Distribuição espacial de Alabama argillacea (Hübner) (Lepidoptera: Noctuidae) em algodoeiro

O conhecimento do modelo de distribuição espacial de pragas na cultura é fundamental para estabelecer um plano adequado de amostragem seqüencial e, assim, permitir a correta utilização das estratégias de controle e a otimização das técnicas de amostragem. Esta pesquisa objetivou estudar a distribuição espacial de lagartas de Alabama argillacea (Hübner) na cultura do algodoeiro, cultivar CNPA ITA-90. A coleta de dados ocorreu durante o ano agrícola de 1998/99 na Fazenda Itamarati Sul S.A., localizada no município de Ponta Porã, MS, em três diferentes áreas de 10.000 m² cada uma. Cada área amostral foi composta de 100 parcelas com 100 m² cada. Foi realizada semanalmente a contagem das lagartas pequenas, médias e grandes, encontradas em cinco plantas por parcela. Os índices de agregação (razão variância/média e índice de Morisita), o teste de qui-quadrado com o ajuste dos valores encontrados e esperados às distribuições teóricas de freqüência (Poisson, binomial positiva e binomial negativa), mostraram que todos os estádios das lagartas estão distribuídos de acordo com o modelo de distribuição contagiosa, ajustando-se ao padrão da Distribuição Binomial Negativa durante todo o período de infestação.

Distribution of stream macroalgal communities from the mid-western region of Paraná state, southern Brazil: importance of local scale variation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Repercussions of mild diabetes on pregnancy in Wistar rats and on the fetal development

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

Comparison of Single-Standing or Connected Implants on Stress Distribution in Bone of Mandibular Overdentures: A Two-Dimensional Finite Element Analysis

This study aimed to compare the influence of single-standing or connected implants on stress distribution in bone of mandibular overdentures by means of two-dimensional finite element analysis. Two finite element models were designed using software (ANSYS) for 2 situations: bar-clip (BC) group-model of an edentulous mandible supporting an overdenture over 2 connected implants with BC system, and o'ring (OR) group-model of an edentulous mandible supporting an overdenture over 2 single-standing implants with OR abutments. Axial loads (100 N) were applied on either central (L1) or lateral (L2) regions of the models. Stress distribution was concentrated mostly in the cortical bone surrounding the implants. When comparing the groups, BC (L1, 52.0 MPa and L2, 74.2 MPa) showed lower first principal stress values on supporting tissue than OR (L1, 78.4 MPa and L2, 76.7 MPa). Connected implants with BC attachment were more favorable on stress distribution over peri-implant-supporting tissue for both loading conditions.

Measurement of the shape of the boson-transverse momentum distribution in p(p)over-bar -> Z/gamma*-> e(+)e(-)+X events produced at root s=1.96 TeV

We present a measurement of the shape of the Z/gamma* boson transverse momentum (q(T)) distribution in p (p) over bar -> Z/gamma(*)-> e(+)e(-)+X events at a center-of-mass energy of 1.96 TeV using 0.98 fb(-1) of data collected with the D0 detector at the Fermilab Tevatron collider. The data are found to be consistent with the resummation prediction at low q(T), but above the perturbative QCD calculation in the region of q(T)> 30 GeV/c. Using events with q(T)< 30 GeV/c, we extract the value of g(2), one of the nonperturbative parameters for the resummation calculation. Data at large boson rapidity y are compared with the prediction of resummation and with alternative models that employ a resummed form factor with modifications in the small Bjorken x region of the proton wave function.

Generalised single-equation load flow method for unbalanced distribution systems

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

Modelos de regressão aplicado no absenteísmo em uma empresa do setor sucroalcooleiro

Pós-graduação em Engenharia de Produção - FEB

Distribuição espacial e amostragem de adultos de Toxoptera citricida Kirkaldy (Hemiptera: Aphididae) na cultura de citros

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Diabete moderado induzido em diferentes fases da vida de ratas Wistar: repercussões na reprodução materna e na freqüência de anomalias fetais

