Optimisation of a continuous flash fermentation for butanol production using the response surface methodology

Factorial design and response surface techniques were used in combination with mathematical modelling and computational simulation to optimise an innovative industrial bioprocess, the production of biobutanol employing the flash fermentation technology. A parametric analysis performed by means of a full factorial design at two levels determined the influence of operating variables on butanol yield and productivity. A second set of simulations were carried out based on the central composite rotatable design. This procedure generated simplified statistical models that describe butanol yield and productivity as functions of the significant operating variables. From these models, response surfaces were obtained and used to optimise the process. For a range of substrate concentration from 130 to 180 g/l, the optimum operating ranges ensure butanol productivity between 7.0 and 8.0 g/l h, butanol yield between 19 and 22%, substrate conversion above 90% and final butanol concentration around 25 g/l.     

Hybrid modeling of inulinase bio‐production process

BACKGROUND: A potential application of inulinase in the food industry is the production of fructooligosaccharides (FOS) through transfructosilation of sucrose. Besides their ability to increase the shelf‐life and flavor of many products, FOS have many interesting functional properties. The use of an industrial medium may represent a good, cost‐effective alternative to produce inulinase, since the activity of the enzyme produced may be improved or at least remain the same compared with that obtained using a synthetic medium. Thus, inulinase production for use in FOS synthesis is of considerable scientific and technological appeal, as is the development of a reliable mathematical model of the process. This paper describes a hybrid neural network approach to model inulinase production in a batch bioreactor using agroindustrial residues as substrate. The hybrid modeling makes use of a series artificial neural network to estimate the kinetic parameters of the process and the mass balance as constitutive equations. RESULTS: The proposed model was shown to be capable of describing the complex behavior of inulinase production employing agroindustrial residues as substrate, so that the mathematical framework developed is a useful tool for simulation of this process. CONCLUSION: The hybrid neural network model developed was shown to be an interesting alternative to estimate model parameters since complete elucidation of the phenomena and mechanisms involved in the fermentation is not required owing to the black‐box nature of the ANN used as parameter estimator. Copyright © 2010 Society of Chemical Industry     

Use of the Cone Calorimeter and ConeTools software for development of innovative intumescing graphite systems

The Cone Calorimeter test method has been one of the most used small‐scale fire test method for years now and is at present widely spread over the world. In contrast to many other fire test methods, the Cone Calorimeter provides a range of data with sound scientific basis, which allows a wide range of applications. It can be used for modelling and also for enhanced product development. This paper describes the use of the Cone Calorimeter for the development of new innovative materials in combination with a mathematical model. As example, the cost effective development of an innovative intumescing graphite system for protecting particle board is explained. The performance goal of the project is to obtain the threshold values for a B class in the Single Burning Item (SBI) test method used for the newly developed Euroclass system. The focus of this paper is on the development tools and not on the chemical development of the protective system. During the research it was necessary to develop a new sample holder for the Cone Calorimeter. The results from the project show that the industry can save development time and resources by using the Cone Calorimeter in combination with a simple mathematical model. Copyright © 2010 John Wiley & Sons, Ltd.     

Novel supports for nickel-based catalysts for the partial oxidation of methane

Zirconia-supported nickel catalysts with different amounts of aluminum (Al/Zr = 0.2, 1 and 2) were studied in this work in order to find alternative supports for nickel-based catalysts for the partial oxidation of methane. This reaction is a promising route for producing hydrogen and syngas for different applications. Samples were prepared by precipitation and impregnation techniques, characterized by several techniques and evaluated in the partial oxidation of methane in the range of 450–750 °C and 1 atm. It was found that aluminum affects the textural and catalytic properties of zirconia-supported nickel catalysts. The tetragonal phase of zirconia was stabilized by aluminum and gamma-alumina was also found in the aluminum-richest samples. Aluminum increased the porosity and the specific surface area of the solids. The catalytic activity also increased with the amount of aluminum in solids probably due to the stronger interaction of nickel with the support, which slowly generates active sites during the reduction step. The methane conversion and hydrogen selectivity increased with temperature, indicating no deactivation. The hydrogen to carbon monoxide molar ratio decreased due to aluminum but was not significantly affected by temperature. The coke produced was not harmful to the catalysts and aluminum affected its amount, although no simple relationship was found between these parameters. The most promising catalyst was the sample with aluminum to zirconium molar ratio of 2, which showed high activity and hydrogen selectivity and was stable under the reaction condition.     

