylalanine-arginine (PheArg) -- as carriers, were designed to be selectively cleaved by cruzain, a specific cysteine protease of T. cruzi. The prodrugs have shown to be active against tripomastigote forms according to this order: LysArg-PQ> PheAla-PQ> PheArg-PQ. The molecular mechanism of action considered a probable nucleophilic attack of the catalytic residue of cruzain (Cys25) on the respective prodrug amide carbonyl carbon, releasing PQ. In order to test this hypothesis, molecular modeling studies were performed, physicochemical parameters and stereoelectronic features calculated by using the AM1 semi-empirical method suggest that the amide carbonyl carbon is favorable for cleavage, where the LysArg showed the most electronic reactive and sterically disposable, leading to the prodrug release and action. In addition, the docking study indicates the occurrence of specific interactions between prodrugs and the pockets S1 and S2 of cruzain through the dipeptides carriers, being the distance between cruzain Cys25 and the amide carbonyl group related to the biological activity of the prodrugs.

QSAR Modeling of a Set of Pyrazinoate Esters as Antituberculosis Prodrugs

Tuberculosis is an infection caused mainly by Mycobacterium tuberculosis. A first-line antimycobacterial drug is pyrazinamide (PZA), which acts partially as a prodrug activated by a pyrazinamidase releasing the active agent, pyrazinoic acid (POA). As pyrazinoic acid presents some difficulty to cross the mycobacterial cell wall, and also the pyrazinamide-resistant strains do not express the pyrazinamidase, a set of pyrazinoic acid esters have been evaluated as antimycobacterial agents. In this work, a QSAR approach was applied to a set of forty-three pyrazinoates against M. tuberculosis ATCC 27294, using genetic algorithm function and partial least squares regression (WOLF 5.5 program). The independent variables selected were the Balaban index (I), calculated n-octanol/water partition coefficient (ClogP), van-der-Waals surface area, dipole moment, and stretching-energy contribution. The final QSAR model (N = 32, r(2) = 0.68, q(2) = 0.59, LOF = 0.25, and LSE = 0.19) was fully validated employing leave-N-out cross-validation and y-scrambling techniques. The test set (N = 11) presented an external prediction power of 73%. In conclusion, the QSAR model generated can be used as a valuable tool to optimize the activity of future pyrazinoic acid esters in the designing of new antituberculosis agents.

Molecular modeling as a promising tool to study dendrimer prodrugs delivery

Molecular modeling methodologies were applied to perform preliminary studies concerning the release of active agents from potentially antichagasic and antileishmanial dendrimer prodrugs. The dendrimer was designed having myo-inositol as a core, L-malic acid as a spacer group, and hydroxymethylnitrofurazone (NFOH), 3-hydroxyflavone or quercetin, as active compounds. Each dendrimer presented a particular behavior concerning to the following investigated properties: spatial hindrance, map of electrostatic potential (MEP), and the lowest unoccupied molecular orbital energy (E(LUMO)). Additionally, the findings suggested that the carbonyl group next to the active agent seems to be the most promising ester breaking point. (C) 2009 Elsevier B.V. All rights reserved.

Molecular modeling and QSAR studies of a set of indole and benzimidazole derivatives as H(4) receptor antagonists

Histamine is an important biogenic amine, which acts with a group of four G-protein coupled receptors (GPCRs), namely H(1) to H(4) (H(1)R - H(4)R) receptors. The actions of histamine at H(4)R are related to immunological and inflammatory processes, particularly in pathophysiology of asthma, and H(4)R ligands having antagonistic properties could be helpful as antiinflammatory agents. In this work, molecular modeling and QSAR studies of a set of 30 compounds, indole and benzimidazole derivatives, as H(4)R antagonists were performed. The QSAR models were built and optimized using a genetic algorithm function and partial least squares regression (WOLF 5.5 program). The best QSAR model constructed with training set (N = 25) presented the following statistical measures: r (2) = 0.76, q (2) = 0.62, LOF = 0.15, and LSE = 0.07, and was validated using the LNO and y-randomization techniques. Four of five compounds of test set were well predicted by the selected QSAR model, which presented an external prediction power of 80%. These findings can be quite useful to aid the designing of new anti-H(4) compounds with improved biological response.