The world is in my head : my body is in the world : a condição paratópica em Paul Auster : incidências e projecções do espaço na produção literária em prosa

Tese de Doutoramento em Estudos Americanos apresentada à Universidade AbertaEste trabalho analisa, de forma detalhada, as representações do espaço na produção literária, em prosa, de Paul Auster, publicada entre 1987 e 2004. Partimos do princípio de que cada obra austeriana analisada funciona como mapa de uma colocação individual e social, porque nela escritor e leitor encontram a possibilidade de aspirar a um entendimento do real. Neste pressuposto, que procuramos dilucidar ao longo da investigação – quer no plano da selecção do enquadramento teórico, quer na posterior envolvência dele com a análise do corpus – considerámos que, com subtilezas de intensidade, cada produção literária observada concretiza o nexo vida-livro, ao ponto de tornar lícita a declaração de que, em Auster, a vida se configura como epifenómeno da literatura. De acordo com esta premissa – que radicámos na condição paratópica inerente ao lugar problemático na estrutura espacial, social e identitária a que o escritor se encontra votado – a hipótese que procurámos verificar com o escrutínio do corpus é a de que cada obra, enquanto condição e produto da paratopia austeriana, se constitui localidade paradoxal e parasitária, consequente de uma carência de lugar de pertença na realidade. Neste contexto, o enquadramento teórico percorre obras que elegeram o espaço como principal objecto de estudo no âmbito da literatura mas a capacidade enunciativa e o poder evocativo da produção literária austeriana também impuseram a necessidade de procurar o contributo de autores que, não tomando como centro de reflexão a questão espacial à luz deste ramo do conhecimento, se debruçaram, num momento ou noutro, sobre problemáticas do espaço ou a ele atinentes. Com base nas propostas enunciadas, o intuito primeiro do estudo foi avaliar até que ponto cada produção literária consubstancia a oscilação de desenraizamentos, níveis entrecruzados de acções e reacções, ajustamentos instáveis e identidades negociadas entre o biografismo e a ficção de Paul Auster.This work analyses, with detail, the spatial representations of Paul Auster’s literary production in prose, published between 1987 and 2004. As both writer and reader find in each of Auster’s work a possibility of aspiring to an understanding of reality, the departing principle for the scrutiny was that each narrative functions as a map of an individual and social placement. Following this premisse – which the study delucidates through theorethical framing and its subsequent involvement in the analysis of the corpus – we considered that, with subtleties of intensity, each literary work scrutinized renders concrete the life-book nexus to a point that legitimates the statement that, in Auster, life is configured as an epiphenomenon of literature. According to this reasoning – that we radicate in the paratopic condition inherent to the problematical place (in spatial and social estructure, as well as in terms of identity) to which the writer is condemned to – the hypothesis we tried to verify with the examination of the corpus was that each work, as condition and product of the austerian paratopia, becomes a paradoxal and parasitical location, consequent of the lack of a belonging place in reality. In this context, the theoretical approach of this investigation goes through works that elected space in literature as main issue. Nevertheless, the enunciative capacity and the evocative power of Auster’s production also imposed the need to search for contributions of authors who didn’t center their studies in the spatial matter concerning literature, but leant over this category off and on. Based upon these propositions, the investigation evaluates to what extent each literary production analised consubstantiantes the fluctuation of unrootings, intersected levels of actions and reactions, unstable adjustments, and negotiated identities between Paul Auster’s biographic data and fiction

Methods to detect spatial biases in tracking studies caused by differential representativeness of individuals, populations and time

