Microwave-assisted enzymatic synthesis of beef tallow biodiesel

Optimal conditions for the microwave-assisted enzymatic synthesis of biodiesel have been developed by a full 2(2) factorial design leading to a set of seven runs with different combinations of molar ratio and temperature. The main goal was to reduce the reaction time preliminarily established by a process of conventional heating. Reactions yielding biodiesel, in which beef tallow and ethanol used as raw materials were catalyzed by lipase from Burkholderia cepacia immobilized on silica-PVA and microwave irradiations within the range of 8-15 W were performed to reach the reaction temperature. Under optimized conditions (1:6 molar ratio of beef tallow to ethanol molar ratio at 50A degrees C) almost total conversion of the fatty acid presented in the original beef tallow was converted into ethyl esters in a reaction that required 8 h, i.e., a productivity of about 92 mg ethyl esters g(-1) h(-1). This represents an increase of sixfold for the process carried out under conventional heating. In general, the process promises low energy demand and higher biodiesel productivity. The microwave assistance speeds up the enzyme catalyzed reactions, decreases the destructive effects on the enzyme of the operational conditions such as, higher temperature, stability, and specificity to its substrate, and allows the entire reaction medium to be heated uniformly.

Co-metabolic models of Streptococcus thermophilus in co-culture with Lactobacillus bulgaricus or Lactobacillus acidophilus

To shed light on the interactions occurring in fermented milks when using co-cultures of Streptococcus thermophilus with Lactobacillus bulgaricus (StLb) or Lactobacillus acidophilus (StLa), a new co-metabolic model was proposed and checked either in the presence of Inulin as a prebiotic or not. For this purpose, the experimental data of concentrations of substrates and fermented products were utilized in balances of carbon, reduction degree and ATP. S. thermophilus exhibited always quicker growth compared to the other two microorganisms, while the percentage of lactose fermented to lactic acid, that of galactose metabolized, and the levels of diacetyl and acetoin formed strongly depended on the type of co-culture and the presence of inulin. The StLb co-culture led to higher acetoin and lower diacetyl levels compared to StLa, probably because of more reducing conditions or limited acetoin dehydrogenation. Inulin addition to StLa suppressed acetoin accumulation and hindered that of diacetyl, suggesting catabolite repression of alpha-acetolactate synthase expression in S. thermophilus. Both co-cultures showed the highest ATP requirements for biomass growth and maintenance at the beginning of fermentation, consistently with the high energy demand of enzyme induction during lag phase. Inulin reduced these requirements making biomass synthesis and maintenance less energy-consuming. Only a fraction of galactose was released from lactose, consistently with the galactose-positive phenotype of most dairy strains. The galactose fraction metabolized without inulin was about twice that in its presence, which suggests inhibition of the galactose transport system of S. thermophilus by fructose released from partial inulin hydrolysis. (C) 2012 Elsevier B.V. All rights reserved.

Feasibility Study of a Solar Reactor for Phenol Treatment by the Photo-Fenton process in Aqueous Solution

Solar reactors can be attractive in photodegradation processes due to lower electrical energy demand. The performance of a solar reactor for two flow configurations, i.e., plug flow and mixed flow, is compared based on experimental results with a pilot-scale solar reactor. Aqueous solutions of phenol were used as a model for industrial wastewater containing organic contaminants. Batch experiments were carried out under clear sky, resulting in removal rates in the range of 96100?%. The dissolved organic carbon removal rate was simulated by an empirical model based on neural networks, which was adjusted to the experimental data, resulting in a correlation coefficient of 0.9856. This approach enabled to estimate effects of process variables which could not be evaluated from the experiments. Simulations with different reactor configurations indicated relevant aspects for the design of solar reactors.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Hydrogen and Methane Production, Energy Recovery, and Organic Matter Removal from Effluents in a Two-Stage Fermentative Process

This study evaluates the potential for using different effluents for simultaneous H-2 and CH4 production in a two-stage batch fermentation process with mixed microflora. An appreciable amount of H-2 was produced from parboiled rice wastewater (23.9 mL g(-1) chemical oxygen demand [COD]) and vinasse (20.8 mL g(-1) COD), while other effluents supported CH4 generation. The amount of CH4 produced was minimum for sewage (46.3 mL g(-1) COD), followed by parboiled rice wastewater (115.5 mL g(-1) COD) and glycerol (180.1 mL g(-1) COD). The maximum amount of CH4 was observed for vinasse (255.4 mL g(-1) COD). The total energy recovery from vinasse (10.4 kJ g(-1) COD) corresponded to the maximum COD reduction (74.7 %), followed by glycerol (70.38 %, 7.20 kJ g(-1) COD), parboiled rice wastewater (63.91 %, 4.92 kJ g(-1) COD), and sewage (51.11 %, 1.85 kJ g(-1) COD). The relatively high performance of vinasse in such comparisons could be attributed to the elevated concentrations of macronutrients contained in raw vinasse. The observations are based on kinetic parameters of H-2 and CH4 production and global energy recovery of the process. These observations collectively suggest that organic-rich effluents can be deployed for energy recovery with sequential generation of H-2 and CH4.