Procjena prošlih promjena u okolišu proučavanjem sedimenata u hiperslanoj laguni

Carbon and oxygen isotopes, organic matter elemental composition, and mineralogy of carbonates were used as proxies to investigate environmental changes recorded in the carbonate-rich sediment of the hypersaline lagoon "Vermelha", Rio de Janeiro. Isotopic and other data suggest that two striking shifts in environmental conditions occurred about 1900 and 3200 years ago. Carbonates δ(18O) and δ(13C) were found in the range of +1.5‰ to +4.5 ‰ (PDB), and –2 ‰ to –11‰ (PDB), respectively. In organic matter, δ(13C) ranged from –22 ‰ to –15 ‰ (PDB). Calcites and dolomites are present in the studied core; their relative abundance seems to be related to the observed changes. Calcites are enriched up 38 % in MgCO3 (mole fraction, x). As distinct from calcites with lower magnesium contents, Mg-calcite with x(Mg) > 20 % shows an additional peak at 0.2929 nm in the X-ray diffractogram. Samples that contain Mg-calcite or 100 % dolomite show similar δ(13C) values. There are strong indications for an early formation of dolomite already in the microbial mat region. 18O and 2H determinations in lagoon water confirm evaporation as the water balance controlling processU radu je opisana uporaba izotopa ugljika i kisika, elementnog sastava organske tvari i mineralogije karbonata kao faktora u istraživanju promjena na okolišu utvrđenih u karbonatom bogatim sedimentima hiperslane lagune "Vermelha" kod Rio de Janeira u Brazilu. Izotopski i drugi podaci ukazuju na dvije značajne promjene okolišnih uvjeta, koje su se dogodile prije 1900 odnosno 3200 godina. U karbonatima, vrijednosti δ(18O) i δ(13C) izmjerene su u rasponu od +1,5 ‰ do +4,5 ‰, odnosno od –2 ‰ do –11 ‰ (standard Pee Dee Belemnite – PDB). Kod organske tvari, vrijednost δ(13C) varira u rasponu od –22 ‰ do –15 ‰ (PDB). U istraživanoj su sedimentnoj jezgri utvrđeni kalcit i dolomit, a njihova relativna zastupljenost povezana je s utvrđenim okoliš nim promjenama. Kalciti sadrže do 38 % MgCO3 (molni udjeli, x). Za razliku od kalcita s nižim sadržajem magnezija, magnezijev kalcit (x(Mg) > 20 %) pokazuje dodatnu liniju na rendgenskom difraktogramu kod 2929 nm. Uzorci koji sadrže magnezijev kalcit ili čisti dolomit pokazuju slične vrijednosti δ(13C). Postoje snažne indicije za stvaranje dolomita već u području mikrobnih pokrova. Vrijednosti 18O i 2H u vodi lagune ukazuju na to da je isparavanje proces koji kontrolira bilancu vode u sustavu

Multiple sex partner behavior in female undergraduate students in China: A multi-campus survey

<p>Abstract</p> <p>Background</p> <p>China is realizing increases in women engaged in premarital sex and multiple sex partner behavior. Our aim was to examine prevalence and determinants of multiple sex partner behavior among female undergraduates in China.</p> <p>Methods</p> <p>Anonymously completed questionnaires were received from 4,769 unmarried female undergraduates, recruited using randomized cluster sampling by type of university and students' major and grade. Items captured demographic, family, peer and work influence, and student factors (major, academic performance, and sex-related knowledge and attitudes). To examine risk factors for sexual behaviors, we used multi-level logistic regression, yielding odds ratios (OR) and 95% confidence intervals (95% CI).</p> <p>Results</p> <p>Of 4,769 female students, 863 (18.10%) reported ever having sexual intercourse, and 5.31% reported having multiple sex partners (29.32% of all women having sexual intercourse). Several demographic, family, peer and work influences, and student factors (including major, performance, knowledge, and attitude toward sex) were risk factors for ever having sex. However, risk factors for multiple sex partners only included working in a place of entertainment, having current close friends that were living with boyfriends, poor academic performance, and positive attitudes toward multiple partners. These women also were more likely to practice masturbation, start having sex at a younger age, have sex with married men and/or men not their "boyfriends" at first coitus, and not use condoms consistently.</p> <p>Conclusion</p> <p>A small but important subset of Chinese female undergraduates is engaged in unprotected sex with multiple sex partners. Interventions need to target at risk women, stressing the importance of consistent condom use.</p

Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15–49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75·7% of the lakeside population and 16·2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13·7%] in inland and 2439 [40·1%] in fishing communities). 3878 (75·4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68·4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5·7% (95% credibility interval 4·4–7·3) of transmissions occurred within lakeside areas, 89·2% (86·0–91·8) within inland areas, 1·3% (0·6–2·6) from lakeside to inland areas, and 3·7% (2·3–5·8) from inland to lakeside areas. Interpretation Cross-community HIV transmissions between Lake Victoria hotspots and surrounding inland populations are infrequent and when they occur, virus more commonly flows into rather than out of hotspots. This result suggests that targeted interventions to these hotspots will not alone control the epidemic in inland populations, where most transmissions occur. Thus, geographical targeting of high prevalence areas might not be effective for broader epidemic control depending on underlying epidemic dynamics. Funding The Bill & Melinda Gates Foundation, the National Institute of Allergy and Infectious Diseases, the National Institute of Mental Health, the National Institute of Child Health and Development, the Division of Intramural Research of the National Institute for Allergy and Infectious Diseases, the World Bank, the Doris Duke Charitable Foundation, the Johns Hopkins University Center for AIDS Research, and the President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention

Analysis and Functional Annotation of an Expressed Sequence Tag Collection for Tropical Crop Sugarcane

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged

Bacterial diversity and biogeography in deep-sea surface sediments of the South Atlantic Ocean

Microbial biogeographic patterns in the deep sea depend on the ability of microorganisms to disperse. One possible limitation to microbial dispersal may be the Walvis Ridge that separates the Antarctic Lower Circumpolar Deep Water from the North Atlantic Deep Water. We examined bacterial communities in three basins of the eastern South Atlantic Ocean to determine diversity and biogeography of bacterial communities in deep-sea surface sediments. The analysis of 16S ribosomal RNA (rRNA) gene clone libraries in each basin revealed a high diversity, representing 521 phylotypes with 98% identity in 1051 sequences. Phylotypes affiliated with Gammaproteobacteria, Deltaproteobacteria and Acidobacteria were present in all three basins. The distribution of these shared phylotypes seemed to be influenced neither by the Walvis Ridge nor by different deep water masses, suggesting a high dispersal capability, as also indicated by low distance–decay relationships. However, the total bacterial diversity showed significant differences between the basins, based on 16S rRNA gene sequences as well as on terminal restriction fragment length polymorphism fingerprints. Noticeably, both geographic distance and environmental heterogeneity influenced bacterial diversity at intermediate (10–3000 km) and large scales (>3000 km), indicating a complex interplay of local contemporary environmental effects and dispersal limitation

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

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

non present