Clinical oxidative stress during leprosy multidrug therapy:impact of dapsone oxidation

This study aims to assess the oxidative stress in leprosy patients under multidrug therapy (MDT; dapsone, clofazimine and rifampicin), evaluating the nitric oxide (NO) concentration, catalase (CAT) and superoxide dismutase (SOD) activities, glutathione (GSH) levels, total antioxidant capacity, lipid peroxidation, and methemoglobin formation. For this, we analyzed 23 leprosy patients and 20 healthy individuals from the Amazon region, Brazil, aged between 20 and 45 years. Blood sampling enabled the evaluation of leprosy patients prior to starting multidrug therapy (called MDT 0) and until the third month of multidrug therapy (MDT 3). With regard to dapsone (DDS) plasma levels, we showed that there was no statistical difference in drug plasma levels between multibacillary (0.518±0.029 μg/mL) and paucibacillary (0.662±0.123 μg/mL) patients. The methemoglobin levels and numbers of Heinz bodies were significantly enhanced after the third MDTsupervised dose, but this treatment did not significantly change the lipid peroxidation and NO levels in these leprosy patients. In addition, CAT activity was significantly reduced in MDT-treated leprosy patients, while GSH content was increased in these patients. However, SOD and Trolox equivalent antioxidant capacity levels were similar in patients with and without treatment. These data suggest that MDT can reduce the activity of some antioxidant enzyme and influence ROS accumulation, which may induce hematological changes, such as methemoglobinemia in patients with leprosy. We also explored some redox mechanisms associated with DDS and its main oxidative metabolite DDS-NHOH and we explored the possible binding of DDS to the active site of CYP2C19 with the aid of molecular modeling software

Representation of the CYP 2C19.

<p>Area covered (depicted as <i>light blue</i> transparent <i>solid surface</i>) by the two internal cavities (catalytic site cavity and adjacent cavity) of human microsomal cytochrome P450 (CYP) 2C19 (<i>brown</i>). The heme prosthetic group is represented in <i>green</i> and the molecule of dapsone in the color <i>red</i> (<b>a</b>). Delimitation of the area occupied by the two internal cavities (catalytic site cavity and adjacent cavity) of the CYP2C19 (<b>b</b>).</p

Determination of nitric oxide (NO) in serum (a), percentage of blood methemoglobin (b) levels of malondialdehyde (MDA) in plasma (c) of patients with untreated leprosy (MDT 0) and after the third dose supervised treatment (MDT 3).

<p>Figures in the chart are expressed as mean ± SD. *p<0.05 compared to MDT0 (ANOVA).</p

Thresholds of freshwater biodiversity in response to riparian vegetation loss in the Neotropical region

Protecting riparian vegetation around streams is vital in reducing the detrimental effects of environmental change on freshwater ecosystems and in maintaining aquatic biodiversity. Thus, identifying ecological thresholds is useful for defining regulatory limits and for guiding the management of riparian zones towards the conservation of freshwater biota. Using nationwide data on fish and invertebrates occurring in small Brazilian streams, we estimated thresholds of native vegetation loss in which there are abrupt changes in the occurrence and abundance of freshwater bioindicators and tested whether there are congruent responses among different biomes, biological groups and riparian buffer sizes. Mean thresholds of native vegetation cover loss varied widely among biomes, buffer sizes and biological groups: ranging from 0.5% to 77.4% for fish, from 2.9% to 37.0% for aquatic invertebrates and from 3.8% to 43.2% for a subset of aquatic invertebrates. Confidence intervals for thresholds were wide, but the minimum values of these intervals were lower for the smaller riparian buffers (50 and 100 m) than larger ones (200 and 500 m), indicating that land use should be kept away from the streams. Also, thresholds occurred at a lower percentage of riparian vegetation loss in the smaller buffers, and were critically lower for invertebrates: reducing only 6.5% of native vegetation cover within a 50-m riparian buffer is enough to cross thresholds for invertebrates. Synthesis and applications. The high variability in biodiversity responses to loss of native riparian vegetation suggests caution in the use of a single riparian width for conservation actions or policy definitions nationwide. The most sensitive bioindicators can be used as early warning signals of abrupt changes in freshwater biodiversity. In practice, maintaining at least 50-m wide riparian reserves on each side of streams would be more effective to protect freshwater biodiversity in Brazil. However, incentives and conservation strategies to protect even wider riparian reserves (~100 m) and also taking into consideration the regional context will promote a greater benefit. This information should be used to set conservation goals and to create complementary mechanisms and policies to protect wider riparian reserves than those currently required by the federal law

