An Underactuated Wearable Robotic Glove Driven by Myoelectric Control Input / Uma luva robótica vestível subatuada acionada por entrada de controle mioelétrico

People who have hand impairments caused by the most common neurological and degenerative musculoskeletal diseases face trouble to achieve their everyday tasks. To try to help these people, in this works is presented a prototype of a glove-like orthosis for upper limbs. It is an underactuated robotic glove controlled by myoeletric input signals collected by the Myo armband. The development and its details are all described so that it can be reproduced with improvements and used as an assistive device. To the authors' knowledge, in Brazil, there is no one similar orthosis such this one developed thus far

Immunity and vaccine development efforts against Trypanosoma cruzi

Artículo de revisión especializadoTrypanosoma cruzi (T. cruzi) is the causative agent for Chagas disease (CD). There is a critical lack of methods for prevention of infection or treatment of acute infection and chronic disease. Studies in experimental models have suggested that the protective immunity against T. cruzi infection requires the elicitation of Th1 cytokines, lytic antibodies and the concerted activities of macrophages, T helper cells, and cytotoxic T lymphocytes (CTLs). In this review, we summarize the research efforts in vaccine development to date and the challenges faced in achieving an efficient prophylactic or therapeutic vaccine against human CD.UTM

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