Este artículo contiene 20 páginas, 6 figuras, 4 tablas.Aim: Over the last decades, the study of movement through tracking data has grown exceeding the expectations of movement ecologists. This has posed new challenges, specifically when using individual tracking data to infer higher- level distributions (e.g. population and species). Sources of variability such as individual site fidelity (ISF), en-vironmental stochasticity over time, and space-use variability across species ranges must be considered, and their effects identified and corrected, to produce accurate estimates of spatial distribution using tracking data. Innovation: We developed R functions to detect the effect of these sources of vari-ability in the distribution of animal groups when inferred from individual tracking data. These procedures can be adapted for their use in most tracking datasets and tracking techniques. We demonstrated our procedures with simulated datasets and showed their applicability on a real-world dataset containing 1346 year- round migratory trips from 805 individuals of three closely related seabird species breeding in 34 colonies in the Mediterranean Sea and the Atlantic Ocean, spanning 10 years. We detected an effect of ISF in one of the colonies, but no effect of the environmental stochasticity on the distribution of birds for any of the species. We also identified among-colony variability in nonbreeding space use for one species, with significant effects of popu-lation size and longitude. Main conclusions: This work provides a useful, much- needed tool for researchers using animal tracking data to model species distributions or establish conservation measures. This methodology may be applied in studies using individual tracking data to accurately infer the distribution of a population or species and support the deline-ation of important areas for conservation based on tracking data. This step, designed to precede any analysis, has become increasingly relevant with the proliferation of studies using large tracking datasets that has accompanied the globalization process in science driving collaborations and tracking data sharing initiatives.We thank the following institutions for funding: EU H2020 pro-gramme through grant 634495; Seventh Framework Programme (Research Executive Agency) through Marie Curie Career Integration Grant 618841 (FP7-PEOPLE-2013- CIG); ESFRI LifeWatch Project; LIFE programme of the European Commission through projects LIFE10 NAT/MT090 and LIFE11 NAT/IT/000093; Ministerio de Ciencia e Innovación/Ministerio de Economia y Competitividad (Spain) through projects CGL2009- 11278/BOS, CGL2013-42585-P, C G L 2 0 1 3 - 4 2 2 0 3 - R , C G L 2 0 16 - 7 8 5 3 0 - R a n d C G L 2 0 17- 8 52 10 - P ; Organismo Autónomo de Parques Nacionales (Spain) through pro-ject 1248/2014; Fundação para a Ciência e a Tecnologia (MCTES, Portugal) through projects MARE-UID/MAR/04292/2019; IF/00502/2013/CP1186/CT0003, PTDC/BIA-ANM/3743/2014, PTDC/MAR-PRO/0929/2014, UID/AMB/50017/2019 and UIDP/50017/2020 + UIDB/50017/2020 (to CESAM); Office Français de la Biodiversité (France), through the Programme PACOMM, Natura2000 en mer; Hellenic Bird Ringing Centre; MSDEC (Malta). VMP was supported by pre-doctoral contract BES-2014- 068025 of the Spanish Ministerio de Industria, Economía y Competitividad; MM by grant SFRH/BPD/47047/2008 from the Portuguese Foundation for Science and Technology; JMRG by Ph.D. grant AP2009-2163 from the Spanish Ministerio de Educación; GDO and MMü by Ornis italica and by the Regione Siciliana and Assessorato Risorse Agricole e Alimentari thoriugh a grant to the Ringing Unit of Palermo; VHP by grant SFRH/BPD/85024/2012 from the Portuguese Foundation for Science and Technology; VN by grant SFRH/BPD/88914/2012 from the Portuguese Foundation for Science and Technology; and JN by the Spanish National Programme Ramón y Cajal (RYC-2015- 17809); GK and SX were partially funded by the Operational Program “Environment and Sustainable Development” (EPPERAA) of the National Strategic Reference Framework (NSRF) 2007-2013, co- financed by the ERDF and Greek EDP; FdF by a Ph.D. grant from the Coordination for the Improvement of Higher Education Personnel (CAPES—Brazilian government agency; Bex Process 1307/13-4); ZZ by a PhD grant from the University of Barcelona (APIF/2012); MCF by a PhD grant from the University of Barcelona; and RR by post-doctoral contracts of the PLEAMAR programme from MINECO and Fundación Biodiversidad (2017/2349), and Ministerio de Ciencia, in-novación y Universidades (RYC-2017- 22055). This publication is part of the project I+D+i/PID2020-117155GB-I00, funded by MCIN/ AEI/10.13039/501100011033.Peer reviewe

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Cory’s, Scopoli’s, and Cabo Verde shearwaters non-breeding locations [Dataset]

