GERMINATION AND VIGOR OF Bixa orellana L. SEEDS PRE-SOAKED IN A PLANT BIOSTIMULANT

The aim of this study was to assess the germination and vigor of Bixa orellana seeds that were pre-soaked in different concentrations of Stimulate® plant biostimulant. For the standard germination test, Bixa orellana seeds from the Embrapa 37 Cultivar were pre-soaked (for periods of four and eight hours) in the following concentrations of Stimulate® aqueous solution: 3.0; 6.0; 9.0; and 12.0 mL L-1. Seeds that were pre-soaked in distilled water were used as control. The following parameters were tested: germination; first germination count; abnormal seedlings; length; and seedling dry mass. The experimental design was completely randomized and a 2 x 5 + 1 factorial design was used (with two pre-soaking periods, five Stimulate® concentrations, and one additional control without pre-soaking). Four replicates of 50 seeds were performed for each treatment. Water immersion treatments for four and eight hours were efficient for breaking dormancy in Bixa orellana seeds, since they promoted better germination in relation to the intact seeds that were not pre-soaked. The pre-soaking of Bixa orellana seeds for eight hours in a 12.0 mL L-1 Stimulate® concentration presented the best results in terms of germinative performance and seedling growth, with greater accumulation of dry mass. Therefore, this practice is recommended for the production of seedlings of this species.The aim of this study was to assess the germination and vigor of Bixa orellana seeds that were pre-soaked in different concentrations of Stimulate® plant biostimulant. For the standard germination test, Bixa orellana seeds from the Embrapa 37 cultivar were pre-soaked (for periods of four and eight hours) in the following concentrations of Stimulate® aqueous solution: 3.0; 6.0; 9.0; and 12.0 mL L-1. Seeds that were pre-soaked in distilled water were used as control. The following parameters were tested: germination; first germination count; abnormal seedlings; length; and seedling dry mass. The experimental design was completely randomized. A 2 x 5 + 1 factorial design was used (with two pre-soaking periods, five Stimulate® concentrations, and one additional control without pre-soaking). Four replicates with 50 seeds were performed for each treatment. Water immersion treatments for four and eight hours were efficient in breaking dormancy in Bixa orellana seeds, since they promoted better germination in relation to the intact seeds that were not pre-soaked. The pre-soaking of Bixa orellana seeds for eight hours in a 12.0 mL L-1 Stimulate® concentration presented the best results in terms of germinative performance and seedling growth, with greater accumulation of dry mass. Therefore, this practice is recommended for the production of seedlings of this species

Determinants of intensive insulin therapeutic regimens in patients with type 1 diabetes: data from a nationwide multicenter survey in Brazil

