Encapsulation into Stealth Liposomes Enhances the Antitumor Action of Recombinant Cratylia mollis Lectin Expressed in Escherichia coli

This study evaluated the in vivo antitumor potential of new recombinant lectin from seeds of Cratylia mollis (rCramoll) expressed in Escherichia coli, free or encapsulated in stealth liposomes, using mice transplanted with sarcoma 180. rCramoll-loaded stealth liposomes (rCramoll-lipo) were formulated by hydration of the lipid film followed by cycles of freezing and thawing, and about 60% of rCramoll was encapsulated. This novel preparation showed particle size, polydispersity index, and pH suitable for the evaluation of antitumor activity in vivo. Tumor growth inhibition rates were 68% for rCramoll and 80% for rCramoll-lipo. Histopathological analysis of the experimental groups showed that both free and encapsulated lectin caused no changes in the kidneys of animals. Hematological analysis revealed that treatment with rCramoll-lipo significantly increased leukocyte concentration when compared with the untreated and pCramoll group. In conclusion, the encapsulation of rCramoll in stealth liposomes improves its antitumor activity without substantial toxicity; this approach was more successful than the previous results reported for pCramoll loaded into conventional liposomes. At this point, a crucial difference between the antitumor action of free and encapsulated rCramoll was found along with their effects on immune cells. Further investigations are required to elucidate the mechanism(s) of the antitumor effect induced by rCramoll

Volume fraction calculation in multiphase system such as oil-water-gas using neutron

Multi-phase flows are common in diverse industrial sectors and the attainment of the volume fraction of each element that composes the flow system presents difficulties for the engineering process, therefore, to determine them is very important. In this work is presented methodology for determination of volume fractions in annular three-phase flow systems, such as oil-water-gas, based on the use of nuclear techniques and artificial intelligence. Using the principle of the fast-neutron transmission/scattering, come from an isotopic 241Am-Be source, and two point detectors, is gotten measured that they are influenced by the variations of the volumec fractions of each phase present in the flow. An artificial neural network is trained to correlate such measures with the respective volume fractions. In order to get the data for training of the artificial neural network without necessity to carry through experiments, MCNP-X code is used, that simulates computational of the neutrons transport. The methodology is sufficiently advantageous, therefore, allows to develop a measurement system capable to determine the fractions of the phases (oil-water-gas), with proper requirements of each petroliferous installation and with national technology contributing, possibly, with reduction of costs and increase of productivity

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

Evaluation experiences of the supplementary care sector: contributions of integrality

Este trabalho identifica aspectos de integralidade nas propostas de avaliação de assistência à saúde da Agência Nacional de Saúde Suplementar (ANS), no Brasil, e do National Commitee for Quality Assurance (NCQA), nos Estados Unidos. A metodologia adotada foi a da análise documental das propostas encontradas nos sítios eletrônicos das instituições no segundo semestre de 2006. Os dados foram sistematizados numa matriz analítica com atributos das práticas de gestão e organização de serviços; dos conhecimentos e práticas dos trabalhadores de saúde; e das práticas de controle pela sociedade. Os resultados apresentados destacam, no caso brasileiro, uma ênfase no primeiro e terceiro atributos, com a avaliação centrada nas operadoras – os planos de saúde não foram avaliados. No caso americano, houve um equilíbrio nos três conjuntos de atributos, sendo a avaliação direcionada aos planos de saúde. Ambas as propostas mensuraram a satisfação dos beneficiários e divulgam os resultados das avaliações em sítios eletrônicos. Em conclusão, destaca-se a importância de conceitos e abordagens avaliativas da integralidade nas operadoras de planos privados de saúde no setor suplementar brasileiro.SimThis work identifies aspects of comprehensiveness in the proposals for healthcare evaluation of the Agência Nacional de Saúde Suplementar (ANS) in Brazil, and of the National Commitee Quality Assurance (NCQA) in the U.S.A. The investigation was based on a documental analysis of the proposals found in the websites of both institutions in the second semester of 2006. The data were systemized according to pre-established attributes, building an analytical matrix for evaluating the following three dimensions: management practices and service organization; quality of knowledge and of practices of the health workers; and quality of the control practices of the society. In the Brazilian case there was an emphasis on the first and the third dimensions. The evaluation focalized the operators; the health plans were not evaluated. In the American case there was a balance between the three sets of attributes and the evaluation was focused on the health plans. Both proposals measured the satisfaction of the beneficiaries and made the results of the evaluations available in their websites. In conclusion we emphasize the importance of evaluative concepts and approaches for measuring the integrality of private health plan operators in the Brazilian supplementary health sector