Illuminating the Brain With X-Rays: Contributions and Future Perspectives of High-Resolution Microtomography to Neuroscience

The assessment of three-dimensional (3D) brain cytoarchitecture at a cellular resolution remains a great challenge in the field of neuroscience and constant development of imaging techniques has become crucial, particularly when it comes to offering direct and clear obtention of data from macro to nano scales. Magnetic resonance imaging (MRI) and electron or optical microscopy, although valuable, still face some issues such as the lack of contrast and extensive sample preparation protocols. In this context, x-ray microtomography (μCT) has become a promising non-destructive tool for imaging a broad range of samples, from dense materials to soft biological specimens. It is a new supplemental method to be explored for deciphering the cytoarchitecture and connectivity of the brain. This review aims to bring together published works using x-ray μCT in neurobiology in order to discuss the achievements made so far and the future of this technique for neuroscience

The Antinociceptive and Anti-Inflammatory Activities of Caulerpin, a Bisindole Alkaloid Isolated from Seaweeds of the Genus Caulerpa

The antinociceptive and anti-inflammatory activity of caulerpin was investigated. This bisindole alkaloid was isolated from the lipoid extract of Caulerpa racemosa and its structure was identified by spectroscopic methods, including IR and NMR techniques. The pharmacological assays used were the writhing and the hot plate tests, the formalin-induced pain, the capsaicin-induced ear edema and the carrageenan-induced peritonitis. Caulerpin was given orally at a concentration of 100 μmol/kg. In the abdominal constriction test caulerpin showed reduction in the acetic acid-induced nociception at 0.0945 μmol (0.0103–1.0984) and for dypirone it was 0.0426 μmol (0.0092–0.1972). In the hot plate test in vivo the inhibition of nociception by caulerpin (100 μmol/kg, p.o.) was also favorable. This result suggests that this compound exhibits a central activity, without changing the motor activity (seen in the rotarod test). Caulerpin (100 μmol/kg, p.o.) reduced the formalin effects in both phases by 35.4% and 45.6%, respectively. The possible anti-inflammatory activity observed in the second phase in the formalin test of caulerpin (100 μmol/kg, p.o.) was confirmed on the capsaicin-induced ear edema model, where an inhibition of 55.8% was presented. Indeed, it was also observed in the carrageenan-induced peritonitis that caulerpin (100 μmol/kg, p.o.) exhibited anti-inflammatory activity, reducing significantly the number of recruit cells by 48.3%. Pharmacological studies are continuing in order to characterize the mechanism(s) responsible for the antinociceptive and anti-inflammatory actions and also to identify other active principles present in Caulerpa racemosa

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

Núcleos de Ensino da Unesp: artigos 2008

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq