Differences in the clinical and hormonal presentation of patients with familial and sporadic primary aldosteronism

Purpose: To compare the clinical and hormonal characteristics of patients with familial hyperaldosteronism (FH) and sporadic primary aldosteronism (PA). Methods: A systematic review of the literature was performed for the identification of FH patients. The SPAIN-ALDO registry cohort of patients with no suspicion of FH was chosen as the comparator group (sporadic group). Results: A total of 360 FH (246 FH type I, 73 type II, 29 type III, and 12 type IV) cases and 830 sporadic PA patients were included. Patients with FH-I were younger than sporadic cases, and women were more commonly affected (P = 0.003). In addition, the plasma aldosterone concentration (PAC) was lower, plasma renin activity (PRA) higher, and hypokalemia (P < 0.001) less frequent than in sporadic cases. Except for a younger age (P < 0.001) and higher diastolic blood pressure (P = 0.006), the clinical and hormonal profiles of FH-II and sporadic cases were similar. FH-III had a distinct phenotype, with higher PAC and higher frequency of hypokalemia (P < 0.001), and presented 45 years before sporadic cases. Nevertheless, the clinical and hormonal phenotypes of FH-IV and sporadic cases were similar, with the former being younger and having lower serum potassium levels. Conclusion: In addition to being younger and having a family history of PA, FH-I and III share other typical characteristics. In this regard, FH-I is characterized by a low prevalence of hypokalemia and FH-III by a severe aldosterone excess causing hypokalemia in more than 85% of patients. The clinical and hormonal phenotype of type II and IV is similar to the sporadic case

Transancestral mapping and genetic load in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease with marked gender and ethnic disparities. We report a large transancestral association study of SLE using Immunochip genotype data from 27,574 individuals of European (EA), African (AA) and Hispanic Amerindian (HA) ancestry. We identify 58 distinct non-HLA regions in EA, 9 in AA and 16 in HA (B50% of these regions have multiple independent associations); these include 24 novel SLE regions (Po5 10 8), refined association signals in established regions, extended associations to additional ancestries, and a disentangled complex HLA multigenic effect. The risk allele count (genetic load) exhibits an accelerating pattern of SLE risk, leading us to posit a cumulative hit hypothesis for autoimmune disease. Comparing results across the three ancestries identifies both ancestry-dependent and ancestry-independent contributions to SLE risk. Our results are consistent with the unique and complex histories of the populations sampled, and collectively help clarify the genetic architecture and ethnic disparities in SL

Influence of Antisynthetase Antibodies Specificities on Antisynthetase Syndrome Clinical Spectrum TimeCourse

Introduction: Increased cardiovascular (CV) morbidity and mortality is observed in inflammatory joint diseases (IJDs) such as rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis. However, the management of CV disease in these conditions is far from being well established.Areas covered: This review summarizes the main epidemiologic, pathophysiological, and clinical risk factors of CV disease associated with IJDs. Less common aspects on early diagnosis and risk stratification of the CV disease in these conditions are also discussed. In Europe, the most commonly used risk algorithm in patients with IJDs is the modified SCORE index based on the revised recommendations proposed by the EULAR task force in 2017.Expert opinion: Early identification of IJD patients at high risk of CV disease is essential. It should include the use of complementary noninvasive imaging techniques. A multidisciplinary approach aimed to improve heart-healthy habits, including strict control of classic CV risk factors is crucial. Adequate management of the underlying IJD is also of main importance since the reduction of disease activity decreases the risk of CV events. Non-steroidal anti-inflammatory drugs may have a lesser harmful effect in IJD than in the general population, due to their anti-inflammatory effects along with other potential beneficial effects.This research was partially funded by FOREUM—Foundation for Research in Rheumatolog

Classificação contextual de imagens multiespectrais

This study applies contextual attributes to improve the accuracy of the Gaussian Maximum Likelihood classification of remote sensing images. Therefore, the probabilistic relaxation is tested. Relaxation processes start making a first estimate of the probabilities that relate each pixel to the classes considered in the classification. This estimates are then iteratively updated using the compatibility coefficients. An alternative procedure is introduced, in which the probability values are first filtered using a low-pass filter and then the probabilistic relaxation is used. Tests with synthetic images and real LANDSAT scenes confirm that the accuracy of the classification can be incremented using contextual information.Pages: 328-33

AmazonCRIME: a Geospatial Artificial Intelligence dataset and benchmark for the classification of potential areas linked to Transnational Environmental Crimes in the Amazon Rainforest

