Validação da curva de calibração (linearidade e homocedasticidade) do ?-pineno por cromatografia em fase gasosa com detecção por ionização em chama (CG-DIC) no óleo essencial de Schinus Terebenthifolius Raddi / Validation of the calibration curve (linearity and homocedasticity) of ?-pinene by gas chromatography with flame ionization detection (CG-DIC) in the essential oil of Schinus Terebenthifolius Raddi

A espécie Schinus terebenthifolius Raddi. (Aroeira) é bastante conhecida por apresentar diversas atividades biológicas. Alguns autores descrevem que o a- pineno é o componente majoritário presente no óleo essencial dos frutos de S. terebenthifolius. Apesar da importância econômica e biológica do a- pineno verificamos na literatura a ausência de métodos analíticos que validem intralaboratorial, sob diferentes condições, em um intervalo de tempo justificado a função de calibração. Este trabalho teve como objetivo avaliação de linearidade e homocedasticidade através da preparação de três curvas de calibração em três dias distintos afim de verificar possíveis diferenças de comportamento linear do a-pineno, do óleo essencial de S. terebenthifollius, com variação diária da análise, um dos requisitos mínimos para a validação de métodos analíticos. Verificamos que porcentagem do ?-pineno presente neste óleo essencial foi de 25,4 % ± 0,7. O teste de Levene indicou homogeneidade duvidosa dos dados do segundo dia e variâncias constantes no primeiro e terceiro dia de análise. A distribuição de probabilidade apresentou-se normal somente para o primeiro dia de avaliação. A regressão se mostrou significativa para os três dias de avaliação. Verificamos também que a linearidade foi comprovada na faixa de concentração avaliada, porém através do modelo linear obtido pelo MMQP. Concluímos que para cada dia de avaliação do óleo essencial deve-se preparar uma curva de calibração para quantificação do a- pineno, devido a significância estatística do intercepto em um dos três dias de avaliação. 

Os aspectos atuais epidemiológicos e clínicos da Monkeypox: uma revisão de literatura

Neste artigo propomos um estudo que visa entender a fisiopatologia da Varíola dos Macacos, bem como seu quadro clínico e sua epidemiologia atual. Revisão de literatura de caráter exploratório, com uma avaliação de pesquisas e casos da prática clínica, em que se fez uma análise da epidemiologia da Varíola dos Macacos e seu quadro clínico. Foram selecionados 31 estudos para compor essa revisão de literatura. Entre as bases de dados selecionadas estão: PubMed, BVS, Google Scholar e SciELO. A análise das pesquisas mostrou uma ascensão da Monkeypox por todo o mundo após o ano de 2022.  A sintomatologia tem sido muito diversa, tendo como principais sinais e sintomas lesões cutâneas, febre e linfadenopatias. A maioria dos casos não precisou de hospitalização. Contudo, em pacientes imunossuprimidos, crianças e gestantes a infecção se mostrou mais perigosa. A Monkeypox deixou de ser endêmica da África Ocidental no ano de 2022 e vem tomando proporções globais desde então. É de suma importância pesquisas epidemiológicas de rotina para que a doença seja controlada de perto e para que os profissionais da saúde tenham consciência de seu quadro clínico para a adequada notificação da doença

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

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status