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

Análise fílmica: O transtorno obsessivo compulsivo e a bipolaridade nos personagens do filme O lado bom da vida

The present study aimed to discuss bipolarity, obsessive compulsive disorder (OCD) and, briefly about sexual compulsion, pathologies identified in some of the characters of the cinematic narrative “The good side of life” (2012). This is a study of narrative review of the literature, carried out over a period of one month in 2019, in which articles, books and epidemiological bulletins were used that covered the delimited subject. It was identified as main results, that the risk factors that cause OCD and bipolarity contemplate issues that are not only psychological, but also biological and physiological. It is concluded that in addition to the techniques usually used to treat and control these psychopathologies, art is of great importance during the therapeutic process, providing greater control of symptoms.O presente estudo teve por objetivo realizar uma análise sobre a bipolaridade, o transtorno obsessivo compulsivo (TOC) e, sumariamente sobre a compulsão sexual, patologias identificadas em alguns dos personagens da narrativa cinematográfica “O lado bom da vida” (2012). Trata-se de um estudo de revisão narrativa da literatura, feito num período de um mês no ano de 2019, no qual se utilizaram artigos, livros e boletins epidemiológicos que abrangessem o assunto delimitado. Identificou-se como principais resultados, que os fatores de riscos causadores do TOC e da bipolaridade contemplam questões não só psicológicas, mas também, biológicas e fisiológicas. Conclui-se que além das técnicas usualmente utilizadas para tratamento e controle das referidas psicopatologias, a arte tem grande importância durante o processo terapêutico, fornecendo maior controle da sintomatologia.El presente estudio tuvo como objetivo discutir la bipolaridad, el trastorno obsesivo compulsivo (TOC) y, brevemente sobre la compulsión sexual, las patologías identificadas en algunos de los personajes de la narrativa cinematográfica "El lado bueno de la vida" (2012). Este es un estudio de revisión narrativa de la literatura, realizado durante un período de un mes en 2019, en el que se utilizaron artículos, libros y boletines epidemiológicos que cubrieron el tema delimitado. Se identificaron como resultados principales, que los factores de riesgo que causan TOC y bipolaridad contemplan problemas que no solo son psicológicos, sino también biológicos y fisiológicos. Se concluye que, además de las técnicas generalmente utilizadas para tratar y controlar estas psicopatologías, el arte es de gran importancia durante el proceso terapéutico, ya que proporciona un mayor control de los síntomas

Correction: Performance of rK39-based immunochromatographic rapid diagnostic test for serodiagnosis of visceral leishmaniasis using whole blood, serum and oral fluid.

[This corrects the article DOI: 10.1371/journal.pone.0230610.]

Systematic Review and Meta-Analysis of Congenital Toxoplasmosis Diagnosis: Advances and Challenges

Objective. To understand how congenital toxoplasmosis (CT) diagnosis has evolved over the years, we performed a systematic review and meta-analysis to summarize the kind of analysis that has been employed for CT diagnosis. Methods. PubMed and Lilacs databases were used in order to access the kind of analysis that has been employed for CT diagnosis in several samples. Our search combined the following combining terms: “congenital toxoplasmosis” or “gestational toxoplasmosis” and “diagnosis” and “blood,” “serum,” “amniotic fluid,” “placenta,” or “colostrum.” We extracted data on true positive, true negative, false positive, and false negative to generate pooled sensitivity, specificity, and diagnostic odds ratio (DOR). Random-effects models using MetaDTA were used for analysis. Results. Sixty-five articles were included in the study aiming for comparisons (75.4%), diagnosis performance (52.3%), diagnosis improvement (32.3%), or to distinguish acute/chronic infection phases (36.9%). Amniotic fluid (AF) and placenta were used in 36.9% and 10.8% of articles, respectively, targeting parasites and/or T. gondii DNA. Blood was used in 86% of articles for enzymatic assays. Colostrum was used in one article to search for antibodies. In meta-analysis, PCR in AF showed the best performance for CT diagnosis based on the highest summary sensitivity (85.1%) and specificity (99.7%) added to lower magnitude heterogeneity. Conclusion. Most of the assays being researched to diagnose CT are basically the same traditional approaches available for clinical purposes. The range in diagnostic performance and the challenges imposed by CT diagnosis indicate the need to better explore pregnancy samples in search of new possibilities for diagnostic tools. Exploring immunological markers and using bioinformatics tools and T. gondii recombinant antigens should address the research needed for a new generation of diagnostic tools to face these challenges

Aqueous extract from Mangifera indica Linn. (Anacardiaceae) leaves exerts long-term hypoglycemic effect, increases insulin sensitivity and plasma insulin levels on diabetic Wistar rats.

BACKGROUND:Diabetes mellitus is one of the most common todays public health problems. According to a survey by the World Health Organization, this metabolic disorder has reached global epidemic proportions, with a worldwide prevalence of 8.5% in the adult population. OBJECTIVES:The present study aimed to investigate the hypoglycemic effect of aqueous extract of Mangifera indica (EAMI) leaves in streptozotocin-induced diabetic rats. METHODS:Sixty male rats were divided into 2 groups: Normoglycemic and Diabetic. Each group was subdivided into negative control, glibenclamide 3 or 10 mg/kg, EAMI 125, 250, 500, and 1000 mg/kg. Intraperitoneal injection of streptozotocin 100 mg/kg was used to DM induction. The hypoglycemic response was assessed acutely after two and four weeks of treatment. After a 6-hour fasting period, the fasting blood glucose of animals was verified, and 2.5 g/kg glucose solution was orally administered. The insulin tolerance test and plasma insulin levels assessment were performed in the morning after fasting of 12 to 14 hours. RESULTS AND CONCLUSION:The chemical analysis of EAMI showed high levels of phenolic compounds. There was no significant difference in fasting blood glucose between normoglycemic and diabetic groups, and that EAMI did not have an acute effect on diabetes. After two and four weeks of treatment, the extract significantly reduced blood glucose levels, exceeding glibenclamide effects. EAMI was effective in maintaining the long-term hypoglycemic effect, as well as, significantly increased the sensitivity of diabetic animals to insulin and the plasma insulin level