Membranous nephropathy

ABSTRACT Membranous nephropathy is a glomerulopathy, which main affected target is the podocyte, and has consequences on the glomerular basement membrane. It is more common in adults, especially over 50 years of age. The clinical presentation is nephrotic syndrome, but many cases can evolve with asymptomatic non-nephrotic proteinuria. The mechanism consists of the deposition of immune complexes in the subepithelial space of the glomerular capillary loop with subsequent activation of the complement system. Great advances in the identification of potential target antigens have occurred in the last twenty years, and the main one is the protein “M-type phospholipase-A2 receptor” (PLA2R) with the circulating anti-PLA2R antibody, which makes it possible to evaluate the activity and prognosis of this nephropathy. This route of injury corresponds to approximately 70% to 80% of cases of membranous nephropathy characterized as primary. In the last 10 years, several other potential target antigens have been identified. This review proposes to present clinical, etiopathogenic and therapeutic aspects of membranous nephropathy in a didactic manner, including cases that occur during kidney transplantation

Residual biomass potential of commercial and pre-commercial sugarcane cultivars

Sugarcane (Saccharum spp.) is an efficient and sustainable alternative for energy generation compared to non-renewable sources. Currently, during the mechanized harvest process, the straw left in the field can be used in part for the second generation ethanol and increasing the electric energy production. Thus, this study aimed to provide information on the potential for residual biomass cultivars of sugarcane cropping system. This study provides the following information: yield of straw, depending on the calculated leaf area index and the number of tillers per linear meter; primary energy production of several sugarcane genotypes; contribution of dry tops and leaves; biomass yield; and evaluation of fiber, cellulose, hemicellulose and lignin. Preliminary results obtained by researchers of the State of São Paulo, Brazil, and reCviews related studies are presented. The results suggest that the production of sugarcane straw content varies according to the cultivars; the greater mass of sugarcane straw is in the top leaves and that the potential for the crude energy production of sugarcane per area unit can be increased using fiber-rich species or species that produce more straw. The straw indexes was shown to be a good indicator and allow the estimation of straw volumes generated in a sugarcane crop. The cellulose, hemicellulose and lignin composition in sugarcane is distinct among varieties. Therefore, it is possible to develop distinct biomass materials for energy production and for the development of sugarcane mills using biochemical processes and thermal routes

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

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

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