Tonsil fibromatosis

UNIFESP-EPM Departamento de Otorrinolaringologia e Cirurgia de Cabeça e PescoçoUNIFESP-EPM Clínica de Otorrinolaringologia PediátricaUNIFESP, EPM, Depto. de Otorrinolaringologia e Cirurgia de Cabeça e PescoçoUNIFESP, EPM Clínica de Otorrinolaringologia PediátricaSciEL

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. Please cite this Data Paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. © 2018 by the The Authors. Ecology © 2018 The Ecological Society of Americ

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Criação de modelo virtual individualizado do osso temporal humano para impressão tridimensional

Dissection of the temporal bone is a fundamental part in otological training. Traditionally this training is done with temporal bones from cadavers, but currently the legal acquisition of these bones is quite complex and troublesome. At the same time, the otologic surgeon does not have a reliable way to simulate in advance the surgical procedure, since even owning an anatomical part, the difference in anatomy between individuals, creates a unique need every patient. Objective: Get custom virtual models of bones time that could be used for rapid prototyping printers to create physical models using digital tools available to any public, following defined steps. Method: We use 10 CT scans of the temporal bones of patients without ear disease, in DICOM format, with number of slices ranging from 186 to 320. In them we evaluated the presence of pre-defined anatomical structures. We employed the programs InVesalius to create the virtual model of the temporal bones, Blender to remove artifacts and Private NetFabb for optimizing models for 3D printing. Results: Of the anatomical structures sought in 10 CT scans, the stapes bone and the facial nerve canal were not always present on the images of the exams. In InVesalius program were made the reconstruction of all bone structures present in 10 CT scans; gray scale was used, which average values for the 10 reconstructions were -466 for the dark tones and 2700 for light. In the 3 CT scans that had 186 cuts, the reconstructions were not satisfactory. Still in this program was made the delimitation of the temporal bones. All reconstructions showed structural artifacts and errors. In the program Blender 3D was possible to remove all artifacts from the 7 satisfactory reconstructions. The NetFabb Private program, after analysing the models, identified and corrected structural errors in the 7 reconstructions, optimizing them for three-dimensional printing. Conclusion: It is possible to get custom virtual models of human temporal bone for actual three-dimensional printing using digital tools, following defined steps.A dissecção do osso temporal é parte fundamental no treinamento cirúrgico otológico. Tradicionalmente este treinamento é feito com ossos temporais de cadáveres, mas atualmente a aquisição legal destes ossos é bastante complexa e dificultosa. Ao mesmo tempo, o cirurgião otológico não tem uma forma confiável de simular antecipadamente o procedimento cirúrgico, visto que mesmo em posse de peça anatômica, a diferença na anatomia entre indivíduos, cria uma necessidade singular a cada paciente Objetivo: Obter modelos virtuais personalizados de ossos temporais que possam ser utilizados por impressoras de prototipagem rápida na criação de modelos físicos, utilizando ferramentas digitais disponíveis a qualquer público, seguindo etapas definidas. Método: Utilizamos 10 tomografias computadorizadas de ossos temporais de pacientes sem doença otológica em formato DICOM, com número de cortes variando de 186 a 320. Nelas avaliamos a presença de estruturas anatômicas pré-definidas. Foram empregados os programas InVesalius para criar o modelo virtual dos ossos temporais, Blender para remoção de artefatos e NetFabb Private para a otimização dos modelos para impressão 3D. Resultados: Das estruturas anatômicas procuradas nas 10 tomografias, o osso estribo e o canal do nervo facial nem sempre estavam presentes nas imagens do exame. No programa InVesalius fez-se a reconstrução de todas as estruturas ósseas presentes nas 10 tomografias; foi utilizada escala de cinza, cuja média dos valores para as 10 reconstruções foram -466 para os tons escuros e 2700 para os claros. Nas 3 tomografias que possuíam 186 cortes as reconstruções não foram satisfatórias. Ainda neste programa fez-se a delimitação dos ossos temporais. Todas as reconstruções apresentaram artefatos e erros estruturais. No programa Blender 3D foi possível fazer a remoção de todos os artefatos das 07 reconstruções satisfatórias. O programa NetFabb Private, após a análise dos modelos, identificou e corrigiu erros estruturais nas 07 reconstruções, otimizando-as para impressão tridimensional. Conclusão: É possível obter modelos virtuais personalizados de osso temporal humano para impressão tridimensional de modelo real utilizando ferramentas digitais, seguindo etapas definidas.Dados abertos - Sucupira - Teses e dissertações (2013 a 2016

Vocal Tract Discomfort and Risk Factors in University Teachers

Objectives. To characterize the presence of and risk factors for throat pain or irritation among male and female university teachers in private institutions within the city of Sao Paulo. Study Design. This is a cross-sectional survey. Methods. Voice self-evaluation forms prepared by the Brazilian Ministry of Labor were administered to 846 university teachers in a private institution in the city of Sao Paulo, Brazil. Results. The prevalence of throat pain or irritation was 50.8% and was higher in the women (62.7%) than in the men (43.5%). The prevalence of throat pain or irritation was higher among professionals <= 60 years old and among those who spent most of their time teaching compared with those who spent most of their time performing other professional activities. Other factors, such as noise and sound competition, air pollution, stress and anxiety, personal habits, and lifestyle/quality of life, were related to the presence of throat pain or irritation. Conclusions. University teachers demonstrated a high prevalence of throat pain or irritation. Factors such as age <= 60 years, female gender, time-consuming professional activities, noise and sound competition in the work environment, stress and anxiety, air pollution, access to water, personal habits, and lifestyle/quality of life were related to the presence of throat pain or irritation.Univ Fed Sao Paulo, Dept Otolaryngol Head & Neck Surg, Sao Paulo, BrazilUniv Fed Sao Paulo, Dept Otolaryngol Head & Neck Surg, Sao Paulo, BrazilWeb of Scienc