1,364 research outputs found

    Diagnóstico diferencial de ascitis en gatos

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    En el presente trabajo el autor presenta un nuevo protocolo para el diagnóstico diferencial de ascitis en gatos.In this work the author presents a new protocol to study the differential diagnosis in feline ascitis

    Water supply and energy in residential buildings: Potential savings and financial profitability

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    This article examines the suitability of water supply installations in residential buildings for the pressure conditions of the main water network, and evaluates the energy saving possibilities associated with pumping water into homes. It assesses the situation and the options for renovation in a sample of 151 buildings in the city of Zaragoza (Spain), estimating the savings in electric power and the possible financial returns that could be obtained. The results show that in half the buildings, the installations are inadequate and lead to inefficient energy use, which could be avoided by renovation. However, they also show that in many cases, this type of retrofitting would not be profitable for the building owners, meaning that technically viable solutions may not necessarily be financially viable. To mitigate or avoid the energy inefficiency in question, the public sector could step in by informing and financing support for building owners and regulating in the areas of town planning and construction

    Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

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    BACKGROUND: We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. RESULTS: We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. CONCLUSION: Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems

    Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy

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    [Abstract] Background The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. Results The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. Conclusions The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.Ministerio de Economía y Competitividad; DPI2011-28112-C04-03Ministerio de Economía y Competitividad; DPI2011-28112-C04-04Ministerio de Economía y Competitividad; DPI2014-55276-C5-2-RMinisterio de Economía y Competitividad; TIN2013-42148-PMinisterio de Economía y Competitividad; TIN2016-75845-PGalicia. Consellería de Cultura, Educación e Ordenación Universitaria; R2014/041Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; R2016/045Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; GRC2013/05

    Transcorneal Permeation in a Corneal Device of Non-Steroidal Anti-Inflammatory Drugs in Drug Delivery Systems

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    This work is focused on the ex vivo study of corneal permeation of two anti-inflammatory drugs: diclofenac, and flurbiprofen (as a model of hydrophilic and lipophilic drug, respectively) loaded to cyclodextrins or polymeric nanoparticles in order to determine differences in their corneal permeation against free drug or commercial eye drops. These studies were carried out in a corneal device designed and developed in our laboratory. In this work the habitual conditions for the permeation studies were modified to reproduce the behaviour when eye drops were administered. For this reason a new tetracompartmental pharmacokinetic model was developed. The complex formation of diclofenac with cyclodextrins and the flurbiprofen loaded to polymeric nanoparticles has been shown as effective procedures to remarkably increase the bioavailability of the anti-inflammatory drugs. The efficiency of polymeric nanoparticles of Poly (D-L lactic-coglycolyc) acid and poly-ε-caprolacton as intraocular targeting of NSAIDs has also been proved, being the latter polymer more effective to increase the flurbiprofen corneal permeation. The apparent corneal permeability coefficient of samples has been calculated getting a low permeation values for free drugs

    Apoptosis y cáncer

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    Longer-term mortality following SARS-CoV-2 infection in people with severe mental illness: retrospective case-matched study.

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    Persisting symptoms and dysfunction after SARS-CoV-2 infection have frequently been observed. However, information on the aftermath of COVID-19 is inadequate. We followed up people with severe mental illness (SMI) infected with SARS-CoV-2, and evaluated their longer-term mortality, using data from Cambridgeshire and Peterborough NHS Foundation Trust, UK. We examined the time course and duration of mortality risk from the point of diagnosis. After SARS-CoV-2 infection, people with SMI had a substantially higher risk of death (hazard ratio (HR) = 5.16, 95% confidence interval (CI) 1.56-17.03; P = 0.007) during the first 28 days and during the following 28-60 days (HR = 2.96, 95% CI 1.21-7.26; P = 0.018) than those without infection, but after 60 days the additional risk of death was no longer significant (HR = 2.33, 95% CI 0.83-6.53; P = 0.107)
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