Perivascular malignant epithelioid cell tumor (PEComa) of the uterus:: a case report

Perivascular epithelioid cell tumors, called PEComas, have a mesenchymal origin with immunoreactivity for melanocytic and smooth muscle markers. Its incidence in the form of uterine involvement is rare, between 1 and 2 cases per million inhabitants, affecting mainly women in their fifth decade of life. The present study was elaborated according to the rules of the CARE case report. The patient's medical record was analyzed, and who authorized access to it and signed the Free and Informed Consent Form, together with those involved in this work. This patient underwent treatment and medical follow-up with the supervisor of this work. Therefore, this study aimed to describe a rare clinical case report of uterine malignant perivascular epithelioid cell tumor (PEComa). Although the literature on this subject is scarce and there are no consistent criteria for diagnosis and treatment, our case in question presented aspects of unfavorable evolution (a large number of cytological atypia and high mitotic index) characterizing a PEComa with uncertain malignant potential, requiring a treatment adjuvant after surgery. The patient evolved well after the surgery and adjuvant treatment, undergoing quarterly follow-ups at the oncology and gynecology outpatient clinic, with a physical examination and nuclear magnetic resonance of the pelvis for control purposes

Manifesto à cidade de Ponta Delgada dos arquitetos e estudantes de arquitetura micaelense

Os micaelenses sabem-no já: o importante conjunto da nova praça lado-sul da matriz, está projectado e vai erguer-se em moldes pombalinos!... A incongruência e o absurdo de uma tal proposição sente-o todo e qualquer leigo; basta para tanto boa fé e um pouco de bom senso

EVOLUÇÃO DO PERFIL CLÍNICO E EPIDEMIOLÓGICO DA TUBERCULOSE NO NORTE E NORDESTE BRASILEIRO: 2018- 2023

Tuberculosis (TB) is a disease caused by Mycobacterium tuberculosis. It is transmitted through the inhalation of aerosols and leads to a granulomatous infection in the lower respiratory tract. Patients with TB present with a clinical picture characterized by: fever, weakness, anorexia, weight loss and symptoms specific to the affected area. In view of this, TB can be classified into two forms: pulmonary and extrapulmonary. This is an ecological, descriptive, retrospective and quantitative study based on secondary data obtained from the Informatics Department of the Unified Health System (DATASUS). The study evaluated confirmed cases of Tuberculosis in the population of the North and Northeast of the country, between 2018 and 2023. The total number of confirmed cases of Tuberculosis in the North and Northeast of Brazil, between 2018 and 2023, was 222,594 cases, the population affected by tuberculosis, in the North and Northeast of Brazil, between 2018 and 2023, are men, between 20 and 39 years old, brown, residents of the Northeast region of the country, presenting the form of pulmonary tuberculosis and evolving to cure. There is a need for further studies on the prevalence of Tuberculosis in the northern and northeastern population, for the development of public policies to control this disease.  A tuberculose (TB) é uma doença que tem como agente etiológico o Mycobacterium tuberculosis.É transmitida através da inalação de aerossóis e conduz uma infecção granulomatosa  no trato respiratório inferior. Os pacientes com TB apresentam um quadro clínico caracterizado por: febre, adinamia, anorexia, emagrecimento e sintomas específicos do local em que foi acometido. À vista disso, tem-se que a TB pode ser classificada em duas formas: pulmonar e extrapulmonar. Trata-se de um estudo ecológico ,descritivo,retrospectivo e quantitativo com base em dados secundários obtidos no Departamento de  Informática do Sistema Único de Saúde (DATASUS).O estudo avaliou os casos confirmados de Tuberculose,na população do Norte e Nordeste do país, entre 2018 e 2023.O total de casos confirmados de Tuberculose , no Norte e Nordeste do Brasil, entre 2018 e 2023, foi de 222.594 casos, a população afetada pela tuberculose , no Norte e Nordeste do Brasil, entre 2018 e 2023, são homens, entre 20 e 39 anos, pardos, residentes da região Nordeste do país, apresentando a forma de tuberculose pulmonar e evoluindo para cura.Nota-se a necessidade de mais estudos acerca da prevalência da Tuberculose na população nortista e nordestina, para o desenvolvimento de políticas públicas de controle dessa doença

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

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

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

Forest harvest management systems and residual phytomass affecting physical properties of a sandy soil

Organic carbon introduced in soils, mainly through organic matter, has a relevant role in various soil properties and is particularly important in sandy soils. In these soils, the input of organic material is necessary to ensure the sustainability of production systems. This study aimed to investigate the changes in total organic carbon content and its effect on physical properties in areas under different harvest management systems (HMS) after the harvest of eucalyptus. The study was performed in December 2017 in a Eucalyptus urograndis (clone E13) commercial plantation, in the municipality of Água Clara, Mato Grosso do Sul State, Brazil. The soil of this area was classified as a sandy-textured Neossolo quartzarênico, which corresponds to Quartzipsamments. Soil samples were taken from the 0.00-0.05, 0.05-0.10 and 0.10-0.20 m layers for determinations of aggregate stability, soil bulk density (BD), macroporosity (Macro), microporosity (Micro), total porosity (TP) and total organic carbon (TOC); and for calculation of carbon stock (CS). Total organic carbon and CS continued down into the 0.20-0.40, 0.40-0.60, 0.60-0.80, and 0.80-1.00 m layers. Soil mechanical penetration resistance (PR) was determined to the 0.40 m depth in 0.10 m intervals. Carbon content was evaluated in the aggregates of the 0.00-0.05 m layer after wet sieving in 2000, 1000, 250 and 53 μm diameter sieves. Statistical evaluation consisted of analysis of variance, the Tukey test, and regression for the sources of variation that showed significance at 5 %. The data suggest that keeping the residual phytomass on the soil surface can positively impact total organic carbon, with a smaller reduction under the cut-to-length harvest management system. However, carbon stock is greater at the layer of 0.20-0.60 m; as the soil has a sandy texture, carbon moves through the soil profile, which has lower soil mechanical penetration resistance at the surface layers (0.00-0.10 m), once more under the cut-to-length system. Maintaining crop residual phytomass on the soil surface in the cut-to-length harvest management system provides better soil physical conditions, with greater macroporosity (0.00-0.05 m), aggregates with more carbon, and lower soil mechanical penetration resistance compared to systems that maintain only part of the harvest residual phytomass or no residual phytomass on the surface

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data