Background The aim of this study was to assess whether two-years treatment with Pirfenidone influences necroinflammation, fibrosis and steatosis, serum levels of TGF-β1, IL-6, TNF-α and CB1 and CB2 gene expression, in patients with chronic hepatitis C (CHC). Methods Twenty-eight patients out of 34 with CHC virus infection were enrolled in the study and received Pirfenidone (1200 mg/day) for 24 months. Six patients dropped out after 12 months of PFD. Liver biopsies and serum samples were obtained at the beginning and end of treatment. Modified HAI was calculated. CB1 and CB2 gene expression was correlated with fibrosis progression alongside with necroinflammation and steatosis. TGF-β1, IL-6, TNF-α and liver transaminases were measured in serum at two-months intervals. HCV genotype and viral load were also assessed. Quality of life was evaluated by SF36 questionnaires and the prognosis of disease was assessed with Child-Pugh score. The Wilcoxon test matched-pair signed ranks were used to analyze the outcomes. Results Intention to treat analyses were performed for biochemistry and clinical parameters. At the end of treatment, necroinflammation grading was reduced in an average of 3.2 points in 82% of patients (p < 0.05) and Ishak’s fibrosis stage decreased 2-points average in 67% of patients (p < 0.05). Steatosis decreased in 61% of patients. IL-6 and TGF-β1 serum levels decreased significantly in 93% and 67% of patients (p < 0.05), respectively, while TNF-α diminished in 47% of patients. ALT and AST tended to normalize in 81% of patients; CB2 mRNA levels increased in 86% and CB1 expression diminished in 29% of patients. Both, quality of life and Child-Pugh score improvements were reported in all patients. Conclusions Pirfenidone for two years benefits CHC patients and improves inflammation, fibrosis and steatosis in higher number of patients as previously shown for 12-months treatment with PFD. Additionally, PFD improved TGFβ1 and IL-6 levels and diminished liver expression of anti-fibrogenic receptor CB2. Trial registration ClinicalTrials.gov identifier: NCT02161952. Protocol Registration Date: 06/11/2014.

Extractive distillation with salts, unlike other dehydration technologies, is better due to the null toxicity that exists in the distillate, since salt cannot be evaporated. With this distillation technology, it is possible to obtain a high concentration of ethanol, however, there are still problems in the control of the distillation columns in the presence of disturbances. The present work deals with the simulation and control of an extractive distillation column using CaCl${}_2$ as a separating agent, for which the Aspen Dynamics^® simulator is used. The measurement and control of the ethanol composition are carried out by means of temperature, in addition, four control structures are evaluated and compared. These structures are L, D, LV, and DV, which are the most common in conventional distillation, and their performance is measured by means of deterministic indicators applying changes (disturbances) of composition and the flow rate in the main feed of the column. The most relevant results of this work lead to the fact that by applying a controller, it is possible to maintain the desired purity above the international purity standards (99% ethanol) that govern biofuels.

Renal fibrosis is the final stage of chronic kidney injury characterized by glomerulosclerosis and tubulointerstitial fibrosis with parenchymal destruction. Quercetin belongs to the most studied flavonoids with antioxidant, anti-inflammatory, antifibrogenic, and antitumor activity. It modifies the TGF-β/Smad signaling pathway, decreasing profibrogenic expression molecules and inducing the expression of antioxidant, anti-inflammatory, and antifibrogenic molecules. However, quercetin exhibits poor water solubility and low absorption and bioavailability. This limitation was solved by developing a nanoparticles formulation that improves the solubility and bioavailability of several bioactive compounds. Therefore, we aimed to investigate the in vivo antifibrogenic effect of a quercetin nanoparticles formulation. Male C57BL/6 mice were induced into chronic renal failure with 50 mg/kg of adenine for four weeks. The animals were randomly grouped and treated with 25, 50, or 100 mg/kg of quercetin, either macroparticles or nanoparticles formulation. We performed biochemical, histological, and molecular analyses to evaluate and compare the effect of macroparticles versus nanoparticles formulation on kidney damage. Here, we demonstrated that smaller doses of nanoparticles exhibited the same beneficial effect as larger doses of macroparticles on preventing kidney damage. This finding translates into less quercetin consumption reaching the desired therapeutic effect.

This paper shows the implementation of the Moth–Flame Optimization algorithm in a Cascade-H multilevel inverter with five and seven levels to determine the optimal switching sequence of the inverter’s semiconductor devices. The algorithm was coded in Matlab software, and the obtained switching sequences were implemented in a Cascade-H multilevel inverter laboratory prototype, where the output voltage waveform was obtained using a digital oscilloscope. The experimental Total Harmonic Distortion was obtained using a power quality analyzer. The experimental results show the improvement of the Total Harmonic Distortion in the voltage output. These results were compared with other papers in the literature with different metaheuristic methods concerning the same modulation. These findings demonstrate the feasibility of employing the Moth–Flame Optimization Algorithm to significantly reduce the Total Harmonic Distortion, obtaining a lower value than most analyzed papers.

Biohydrogen has been identified as an attractive renewable energy carrier due to its high energy density and green production from biomass and organic wastes. Efficient biohydrogen production is a challenge that demands precise control of process parameters. Regulation and optimization of biohydrogen production through advanced approaches are therefore necessary to improve its industrial viability. This study introduces an innovative proposal for controlling the Pressure Swing Adsorption (PSA) process by employing a neural network-based controller derived from a PID control framework. The neural network was trained using input–output data, enabling it to maintain biohydrogen production purity at approximately 99%. The proposed neural network effectively simulates the dynamics of the PSA model, which is traditionally controlled using a PID controller. The results demonstrate exceptional performance and strong robustness against disturbances. Specifically, the neural network enables precise tracking of the desired trajectory and effective attenuation of disturbances, achieving a biohydrogen purity level with a molar fraction of 0.99.

The present paper addresses linear parameter-varying systems with high-order time-varying parameter dependency known as polynomial LPV systems and their controller design. Throughout this work, a procedure ensuring a state-feedback controller from a parameterized linear matrix inequality (PLMI) solution is presented. As the main contribution of this paper, the controller is designed by considering the time-varying parameter rate as a tuning parameter with a continuous control gain in such a way that the closed-loop eigenvalues lie in a complex plane subset, with high-order time-varying parameters defining the system dynamics. Simulation results are presented, aiming to show the effectiveness of the proposed controller design.