Establishment and cryptic transmission of Zika virus in Brazil and the Americas

University of Oxford. Department of Zoology, Oxford, UK / Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.University of Birmingham. Institute of Microbiology and Infection. Birmingham, UK.University of Oxford. Department of Zoology. Oxford UK.University of Oxford. Department of Zoology. Oxford, UK / Harvard Medical School. Boston, MA, USA / Boston Children's Hospital. Boston, MA, USA.University of Oxford. Department of Zoology. Oxford, UK.Fred Hutchinson Cancer Research Center. Vaccine and Infectious Disease Division. Seattle, WA, USA / University of Washington. Department of Epidemiology. Seattle, WA, USA.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.University of Oxford. Department of Statistics. Oxford, UK.University of Oxford. Department of Zoology. Oxford, UK.Institut Pasteur. Biostatistics and Integrative Biology. Mathematical Modelling of Infectious Diseases and Center of Bioinformatics. Paris, FR / Centre National de la Recherche Scientifique. Paris, FR.University of Oxford. Department of Zoology. Oxford, UK.Ministry of Health. Coordenação dos Laboratórios de Saúde. Brasília, DF, Brazil.Ministry of Health. Coordenação Geral de Vigilância e Resposta às Emergências em Saúde Pública. Brasília, DF, Brazil / Fundação Oswaldo Cruz. Center of Data and Knowledge Integration for Health. Salvador, BA, Brazil.Ministry of Health. Departamento de Vigilância das Doenças Transmissíveis. Brasilia, DF, Brazil.Ministry of Health. Coordenação Geral dos Programas de Controle e Prevenção da Malária e das Doenças Transmitidas pelo Aedes. Brasília, DF, Brazil / Pan American Health Organization (PAHO). Buenos Aires, AR.Ministry of Health. Coordenação Geral dos Programas de Controle e Prevenção da Malária e das Doenças Transmitidas pelo Aedes. Brasília, DF, Brazil / Fundação Oswaldo Cruz. Rio de Janeiro, RJ, Brazil.Ministry of Health. Coordenação Geral dos Programas de Controle e Prevenção da Malária e das Doenças Transmitidas pelo Aedes. Brasília, DF, BrazilMinistry of Health. Departamento de Vigilância das Doenças Transmissíveis. Brasilia, DF, Brazil.Ontario Institute for Cancer Research. Toronto, ON, Canada.University of Nottingham. Nottingham, UKThe Scripps Research Institute. Department of Immunology and Microbial Science. La Jolla, CA, USA.The Scripps Research Institute. Department of Immunology and Microbial Science. La Jolla, CA, USA.University of California. Departments of Laboratory Medicine and Medicine & Infectious Diseases. San Francisco, CA, USA.University of California. Departments of Laboratory Medicine and Medicine & Infectious Diseases. San Francisco, CA, USA.Instituto Mexicano del Seguro Social. División de Laboratorios de Vigilancia e Investigación Epidemiológica. Ciudad de México, MC.Instituto Mexicano del Seguro Social. División de Laboratorios de Vigilancia e Investigación Epidemiológica. Ciudad de México, MC.Universidad Nacional Autónoma de México. Instituto de Biotecnología. Cuernavaca, MC.Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brazil.Paul-Ehrlich-Institut. Langen, Germany.Laboratório Central de Saúde Pública Noel Nutels. Rio de Janeiro, RJ, Brazil.Laboratório Central de Saúde Pública Noel Nutels. Rio de Janeiro, RJ, Brazil.Laboratório Central de Saúde Pública Noel Nutels. Rio de Janeiro, RJ, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Fundação Oswaldo Cruz. Salvador, BA, Brazil.Laboratório Central de Saúde Pública. Natal, RN, Brazil.Laboratório Central de Saúde Pública. Natal, RN, Brazil / Universidade Potiguar. Natal, RN, Brazil.Laboratório Central de Saúde Pública. Natal, RN, Brazil / Faculdade Natalense de Ensino e Cultura. Natal, RN, Brazil.Laboratório Central de Saúde Pública. João Pessoa, PB, Brazil.Laboratório Central de Saúde Pública. João Pessoa, PB, Brazil.Laboratório Central de Saúde Pública. João Pessoa, PB, Brazil.Laboratório Central de Saúde Pública. João Pessoa, PB, Brazil.Fundação Oswaldo Cruz. Recife, PE, Brazil.Fundação Oswaldo Cruz. Recife, PE, Brazil.Fundação Oswaldo Cruz. Recife, PE, Brazil / Colorado State University. Department of Microbiology, Immunology &Pathology. Fort Collins, CO, USA.Fundação Oswaldo Cruz. Recife, PE, Brazil.Heidelberg University Hospital. Department for Infectious Diseases. Section Clinical Tropical Medicine. Heidelberg, Germany.Fundação Oswaldo Cruz. Recife, PE, Brazil.Laboratório Central de Saúde Pública. Maceió, AL, Brazil.Laboratório Central de Saúde Pública. Maceió, AL, Brazil.Laboratório Central de Saúde Pública. Maceió, AL, Brazil.Universidade Estadual de Feira de Santana. Feira de Santana, BA, Brazil.Secretaria de Saúde de Feira de Santana. Feira de Santana, BA, Brazil.Universidade Federal do Amazonas. Manaus, AM, Brazil.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.Hospital São Francisco. Ribeirão Preto, SP, Brazil.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.Universidade Federal do Tocantins. Palmas, TO, Brazil.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.University of Sydney. Sydney, Australia.University of Edinburgh. Institute of Evolutionary Biology. Edinburgh, UK / National Institutes of Health. Fogarty International Center. Bethesda, MD, USA.Fred Hutchinson Cancer Research Center. Vaccine and Infectious Disease Division. Seattle, WA, USA.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil / University of Texas Medical Branch. Department of Pathology. Galveston, TX, USA.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.Fundação Oswaldo Cruz. Salvador, BA, Brazil.University of Birmingham. Institute of Microbiology and Infection. Birmingham, UK.University of Oxford. Department of Zoology, Oxford, UK / Metabiota. San Francisco, CA, USA.University of São Paulo. School of Medicine &Institute of Tropical Medicine. Department of Infectious Disease. São Paulo, SP, Brazil.Fundação Oswaldo Cruz. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Salvador, BA, Brazil / University of Rome Tor Vergata. Rome, Italy.Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 2016) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 2016). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus