Nanofósseis Calcários Neógenos da Elevação do Rio Grande e Canal de Vema (DSDP - Leg 72, Sites 516, 516A e 518 - Oceano Atlântico Sul): Sistemática do Gênero Discoaster

Os discoasteres são nanofósseis calcários de ampla distribuição e especiação no Cenozoico, apresentando formas de estrelas ou rosetas. No Neógeno, este gênero orienta a detecção de diversas biozonas, através de seus surgimentos e extinções. Porém, por possuírem raios compostos por calcitas de hábito tabular, são mais suscetíveis aos efeitos de supercrescimento e recristalização que os cocólitos, sendo muitos indivíduos, morfologicamente diferentes, englobados numa mesma espécie, e apresentados como variações preservacionais. Ao investigarmos os estratos mio-pliocênicos da Elevação do Rio Grande e Canal de Vema, nos deparamos com quantidades representativas destas variantes preservacionais, que são discutidas neste trabalho. Vinte e três táxons foram descritos e oito variantes foram destacadas, de forma a apresentarmos novas observações e discussões, visando possíveis aplicações bioestratigráficas em investigações futuras

Estudo Bioestratigráfico e Inferências Paleoclimáticas com Base em Nanofósseis Calcários, Eoceno-Oligoceno, Leg 39 - Site 354 (DSDP): Elevação Ceará (Atlântico Equatorial)

As amostras utilizadas para este estudo de nanofósseis calcários foram cedidas pelo Deep Sea Drilling Project (DSDP) e referem-se ao Site 354, Leg 39. O poço está situado na borda noroeste da Elevação Ceará, em uma feição topográfica distante cento e cinquenta metros do cone amazônico (Atlântico Equatorial). A partir da distribuição estratigráfica das espécies, a seção investigada foi refinada bioestratigraficamente e, posteriormente, intervalos cronoestratigráficos foram identificados. Foram descritas um total de seis biozonas, referentes ao intervalo Eoceno/Oligoceno. Dentre os nanofósseis calcários descritos e registrados destacam-se: Isthmolithus recurvus, Sphenolithus pseudoradians, Sphenolithus ciperoensis, Discoaster barbadiensis, Discoaster saipanensis, Sphenolithus intercalaris, Clausicoccus subdistichus, Sphenolithus distentus, Sphenolithus predistentus, Cyclicargolithus abisectus, Helicosphaera recta, Discoaster tanii, Coccolithus pelagicus, Helicosphaera euphratis e Triquetrorhabdulus milowii. Todas as principais espécies foram devidamente fotografadas e mensuradas, a fim de ilustrar o estudo e construir um biozoneamento de detalhe no intervalo em questão. A partir do comportamento da associação de nanofósseis, inferências paleoclimáticas foram sugeridas

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

Regional differences in clinical care among patients with type 1 diabetes in Brazil: Brazilian Type 1 Diabetes Study Group

Background\ud To determine the characteristics of clinical care offered to type 1 diabetic patients across the four distinct regions of Brazil, with geographic and contrasting socioeconomic differences. Glycemic control, prevalence of cardiovascular risk factors, screening for chronic complications and the frequency that the recommended treatment goals were met using the American Diabetes Association guidelines were evaluated.\ud \ud Methods\ud This was a cross-sectional, multicenter study conducted from December 2008 to December 2010 in 28 secondary and tertiary care public clinics in 20 Brazilian cities in north/northeast, mid-west, southeast and south regions. The data were obtained from 3,591 patients (56.0% females and 57.1% Caucasians) aged 21.2 ± 11.7 years with a disease duration of 9.6 ± 8.1 years (<1 to 50 years).\ud \ud Results\ud Overall, 18.4% patients had HbA1c levels <7.0%, and 47.5% patients had HbA1c levels ≥ 9%. HbA1c levels were associated with lower economic status, female gender, age and the daily frequency of self-blood glucose monitoring (SBGM) but not with insulin regimen and geographic region. Hypertension was more frequent in the mid-west (32%) and north/northeast (25%) than in the southeast (19%) and south (17%) regions (p<0.001). More patients from the southeast region achieved LDL cholesterol goals and were treated with statins (p<0.001). Fewer patients from the north/northeast and mid-west regions were screened for retinopathy and nephropathy, compared with patients from the south and southeast. Patients from the south/southeast regions had more intensive insulin regimens than patients from the north/northeast and mid-west regions (p<0.001). The most common insulin therapy combination was intermediate-acting with regular human insulin, mainly in the north/northeast region (p<0.001). The combination of insulin glargine with lispro and glulisine was more frequently used in the mid-west region (p<0.001). Patients from the north/northeast region were younger, non-Caucasian, from lower economic status, used less continuous subcutaneous insulin infusion, performed less SBGM and were less overweight/obese (p<0.001).\ud \ud Conclusions\ud A majority of patients, mainly in the north/northeast and mid-west regions, did not meet metabolic control goals and were not screened for diabetes-related chronic complications. These results should guide governmental health policy decisions, specific to each geographic region, to improve diabetes care and decrease the negative impact diabetes has on the public health system.We thank Mrs. Karianne Aroeira Davidson, Mrs. Anna Maria Ferreira, Mrs. Elisangela Santos and Sandro Sperandei for their technical assistance.This work was supported by grants from Farmanguinhos/Fundação Oswaldo Cruz/National Health Ministry, the Brazilian Diabetes Society, Fundação do Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico do Brasil

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