A tabular spreadsheet with the species, colony, unique identifiers for each bird and trip, latitude, longitude, year of tracking (1st year, 2nd year, etc.), and an ordering column that allows the positions to be ordered to form a track.on-breeding locations of Cory’s shearwaters (Calonectris borealis), Scopoli’s shearwaters (C. diomedea), and Cabo Verde shearwaters (C. edwardsii) tracked from the colonies of Berlenga, Chafarinas, Corvo, Faial, Graciosa, Montaña Clara, Pico, Selvagem, Sisargas, Terreros, Timanfaya, Veneguera, and Vila for Cory’s shearwaters; Cala Morell, Chafarinas, Filfla, Frioul, Giraglia, Gozo, Lavezzi, Linosa, Malta, Na Foradada, Na Pobra, Palomas, Pantaleu, Paximada, Porquerolles, Riou, Strofades, Tremiti, and Zembra for Scopoli’s shearwaters; and Curral Velho and Raso for Cabo Verde’s shearwaters. Animals were tracked between the years of 2006 and 2016, and data includes species, colony, unique identifiers for each bird and trip, latitude, longitude, year of tracking (1st year, 2nd year, etc.), and an ordering column that allows the positions to be ordered to form a track.Peer reviewe

Methods to detect spatial biases in tracking studies caused by differential representativeness of individuals, populations and time

Aim: Over the last decades, the study of movement through tracking data has grown exceeding the expectations of movement ecologists. This has posed new challenges, specifically when using individual tracking data to infer higher-level distributions (e.g. population and species). Sources of variability such as individual site fidelity (ISF), environmental stochasticity over time, and space-use variability across species ranges must be considered, and their effects identified and corrected, to produce accurate estimates of spatial distribution using tracking data. Innovation: We developed R functions to detect the effect of these sources of variability in the distribution of animal groups when inferred from individual tracking data. These procedures can be adapted for their use in most tracking datasets and tracking techniques. We demonstrated our procedures with simulated datasets and showed their applicability on a real-world dataset containing 1346 year-round migratory trips from 805 individuals of three closely related seabird species breeding in 34 colonies in the Mediterranean Sea and the Atlantic Ocean, spanning 10 years. We detected an effect of ISF in one of the colonies, but no effect of the environmental stochasticity on the distribution of birds for any of the species. We also identified among-colony variability in nonbreeding space use for one species, with significant effects of population size and longitude. Main conclusions: This work provides a useful, much-needed tool for researchers using animal tracking data to model species distributions or establish conservation measures. This methodology may be applied in studies using individual tracking data to accurately infer the distribution of a population or species and support the delineation of important areas for conservation based on tracking data. This step, designed to precede any analysis, has become increasingly relevant with the proliferation of studies using large tracking datasets that has accompanied the globalization process in science driving collaborations and tracking data sharing initiatives

Relações entre profissionais de saúde e usuários durante as práticas em saúde Relationships between health professionals and users throughout health care practices

Apresenta-se uma revisão integrativa sobre estudos que abordam as relações entre profissionais de saúde e usuários durante as práticas em saúde. Objetivou-se identificar os aspectos pesquisados no cotidiano dos serviços acerca dessas relações. A coleta foi realizada nas bases Lilacs e Pubmed segundo os descritores: acolhimento; relações profissional-família; relações profissional-paciente; humanização da assistência; e a palavra 'vínculo' associada ao descritor Sistema Único de Saúde. Selecionaram-se 290 estudos publicados entre 1990 e 2010. Por meio da análise temática, foram criados cinco núcleos de sentido: a relevância da confiança na relação profissional-usuário; sentimentos e sentidos na prática do cuidado; a importância da comunicação nos serviços de saúde; modo de organização das práticas em saúde; e (des)colonialismo. Identificou-se que as relações estabelecidas nas práticas de saúde têm uma dimensão transformadora. No entanto, permanece o desafio de humanizar os serviços de saúde. A enfermagem se destaca na produção do conhecimento nessa temática.<br>This article presents an integrative review about studies that address the relationships between health professionals and users in health care practices. It aimed to identify aspects that were researched on the daily life of the services concerning such relationships. Data were collected from the Lilacs and Pubmed databases based on these descriptors: user embracement; professionalfamily relations; professionalpatient relations; humanization of the care; and the bonding word associated to the Single Health System descriptor. Two hundred and ninety studies, published from 1990 to 2010, were selected. Through thematic analyses, five meaning cores were created: the relevance of the confidence in the professionaluser relationship; feelings and senses in the health care practice; the importance of communications in health care services; ways to organize health care practices and (de)colonialism. It was found that relationships established in health care practices have a transformative dimension. However, the challenge to humanize health care services remains. Nursing stands out in the production of knowledge on such theme

Field and classroom initiatives for portable sequence-based monitoring of dengue virus in Brazil

