AVALIAÇÃO DA QUALIDADE DE VIDA DOS ACADÊMICOS DE ENGENHARIA DE PRODUÇÃO DA UNOESC

O presente artigo tem por objetivo discorrer e analisar a Qualidade Vida dos acadêmicos de Engenharia de Produção da Universidade do Oeste de Santa Catarina – UNOESC e Qualidade de Vida no Trabalho dos alunos que trabalham e estudam através de um questionário biopsicossocial. Foram questionados hábitos alimentares, frequência de atividade física, regularidade do sono e como é avaliado na sua individualidade seu bem-estar pessoal e no trabalho, também sua inserção pessoal. Ainda é questionado sobre laser e diversão e como o indivíduo avalia sua qualidade de vida. Pode-se perceber que os estudantes estão preocupados em ter uma melhor qualidade de vida, a fim de ter maior satisfação pessoal e profissional.Palavras chaves: qualidade de vida, pesquisa biopsicossocial, estudante, trabalhador, saúde

A POSSE RESPONSÁVEL DE ANIMAIS DOMÉSTICOS EM SÃO GABRIEL

UNIPAMPA SÃO GABRIE

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

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

A prenylated dsRNA sensor protects against severe COVID-19

Inherited genetic factors can influence the severity of COVID-19, but the molecular explanation underpinning a genetic association is often unclear. Intracellular antiviral defenses can inhibit the replication of viruses and reduce disease severity. To better understand the antiviral defenses relevant to COVID-19, we used interferon-stimulated gene (ISG) expression screening to reveal that OAS1, through RNase L, potently inhibits SARS-CoV-2. We show that a common splice-acceptor SNP (Rs10774671) governs whether people express prenylated OAS1 isoforms that are membrane-associated and sense specific regions of SARS-CoV-2 RNAs, or only express cytosolic, nonprenylated OAS1 that does not efficiently detect SARS-CoV-2. Importantly, in hospitalized patients, expression of prenylated OAS1 was associated with protection from severe COVID-19, suggesting this antiviral defense is a major component of a protective antiviral response

Pneumonia estafilocócica adquirida na comunidade

OBJETIVO: A pneumonia estafilocócica geralmente apresenta uma elevada taxa de morbidade e mortalidade. Normalmente ocorre em infecções por influenza (via aerógena) ou durante episódios de bacteremia (via hematogênica). MÉTODOS: Um estudo retrospectivo e descritivo foi realizado com os pacientes que foram admitidos em nosso hospital entre janeiro de 1992 e dezembro de 2003 com diagnóstico de pneumonia adquirida na comunidade causada por Staphylococcus aureus. Todos eles eram maiores de 14 anos e não usuários de drogas endovenosas. RESULTADOS: De um total de 332 casos de pneumonia adquirida na comunidade, foram encontrados 24 pacientes (7,3%) com pneumonia estafilocócica. A idade mínima e máxima eram de, respectivamente, 14 anos e 89 anos. Quinze pacientes eram homens e nove eram mulheres. Doze pacientes preenchiam critérios para pneumonia grave. O radiograma de tórax evidenciou consolidação unilateral em 14 casos, bilateral em 10, derrame pleural em 15, rápida progressão radiológica das lesões pulmonares em 14, presença de cavitação em 6 e pneumotórax em 1 paciente. A maioria dos pacientes apresentou co-morbidades e diabetes mellitus foi a mais freqüente. Doze pacientes apresentaram complicações como empiema e choque séptico. Houve quatro óbitos, o que representou 16,6% da amostra. CONCLUSÕES: A apresentação clínica da pneumonia causada por S. aureus é similar à apresentação das pneumonias originadas por outros agentes etiológicos. Os achados radiológicos, os dados epidemiológicos e os fatores de risco fornecem importantes indícios para o diagnóstico. Estes fatores são importantes para uma suspeição clínica, já que o S. aureus normalmente não é incluído nos tratamentos empíricos