Liquid-liquid extraction of protease from cold-adapted yeast Rhodotorula mucilaginosa L7 using biocompatible and biodegradable aqueous two-phase systems

This work aimed to optimize the extraction of an extracellular protease produced by the cold-adapted yeast Rhodotorula mucilaginosa L7 using aqueous two-phase systems (ATPS) comprising polyethylene glycol (PEG) and sodium citrate or sodium tartrate. First, the biocompatibility of the phase forming agents was assessed. The results obtained with PEG-2000, PEG-4000, and PEG-6000 demonstrated that even at large PEG concentrations (32 wt%) the protease maintains its activity after 3 h of reaction, whereas an increase in salt concentration provokes a gradual decrease in protease stability. Subsequently, the partitioning of the protease in both types of ATPS was assessed, evaluating the effect of temperature, molecular weight, and concentration of PEG on protease purification, using two 2³-full factorial designs. The best partitioning conditions were obtained in PEG-6000/sodium tartrate-based ATPS, at 30ºC (with a yield of 81.09 ± 0.66% and a purification factor of 2.51 ± 0.03). Thus, considering the biodegradable characteristics of the system, the PEG/sodium tartrate ATPS is a viable and economic low-resolution step in protease purification, with a strong potential for future industrial application.     

Pain Modulation from the Locus Coeruleus in a Model of Hydrocephalus: Searching for Oxidative Stress-Induced Noradrenergic Neuroprotection

Pain transmission at the spinal cord is modulated by noradrenaline (NA)-mediated actions that arise from supraspinal areas. We studied the locus coeruleus (LC) to evaluate the expression of the cathecolamine-synthetizing enzyme tyrosine hydroxylase (TH) and search for local oxidative stress and possible consequences in descending pain modulation in a model of hydrocephalus, a disease characterized by enlargement of the cerebral ventricular system usually due to the obstruction of cerebrospinal fluid flow. Four weeks after kaolin injection into the cisterna magna, immunodetection of the catecholamine-synthetizing enzymes TH and dopamine-β-hydroxylase (DBH) was performed in the LC and spinal cord. Colocalization of the oxidative stress marker 8-OHdG (8-hydroxyguanosine; 8-OHdG), with TH in the LC was performed. Formalin was injected in the hindpaw both for behavioral nociceptive evaluation and the immunodetection of Fos expression in the spinal cord. Hydrocephalic rats presented with a higher expression of TH at the LC, of TH and DBH at the spinal dorsal horn along with decreased nociceptive behavioral responses in the second (inflammatory) phase of the formalin test, and formalin-evoked Fos expression at the spinal dorsal horn. The expression of 8-OHdG was increased in the LC neurons, with higher co-localization in TH-immunoreactive neurons. Collectively, the results indicate increased noradrenergic expression at the LC during hydrocephalus. The strong oxidative stress damage at the LC neurons may lead to local neuroprotective-mediated increases in NA levels. The increased expression of catecholamine-synthetizing enzymes along with the decreased nociception-induced neuronal activation of dorsal horn neurons and behavioral pain signs may indicate that hydrocephalus is associated with alterations in descending pain modulation.     

A neural network approach to predict activity coefficients

Artificial neural networks (ANNs) and a group‐contribution approach were used to develop an algorithm to predict activity coefficients for binary solutions. The Levenberg–Marquardt algorithm was used to train the ANN and to predict the parameters of the Margules equation. The ANN was trained using phase‐equilibrium database from DECHEMA. The selected systems include alcohols, phenols, aldehydes, ketones, and ethers. The trim mean based on 20% data elimination was selected as the best representation of the Margules‐equation parameters. The algorithm was validated with 121 VLE systems and results show that the ANN provides a relative improvement over the UNIFAC method.     

Ultrafine grinding of sugar cane bagasse ash for application as pozzolanic admixture in concrete

Sugar cane bagasse ash, a byproduct of sugar and alcohol production, is a potential pozzolanic material. However, its effective application in mortar and concrete requires first the controlled use of grinding and classification processes to allow it to achieve the fineness and homogeneity that are required to meet industry standards. The present paper investigates the role of mill type and grinding circuit configuration in grinding in laboratory- and pilot plant-scale on the particle size, specific surface area and pozzolanic activity of the produced ashes. It was observed that, although different size distributions were produced by the different mills and milling configurations, the pozzolanic activity of the ground ash was directly correlated to its fineness, characterized by its 80% passing size or Blaine specific surface area. From a low pozzolanic activity of less than 50% of the as-received ash, values above 100% could be reached after prolonged grinding times. Electric power requirements to reach the minimum pozzolanic activity were estimated to be in the order of 42 kWh/t in an industrial ball mill. Incorporation of an ultrafinely-ground ash in a high-performance concrete in partial replacement of Portland cement (10, 15 and 20% by mass) resulted in no measurable change in mechanical behavior, but improved rheology and resistance to penetration of chloride ions.     