This work was supported by Decit, SCTIE, Brazilian Ministry of Health, Conselho Nacional de Desenvolvimento Científico - CNPq (440685/ 2016-8, 440856/2016-7 and 421598/2018-2), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES - (88887.130716/2016-00), European Union’s Horizon 2020 Research and Innovation Programme under ZIKAlliance Grant Agreement (734548), STARBIOS (709517), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – FAPERJ (E-26/2002.930/2016), International Development Research Centre (IDRC) Canada (108411-001), European Union’s Horizon 2020 under grant agreements ZIKACTION (734857) and ZIKAPLAN (734548).Fundação Ezequiel Dias. Laboratório Central de Saúde Pública do Estado de Minas Gerais. Belo Horizonte, MG, Brazil / Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil Latin American Genomic Surveillance Arboviral Network.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Secretaria de Saúde do Estado de Mato Grosso do Sul. Laboratório Central de Saúde Pública. Campo Grande, MS, Brazil.Fundação Ezequiel Dias. Laboratório Central de Saúde Pública do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.Laboratório Central de Saúde Pública Dr. Giovanni Cysneiros. Goiânia, GO, Brazil.Laboratório Central de Saúde Pública Professor Gonçalo Moniz. Salvador, BA, Brazil.Secretaria de Saúde do Estado da Bahia. Salvador, BA, Brazil.Laboratório Central de Saúde Pública Dr. Milton Bezerra Sobral. Recife, PE, Brazil.Laboratório Central de Saúde Pública do Estado de Mato Grosso. Cuiabá, MT, Brazil.Laboratório Central de Saúde Pública do Distrito Federal. Brasília, DF, Brazil.Fundação Ezequiel Dias. Laboratório Central de Saúde Pública do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Coordenação Geral dos Laboratórios de Saúde Pública. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Coordenação Geral dos Laboratórios de Saúde Pública. Brasília, DF, Brazil.Organização Pan-Americana da Saúde / Organização Mundial da Saúde. Brasília, DF, Brazil.Organização Pan-Americana da Saúde / Organização Mundial da Saúde. Brasília, DF, Brazil.Organização Pan-Americana da Saúde / Organização Mundial da Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde Coordenação Geral das Arboviroses. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde Coordenação Geral das Arboviroses. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde Coordenação Geral das Arboviroses. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde Coordenação Geral das Arboviroses. Brasília, DF, Brazil.Fundação Hemocentro de Ribeirão Preto. Ribeirão Preto, SP, Brazil.Gorgas Memorial Institute for Health Studies. Panama, Panama.Universidade Federal da Bahia. Vitória da Conquista, BA, Brazil.Laboratorio Central de Salud Pública. Asunción, Paraguay.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Coordenação Geral dos Laboratórios de Saúde Pública. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, BrazilFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, BrazilMinistério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Laboratório Central de Saúde Pública do Estado de Mato Grosso do Sul. Campo Grande, MS, Brazil.Laboratório Central de Saúde Pública do Estado de Mato Grosso do Sul. Campo Grande, MS, Brazil.Instituto de Investigaciones en Ciencias de la Salud. San Lorenzo, Paraguay.Secretaria de Estado de Saúde de Mato Grosso do Sul. Campo Grande, MS, Brazil.Fundação Oswaldo Cruz. Campo Grande, MS, Brazil.Fundação Hemocentro de Ribeirão Preto. Ribeirão Preto, SP, Brazil.Laboratório Central de Saúde Pública Dr. Giovanni Cysneiros. Goiânia, GO, Brazil.Laboratório Central de Saúde Pública Dr. Giovanni Cysneiros. Goiânia, GO, Brazil.Laboratório Central de Saúde Pública Professor Gonçalo Moniz. Salvador, BA, Brazil.Laboratório Central de Saúde Pública Dr. Milton Bezerra Sobral. Recife, PE, Brazil.Laboratório Central de Saúde Pública do Distrito Federal. Brasília, DF, Brazil.Secretaria de Saúde de Feira de Santana. Feira de Santana, Ba, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Secretaria de Saúde do Estado de Minas Gerais. Belo Horizonte, MG, Brazil.Hospital das Forças Armadas. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Universidade Nova de Lisboa. Instituto de Higiene e Medicina Tropical. Lisboa, Portugal.University of Sydney. School of Life and Environmental Sciences and School of Medical Sciences. Marie Bashir Institute for Infectious Diseases and Biosecurity. Sydney, NSW, Australia.University of KwaZulu-Natal. College of Health Sciences. KwaZulu-Natal Research Innovation and Sequencing Platform. Durban, South Africa.University of Oxford. Peter Medawar Building. Department of Zoology. Oxford, UK.