Experimental models are necessary to elucidate pathophysiological mechanisms not yet understood in humans. To evaluate the repercussions of the diabetes, considering two methodologies, on the pregnancy of Wistar rats and on the development of their offspring. In the 1st induction, female offspring were distributed into two experimental groups: Group streptozotocin (STZ, n=67): received the β-cytotoxic agent (100mg STZ/kg body weight - sc) on the 1st day of the life; and Non-diabetic Group (ND, n=14): received the vehicle in a similar time period. In the adult life, the animals were mated. After a positive diagnosis of pregnancy (0), female rats from group STZ presenting with lower glycemia than 120 mg/dL received more 20 mg STZ/kg (ip) at day 7 of pregnancy (2nd induction). The female rats with glycemia higher than 120mg/dL were discarded because they reproduced results already found in the literature. In the mornings of days 0, 7, 14 and 21 of the pregnancy glycemia was determined. At day 21 of pregnancy (at term), the female rats were anesthetized and killed for maternal reproductive performance and fetal development analysis. The data were analyzed using Student-Newman-Keuls, Chi-square and Zero-inflated Poisson (ZIP) Tests (p<0.05). STZ rats presented with increased rates of pre (STZ=22.0%; ND=5.1%) and post-implantation losses (STZ=26.1%; ND=5.7%), reduced rates of fetuses with appropriate weight for gestational age (STZ=66%; ND=93%) and reduced degree of development (ossification sites). Conclusion: Mild diabetes led a negative impact on maternal reproductive performance and caused intrauterine growth restriction and impaired fetal development

Marcadores de ativação imune, inflamação crônica e estresse oxidativo em pessoas que vivem com o HIV/Aids: a busca do melhor prognóstico

Pós-graduação em Doenças Tropicais - FMB

A Bayesian analysis of the Conway-Maxwell-Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

Predictors for hospitalization and outpatient visits in patients with inflammatory bowel disease: results from the Swiss Inflammatory Bowel Disease Cohort Study

OBJECTIVES Patients with inflammatory bowel disease (IBD) have a high resource consumption, with considerable costs for the healthcare system. In a system with sparse resources, treatment is influenced not only by clinical judgement but also by resource consumption. We aimed to determine the resource consumption of IBD patients and to identify its significant predictors. MATERIALS AND METHODS Data from the prospective Swiss Inflammatory Bowel Disease Cohort Study were analysed for the resource consumption endpoints hospitalization and outpatient consultations at enrolment [1187 patients; 41.1% ulcerative colitis (UC), 58.9% Crohn's disease (CD)] and at 1-year follow-up (794 patients). Predictors of interest were chosen through an expert panel and a review of the relevant literature. Logistic regressions were used for binary endpoints, and negative binomial regressions and zero-inflated Poisson regressions were used for count data. RESULTS For CD, fistula, use of biologics and disease activity were significant predictors for hospitalization days (all P-values <0.001); age, sex, steroid therapy and biologics were significant predictors for the number of outpatient visits (P=0.0368, 0.023, 0.0002, 0.0003, respectively). For UC, biologics, C-reactive protein, smoke quitters, age and sex were significantly predictive for hospitalization days (P=0.0167, 0.0003, 0.0003, 0.0076 and 0.0175 respectively); disease activity and immunosuppressive therapy predicted the number of outpatient visits (P=0.0009 and 0.0017, respectively). The results of multivariate regressions are shown in detail. CONCLUSION Several highly significant clinical predictors for resource consumption in IBD were identified that might be considered in medical decision-making. In terms of resource consumption and its predictors, CD and UC show a different behaviour.

Estimating the prevalence of comorbid conditions and their effect on health care costs in patients with diabetes mellitus in Switzerland.

BACKGROUND Estimating the prevalence of comorbidities and their associated costs in patients with diabetes is fundamental to optimizing health care management. This study assesses the prevalence and health care costs of comorbid conditions among patients with diabetes compared with patients without diabetes. Distinguishing potentially diabetes- and nondiabetes-related comorbidities in patients with diabetes, we also determined the most frequent chronic conditions and estimated their effect on costs across different health care settings in Switzerland. METHODS Using health care claims data from 2011, we calculated the prevalence and average health care costs of comorbidities among patients with and without diabetes in inpatient and outpatient settings. Patients with diabetes and comorbid conditions were identified using pharmacy-based cost groups. Generalized linear models with negative binomial distribution were used to analyze the effect of comorbidities on health care costs. RESULTS A total of 932,612 persons, including 50,751 patients with diabetes, were enrolled. The most frequent potentially diabetes- and nondiabetes-related comorbidities in patients older than 64 years were cardiovascular diseases (91%), rheumatologic conditions (55%), and hyperlipidemia (53%). The mean total health care costs for diabetes patients varied substantially by comorbidity status (US$3,203-$14,223). Patients with diabetes and more than two comorbidities incurred US$10,584 higher total costs than patients without comorbidity. Costs were significantly higher in patients with diabetes and comorbid cardiovascular disease (US$4,788), hyperlipidemia (US$2,163), hyperacidity disorders (US$8,753), and pain (US$8,324) compared with in those without the given disease. CONCLUSION Comorbidities in patients with diabetes are highly prevalent and have substantial consequences for medical expenditures. Interestingly, hyperacidity disorders and pain were the most costly conditions. Our findings highlight the importance of developing strategies that meet the needs of patients with diabetes and comorbidities. Integrated diabetes care such as used in the Chronic Care Model may represent a useful strategy.