Health-related quality of life in patients with type 1 diabetes mellitus in the different geographical regions of Brazil : data from the Brazilian Type 1 Diabetes Study Group

Background: In type 1 diabetes mellitus (T1DM) management, enhancing health-related quality of life (HRQoL) is as important as good metabolic control and prevention of secondary complications. This study aims to evaluate possible regional differences in HRQoL, demographic features and clinical characteristics of patients with T1DM in Brazil, a country of continental proportions, as well as investigate which variables could influence the HRQoL of these individuals and contribute to these regional disparities. Methods: This was a retrospective, cross-sectional, multicenter study performed by the Brazilian Type 1 Diabetes Study Group (BrazDiab1SG), by analyzing EuroQol scores from 3005 participants with T1DM, in 28 public clinics, among all geographical regions of Brazil. Data on demography, economic status, chronic complications, glycemic control and lipid profile were also collected. Results: We have found that the North-Northeast region presents a higher index in the assessment of the overall health status (EQ-VAS) compared to the Southeast (74.6 ± 30 and 70.4 ± 19, respectively; p < 0.05). In addition, North- Northeast presented a lower frequency of self-reported anxiety-depression compared to all regions of the country (North-Northeast: 1.53 ± 0.6; Southeast: 1.65 ± 0.7; South: 1.72 ± 0.7; Midwest: 1.67 ± 0.7; p < 0.05). These findings could not be entirely explained by the HbA1c levels or the other variables examined. Conclusions: Our study points to the existence of additional factors not yet evaluated that could be determinant in the HRQoL of people with T1DM and contribute to these regional disparities

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

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

Subdoses of 17DD yellow fever vaccine elicit equivalent virological/immunological kinetics timeline

Submitted by Nuzia Santos ([email protected]) on 2015-03-02T18:59:13Z No. of bitstreams: 1 2014_133.pdf: 1767507 bytes, checksum: 7391488fb6c7b01f4d8694e5da140f58 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-03-02T18:59:19Z (GMT) No. of bitstreams: 1 2014_133.pdf: 1767507 bytes, checksum: 7391488fb6c7b01f4d8694e5da140f58 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-03-02T19:12:15Z (GMT) No. of bitstreams: 1 2014_133.pdf: 1767507 bytes, checksum: 7391488fb6c7b01f4d8694e5da140f58 (MD5)Made available in DSpace on 2015-03-02T19:12:15Z (GMT). No. of bitstreams: 1 2014_133.pdf: 1767507 bytes, checksum: 7391488fb6c7b01f4d8694e5da140f58 (MD5) Previous issue date: 2014Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro,RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Instituto de Biologia do Exército. Rio de Janeiro, RJ, Brasil.Instituto de Biologia do Exército. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Fundação Oswaldo Cruz. Bio-Manguinhos. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, Minas Gerais, Brasil.Background: The live attenuated 17DD Yellow Fever vaccine is one of the most successful prophylactic interventions for controlling disease expansion ever designed and utilized in larger scale. However, increase on worldwide vaccine demands and manufacturing restrictions urge for more detailed dose sparing studies. The establishment of complementary biomarkers in addition to PRNT and Viremia could support a secure decision-making regarding the use of 17DD YF vaccine subdoses. The present work aimed at comparing the serum chemokine and cytokine kinetics triggered by five subdoses of 17DD YF Vaccine. Methods: Neutralizing antibody titers, viremia, cytokines and chemokines were tested on blood samples obtained from eligible primary vaccinees. Results and discussion: The results demonstrated that a fifty-fold lower dose of 17DD-YF vaccine (587 IU) is able to trigger similar immunogenicity, as evidenced by significant titers of anti-YF PRNT. However, only subdoses as low as 3,013 IU elicit viremia kinetics with an early peak at five days after primary vaccination equivalent to the current dose (27,476 IU), while other subdoses show a distinct, lower in magnitude and later peak at day 6 post-vaccination. Although the subdose of 587 IU is able to trigger equivalent kinetics of IL-8/CXCL-8 and MCP-1/CCL-2, only the subdose of 3,013 IU is able to trigger similar kinetics of MIG/CXCL-9, pro-inflammatory (TNF, IFN-γ and IL-2) and modulatory cytokines (IL-5 and IL-10). Conclusions: The analysis of serum biomarkers IFN-γ and IL-10, in association to PRNT and viremia, support the recommendation of use of a ten-fold lower subdose (3,013 IU) of 17DD-YF vaccine

Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody

Submitted by Nuzia Santos ([email protected]) on 2015-01-08T11:26:26Z No. of bitstreams: 1 Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody.pdf: 966125 bytes, checksum: 28568df442b4339a0d66df8a67105883 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-08T11:28:11Z (GMT) No. of bitstreams: 1 Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody.pdf: 966125 bytes, checksum: 28568df442b4339a0d66df8a67105883 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-08T11:35:53Z (GMT) No. of bitstreams: 1 Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody.pdf: 966125 bytes, checksum: 28568df442b4339a0d66df8a67105883 (MD5)Made available in DSpace on 2015-01-08T11:35:53Z (GMT). No. of bitstreams: 1 Cytokine Signatures of Innate and Adaptive Immunity in 17DD Yellow Fever Vaccinated Children and Its Association With the Level of Neutralizing Antibody.pdf: 966125 bytes, checksum: 28568df442b4339a0d66df8a67105883 (MD5) Previous issue date: 2011Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilUniversidade Federal de Ouro Preto. Ouro Preto, MG, BrasilFundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Bio-Manguinhos. Rio de Janeiro, RJ, BrasilSecretaria de Estado de Saúde de Minas Gerais. Belo Horizonte, MG, BrasilSecretaria de Estado de Saúde de Minas Gerais. Belo Horizonte, MG, BrasilUniversidade de São Paulo. Faculdade de Medicina de Ribeirão Preto. Hospital das Clínicas. Ribeirão Preto, SP, BrasilUniversidade Federal de Minas Gerais. Faculdade de Medicina. Departamento de Propedêutica Complementar Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Biomarcadores de Diagnóstico e Monitoração. Belo Horizonte, MG, BrasilBackground. The live attenuated yellow fever (YF) vaccines have been available for decades and are considered highly effective and one of the safest vaccines worldwide. Methods. The impact of YF-17DD-antigens recall on cytokine profiles of YF-17DD-vaccinated children were characterized using short-term cultures of whole blood samples and single-cell flow cytometry. This study enrolled seroconverters and nonseroconverters after primovaccination (PV-PRNT1 and PV-PRNT2), seroconverters after revaccination (RV-PRNT1), and unvaccinated volunteers (UV-PRNT2). Results. The analysis demonstrated in the PV-PRNT1 group a balanced involvement of pro-inflammatory/ regulatory adaptive immunity with a prominent participation of innate immunity pro-inflammatory events (IL-121 and TNF-a1 NEU and MON). Using the PV-PRNT1 cytokine signature as a reference profile, PV-PRNT2 presented a striking lack of innate immunity proinflammatory response along with an increased adaptive regulatory profile (IL-41CD41 T cells and IL-101 and IL-51CD81 T cells). Conversely, the RV-PRNT1 shifted the overall cytokine signatures toward an innate immunity pro-inflammatory profile and restored the adaptive regulatory response. Conclusions. The data demonstrated that the overall cytokine signature was associated with the levels of PRNT antibodies with a balanced innate/adaptive immunity with proinflammatory/regulatory profile as the hallmark of PV-PRNTMEDIUM1, whereas a polarized regulatory response was observed in PV-PRNT2 and a prominent proinflammatory signature was the characteristic of PV-PRNTHIGH1