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

Effect of the Copaifera langsdorffii Desf. Leaf Extract on the Ethylene Glycol-Induced Nephrolithiasis in Rats

The potential of the Copaifera langsdorffii leaves extract to prevent stone formation was analyzed by means of an ethylene glycol (EG) animal model of nephrolithiasis and an in vitro crystallization assay. Different doses of the C. langsdorffii leaves extract were administered to rats treated with EG. Urine biochemical parameters were quantified. CaOx deposits count and analysis of osteopontin expression were conducted on kidneys fixed in formalin. The in vitro assay was performed by turbidimetry. Phytochemical analyses of the extract were accomplished by HPLC-UV-DAD, and several compounds were isolated. C. langsdorffii leaf extract was able to avoid stone formation. The number of deposits was 50.30±31.29 at the higher extract dose, compared to the value of 179.5±45.96 achieved with the EG control. Significantly lower oxalate levels and OPN expression and increased citrate levels were observed after extract administration. In the in vitro assay, the extract diluted the formed crystals. Phytochemical analyses showed that the extract is rich in phenolic compounds that are capable of preventing stone formation. Thus, on the basis of our results, we suggest that the C. langsdorffii leaf extract has potential application in the prevention of kidney stone formation

A cidade de São Paulo e a era dos melhoramentos materiaes: Obras públicas e arquitetura vistas por meio de fotografias de autoria de Militão Augusto de Azevedo, datadas do período 1862-1863

The first photographs of São Paulo, taken by Militão Augusto de Azevedo between\ud 1862 and 1863, are always cited as documentary evidence of the citys backwardness,\ud deterioration, and lethargy in the mid 19th century. However, our view is that things were\ud quite different, based on a reading of prime sources dating back to that period. In fact, the\ud architecture and urban spaces of São Paulo already showed clear signs of modernization\ud between the years 1850 and 1860, as depicted in Azevedos photographs, which belong\ud to the collection of Paulista Museum and also of the Iconography and Museums Division of\ud the São Paulo Heritage Department