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

Educomunicação, Transformação Social e Desenvolvimento Sustentável

Esta publicação apresenta os principais trabalhos dos GTs do II Congresso Internacional de Comunicação e Educação nos temas Transformação social, com os artigos que abordam principalmente Educomunicação e/ou Mídia-Educação, no contexto de políticas de diversidade, inclusão e equidade; e, em Desenvolvimento Sustentável os artigos que abordam os avanços da relação comunicação/educação no contexto da educação ambiental e desenvolvimento sustentável

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

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

Papilomatose respiratória recorrente

A papilomatose respiratória recorrente da criança é uma doença rara, mas potencialmente ameaçadora da vida, e que atinge o trato respiratório com predilecção pela laringe e traqueia. É causada pelo papiloma-vírus humano (tipo 6 e 11).É uma das causas de rouquidão e obstrução da via aérea. É necessário um elevado grau de suspeição diagnóstica, tendo em conta as várias formas de apresentação. Apresenta-se o caso de uma criança de quatro anos de idade, com antecedentes de papilomatose laríngea, internada por obstrução respiratória alta grave e necessidade de traqueotomia de emergência.A tipagem viral realizada posteriormente revelou tratar-se do papilomavírus humano tipo 11 e 72. Nos catorze meses seguintes foi submetida a seis intervenções cirúrgicas, inicialmente por técnicas convencionais e laser de CO2, e de seguida utilizando o novo método de microdebridador e aplicação de cidofovir intralesional. Trata-se de um caso ilustrativo de doença extremamente agressiva, que pôs em risco a vida da criança e com óbvia repercussão na sua qualidade de vida. A papilomatose respiratória recorrente, embora rara, deve estar presente nos diagnósticos diferenciais de estridor na criança, de modo a prevenir o crescimento de papilomas e a consequente obstrução grave das vias aéreas

Gold nanoparticle-based fluorescence immunoassay for malaria antigen detection

The development of rapid detection assays for malaria diagnostics is an area of intensive research, as the traditional microscopic analysis of blood smears is cumbersome and requires skilled personnel. Here, we describe a simple and sensitive immunoassay that successfully detects malaria antigens in infected blood cultures. This homogeneous assay is based on the fluorescence quenching of cyanine 3B (Cy3B)-labeled recombinant Plasmodium falciparum heat shock protein 70 (PfHsp70) upon binding to gold nanoparticles (AuNPs) functionalized with an anti-Hsp70 monoclonal antibody. Upon competition with the free antigen, the Cy3B-labeled recombinant PfHsp70 is released to solution resulting in an increase of fluorescence intensity. Two types of AuNP-antibody conjugates were used as probes, one obtained by electrostatic adsorption of the antibody on AuNPs surface and the other by covalent bonding using protein cross-linking agents. In comparison with cross-linked antibodies, electrostatic adsorption of the antibodies to the AuNPs surfaces generated conjugates with increased activity and linearity of response, within a range of antigen concentration from 8.2 to 23.8 μg.mL−1. The estimated LOD for the assay is 2.4 μg.mL−1 and the LOQ is 7.3 μg.mL−1. The fluorescence immunoassay was successfully applied to the detection of antigen in malaria-infected human blood cultures at a 3% parasitemia level, and is assumed to detect parasite densities as low as 1,000 parasites.μL−1

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