Reconceptualizing the Periaqueductal Grey: Fear, Anxiety and Motivational Systems in an Ancient Structure

The periaqueductal grey (PAG) is classically seen as a region responsible for the control of defensive reactions. This thesis provides a detailed review of anatomical and functional data on the different parts of the PAG together with the dorsal raphe. Based on anatomical features, this thesis proposes a new subdivision of the PAG that accounts for the distinct characteristics of the area. I provide a comprehensive functional view of the PAG, going beyond simple panic and escape to integrate data on fear, anxiety, and depression. Importantly, I conclude that this periaqueductal cluster of nuclei is broadly involved in motivated behavior controlling not only aversive but also appetitive behavior and with some involvement in more complex motivational processes such as approach-avoidance conflict resolution. To test some of these hypotheses, I present experimental evidence showing that the PAG can produce an anxiety-like signal in the forebrain, and compare it to the signal evoked by reticular stimulant. Furthermore, I explore the effect of pharmacological interventions in tegmental areas and how these impact PAG- and RPO-evoked responses. In sum, I propose that the PAG is a highly conserved region surrounding the aqueduct and it appears to be the simplest, foundational, element of controlling integrated motivated goal-directed behaviors of all types

Modulatory effect of diphenyl diselenide in Carioca High- and Low-conditioned Freezing rats

AbstractDiphenyl diselenide ([PhSe]2)is an organoselenium compound that has interesting pharmacological properties, including antioxidant, glutathione peroxidase-mimetic, and neuroprotective effects. The objective of the present study was to investigate the possible modulatory effect of (PhSe)2 in 17th-generation Carioca high-and low-conditioned freezing (CHF and CLF) rats, an animal model of generalized anxiety disorders. (PhSe)2 was administered at three doses (10, 50, and 100mg/kg) in CHF and CLF rats, and their anxiety-like profiles (conditioned freezing patterns) were measured before and 30min after treatment. A significant difference was found in freezing scores between CHF and CLF animals before treatment (t70=12.50, p<0.001). Treatment with (PhSe)2 at 10 and 50mg/kg decreased freezing in CHF rats but significantly increased freezing at 100mg/kg. (PhSe)2 increased freezing in CLF animals at 50 and 100mg/kg (p<0.01). These results indicate that (PhSe)2 exerts both anxiolytic- and anxiogenic-like effects in bi-directional rat lines. Distinct genetic profiles of the CHF and CLF lines may influence biochemical functions and lead to differential responses to aversive situations and various drugs like (PhSe)2

Genetic Risk Factors and Lysosomal Function in Parkinson Disease

Parkinson disease is a complex disease that has multiple genetic and environmental factors. To achieve the early diagnosis and to be able to modify the disease progression, efforts are being made to identify individuals at risk. About 20 year ago, an evidence of major prevalence of Parkinsonism in patients with Gaucher Disease reported by studies worldwide led to the putative involvement of the GBA gene. Nowadays, the link from a rare disease with a common disease is well known and it is confirmed that mutations in the GBA gene are the most important genetic risk factor. Apart from rare mutations, genetic association studied appointed common variants in genes well associated with familial cases as LRRK2 and SNCA may also contribute to the increased risk for sporadic cases. Other common variants in the MAPT gene were also reported. At least, genetic studies have been observed an excessive burden of relevant variants in genes with lysosomal function. Thus, a synergistic action of variants in genes that codifies proteins involved with the lysosome may be a mean of modulating the risk. In this chapter, we review the most robust genetic risk factor and the relevance of lysosomal function for Parkinson disease

Recognition of the genus Thaumatophyllum Schott − formerly Philodendron subg. Meconostigma (Araceae) − based on molecular and morphological evidence

Philodendron subgenus Meconostigma has been a well-circumscribed group since 1829. Members of this group are easily distinguished by diagnostic morphological characters as well as by a distinct ecology and geographical distribution. Based on molecular, morphological and cytological evidence, we propose the recognition of P. subg. Meconostigma as a distinct genus, Thaumatophyllum Schott. We also present the necessary new combinations, an emended key and some nomenclatural and taxonomic corrections regarding 21 names of Thaumatophyllum

6ª Diretriz de monitorização ambulatorial da pressão arterial e 4ª diretriz de monitorização residencial da pressão arterial

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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