[EN] In this article the challenge of detecting areas linked to transnational environmental crimes in the Amazon rainforest is addressed using Geospatial Intelligence data, open access Sentinel-2 imagery provided by the Copernicus programme, as well as the cloud processing capabilities of the Google Earth Engine platform. For this, a dataset consisting of 6 classes with a total of 30,000 labelled and geo-referenced 13-band multispectral images was generated, which is used to feed advanced Geospatial Artificial Intelligence models (deep convolutional neural networks) specialised in image classification tasks. With the dataset presented in this paper it is possible to obtain a classification overall accuracy of 96.56%. It is also demonstrated how the results obtained can be used in real applications to support decision making aimed at preventing Transnational Environmental Crimes in the Amazon rainforest. The AmazonCRIME Dataset is made publicly available in the repository: https://github.com/jp-geoAI/AmazonCRIME.git.[ES] En este artículo es abordado el desafío de detectar áreas vinculadas con crímenes ambientales trasnacionales en la selva amazónica usando datos de Inteligencia Geoespacial, imágenes de libre acceso Sentinel-2 proporcionadas por el programa Copernicus, así como también las capacidades de procesamiento en la nube de la plataforma Google Earth Engine. Para esto, se generó un conjunto de datos que consta de 6 clases con un total de 30.000 imágenes multiespectrales de 13 bandas, etiquetadas y georreferenciadas que es usado para alimentar modelos avanzados de Inteligencia Artificial Geoespacial (redes neuronales convolucionales profundas) especializados en las tareas de clasificación de imágenes. Con el conjunto de datos presentado en este artículo es posible obtener una exactitud global (overall accuracy) de clasificación de 96.56%. Es también demostrado cómo los resultados obtenidos se pueden utilizar en aplicaciones reales para apoyar la toma de decisiones destinadas a prevenir los Crímenes Ambientales Transnacionales en la selva Amazónica. El Conjunto de datos AmazonCRIME se coloca a disposición del público en el repositorio: https://github.com/jp-geoAI/AmazonCRIME.git.Agradecemos al Programa de Posgraduación en Ciencias Geodésicas de la Universidad Federal de Paraná y el apoyo financiero al Consejo Nacional de Desarrollo Científico y Tecnológico de Brasil (CNPq) (190032/2017-0).Pinto-Hidalgo, JJ.; Silva-Centeno, JA. (2022). AmazonCRIME: un conjunto de datos y punto de referencia de Inteligencia Artificial Geoespacial para la clasificación de áreas potenciales vinculadas a Crímenes Ambientales Transnacionales en la Selva Amazónica. Revista de Teledetección. 0(59):1-21. https://doi.org/10.4995/raet.2022.15710OJS121059Abdani, S.R., & Zulkifley, M.A. 2019. 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Illegal Mining: Organized Crime, Corruption and Ecocide in a Resource-Scarce World.

Estimativa de parâmetros de qualidade de água através de técnicas de sensoriamento remoto e métodos de análise multivariada

Pages: 840-84

Estimativa da produção não pontual de poluentes utilizando imagens Landsat e SIG

Nutrients, as phosporus, can cause eutrophication of lakes and, therefore, their sources within the basin must be monitored. The purpose of this study is to apply remote sensing and Geographic Information Systems (GIS) technologies to obtain information about non-point pollution from runoff and its impact in water bodies. This task is performed using a Landsat - TM image, to estimate land-cover parameters, and a GIS to combine them with other informations like topography and soils. The experiment described shows the feasibility of using these techniques as an ancilliary tool for watershed management and environmental protection of lakes. RESUMO: Nutrientes, como fósforo, podem conduzir à eutrofização de lagos e, portanto, suas fontes dentro da bacia são importantes de serem monitoradas. A finalidade deste estudo é aplicar técnicas de sensoriamento remoto e sistemas de informações geográficas (SIG) para obter informações sobre as fontes difusas de poluentes e seu impacto em corpos de água. Isto é efetuado utilizando uma imagem Landsat - TM para estimar parâmetros sobre a cobertura e uso do solo e um SIG para combinar estes dados com outras informações como topografia e pedologia. O experimento descrito comprova a viabilidade do uso destas técnicas como ferramenta auxiliar para o manejo de bacias contribuintes a lagos e para a preservação ambiental destes corpos de água.Pages: 152-15

Produção de uma carta imagem turística e sua disponibilização na Internet

Nowadays, the internet has become one of the most important media in many branches. Specially tourism profits from the internet, since tourism depends on the information that reaches people in other countries or cities. This paper describes the production of a tourist map for the internet. The map integrates satellite imagery and digitized features, since the new digital media turns it possible to augment the amount of information present in a map. In order to improve the visual information, the multispectral bands of a Landsat image were fused with the panchromatic band. The result is a hybrid image, with higher information contents. A map was produced using the image and available vector data. The product was plotted as a conventional map and later used to produce a second version, a map that is available in the internet.Pages: 1077-107