Prevalência de infecção chagásica em doadores de sangue no estado de Pernambuco, Brasil

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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

Human T-Lymphotropic Virus Type 1 and Type 2 Seroprevalence, Incidence, and Residual Transfusion Risk Among Blood Donors in Brazil During 2007–2009

Human T-lymphotropic virus type 1/2 (HTLV-1/2) infection is endemic in Brazil but representative donor prevalence and incidence data are lacking. All blood donations (2007-2009) from three blood centers in Brazil were studied. Samples reactive on one HTLV screening test (EIA) were retested with a different EIA; dual EIA reactivity correlated strongly with a confirmatory Western blot. Prevalence, incidence, and residual transfusion risk were calculated. Among 281,760 first-time donors, 363 were positive for HTLV on both EIAs (135 per 10(5), 95% CI 122-150). Prevalence differed considerably by region, from 83 to 222 per 10(5). Overall incidence rate was 3.6/10(5) person-years and residual transfusion risk was 5.0/10(6) per blood unit transfused. The logistic regression model showed significant associations with: age [adjusted odds ratio (aOR)=5.23 for age 50+ vs. <20], female sex (aOR=1.97), black (aOR=2.70 vs. white), and mixed skin colors (aOR=1.78 vs. white), and inversely with education (aOR=0.49, college vs. less than high school). HTLV testing with a dual-EIA strategy is feasible and can be useful in areas with low resources. Incidence and residual risk of HTLV-1 transmission by transfusion were relatively high and could be reduced by improving donor recruitment and selection in high prevalence areas. Blood center data may contribute to surveillance for HTLV infection

Human T-lymphotropic virus type 1 and type 2 seroprevalence, incidence, and residual transfusion risk among blood donors in Brazil during 2007-2009.

Human T-lymphotropic virus type 1/2 (HTLV-1/2) infection is endemic in Brazil but representative donor prevalence and incidence data are lacking. All blood donations (2007-2009) from three blood centers in Brazil were studied. Samples reactive on one HTLV screening test (EIA) were retested with a different EIA; dual EIA reactivity correlated strongly with a confirmatory Western blot. Prevalence, incidence, and residual transfusion risk were calculated. Among 281,760 first-time donors, 363 were positive for HTLV on both EIAs (135 per 10(5), 95% CI 122-150). Prevalence differed considerably by region, from 83 to 222 per 10(5). Overall incidence rate was 3.6/10(5) person-years and residual transfusion risk was 5.0/10(6) per blood unit transfused. The logistic regression model showed significant associations with: age [adjusted odds ratio (aOR)=5.23 for age 50+ vs. <20], female sex (aOR=1.97), black (aOR=2.70 vs. white), and mixed skin colors (aOR=1.78 vs. white), and inversely with education (aOR=0.49, college vs. less than high school). HTLV testing with a dual-EIA strategy is feasible and can be useful in areas with low resources. Incidence and residual risk of HTLV-1 transmission by transfusion were relatively high and could be reduced by improving donor recruitment and selection in high prevalence areas. Blood center data may contribute to surveillance for HTLV infection

Ocular toxoplasmosis: evaluation of lacrimal - specific secretory IgA levels in both patients with active and inactive phases of the disease

Ocular toxoplasmosis can result in recurrent uveitis. Studies have shown that a correlation between active ocular toxoplasmosis and the presence of anti-Toxoplasma gondii secretory IgA (SIgA) in tears. This study compares anti-T. gondii SIgA levels in patients' tears during the acute and inactive phases of toxoplasmic uveitis. Twenty-nine positive tear specific SIgA for T. gondii patients with acute toxoplasmic uveitis were selected and were followed-up for at least two years, when the anti-T. gondii SIgA tears levels were determined. Specific SIgA for T. gondii was negative in 22 patients (75.86%) and positive in seven patients (24.13%) of whom six (85.7%) were followed over three years. Average SIgA levels during the acute phase are 1.54 and decrease significantly to 0.72 (p = 0.0001) during the inactive phase of disease. Because anti-T. gondii SIgA in the tear is negative in 75.86% of patients after the acute phase of infection, T. gondii SIgA levels may be used as a complementary diagnostic marker for active ocular toxoplasmosis