Background: To evaluate the determinants of intensive insulin regimens (ITs) in patients with type 1 diabetes (T1D).Methods: This multicenter study was conducted between December 2008 and December 2010 in 28 public clinics in 20 Brazilian cities. Data were obtained from 3,591 patients (56.0% female, 57.1% Caucasian). Insulin regimens were classified as follows: group 1, conventional therapy (CT) (intermediate human insulin, one to two injections daily); group 2 (three or more insulin injections of intermediate plus regular human insulin); group 3 (three or more insulin injections of intermediate human insulin plus short-acting insulin analogues); group 4, basal-bolus (one or two insulin injections of long-acting plus short-acting insulin analogues or regular insulin); and group 5, basal-bolus with continuous subcutaneous insulin infusion (CSII). Groups 2 to 5 were considered IT groups.Results: We obtained complete data from 2,961 patients. Combined intermediate plus regular human insulin was the most used therapeutic regimen. CSII was used by 37 (1.2%) patients and IT by 2,669 (90.2%) patients. More patients on IT performed self-monitoring of blood glucose and were treated at the tertiary care level compared to CT patients (p < 0.001). the majority of patients from all groups had HbA1c levels above the target. Overweight or obesity was not associated with insulin regimen. Logistic regression analysis showed that economic status, age, ethnicity, and level of care were associated with IT (p < 0.001).Conclusions: Given the prevalence of intensive treatment for T1D in Brazil, more effective therapeutic strategies are needed for long term-health benefits.Farmanguinhos/Fundacao Oswaldo Cruz/National Health MinistryBrazilian Diabetes SocietyFundacao do Amparo a Pesquisa do Estado do Rio de JaneiroConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Estado Rio de Janeiro, Unit Diabet, BR-20551030 Rio de Janeiro, BrazilBaurus Diabet Assoc, São Paulo, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilFed Univ Hosp Porto Alegre, Porto Alegre, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Fed Rio de Janeiro, Rio de Janeiro, BrazilUniv Fed Ceara, Fortaleza, Ceara, BrazilSanta Casa Misericordia, Belo Horizonte, MG, BrazilSanta Casa Misericordia São Paulo, São Paulo, BrazilUniv Fed Amazonas, Manaus, Amazonas, BrazilHosp Geral de Bonsucesso, Rio de Janeiro, BrazilHosp Univ Clementino Fraga Filho IPPMG, Rio de Janeiro, BrazilUniv Hosp São Paulo, São Paulo, BrazilFac Ciencias Med Santa Casa São Paulo, São Paulo, BrazilUniv São Paulo, Inst Crianca, Hosp Clin, São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Hosp Clin, Ribeirao Preto, BrazilAmbulatorio Fac Estadual Med Sao Jose Rio Preto, Ribeirao Preto, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilClin Endocrinol Santa Casa Belo Horizonte, Belo Horizonte, MG, BrazilUniv Estadual Londrina, Londrina, BrazilUniv Fed Parana, Hosp Clin, Porto Alegre, RS, BrazilInst Crianca Com Diabet Rio Grande Sul, Rio Grande Do Sul, RS, BrazilGrp Hosp Conceicao, Inst Crianca Com Diabet, Porto Alegre, RS, BrazilHosp Univ Santa Catarina, Florianopolis, SC, BrazilInst Diabet Endocrinol Joinville, Joinville, BrazilHosp Reg Taguatinga, Brasilia, DF, BrazilHosp Geral Goiania, Goiania, Go, BrazilCtr Diabet & Endocrinol Estado Bahia, Goiania, Go, BrazilUniv Fed Maranhao, Sao Luis, BrazilCtr Integrado Diabet & Hipertensao Ceara, Fortaleza, Ceara, BrazilUniv Fed Sergipe, Aracaju, BrazilHosp Univ Alcides Carneiro, Campina Grande, BrazilHosp Univ Joao de Barros Barreto, Belem, Para, BrazilFed Univ São Paulo State, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, Diabet Unit, São Paulo, BrazilUniv Hosp São Paulo, São Paulo, BrazilEscola Paulista Med, Ctr Diabet, Ribeirao Preto, BrazilWeb of Scienc

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

ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. Please cite this Data Paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. © 2018 by the The Authors. Ecology © 2018 The Ecological Society of Americ

Educomunicação e suas áreas de intervenção: Novos paradigmas para o diálogo intercultural

oai:omp.abpeducom.org.br:publicationFormat/1O material aqui divulgado representa, em essência, a contribuição do VII Encontro Brasileiro de Educomunicação ao V Global MIL Week, da UNESCO, ocorrido na ECA/USP, entre 3&nbsp;e 5 de novembro de 2016. Estamos diante de um conjunto de 104 papers executivos, com uma média de entre 7 e 10 páginas, cada um. Com este rico e abundante material, chegamos ao sétimo e-book publicado pela ABPEducom, em seus seis primeiros anos de existência. A especificidade desta obra é a de trazer as “Áreas de Intervenção” do campo da Educomunicação, colocando-as a serviço de uma meta essencial ao agir educomunicativo: o diálogo intercultural, trabalhado na linha do tema geral do evento internacional: Media and Information Literacy: New Paradigms for Intercultural Dialogue

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

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