Easy mass spectrometry for metabolomics and quality control of vegetable and animal fats

Easy ambient sonic spray ionization (EASI), a novel desorption/ionization technique for ambient mass spectrometry analysis, is shown to permit the characterization of different types of vegetable and animal fats. The taxonomic markers of the oils, mainly fatty acids and phenols, are extracted with methanol/water (1:1) solution and made alkaline with NH₄OH, then placed and dried on the surface of a glass tip and directly analyzed by EASI‐MS in the negative‐ion mode. EASI provides a supersonic cloud of charged droplets that causes efficient desorption and ionization of the oil markers directly from the surface of the glass tip. As proof‐of‐principle cases, EASI(?)‐MS was applied to genuine samples of olive oil, hazelnut oil, soybean oil, grape seed oil, canola oil, butter, and lard. Characteristic metabolomics EASI(?)‐MS profiles of fatty acids and eventually phenols were obtained.     

Cervid Prion Protein Polymorphisms: Role in Chronic Wasting Disease Pathogenesis

Chronic wasting disease (CWD) is a prion disease found in both free-ranging and farmed cervids. Susceptibility of these animals to CWD is governed by various exogenous and endogenous factors. Past studies have demonstrated that polymorphisms within the prion protein (PrP) sequence itself affect an animal’s susceptibility to CWD. PrP polymorphisms can modulate CWD pathogenesis in two ways: the ability of the endogenous prion protein (PrP^C) to convert into infectious prions (PrP^Sc) or it can give rise to novel prion strains. In vivo studies in susceptible cervids, complemented by studies in transgenic mice expressing the corresponding cervid PrP sequence, show that each polymorphism has distinct effects on both PrP^C and PrP^Sc. It is not entirely clear how these polymorphisms are responsible for these effects, but in vitro studies suggest they play a role in modifying PrP epitopes crucial for PrP^C to PrP^Sc conversion and determining PrP^C stability. PrP polymorphisms are unique to one or two cervid species and most confer a certain degree of reduced susceptibility to CWD. However, to date, there are no reports of polymorphic cervid PrP alleles providing absolute resistance to CWD. Studies on polymorphisms have focused on those found in CWD-endemic areas, with the hope that understanding the role of an animal’s genetics in CWD can help to predict, contain, or prevent transmission of CWD.     

Cushing’s Syndrome Effects on the Thyroid

The most known effects of endogenous Cushing’s syndrome are the phenotypic changes and metabolic consequences. However, hypercortisolism can exert important effects on other endocrine axes. The hypothalamus–pituitary–thyroid axis activity can be impaired by the inappropriate cortisol secretion, which determinates the clinical and biochemical features of the “central hypothyroidism”. These findings have been confirmed by several clinical studies, which also showed that the cure of hypercortisolism can determine the recovery of normal hypothalamus–pituitary–thyroid axis activity. During active Cushing’s syndrome, the “immunological tolerance” guaranteed by the hypercortisolism can mask, in predisposed patients, the development of autoimmune thyroid diseases, which increases in prevalence after the resolution of hypercortisolism. However, the immunological mechanism is not the only factor that contributes to this phenomenon, which probably includes also deiodinase-impaired activity. Cushing’s syndrome can also have an indirect impact on thyroid function, considering that some drugs used for the medical control of hypercortisolism are associated with alterations in the thyroid function test. These considerations suggest the utility to check the thyroid function in Cushing’s syndrome patients, both during the active disease and after its remission.