Microstructural modeling approach applied to rock material

The importance of the microstructural parameters in rock mechanical behavior has been investigated by several authors. Moreover, the Weibull statistical model has been used to characterize the heterogeneity of several materials on the basis of the concept that the microscopic defects within the material determine their mechanical strength. The modeling of different rocks is a topic that is fundamental for the prediction of rock fragmentation. In this article, the analysis of rock microstructure is performed using the microstructural modeling approach, which consists of the simplification, quantification, and modeling of the main properties of rock microstructure. The grain size, grain shape, and microcracks are modeled by means of statistical density functions, namely, Cauchy, chi-squared, exponential, extreme value, gamma, Laplace, normal, uniform, and Weibull. It is found that the Weibull distribution is the most appropriate statistical model of the grain size and grain shape, when compared with the other eight statistical models. Regarding microcracks, the results show that the gamma distribution is the most appropriate model. The Weibull and gamma distributions are then used to analyze the heterogeneity of the microstructure. This is done by comparison of the statistical models of each microstructural property evaluated in several thin sections of the same rock. It is found that with respect to grain size and grain shape, the rock is homogeneous, while the size distribution of the microcracks shows a clear trend toward less homogeneity. The microstructural modeling approach is important for modeling, characterizing, and analyzing the microstructure of rock material. Among other applications, it can be used to explain differences in the mechanical behavior obtained in testing several specimens.     

Effects of low-temperature aging on AISI 444 steel

The consequences of aging at 400 and 475 °C on the mechanical properties, corrosion resistance, and magnetic properties of the ferritic stainless steel (SS) AISI 444 were investigated. Age hardening was measured as a function of aging time at both temperatures and was found to be more intense at 475 °C. The localized corrosion susceptibility increased, while the impact toughness decreased with aging time. These two effects were also more important at 475 °C. Unlike duplex SSs, AISI 444 did not present any variation in coercive force or Curie temperature with aging time. The effects on the Mössbauer spectra were also determined and analyzed.     

Hardening behavior and structural evolution upon strain reversal of aluminum alloys

The mechanical behavior and the dislocation structure change upon strain reversal are analyzed for 1050-O and 6022-T4 aluminum alloys. Dissolution of the dislocation structure and related transient hardening rate are observed in the AA1050-O but impeded by the numerous precipitates and the high solute content in the AA6022-T4.     

Performance of Green Solvents in the Extraction of Sunflower Oil from Enzyme-Treated Collets

The main goal of this work is to evaluate the extraction of sunflower oil from enzyme-treated collets using ethanol and isopropanol (IPA) as solvents. The sunflower collets are pretreated with the multienzyme complex Viscozyme L prior to solvent extraction by the Soxhlet method. The influence of the moisture content of the collets, pretreatment, processing time, and solvent type on the amount of total extracted material and the oil extraction efficiency is studied. Some quality parameters such as phospholipid content of the oil and chlorogenic acid content of the residual meal are also analyzed. At low moisture content (7%) the solvents exhibit similar oil extraction ability (98–99%), but with increasing moisture the extraction efficiency of ethanol decreases to about 85%, while no significant differences are observed for IPA. The enzymatic treatment increases the extraction efficiency for all times, especially for ethanol. It is observed that IPA is more efficient in the extraction compared to ethanol, and the amount of nonlipid material is reduced by ≈70%. In addition, the oil extracted with IPA have lower phospholipid content and the residual meal presents a higher chlorogenic acid content. Practical Applications:This work would contribute toward the use of green solvents in the extraction of sunflower oil from collets. Ethanol and isopropanol, used as solvents, present attractive advantages, including low toxicity, good operational security, as well as being obtained from a renewable source. The obtained data provide up-to-date information on the use of these alcohols in the extraction of sunflower oil from collets and the influence of operating conditions, such as moisture content, enzymatic pretreatment of the collets, and the extraction time. Information about oil and meal quality is also reported.     

Neural network-based hybrid models developed for free radical polymerization of styrene

In the present work, the free radical polymerization of styrene is modeled by considering the phenomenology of the process (a simplified model, which does not include the diffusional effects, gel, and glass effects) in combination with an empirical model represented by an artificial neural network. Differential evolution (DE) algorithm, belonging to the class of evolutionary algorithms, is applied for developing the neural models in optimal forms. For improving the results—predicted conversion and molecular weights as function of time, temperature, and initiator concentration—different combinations between phenomenological model and neural network are tested; also, individual and stacked neural networks have been developed for the polymerization process. This methodology based on hybrid models, including neural networks aggregated in stacks, provides accurate results.     

Evaluation of the removal of n-butanol vapor by the poly(lactic acid)-zeolite-TiO2 composite and formation of by-products

The use of polymeric films incorporated with zeolite-TiO₂ composites associated with UV radiation can be an alternative in the removal of volatile organic compounds (VOCs) through the adsorption and photodegradation processes. This study produced poly(lactic acid) (PLA) films incorporated with 13× zeolite, TiO₂, and 13×-TiO₂ zeolite composite to remove n-butanol and evaluate the by-products generated in the process. The results showed that 13× zeolite and TiO₂ added individually or as a composite to PLA, gave the polymer matrix a significant increase in the removal capacity of n-butanol. The best performance was presented by the zeolite-TiO₂, composite, confirming a synergistic effect. However, the formation of CO and CO₂ exceeded the expected values, with the verification that the polymeric matrix underwent photodegradation action by TiO₂. The polymeric film only containing zeolite is the most suitable for the removal of VOCs, as it did not present degradation of the PLA, generating a lower concentration of by-products.