85 research outputs found
Antibody reactivity against potato apyrase, a protein that shares epitopes with Schistosoma mansoni ATP diphosphohydrolase isoforms, in acute and chronically infected mice, after chemotherapy and reinfection
Schistosoma mansoni ATP diphosphohydrolase isoforms and potato apyrase share conserved epitopes. By enzyme-linked immunosorbent assays, elevated levels of IgM, IgG2a and IgG1 antibody reactivity against potato apyrase were observed in S. mansoni-infected BALB/c mice during the acute phase of infection, while only IgM and IgG1 antibody reactivity levels maintained elevated during the chronic phase of infection. Antibody reactivity against potato apyrase was monitored over an 11-month period in chronically-infected mice treated with oxamniquine. Eleven months later, the level of seropositive IgM decreased significantly (~30%) compared to the level found in untreated, infected mice. The level of seropositive IgG1 decreased significantly four months after treatment (MAT) (61%) and remained at this level even after 11 months. The IgG2a reactivity against potato apyrase, although unchanged during chronic phase to 11 MAT, appeared elevated again in re-infected mice suggesting a response similar to that found during the acute phase. BALB/c mouse polyclonal anti-potato apyrase IgG reacted with soluble egg antigens probably due to the recognition of parasite ATP diphosphohydrolase. This study, for the first time, showed that the IgG2a antibody from S. mansoni-infected BALB mice cross-reacts with potato apyrase and the level of IgG2a in infected mice differentiates disease phases. The results also suggest that different conserved-epitopes contribute to the immune response in schistosomiasis
Adsorption of cobalt ferrite nanoparticles within layer-by-layer films: a kinetic study carried out using quartz crystal microbalance
The paper reports on the successful use of the quartz crystal microbalance technique to assess accurate kinetics and equilibrium parameters regarding the investigation of in situ adsorption of nanosized cobalt ferrite particles (CoFe2O4-10.5 nm-diameter) onto two different surfaces. Firstly, a single layer of nanoparticles was deposited onto the surface provided by the gold-coated quartz resonator functionalized with sodium 3-mercapto propanesulfonate (3-MPS). Secondly, the layer-by-layer (LbL) technique was used to build multilayers in which the CoFe2O4 nanoparticle-based layer alternates with the sodium sulfonated polystyrene (PSS) layer. The adsorption experiments were conducted by modulating the number of adsorbed CoFe2O4/PSS bilayers (n) and/or by changing the CoFe2O4 nanoparticle concentration while suspended as a stable colloidal dispersion. Adsorption of CoFe2O4 nanoparticles onto the 3-MPS-functionalized surface follows perfectly a first order kinetic process in a wide range (two orders of magnitude) of nanoparticle concentrations. These data were used to assess the equilibrium constant and the adsorption free energy. Alternatively, the Langmuir adsorption constant was obtained while analyzing the isotherm data at the equilibrium. Adsorption of CoFe2O4 nanoparticles while growing multilayers of CoFe2O4/PSS was conducted using colloidal suspensions with CoFe2O4 concentration in the range of 10-8 to 10-6 (moles of cobalt ferrite per litre) and for different numbers of cycles n = 1, 3, 5, and 10. We found the adsorption of CoFe2O4 nanoparticles within the CoFe2O4/PSS bilayers perfectly following a first order kinetic process, with the characteristic rate constant growing with the increase of CoFe2O4 nanoparticle concentration and decreasing with the rise of the number of LbL cycles (n). Additionally, atomic force microscopy was employed for assessing the LbL film roughness and thickness. We found the film thickness increasing from about 20 to 120 nm while shifting from 3 to 10 CoFe2O4/PSS bilayers, using the 8.9 × 10-6 (moles of cobalt ferrite per litre) suspension.MCT/CNPqFINEPCAPESFUNAPEFINATE
Fasciola hepatica IN BOVINES IN BRAZIL: DATA AVAILABILITY AND SPATIAL DISTRIBUTION
Fasciolosis is a disease of importance for both veterinary and public health. For the first time, georeferenced prevalence data of Fasciola hepatica in bovines were collected and mapped for the Brazilian territory and data availability was discussed. Bovine fasciolosis in Brazil is monitored on a Federal, State and Municipal level, and to improve monitoring it is essential to combine the data collected on these three levels into one dataset. Data were collected for 1032 municipalities where livers were condemned by the Federal Inspection Service (MAPA/SIF) because of the presence of F. hepatica. The information was distributed over 11 states: Espírito Santo, Goiás, Minas Gerais, Mato Grosso do Sul, Mato Grosso, Pará, Paraná, Rio de Janeiro, Rio Grande do Sul, Santa Catarina and São Paulo. The highest prevalence of fasciolosis was observed in the southern states, with disease clusters along the coast of Paraná and Santa Catarina and in Rio Grande do Sul. Also, temporal variation of the prevalence was observed. The observed prevalence and the kriged prevalence maps presented in this paper can assist both animal and human health workers in estimating the risk of infection in their state or municipality
Consenso brasileiro para o tratamento da esclerose múltipla : Academia Brasileira de Neurologia e Comitê Brasileiro de Tratamento e Pesquisa em Esclerose Múltipla
O crescent arsenal terapêutico na esclerose múltipla (EM) tem permitido tratamentos mais efetivos e personalizados, mas a escolha e o manejo das terapias modificadoras da doença (TMDs) tem se tornado cada vez mais complexos. Neste contexto, especialistas do Comitê Brasileiro de Tratamento e Pesquisa em Esclerose Múltipla e do Departamento Científico de Neuroimunologia da Academia Brasileira de Neurologia reuniram-se para estabelecer este Consenso Brasileiro para o Tratamento da EM, baseados no entendimento de que neurologistas devem ter a possibilidade de prescrever TMDs para EM de acordo com o que é melhor para cada paciente, com base em evidências e práticas atualizadas. Por meio deste documento, propomos recomendações práticas para o tratamento da EM, com foco principal na escolha e no manejo das TMDs, e revisamos os argumentos que embasam as estratégias de tratamento na EM.The expanding therapeutic arsenal in multiple sclerosis (MS) has allowed for more effective and personalized treatment, but the choice and management of disease-modifying therapies (DMTs) is becoming increasingly complex. In this context, experts from the Brazilian Committee on Treatment and Research in Multiple Sclerosis and the Neuroimmunology Scientific Department of the Brazilian Academy of Neurology have convened to establish this Brazilian Consensus for the Treatment of MS, based on their understanding that neurologists should be able to prescribe MS DMTs according to what is better for each patient, based on up-to-date evidence and practice. We herein propose practical recommendations for the treatment of MS, with the main focus on the choice and management of DMTs, as well as present a review of the scientific rationale supporting therapeutic strategies in MS
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
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
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