Kinin B(1) receptor deficiency leads to leptin hypersensitivity and resistance to obesity

OBJECTIVE-Kinins mediate pathophysiological processes related to hypertension, pain, and inflammation through the activation of two G-protein-coupled receptors, named B(1) and B(2). Although these peptides have been related to glucose homeostasis, their effects on energy balance are still unknown.RESEARCH DESIGN and METHODS-Using genetic and pharmacological strategies to abrogate the kinin B(1) receptor in different animal models of obesity, here we present evidence of a novel role for kinins in the regulation of satiety and adiposity.RESULTS-Kinin B(1) receptor deficiency in mice (B(1)(-/-)) resulted in less fat content, hypoleptinemia, increased leptin sensitivity, and robust protection against high-fat diet-induced weight gain. Under high-fat diet, B(1)(-/-) also exhibited reduced food intake, improved lipid oxidation, and increased energy expenditure. Surprisingly, B(1) receptor deficiency was not able to decrease food intake and adiposity in obese mice lacking leptin (ob/ob-B(1)(-/-)). However, ob/ob-B(1)(-/-) mice were more responsive to the effects of exogenous leptin on body weight and food intake, suggesting that B(1) receptors may be dependent on leptin to display their metabolic roles. Finally, inhibition of weight gain and food intake by B(1) receptor ablation was pharmacologically confirmed by long-term administration of the kinin B(1) receptor antagonist SSR240612 to mice under high-fat diet.CONCLUSIONS-Our data suggest that kinin B(1) receptors participate in the regulation of the energy balance via a mechanism that could involve the modulation of leptin sensitivity.Universidade Federal de São Paulo, Dept Biophys, BR-04023062 São Paulo, BrazilUniv Mogi das Cruzes, Mogi Das Cruzes, BrazilUniversidade Federal de São Paulo, Dept Physiol, BR-04023062 São Paulo, BrazilSanofi Aventis, Montpellier, FranceUniversidade Federal de São Paulo, Dept Med, BR-04023062 São Paulo, BrazilInst Natl Sante & Rech Med, Dept Renal & Cardiac Remodeling, U858 I2MR, Toulouse, FranceUniv Toulouse 3, Inst Med Mol Rangueil, F-31062 Toulouse, FranceInst Natl Rech Agron AgroParisTech, UMR914 Nutr Physiol & Ingest Behav, Paris, FranceMax Delbruck Ctr Mol Med, Berlin, GermanyUniversidade Federal de São Paulo, Dept Biophys, BR-04023062 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Physiol, BR-04023062 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Med, BR-04023062 São Paulo, BrazilWeb of Scienc

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

Benthic estuarine communities in Brazil: moving forward to long term studies to assess climate change impacts

Abstract Estuaries are unique coastal ecosystems that sustain and provide essential ecological services for mankind. Estuarine ecosystems include a variety of habitats with their own sediment-fauna dynamics, all of them globally undergoing alteration or threatened by human activities. Mangrove forests, saltmarshes, tidal flats and other confined estuarine systems are under increasing stress due to human activities leading to habitat and species loss. Combined changes in estuarine hydromorphology and in climate pose severe threats to estuarine ecosystems on a global scale. The ReBentos network is the first integrated attempt in Brazil to monitor estuarine changes in the long term to detect and assess the effects of global warming. This paper is an initial effort of ReBentos to review current knowledge on benthic estuarine ecology in Brazil. We herein present and synthesize all published work on Brazilian estuaries that has focused on the description of benthic communities and related ecological processes. We then use current data on Brazilian estuaries and present recommendations for future studies to address climate change effects, suggesting trends for possible future research and stressing the need for long-term datasets and international partnerships

Development and analysis of the Soil Water Infiltration Global database

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it