AVALIAÇÃO DA FORÇA DE EXPANSÃO DE PROTÓTIPOS STENTS ARTERIAIS

Objective: Several metal stents have been developed in the last years. There are great  differences concerning their mechanical properties. Aiming at evaluating the performance of the prototype stents, a device and a procedure to obtain curves of Expansion Power (F) X Relative Strain (ε) of these stents were developed.Materials and Methods: Three different stents were chosen to undergo compression analysis: the Talent stent, the X stent prototype, and the Z stent prototype. To determine the F X ε curves of the stents, the Force X Displacement curves of each stent were obtained with the compression device and, based on these figures, the resulting deformation was calculated.Results: The force level presented by the Talent stent was the highest (4.35 N for ε = 0.30) and the X stent prototype presented the lowest force level (0.19 N for ε = 0.30).Conclusions: The results presented show that a reformulation of mechanical characteristics of the X stent prototype is necessary for a more satisfactory performance. The main factors which make the force level presented by this prototype to be so low are its geometric configuration and the diameter of the thread used in its construction.Objetivos: Vários stents de metal foram desenvolvidos nos últimos anos. Há grandes diferenças entre as propriedades mecânicas dos mesmos. Buscando-se avaliar o desempenho de stents protótipos, foram desenvolvidos um equipamento e um procedimento para obtenção de curvas Força de Expansão (F) X Deformação Relativa (ε) dos mesmos.Materiais e Métodos: Três stents diferentes foram escolhidos para proceder a uma análise de compressão: o stent da Talent, o X stent protótipo e o Z stent protótipo. Para determinar as curvas de F X ε dos stents, obteve-se, primeiramente, a curva Força X Deslocamento dos mesmos com o auxílio do dispositivo de compressão construído e, a partir destes valores, calculou-se a deformação resultante.Resultados: O nível de forças apresentado pelo stent da Talent foi o maior (4,35 N para um ε = 0,30) e o X stent protótipo foi o que apresentou o menor nível de forças (0,19 N para um ε = 0,30).Conclusões: Os resultados apresentados mostram que uma reformulação nas características mecânicas do X stent protótipo é necessária para uma ação mais satisfatória do mesmo. Os principais fatores que levam a força de expansão apresentada por este protótipo a ser tão baixa são a sua configuração geométrica e o diâmetro do fio utilizado em sua construção

Nasal polyposis : more than a chronic inflammatory disorder : a disease of mechanical dysfunction : the São Paulo position

Introduction The importance of our study lies in the fact that we have demonstrated the occurrence of mechanical dysfunction within polypoid tissues, which promotes the development of polyps in the nasal cavity. Objective To change the paradigm of nasal polyposis (NP). In this new conception, the chronic nasal inflammatory process that occurs in response to allergies, to pollution, to changes in the epithelial barrier, or to other factors is merely the trigger of the development of the disease in individuals with a genetic predisposition to an abnormal tissue remodeling process, which leads to a derangement of the mechanical properties of the nasal mucosa and, consequently, allows it to grow unchecked. Data Synthesis We propose a fundamentally new approach to intervening in the pathological process of NP, addressing biomechanical properties, fluid dynamics, and the concept of surface tension. Conclusion The incorporation of biomechanical knowledge into our understanding of NP provides a new perspective to help elucidate the physiology and the pathology of nasal polyps, and new avenues for the treatment and cure of NP

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

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