A nested expectation-maximization algorithm for latent class models with covariates

We develop a nested EM routine for latent class models with covariates which allows maximization of the full-model log-likelihood and, differently from current methods, guarantees monotone log-likelihood sequences along with improved convergence rates

Bayesian modeling via discrete nonparametric priors

The availability of complex-structured data has sparked new research directions in statistics and machine learning. Bayesian nonparametrics is at the forefront of this trend thanks to two crucial features: its coherent probabilistic framework, which naturally leads to principled prediction and uncertainty quantification, and its infinite-dimensionality, which exempts from parametric restrictions and ensures full modeling flexibility. In this paper, we provide a concise overview of Bayesian nonparametrics starting from its foundations and the Dirichlet process, the most popular nonparametric prior. We describe the use of the Dirichlet process in species discovery, density estimation, and clustering problems. Among the many generalizations of the Dirichlet process proposed in the literature, we single out the Pitman–Yor process, and compare it to the Dirichlet process. Their different features are showcased with real-data illustrations. Finally, we consider more complex data structures, which require dependent versions of these models. One of the most effective strategies to achieve this goal is represented by hierarchical constructions. We highlight the role of the dependence structure in the borrowing of information and illustrate its effectiveness on unbalanced datasets

Bayesian modeling via discrete nonparametric priors

The availability of complex-structured data has sparked new research directions in statistics and machine learning. Bayesian nonparametrics is at the forefront of this trend thanks to two crucial features: its coherent probabilistic framework, which naturally leads to principled prediction and uncertainty quantification, and its infinite-dimensionality, which exempts from parametric restrictions and ensures full modeling flexibility. In this paper, we provide a concise overview of Bayesian nonparametrics starting from its foundations and the Dirichlet process, the most popular nonparametric prior. We describe the use of the Dirichlet process in species discovery, density estimation, and clustering problems. Among the many generalizations of the Dirichlet process proposed in the literature, we single out the Pitman–Yor process, and compare it to the Dirichlet process. Their different features are showcased with real-data illustrations. Finally, we consider more complex data structures, which require dependent versions of these models. One of the most effective strategies to achieve this goal is represented by hierarchical constructions. We highlight the role of the dependence structure in the borrowing of information and illustrate its effectiveness on unbalanced datasets

Reparação de perfuração ocular em um cão usando pericárdio homólogo preservado em glicerina

As lesões de córnea ocorrem frequentemente em cães. Várias técnicas cirúrgicas são propostas para reparar perfuração de córnea, incluindo flapes conjuntivais, ceratoplastias, enxertos corneanos e implantes biológicos. Um caso de perfuração ocular em um cão tratado com pericárdio homólogo conservado em glicerina é apresentado. Oito anos de idade, macho, Pit Bull foi encaminhado ao Serviço de Oftalmologia do Hospital de Clínicas Veterinárias da Universidade Federal do Rio Grande do Sul (UFRGS) com 12 horas de perfuração corneana. O exame oftálmico revelou desconforto ocular, epífora, hiperemia conjuntival e perfuração corneana central com 5mm no olho direito. A correção cirúrgica foi realizada utilizando pericárdio homólogo conservado em glicerina. O uso de pericárdio homólogo conservado em glicerina foi efetivo na reparação do defeito corneano, preservando as funções e a anatomia oculares

Elevated glutamate and lactate predict brain death after severe head trauma

Objective: Clinical neurological assessment is challenging for severe traumatic brain injury (TBI) patients in the acute setting. Waves of neurochemical abnormalities that follow TBI may serve as fluid biomarkers of neurological status. We assessed the cerebrospinal fluid (CSF) levels of glutamate, lactate, BDNF, and GDNF, to identify potential prognostic biomarkers of neurological outcome. Methods: This cross-sectional study was carried out in a total of 20 consecutive patients (mean [SD] age, 29 [13] years; M/F, 9:1) with severe TBI Glasgow Coma Scale ≤ 8 and abnormal computed tomography scan on admission. Patients were submitted to ventricular drainage and had CSF collected between 2 and 4 h after hospital admission. Patients were then stratified according to two clinical outcomes: deterioration to brain death (nonsurvival, n = 6) or survival (survival, n = 14), within 3 days after hospital admission. CSF levels of brain-derived substances were compared between nonsurvival and survival groups. Clinical and neurological parameters were also assessed. Results: Glutamate and lactate are significantly increased in nonsurvival relative to survival patients. We tested the accuracy of both biomarkers to discriminate patient outcome. Setting a cutoff of >57.75, glutamate provides 80.0% of sensitivity and 84.62% of specificity (AUC: 0.8214, 95% CL: 54.55–98.08%; and a cutoff of >4.65, lactate has 100% of sensitivity and 85.71% of specificity (AUC: 0.8810, 95% CL: 54.55–98.08%). BDNF and GDNF did not discriminate poor outcome. Interpretation: This early study suggests that glutamate and lactate concentrations at hospital admission accurately predict death within 3 days after severe TBI

I Diretriz brasileira de cardio-oncologia pediátrica da Sociedade Brasileira de Cardiologia

Sociedade Brasileira de Oncologia PediátricaUniversidade Federal de São Paulo (UNIFESP) Instituto de Oncologia Pediátrica GRAACCUniversidade Federal de São Paulo (UNIFESP)Universidade de São Paulo Faculdade de Medicina Instituto do Coração do Hospital das ClínicasUniversidade Federal do Rio Grande do Sul Hospital de Clínicas de Porto AlegreInstituto Materno-Infantil de PernambucoHospital de Base de BrasíliaUniversidade de Pernambuco Hospital Universitário Oswaldo CruzHospital A.C. CamargoHospital do CoraçãoSociedade Brasileira de Cardiologia Departamento de Cardiopatias Congênitas e Cardiologia PediátricaInstituto Nacional de CâncerHospital Pequeno PríncipeSanta Casa de Misericórdia de São PauloInstituto do Câncer do Estado de São PauloUniversidade Federal de São Paulo (UNIFESP) Departamento de PatologiaHospital Infantil Joana de GusmãoUNIFESP, Instituto de Oncologia Pediátrica GRAACCUNIFESP, Depto. de PatologiaSciEL

Vascular flora of the Legado das Águas, Reserva Votorantim, municipalities of Tapiraí, Miracatú and Juquiá, São Paulo, Brazil

We present  a list of vascular plants found in Legado das Águas, Reserva Votorantim, a private reserve having an area of approximately 35,000 ha that spans the municipalities of Tapiraí, Miracatú, and Juquiá, in the state of São Paulo, Brazil. The reserve is part of a complex of state-protected areas including Alto Ribeira Touristic State Park, Intervales State Park , Carlos Botelho State Park, Jurupará State Park, and Serra do Mar State Park. Together, these form an important and large area of continuous and well-preserved forest. Our study, which involved two main floristic surveys in March/April 2013 and April 2014, recorded 768 species, representing 131 families and 432 genera. The majority of species were angiosperms (619) representing 106 families and 370 genera. There were also two species of gymnosperms belonging to two genera in separate families; 147 species of ferns and lycophytes belonging to 23 families and 60 genera. In demonstrating the presence of almost 800 species of plants, of which 16 are threatened, our study highlights the importance of floristic surveys and the critical role of private protected areas in managing and preserving native flora

Twenty-three unsolved problems in hydrology (UPH) – a community perspective

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focussed on process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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