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Universidade Estadual de Feira de Santana. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Universidade de Brasília. Brasília, DF, Brazil.Universidade Salvador. Salvador, BA, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Ezequiel Dias. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hantaviroses e Rickettsioses. Rio de Janeiro, RJ, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Faculdade de Medicina Veterinária. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Faculdade de Medicina Veterinária. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brazil.Laboratório Central de Saúde Pública do Estado do Paraná. Curitiba, PR, Brazil.Laboratório Central de Saúde Pública do Estado de Rondônia. Porto Velho, RO, Brazil.Laboratório Central de Saúde Pública do Estado do Amazonas. Manaus, AM, Brazil.Laboratório Central de Saúde Pública do Estado do Rio Grande do Norte. Natal, RN, Brazil.Laboratório Central de Saúde Pública do Estado de Mato Grosso. Cuiabá, MT, Brazil.Laboratório Central de Saúde Pública Professor Gonçalo Moniz. Salvador, BA, Brazil.Laboratório Central de Saúde Pública Professor Gonçalo Moniz. Salvador, BA, Brazil.Laboratório Central de Saúde Pública Noel Nutels. Rio de Janeiro, RJ, Brazil.Instituto Adolfo Lutz. 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.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.Universidade de São Paulo. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Universidade de São Paulo. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Universidade de São Paulo. Instituto de Medicina Tropical. São Paulo, SP, Brazil.University of Oxford. Peter Medawar Building. Department of Zoology. Oxford, UK.Instituto Nacional de Enfermedades Virales Humanas Dr. Julio Maiztegui. Pergamino, Argentina.Gorgas Memorial Institute for Health Studies. Panama, Panama.Gorgas Memorial Institute for Health Studies. Panama, Panama.Gorgas Memorial Institute for Health Studies. Panama, Panama.Instituto de Salud Pública de Chile. Santiago, Chile.Instituto de Diagnóstico y Referencia Epidemiológicos Dr. Manuel Martínez Báez. Ciudad de México, México.Instituto Nacional de Enfermedades Infecciosas Dr Carlos G Malbrán. Buenos Aires, Argentina.Ministerio de Salud Pública de Uruguay. Montevideo, Uruguay.Instituto Costarricense de Investigación y Enseñanza em Nutrición y Salud. Tres Ríos, Costa Rica.Instituto Nacional de Investigacion en Salud Publica Dr Leopoldo Izquieta Pérez. Guayaquil, Ecuador.Instituto Nacional de Investigacion en Salud Publica Dr Leopoldo Izquieta Pérez. Guayaquil, Ecuador.Universidade Federal de Pernambuco. Recife, PE, Brazil.Secretaria de Saúde do Estado de Minas Gerais. Belo Horizonte. MG, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal do Rio de Janeiro. Rio de Janeiro, RJ, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Universidade Federal de Ouro Preto. Ouro Preto, MG, Brazil.Fundação Hemocentro de Ribeirão Preto. Ribeirão Preto, SP, Brazil.Secretaria de Saúde de Feira de Santana. Feira de Santana, BA, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, Brazil.Brazil experienced a large dengue virus (DENV) epidemic in 2019, highlighting a continuous struggle with effective control and public health preparedness. Using Oxford Nanopore sequencing, we led field and classroom initiatives for the monitoring of DENV in Brazil, generating 227 novel genome sequences of DENV1-2 from 85 municipalities (2015–2019). This equated to an over 50% increase in the number of DENV genomes from Brazil available in public databases. Using both phylogenetic and epidemiological models we retrospectively reconstructed the recent transmission history of DENV1-2. Phylogenetic analysis revealed complex patterns of transmission, with both lineage co-circulation and replacement. We identified two lineages within the DENV2 BR-4 clade, for which we estimated the effective reproduction number and pattern of seasonality. Overall, the surveillance outputs and training initiative described here serve as a proof-of-concept for the utility of real-time portable sequencing for research and local capacity building in the genomic surveillance of emerging viruses

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved