Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Synaptic depression and slow oscillatory activity in a biophysical network model of the cerebral cortex

Short-term synaptic depression (STD) is a form of synaptic plasticity that has a large impact on network computations. Experimental results suggest that STD is modulated by cortical activity, decreasing with activity in the network and increasing during silent states. Here, we explored different activity-modulation protocols in a biophysical network model for which the model displayed less STD when the network was active than when it was silent, in agreement with experimental results. Furthermore, we studied how trains of synaptic potentials had lesser decay during periods of activity (UP states) than during silent periods (DOWN states), providing new experimental predictions. We next tackled the inverse question of what is the impact of modifying STD parameters on the emergent activity of the network, a question difficult to answer experimentally. We found that synaptic depression of cortical connections had a critical role to determine the regime of rhythmic cortical activity. While low STD resulted in an emergent rhythmic activity with short UP states and long DOWN states, increasing STD resulted in longer and more frequent UP states interleaved with short silent periods. A still higher synaptic depression set the network into a non-oscillatory firing regime where DOWN states no longer occurred. The speed of propagation of UP states along the network was not found to be modulated by STD during the oscillatory regime; it remained relatively stable over a range of values of STD. Overall, we found that the mutual interactions between synaptic depression and ongoing network activity are critical to determine the mechanisms that modulate cortical emergent patterns.

Filtration of effluents for microirrigation systems

Clogging, measured through head loss across filters, and the filtration quality of different filters using different effluents were studied. The filters used were: 115, 130, and 200 m disc filters; 98, 115, 130, and 178 m screen filters; and a sand filter filled with a single layer of sand with an effective diameter of 0.65 mm. The filters were used with a meat industry effluent and secondary and tertiary effluents of two wastewater treatment plants. It was observed that clogging depended on the type of effluent. With the meat industry effluent, the poorest quality effluent, disc filters clogged more than the other filter types. When the wastewater treatment plant effluents were used, the disc filters showed less frequent clogging. Several physical and chemical parameters, such as total suspended solids, chemical oxygen demand, turbidity, electrical conductivity, pH, and number of particles, were analyzed in the effluents at the entry and exit points of the filters. In general, filters did not reduce the values of the main clogging parameters to a great degree. It was found that the parameter that explained the clogging, expressed as Boucher’s filterability index, was different depending on the type of effluent and filter. The best quality of filtration was achieved with a sand filter when the meat industry effluent was used. No significant differences were observed between the quality of filtration of disc and screen filters when operating with the secondary and tertiary effluents

An active zone characterized by slow normal faults, the northwestern margin of the València trough (NE Iberia): a review

The northwestern margin of the Valencia trough is an area of low strain characterized by slow normal faults and low to moderate seismicity. Since the mid 1990s this area has been the subject of a number of studies on active tectonic which have proposed different approaches to the location of active faults and to the calculation of the parameters that describe their seismic cycle. Fifty-six active faults have been found and a classification has been made in accordance with their characteristics: a) faults with clear evidence of large paleo-, historic or instrumental earthquakes (2/56); b) faults with evidence of accumulated activity during the Plio-Quaternary and with associated instrumental seismicity (7/56); c) faults with evidence of accumulated activity during the Plio-Quaternary and without associated instrumental seismicity (17/56); d) faults with associated instrumental seismicity and without evidence of accumulated activity during the Plio-Quaternary (30/56), and e) faults without evidence of activity or inactive faults. The parameters that describe the seismic cycle of these faults have been evaluated by different methods that use the geological data obtained for each fault except when paleoseismological studies were available. This classification can be applied to other areas with low slip faults because of the simplicity of the approaches adopted. This study reviews the different approaches proposed and describes the active faults located, highlighting the need a) to better understand active faults in slow strain zones through paleoseismological studies, and b) to include them in seismic hazard studies.

Using computational fluid dynamics to predict head losses in the auxiliary elements of a microirrigation sand filter

It is often assumed that total head losses in a sand filter are solely due to the filtration media and that there are analytical solutions, such as the Ergun equation, to compute them. However, total head losses are also due to auxiliary elements (inlet and outlet pipes and filter nozzles), which produce undesirable head losses because they increase energy requirements without contributing to the filtration process. In this study, ANSYS Fluent version 6.3, a commercial computational fluid dynamics (CFD) software program, was used to compute head losses in different parts of a sand filter. Six different numerical filter models of varying complexities were used to understand the hydraulic behavior of the several filter elements and their importance in total head losses. The simulation results show that 84.6% of these were caused by the sand bed and 15.4% were due to auxiliary elements (4.4% in the outlet and inlet pipes, and 11.0% in the perforated plate and nozzles). Simulation results with different models show the important role of the nozzles in the hydraulic behavior of the sand filter. The relationship between the passing area through the nozzles and the passing area through the perforated plate is an important design parameter for the reduction of total head losses. A reduced relationship caused by nozzle clogging would disproportionately increase the total head losses in the sand filter