Role of Endocrine-Disrupting Chemicals in the Pathogenesis of Non-Alcoholic Fatty Liver Disease: A Comprehensive Review

Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required.     

Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

     

ACE2, the Receptor that Enables Infection by SARS-CoV-2: Biochemistry,Structure, Allostery and Evaluation of the Potential Development of ACE2 Modulators

Angiotensin converting enzyme 2 (ACE2) is the human receptor that interacts with the spike protein of coronaviruses, including the one that produced the 2020 coronavirus pandemic (COVID-19). Thus, ACE2 is a potential target for drugs that disrupt the interaction of human cells with SARS-CoV-2 to abolish infection. There is also interest in drugs that inhibit or activate ACE2, that is, for cardiovascular disorders or colitis. Compounds binding at alternative sites could allosterically affect the interaction with the spike protein. Herein, we review biochemical, chemical biology, and structural information on ACE2, including the recent cryoEM structures of full-length ACE2. We conclude that ACE2 is very dynamic and that allosteric drugs could be developed to target ACE2. At the time of the 2020 pandemic, we suggest that available ACE2 inhibitors or activators in advanced development should be tested for their ability to allosterically displace the interaction between ACE2 and the spike protein.     

Bioinformatic characterization of the extracellular lipases from Kluyveromyces marxianus

Lipases are hydrolytic enzymes that break the ester bonds of triglycerides, generating free fatty acids and glycerol. Extracellular lipase activity has been reported for the nonconventional yeast Kluyveromyces marxianus, grown in olive oil as a substrate, and the presence of at least eight putative lipases has been detected in its genome. However, to date, there is no experimental evidence on the physiological role of the putative lipases nor their structural and catalytic properties. In this study, a bioinformatic analysis of the genes of the putative lipases from K. marxianus L-2029 was performed, particularly identifying and characterizing the extracellular expected enzymes, due to their biotechnological relevance. The amino acid sequence of 10 putative lipases, obtained by in silico translation, ranged between 389 and 773 amino acids. Two of the analysed putative proteins showed a signal peptide, 25 and 33 amino acids long for KmYJR107Wp and KmLIP3p, and a molecular weight of 44.53 and 58.23 kDa, respectively. The amino acid alignment of KmLIP3p and KmYJR107Wp with the crystallized lipases from a patatin and the YlLip2 lipase from Yarrowia lipolytica, respectively, revealed the presence of the hydrolase characteristic motifs. From the 3D models of putative extracellular K. marxianus L-2029 lipases, the conserved pentapeptide of each was determined, being GTSMG for KmLIP3p and GHSLG for KmYJR107Wp; besides, the genes of these two enzymes (LIP3 and YJR107W) are apparently regulated by oleate response elements. The phylogenetic analysis of all K. marxianus lipases revealed evolutionary affinities with lipases from abH15.03, abH23.01, and abH23.02 families.     

A new mobile robot control approach via fusion of control signals.

This paper proposes an alternative approach to address the problem of coordinating behaviors in mobile robot navigation: fusion of control signals. Such approach is based on a set of two decentralized information filters, which accomplish the data fusion involved. Besides these two fusion engines, control architectures designed according to this approach also embed a set of different controllers that generate reference signals for the robot linear and angular speeds. Such signals are delivered to the two decentralized information filters, which estimate suitable overall reference signals for the robot linear and angular speeds, respectively. Thus, the background for designing such control architectures is provided by the nonlinear systems theory, which makes this approach different from any other yet proposed. This background also allows checking control architectures designed according to the proposed approach for stability. Such analysis is carried out in the paper, and shows that the robot always reaches its final destination, in spite of either obstacles along its path or the environment layout. As an example, a control architecture is designed to guide a mobile robot in an experiment, whose results allows checking the good performance of the control architecture and validating the design approach proposed as well.     

Free electron laser experiment at Orsay: A review

In this paper we review the results obtained in the last two years with the Orsay free electron laser.     

Dynamical modelling of an activated sludge system of a petrochemical plant operating at high temperatures.

The Mexican petrochemical industry, Morelos S.A. de C.V., is one of the biggest and more important petroleum industries in Mexico and Latin America. It has an activated sludge system to treat its wastewater flow, which is approximately 7,000 m3/d. The wastewater contains volatile organic carbon substances classified as toxics. The old surface aeration system was changed for fine bubble diffusers; however, one major drawback of the new aeration system is that the temperature in the bioreactor has increased due to the compression of the air, which at the compressor exit reaches 85 degrees C. This effect results in the temperature in the bioreactor attaining 32 degrees C during the fall, whereas in the spring and summer, the bioreactor temperature reaches higher values than 40 degrees C. The high temperatures reduce the microorganism activity and cause a higher volatilisation rate of volatile compounds, among other effects, which affect the performance of the biological treatment. This work was performed to obtain a better modelling of the wastewater treatment from the petrochemical industry. The model describes the effect of the temperature on the performance of the biological treatment. The model was obtained from tests that were carried out in laboratory reactors with 14 L capacity, which were operated at different temperatures (from 30 to 45 degrees C), with the same wastewater and conditions as the actual system.