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

Resistance of three implant-abutment interfaces to fatigue testing

The design and retentive properties of implant-abutment connectors affect the mechanical resistance of implants. A number of studies have been carried out to compare the efficacy of connecting mechanisms between abutment and fixture. Objectives: The aims of this study were: 1) to compare 3 implant-abutment interfaces (external hexagon, internal hexagon and cone-in-cone) regarding the fatigue resistance of the prosthetic screw, 2) to evaluate the corresponding mode of failure, and 3) to compare the results of this study with data obtained in previous studies on Nobel Biocare and Straumann connectors. Materials and METHODS: In order to duplicate the alternating and multivectorial intraoral loading pattern, the specimens were submitted to the rotating cantilever beam test. The implants, abutments and restoration analogs were spun around their longitudinal axes while a perpendicular force was applied to the external end. The objective was to determine the force level at which 50% of the specimens survived 10(6) load cycles. The mean force levels at which 50% failed and the corresponding 95% confidence intervals were determined using the staircase procedure. RESULTS: The external hexagon interface presented better than the cone-in-cone and internal hexagon interfaces. There was no significant difference between the cone-in-cone and internal hex interfaces. Conclusion: Although internal connections present a more favorable design, this study did not show any advantage in terms of strength. The external hexagon connector used in this study yielded similar results to those obtained in a previous study with Nobel Biocare and Straumann systems. However, the internal connections (cone-in-cone and internal hexagon) were mechanically inferior compared to previous results

Duration of post-vaccination immunity against yellow fever in adults

Submitted by Nuzia Santos ([email protected]) on 2015-06-22T17:37:43Z No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-06-22T17:37:52Z (GMT) No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-06-22T17:58:36Z (GMT) No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Made available in DSpace on 2015-06-22T17:58:36Z (GMT). No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5) Previous issue date: 2014Fundação Oswaldo Cruz. Brasilia, DF, BrasilFundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, BrazilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicosde Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Imunopatologia .Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Esquistossomose. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFood and Drug Administration Center for Biologics Evaluation and Research. Bethesda, USA.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilUniversidade Federal de Alfenas. Alfenas, MG, BrasilUniversidade de Brasília. Faculdade de Medicina. Brasilia, DF, BrasilFundação Oswaldo Cruz. Instituto Evandro Chagas. Ananindeua, PA, BrasilINTRODUCTION: Available scientific evidence to recommend or to advise against booster doses of yellow fever vaccine (YFV) is inconclusive. A study to estimate the seropositivity rate and geometric mean titres (GMT) of adults with varied times of vaccination was aimed to provide elements to revise the need and the timing of revaccination. METHODS: Adults from the cities of Rio de Janeiro and Alfenas located in non-endemic areas in the Southeast of Brazil, who had one dose of YFV, were tested for YF neutralising antibodies and dengue IgG. Time (in years) since vaccination was based on immunisation cards and other reliable records. RESULTS: From 2011 to 2012 we recruited 691 subjects (73% males), aged 18-83 years. Time since vaccination ranged from 30 days to 18 years. Seropositivity rates (95%C.I.) and GMT (International Units/mL; 95%C.I.) decreased with time since vaccination: 93% (88-96%), 8.8 (7.0-10.9) IU/mL for newly vaccinated; 94% (88-97), 3.0 (2.5-3.6) IU/mL after 1-4 years; 83% (74-90), 2.2 (1.7-2.8) IU/mL after 5-9 years; 76% (68-83), 1.7 (1.4-2.0) IU/mL after 10-11 years; and 85% (80-90), 2.1 (1.7-2.5) IU/mL after 12 years or more. YF seropositivity rates were not affected by previous dengue infection. CONCLUSIONS:Eventhough serological correlates of protection for yellow fever are unknown, seronegativity in vaccinated subjects may indicate primary immunisation failure, or waning of immunity to levels below the protection threshold. Immunogenicity of YFV under routine conditions of immunisation services is likely to be lower than in controlled studies. Moreover, infants and toddlers, who comprise the main target group in YF endemic regions, and populations with high HIV infection rates, respond to YFV with lower antibody levels. In those settings one booster dose, preferably sooner than currently recommended, seems to be necessary to ensure longer protection for all vaccinee

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine