A cirurgia robótica e o processo de enfermagem no período perioperatório: revisão integrativa

 Objective: To know the scientific production on the nursing process facing robotic surgery in the perioperative period. Method: Integrative review, search in databases: US National Library of Medicine National Institutes of Health, Virtual Health Library and Cumulative Index to Nursing and Allied Health Literature, carried out between June and July 2021; 10 selected articles met the inclusion criteria. Results: Articles published in Brazilian journals predominated, with 06 articles in Portuguese, 03 in English and 01 article in Spanish. Two categories were identified where the nursing work process is inserted, assistance, with a focus on the intraoperative period, and management, with actions for the implementation of robotic surgery. Conclusion: The scientific literature is still very focused on issues of surgical techniques, however it is possible to observe a discreet movement in Brazilian nursing in recent years, with few publications on the role of nursing in robotic surgery.Objetivo: Conhecer a produção científica sobre o processo de enfermagem frente à cirurgia robótica no perioperatório. Método: Revisão integrativa, busca nas bases de dados: US National Library of Medicine National Institutes of Health, Biblioteca Virtual em Saúde e Cumulative Index to Nursing and Allied Health Literature, realizada entre junho e julho de 2021; 10 artigos selecionados atendiam aos critérios de inclusão. Resultados:  Predominaram artigos publicados em periódicos brasileiros, com 06 artigos no idioma português, 03 no inglês e 01 artigo no espanhol. Identificou-se duas categorias onde o processo de trabalho da enfermagem está inserido, a assistencial, com foco no intraoperatório e a gerencial com ações para a implementação da cirurgia robótica. Conclusão: A literatura científica ainda é muito voltada para questões de técnicas cirúrgicas, entretanto é possível observar um movimento tímido da enfermagem brasileira nos últimos anos, com discretas publicações sobre a atuação da enfermagem frente à cirurgia robótica

Population Genetics of GYPB and Association Study between GYPB*S/s Polymorphism and Susceptibility to P. falciparum Infection in the Brazilian Amazon

Merozoites of Plasmodium falciparum invade through several pathways using different RBC receptors. Field isolates appear to use a greater variability of these receptors than laboratory isolates. Brazilian field isolates were shown to mostly utilize glycophorin A-independent invasion pathways via glycophorin B (GPB) and/or other receptors. The Brazilian population exhibits extensive polymorphism in blood group antigens, however, no studies have been done to relate the prevalence of the antigens that function as receptors for P. falciparum and the ability of the parasite to invade. Our study aimed to establish whether variation in the GYPB*S/s alleles influences susceptibility to infection with P. falciparum in the admixed population of Brazil.Two groups of Brazilian Amazonians from Porto Velho were studied: P. falciparum infected individuals (cases); and uninfected individuals who were born and/or have lived in the same endemic region for over ten years, were exposed to infection but have not had malaria over the study period (controls). The GPB Ss phenotype and GYPB*S/s alleles were determined by standard methods. Sixty two Ancestry Informative Markers were genotyped on each individual to estimate admixture and control its potential effect on the association between frequency of GYPB*S and malaria infection.GYPB*S is associated with host susceptibility to infection with P. falciparum; GYPB*S/GYPB*S and GYPB*S/GYPB*s were significantly more prevalent in the in the P. falciparum infected individuals than in the controls (69.87% vs. 49.75%; P<0.02). Moreover, population genetics tests applied on the GYPB exon sequencing data suggest that natural selection shaped the observed pattern of nucleotide diversity.Epidemiological and evolutionary approaches suggest an important role for the GPB receptor in RBC invasion by P. falciparum in Brazilian Amazons. Moreover, an increased susceptibility to infection by this parasite is associated with the GPB S+ variant in this population

Prediction of risk and incidence of dry eye in critical patients

Objectives: to estimate the incidence of dry eye, to identify risk factors and to establish a risk prediction model for its development in adult patients admitted to the intensive care unit of a public hospital. Method: concurrent cohort, conducted between March and June, 2014, with 230 patients admitted to an intensive care unit. Data were analyzed by bivariate descriptive statistics, with multivariate survival analysis and Cox regression. Results: 53% out of 230 patients have developed dry eye, with onset mean time of 3.5 days. Independent variables that significantly and concurrently impacted the time for dry eye to occur were: O2 in room air, blinking more than five times per minute (lower risk factors) and presence of vascular disease (higher risk factor). Conclusion: dry eye is a common finding in patients admitted to adults intensive care units, and care for its prevention should be established

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