Multiple-clone infections of Plasmodium vivax: definition of a panel of markers for molecular epidemiology

Submitted by Nuzia Santos ([email protected]) on 2016-02-29T17:46:50Z No. of bitstreams: 1 Multiple-clone infections of Plasmodium.pdf: 5467763 bytes, checksum: b4719a5dd04db8f670d04a87ecc9303f (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2016-02-29T17:50:22Z (GMT) No. of bitstreams: 1 Multiple-clone infections of Plasmodium.pdf: 5467763 bytes, checksum: b4719a5dd04db8f670d04a87ecc9303f (MD5)Made available in DSpace on 2016-02-29T17:50:22Z (GMT). No. of bitstreams: 1 Multiple-clone infections of Plasmodium.pdf: 5467763 bytes, checksum: b4719a5dd04db8f670d04a87ecc9303f (MD5) Previous issue date: 2015Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, BrasilUniversidade Federal de Mato Grosso. Hospital Julio Muller. Cuiabá, MT, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, BrasilBACKGROUND: Plasmodium vivax infections commonly contain multiple genetically distinct parasite clones. The detection of multiple-clone infections depends on several factors, such as the accuracy of the genotyping method, and the type and number of the molecular markers analysed. Characterizing the multiplicity of infection has broad implications that range from population genetic studies of the parasite to malaria treatment and control. This study compared and evaluated the efficiency of neutral and non-neutral markers that are widely used in studies of molecular epidemiology to detect the multiplicity of P. vivax infection. METHODS: The performance of six markers was evaluated using 11 mixtures of DNA with well-defined proportions of two different parasite genotypes for each marker. These mixtures were generated by mixing cloned PCR products or patient-derived genomic DNA. In addition, 51 samples of natural infections from the Brazil were genotyped for all markers. The PCR-capillary electrophoresis-based method was used to permit direct comparisons among the markers. The criteria for differentiating minor peaks from artifacts were also evaluated. RESULTS: The analysis of DNA mixtures showed that the tandem repeat MN21 and the polymorphic blocks 2 (msp1B2) and 10 (msp1B10) of merozoite surface protein-1 allowed for the estimation of the expected ratio of both alleles in the majority of preparations. Nevertheless, msp1B2 was not able to detect the majority of multiple-clone infections in field samples; it identified only 6 % of these infections. The merozoite surface protein-3 alpha and microsatellites (PvMS6 and PvMS7) did not accurately estimate the relative clonal proportions in artificial mixtures, but the microsatellites performed well in detecting natural multiple-clone infections. Notably, the use of a less stringent criterion to score rare alleles significantly increased the sensitivity of the detection of multi-clonal infections. CONCLUSIONS: Depending on the type of marker used, a considerable amplification bias was observed, which may have serious implications for the characterization of the complexity of a P. vivax infection. Based on the performance of markers in artificial mixtures of DNA and natural infections, a minimum panel of four genetic markers (PvMS6, PvMS7, MN21, and msp1B10) was defined, and these markers are highly informative regarding the genetic variability of P. vivax populations

Topical Insulin Accelerates Wound Healing in Diabetes by Enhancing the AKT and ERK Pathways: A Double-Blind Placebo-Controlled Clinical Trial

Background: Wound healing is impaired in diabetes mellitus, but the mechanisms involved in this process are virtually unknown. Proteins belonging to the insulin signaling pathway respond to insulin in the skin of rats. Objective: The purpose of this study was to investigate the regulation of the insulin signaling pathway in wound healing and skin repair of normal and diabetic rats, and, in parallel, the effect of a topical insulin cream on wound healing and on the activation of this pathway. Research Design and Methods: We investigated insulin signaling by immunoblotting during wound healing of control and diabetic animals with or without topical insulin. Diabetic patients with ulcers were randomized to receive topical insulin or placebo in a prospective, double-blind and placebo-controlled, randomized clinical trial (NCT 01295177) of wound healing. Results and Conclusions: Expression of IR, IRS-1, IRS-2, SHC, ERK, and AKT are increased in the tissue of healing wounds compared to intact skin, suggesting that the insulin signaling pathway may have an important role in this process. These pathways were attenuated in the wounded skin of diabetic rats, in parallel with an increase in the time of complete wound healing. Upon topical application of insulin cream, the wound healing time of diabetic animals was normalized, followed by a reversal of defective insulin signal transduction. In addition, the treatment also increased expression of other proteins, such as eNOS (also in bone marrow), VEGF, and SDF-1 alpha in wounded skin. In diabetic patients, topical insulin cream markedly improved wound healing, representing an attractive and cost-free method for treating this devastating complication of diabetes.Sao Paulo Research Foundation (FAPESP)Sao Paulo Research Foundation (FAPESP)National Institute of Science and Technology (INCT)National Institute of Science and Technology (INCT)National Council for Scientific and Technological Development (CNPq)National Council for Scientific and Technological Development (CNPq

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states

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