9 resultados para Network scale-up method

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Background: Great efforts have been made to increase accessibility of HIV antiretroviral therapy (ART) in low and middle-income countries. The threat of wide-scale emergence of drug resistance could severely hamper ART scale-up efforts. Population-based surveillance of transmitted HIV drug resistance ensures the use of appropriate first-line regimens to maximize efficacy of ART programs where drug options are limited. However, traditional HIV genotyping is extremely expensive, providing a cost barrier to wide-scale and frequent HIV drug resistance surveillance. Methods/Results: We have developed a low-cost laboratory-scale next-generation sequencing-based genotyping method to monitor drug resistance. We designed primers specifically to amplify protease and reverse transcriptase from Brazilian HIV subtypes and developed a multiplexing scheme using multiplex identifier tags to minimize cost while providing more robust data than traditional genotyping techniques. Using this approach, we characterized drug resistance from plasma in 81 HIV infected individuals collected in Sao Paulo, Brazil. We describe the complexities of analyzing next-generation sequencing data and present a simplified open-source workflow to analyze drug resistance data. From this data, we identified drug resistance mutations in 20% of treatment naive individuals in our cohort, which is similar to frequencies identified using traditional genotyping in Brazilian patient samples. Conclusion: The developed ultra-wide sequencing approach described here allows multiplexing of at least 48 patient samples per sequencing run, 4 times more than the current genotyping method. This method is also 4-fold more sensitive (5% minimal detection frequency vs. 20%) at a cost 3-5 x less than the traditional Sanger-based genotyping method. Lastly, by using a benchtop next-generation sequencer (Roche/454 GS Junior), this approach can be more easily implemented in low-resource settings. This data provides proof-of-concept that next-generation HIV drug resistance genotyping is a feasible and low-cost alternative to current genotyping methods and may be particularly beneficial for in-country surveillance of transmitted drug resistance.

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This article presents an overview of relevant issues to be considered in the development of standardized phytochemical preparations, focusing on the use of the spouted bed as a drying method. Aspects related to the effects of feed composition properties and processing parameters on system performance and product quality are addressed. From the information presented, it can be concluded that the spouted bed technology can be successfully applied for production of high-quality phytochemical preparations suitable for food and pharmaceutical purposes, considering the requirements for product safety, quality, and efficacy. Nevertheless, it should be emphasized that, at this time, the proposed technology is appropriate for small-scale production, mainly due to difficulties concerning scale-up, modeling, and the simulation of spouted bed systems, and also for predicting product properties and system behavior during operation.

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Bromelain is an aqueous extract of pineapple that contains a complex mixture of proteases and non-protease components. These enzymes perform an important role in proteolytic modulation of the cellular matrix in numerous physiologic processes, including anti-inflammatory, anti-thrombotic and fibrinolytic functions. Due to the scale of global production of pineapple (Ananas comosus L.), and the high percentage of waste generated in their cultivation and processing, several studies have been conducted on the recovery of bromelain. The aim of this study was to purify bromelain from pineapple wastes using an easy-to-scale-up process of precipitation by ethanol. The results showed that bromelain was recovered by using ethanol at concentrations of 30% and 70%, in which a purification factor of 2.28 fold was achieved, and yielded more than 98% of the total enzymatic activity. This enzyme proved to be susceptible to denaturation after the lyophilization process. However, by using 10% (w/v) glucose as a cryoprotector, it was possible to preserve 90% of the original enzymatic activity. The efficiency of the purification process was confirmed by SDS-PAGE, and native-PAGE electrophoresis, fluorimetry, circular dichroism and FTIR analyzes, showing that this method could be used to obtain highly purified and structurally stable bromelain. (C) 2012 Elsevier B.V. All rights reserved.

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We developed cationic liposomes containing DNA through a conventional process involving steps of (i) preformation of liposomes, (ii) extrusion, (iii) drying and rehydration and (iv) DNA complexation. Owing to its high prophylactic potentiality against tuberculosis, which had already been demonstrated in preclinical assays, we introduced modifications into the conventional process towards getting a simpler and more economical process for further scale-up. Elimination of the extrusion step, increasing the lipid concentration (from 16 to 64 mM) of the preformed liposomes and using good manufacturing practice bulk lipids (96-98% purity) instead of analytical grade purity lipids (99.9-100%) were the modifications studied. The differences in the physico-chemical properties, such as average diameter, zeta potential, melting point and morphology of the liposomes prepared through the modified process, were not as significant for the biological properties, such as DNA loading on the cationic liposomes, and effective immune response in mice after immunisation as the control liposomes prepared through the conventional process. Beneficially, the modified process increased productivity by 22% and reduced the cost of raw material by 75%.

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The aim of this Account is to provide an overview of our current research activities on the design and modification of superparamagnetic nanomaterials for application in the field of magnetic separation and catalysis. First, an introduction of magnetism and magnetic separation is done. Then, the synthetic strategies that have been developed for generating superparamagnetic nanoparticles spherically coated by silica and other oxides, with a focus on well characterized systems prepared by methods that generate samples of high quality and easy to scale- up, are discussed. A set of magnetically recoverable catalysts prepared in our research group by the unique combination of superparamagnetic supports and metal nanoparticles is highlighted. This Account is concluded with personal remarks and perspectives on this research field.

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The aim of this Account is to provide an overview of our current research activities on the design and modification of superparamagnetic nanomaterials for application in the field of magnetic separation and catalysis. First, an introduction of magnetism and magnetic separation is done. Then, the synthetic strategies that have been developed for generating superparamagnetic nanoparticles spherically coated by silica and other oxides, with a focus on well characterized systems prepared by methods that generate samples of high quality and easy to scale-up, are discussed. A set of magnetically recoverable catalysts prepared in our research group by the unique combination of superparamagnetic supports and metal nanoparticles is highlighted. This Account is concluded with personal remarks and perspectives on this research field.

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Fluctuation-dissipation theorems can be used to predict characteristics of noise from characteristics of the macroscopic response of a system. In the case of gene networks, feedback control determines the "network rigidity," defined as resistance to slow external changes. We propose an effective Fokker-Planck equation that relates gene expression noise to topology and to time scales of the gene network. We distinguish between two situations referred to as normal and inverted time hierarchies. The noise can be buffered by network feedback in the first situation, whereas it can be topology independent in the latter.

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Too Big to Ignore (TBTI; www.toobigtoignore.net) is a research network and knowledge mobilization partnership established to elevate the profile of small-scale fisheries (SSF), to argue against their marginalization in national and international policies, and to develop research and governance capacity to address global fisheries challenges. Network participants and partners are conducting global and comparative analyses, as well as in-depth studies of SSF in the context of local complexity and dynamics, along with a thorough examination of governance challenges, to encourage careful consideration of this sector in local, regional and global policy arenas. Comprising 15 partners and 62 researchers from 27 countries, TBTI conducts activities in five regions of the world. In Latin America and the Caribbean (LAC) region, we are taking a participative approach to investigate and promote stewardship and self-governance in SSF, seeking best practices and success stories that could be replicated elsewhere. As well, the region will focus to promote sustainable livelihoods of coastal communities. Key activities include workshops and stakeholder meetings, facilitation of policy dialogue and networking, as well as assessing local capacity needs and training. Currently, LAC members are putting together publications that examine key issues concerning SSF in the region and best practices, with a first focus on ecosystem stewardship. Other planned deliverables include comparative analysis, a regional profile on the top research issues on SSF, and a synthesis of SSF knowledge in LAC

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Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.