This paper describes the results of a detailed study relating the performance of undergraduate students admitted to Brazil’s State University of Campinas (Unicamp) from 1994 through 1997 and their socioeconomic and educational background. The study is based on a hierarchical model for the relevant variables involved. The main result is that students coming from disadvantaged backgrounds, in both educational and socioeconomic aspects, have a higher relative performance than their complementary group. We report on an affirmative action programme established at Unicamp for undergraduate admissions, partially motivated by those findings, and present evidence from an initial evaluation showing the programme’s positive impact. Finally, we comment on the effect this study and the Unicamp programme have had on the present debate about affirmative action access policies in Brazilian higher education institutions. by Renato H.L. Pedrosa, J. Norberto W. Dachs, Rafael P. Maia and Cibele Y. Andrade, Benilton S. Carvalho

Background SARS-CoV-2, the virus that causes COVID-19, enters the cells through a mechanism dependent on its binding to angiotensin-converting enzyme 2 (ACE2), a protein highly expressed in the lungs. The putative viral-induced inhibition of ACE2 could result in the defective degradation of bradykinin, a potent inflammatory substance. We hypothesize that increased bradykinin in the lungs is an important mechanism driving the development of pneumonia and respiratory failure in COVID-19. Methods This is a phase II, single-center, three-armed parallel-group, open-label, active control superiority randomized clinical trial. One hundred eighty eligible patients will be randomly assigned in a 1:1:1 ratio to receive either the inhibitor of C1e/kallikrein 20 U/kg intravenously on day 1 and day 4 plus standard care; or icatibant 30 mg subcutaneously, three doses/day for 4 days plus standard care; or standard care alone, as recommended in the clinical trials published to date, which includes supplemental oxygen, non-invasive and invasive ventilation, antibiotic agents, anti-inflammatory agents, prophylactic antithrombotic therapy, vasopressor support, and renal replacement therapy. Discussion Accumulation of bradykinin in the lungs is a common side effect of ACE inhibitors leading to cough. In animal models, the inactivation of ACE2 leads to severe acute pneumonitis in response to lipopolysaccharide (LPS), and the inhibition of bradykinin almost completely restores the lung structure. We believe that inhibition of bradykinin in severe COVID-19 patients could reduce the lung inflammatory response, impacting positively on the severity of disease and mortality rates. Trial registration Brazilian Clinical Trials Registry Universal Trial Number (UTN) U1111-1250-1843. Registered on May/5/2020.

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Dairy cow mortality has been steadily increasing during the last 2 decades in Denmark. This study aims to verify whether genetic mechanisms might be contributing to this increase. To do so, the records of 880,480 Holstein, 142,306 Jersey, and 85,206 Red Danish dairy cows calving from 1990 to 2006 were retrieved from the Danish Cattle register. Two causes of culling of cows were considered: death and slaughtering. Bivariate competing risk genetic models with a sire model structure were used to describe the death and the slaughtering rates simultaneously. The models included 2 random components: a sire random component with pedigree representing the sire genetic effects and a herd-year-season component. Moreover, the level of heterozygosity and the sire breed proportions were included in the models as covariates to account for potential nonadditive genetic effects due to the massive introduction of genetic material from other populations. The correlations between the sire components for death rate and slaughter rate were negative and small for the 3 populations, suggesting the existence of specific genetic mechanisms for each culling reason and common concurrent genetic mechanisms. In the Holstein population, the effects of the changes in the level of heterozygosity, breed composition, and the increasing genetic trend acted in the same direction, increasing the death rate in recent years. In the Jersey population, the effects of the level of heterozygosity and the breed proportion were small, and only the increasing genetic trend can be pointed as a genetic cause to the observed increase in the mortality rate. In the Red Danish population, neither the time-development pattern of the genetic trend nor the changes in the level of heterozygosity and breed composition could be causing the observed increase in the mortality; thus, nongenetic factors must be causing this negative development.

A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant. The discrete time models used are multivariate variants of the discrete relative risk models. These models allow for regular parametric likelihood-based inference by exploring a coincidence of their likelihood functions and the likelihood functions of suitably defined multivariate generalized linear mixed models. The models include a dispersion parameter, which is essential for obtaining a decomposition of the variance of the trait of interest as a sum of parcels representing the additive genetic effects, environmental effects and unspecified sources of variability; as required in quantitative genetic applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed.

Due to recent large outbreaks, peanuts have been considered a product of potential risk for Salmonella. Usually, peanut products show a low water activity (aw) and high fat content, which contribute to increasing the thermal resistance and survival of Salmonella. This study evaluated the long-term kinetics of Salmonella survival on different peanut products under storage at 28°C for 420 days. Samples of raw in-shell peanuts (aw = 0.29), roasted peanuts (aw = 0.39), unblanched peanut kernel (aw = 0.54), peanut brittle (aw = 0.30), paçoca (aw = 0.40) and pé-de-moça (aw = 0.68) were inoculated with Salmonella Typhimurium ATCC 14028 at two inoculum levels (3 and 6 log cfu/ g). The Salmonella behavior was influenced (p<0.05) by aw, lipid, carbohydrate and protein content. In most cases for both inoculum levels, the greatest reductions were seen after the first two weeks of storage, followed by a slower decline phase. The lowest reductions were verified in paçoca and roasted peanuts, with counts of 1.01 and 0.87 log cfu/ g at low inoculum level and 2.53 and 3.82 log cfu/ g at high inoculum level at the end of the storage time. The highest loss of viability was observed in pé-de-moça, with absence of Salmonella in 10-g after 180 days at low inoculum level. The Weibull model provided a suitable fit to the data (R2≥0.81), with δ value ranging from 0.06 to 49.75 days. Therefore, the results demonstrated that Salmonella survives longer in peanut products, beyond the shelf life (>420 days), especially in products with aw around 0.40.

The purpose of this work is to present suitable statistical methods to study the performance of undergraduate students based on the incidence/proportion of failed courses/subjects. Three approaches are considered: first, the proportion of failed subjects is modeled considering a zero-one augmented beta distribution; second, discrete models are used to model the probability of failing subjects with logit link; third, incidence is modeled using regression for count data with log link and the logarithm of the total number of subjects as an offset. Zero-inflated versions are used to account for the excess of zeros in the data when appropriate and we also considered the heterogeneous dispersion parameter, when applicable. Overall, the zeroinflated negative binomial and zero inflated beta-binomial models, with regression on the mean and the dispersion parameters, present good measures of goodness of fit to the data. The database consists of records of Engineering major students who entered the State University of Campinas, Brazil, from 2000 to 2005. Entrance exam scores and demographic variables as well as socio-economic status are considered as covariates in the models.

O objetivo deste trabalho é propor uma metodologia para avaliar o desempenho dos alunos da Universidade Estadual de Campinas, do ingresso à conclusão do curso. A amostra é composta por todos os ingressantes dessa universidade nos anos de 1997 a 2000, e a população que corresponde ao universo dos alunos ingressantes em todo o período de existência da universidade. O conjunto de dados disponível foi obtido a partir dos questionários socioculturais, aplicados pela Comissão Permanente de Vestibulares na inscrição do vestibular, e de informações acadêmicas fornecidas pela Diretoria Acadêmica da Universidade. É proposta uma metodologia com base na variável denominada "ganho relativo" sugerida por Dachs e Maia (2006). Essa nova metodologia fundamenta-se em medidas de diversidades propostas por Rao (1982) e na utilização de U-estatísticas. Propõem-se testes de homogeneidade para avaliar se existe diferença no desempenho entre alunos segundo alguns agrupamentos.