7 research outputs found
OcorrĂŞncia e tratamento de miĂases cutâneas em ovinos criados em condições semiáridas no norte de Minas Gerais
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
Strontium Carbonate and Strontium-Substituted Calcium Carbonate Nanoparticles Form Protective Deposits on Dentin Surface and Enhance Human Dental Pulp Stem Cells Mineralization
Strontium acetate is applied for dental hypersensitivity treatment; however, the use of strontium carbonates for this purpose has not been described. The use of Sr-carbonate nanoparticles takes advantage of both the benefits of strontium on dentin mineralization and the abrasive properties of carbonates. Here in, we aimed to synthesize strontium carbonate and strontium-substituted calcium carbonate nanoparticles and test them as potential compounds in active dentifrices for treating dental hypersensitivity. For this, SrCO3, Sr0.5Ca0.5CO3, and CaCO3 nanoparticles were precipitated using Na2CO3, SrCl2, and/or CaCl2 as precursors. Their morphology and crystallinity were evaluated by electron microscopy (SEM) and X-ray diffraction, respectively. The nanoparticles were added to a poly (vinyl alcohol) gel and used to brush dentin surfaces isolated from human third molars. Dentin chemical composition before and after brushing was investigated by infrared spectroscopy (FTIR) and X-ray dispersive energy spectroscopy. Dentin tubule morphology, obliteration, and resistance of the coatings to acid attack were investigated by SEM and EDS. The cytotoxicity and ability of the particles to trigger the mineralization of hDPSCs in vitro were studied. Dentin brushed with the nanoparticles was coated by a mineral layer that was also able to penetrate the tubules, while CaCO3 remained as individual particles on the surface. FTIR bands related to carbonate groups were intensified after brushing with either SrCO3 or Sr0.5Ca0.5CO3. The shift of the phosphate-related FTIR band to a lower wavenumber indicated that strontium replaced calcium on the dentin structure after treatment. The coating promoted by SrCO3 or Sr0.5Ca0.5CO3 resisted the acid attack, while calcium and phosphorus were removed from the top of the dentin surface. The nanoparticles were not toxic to hDPSCs and elicited mineralization of the cells, as revealed by increased mineral nodule formation and enhanced expression of COL1, ALP, and RUNX2. Adding Sr0.5Ca0.5CO3 as an active ingredient in dentifrices formulations may be commercially advantageous since this compound combines the well-known abrasive properties of calcium carbonate with the mineralization ability of strontium, while the final cost remains between the cost of CaCO3 and SrCO3. The novel Sr0.5Ca0.5CO3 nanoparticles might emerge as an alternative for the treatment of dental hypersensitivity
AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest
The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data