HCV derived from sera of HCV-infected patients induces pro-fibrotic effects in human primary fibroblasts by activating GLI2

Hepatitis C virus (HCV) infection is a leading cause of liver fibrosis, especially in developing countries. The process is characterized by the excess accumulation of ECM that may lead, over time, to hepatic cirrhosis, liver failure and also to hepatocarcinoma. The direct role of HCV in promoting fibroblasts trans-differentiation into myofibroblasts, the major fibrogenic cells, has not been fully clarified. In this study, we found that HCV derived from HCV-infected patients infected and directly induced the trans-differentiation of human primary fibroblasts into myofibroblasts, promoting fibrogenesis. This effect correlated with the activation of GLI2, one of the targets of Hedgehog signaling pathway previously reported to be involved in myofibroblast generation. Moreover, GLI2 activation by HCV correlated with a reduction of autophagy in fibroblasts, that may further promoted fibrosis. GLI2 inhibition by Gant 61 counteracted the pro-fibrotic effects and autophagy inhibition mediated by HCV, suggesting that targeting HH/GLI2 pathway might represent a promising strategy to reduce the HCV-induced fibrosis

Temperature-Dependent Thévenin Model of a Li-Ion Battery for Automotive Management and Control

This paper focuses on the analysis of Li-ion battery behavior at different temperatures through the Thévenin electrical circuit model. First, evaluations for both steady-state and dynamic battery applications are provided, then an overview of the different battery models to describe their dynamic behavior is analyzed. The focus is dedicated to the double polarization Thévenin-based equivalent circuit model since it represents an optimal trade-off between accuracy and computation effort, which justifies its implementation in a Battery Management System (BMS) for automotive real-time monitoring and control. The model is composed of a voltage source, one series resistor and two series RC blocks. The Hybrid Pulse Power Characterization test (HPPC) is performed inside a climatic chamber to extract the electrical parameters of the model and their dependency from both temperature and State Of Charge (SOC). The load-current effects on the battery performance are not considered for the simplicity and lightness of the presented model. The presented procedure has broader validity and is mostly independent of cell format and Li-ion chemistry, despite a specific cylindrical battery cell is chosen for the study. The results of the test are suitable for the future implementation of a proper algorithm for SOC and State Of Health SOH estimations. Moreover, they provide an effective electrical and thermal characterization of the cell to evaluate the heat generation rate inside the cell

Dynamic Electro-Thermal Li-ion Battery Model for Control Algorithms

This paper presents a fast and effective approach to evaluate the heat generation of a Li-ion battery system. The thermal characterization of Li-ion batteries is a relevant topic for the correct monitoring of the battery pack. In particular, a reduced-order model, that estimates the thermal dynamics of a Li-ion battery cell, is reported. The proposed approach relies on the definition of a boundary-value problem for heat conduction, in the form of a linear partial differential equation with the integration of Equivalent Circuit Model. The model is based on the double polarization Thévenin equivalent circuit model since it represents an optimal trade-off between accuracy and computation effort, which justifies its implementation in a Battery Management System (BMS) for automotive real-time monitoring and control. The resulting model predicts the temperature dynamics at the external surface in relation with the rate of the internal heat generation. In this paper, the model is applied to estimate the temperature of a cylindrical cell during a discharging transient and it uses electrical data acquired from experimental tests and is validated Computational fluid dynamics simulation. The results of the test are suitable for the future implementation of a proper algorithm for State of Charge SOC and State of Health SOH estimations

Electrothermal battery pack model for automotive application: Design and validation

Thermal modeling of the battery is an important way to understand how the design and operating variables affect the thermal response during its operation. This paper presents a method for modeling the electrical and thermal behavior of a battery pack, starting from the characterization of the single Lithium-ion battery cell up to extend its validity to module and pack level. The model takes into account both the reversible entropic heat generation and the irreversible resistive heat to predict the temperature of the battery. A coupled CFD and thermal analysis on an elementary module is proposed and experimentally tested to validate the results obtained from the proposed model. Furthermore, the experimental test will verify the effectiveness of air cooling

Distributed Electro-Mechanical Coupling Effects in a Dielectric Elastomer Membrane Array

Background Dielectric elastomer (DE) transducers permit to efectively develop large-deformation, energy-efcient, and compliant mechatronic devices. By arranging many DE elements in an array-like confguration, a soft actuator/sensor system capable of cooperative features can be obtained. When many DE elements are densely packed onto a common elastic membrane, spatial coupling efects introduce electro-mechanical interactions among neighbors, which strongly afect the system actuation and sensing performance. To efectively design cooperative DE systems, those coupling efects must be systematically characterized and understood frst. Objective As a frst step towards the development of complex cooperative DE systems, in this work we present a systematic characterization of the spatial electro-mechanical interactions in a 1-by-3 array of silicone DEs. More specifcally, we investigate how the force and capacitance characteristics of each DE in the array change when its neighbors are subject to diferent types of mechanical or electrical loads. Force and capacitance are chosen for this investigation, since those quantities are directly tied to the DE actuation and sensing behaviors, respectively. Methods An electro-mechanical characterization procedure is implemented through a novel experimental setup, which is specifcally developed for testing soft DE arrays. The setup allows to investigate how the force and capacitance characteristics of each DE are afected by static deformations and/or electrical voltages applied to its nearby elements. Diferent combinations of electro-mechanical loads and DE neighbors are considered in an extensive experimental campaign. Results The conducted investigation shows the existence of strong electro-mechanical coupling efects among the diferent array elements. The interaction intensity depends on multiple parameters, such as the distance between active DEs or the amount of deformation/voltage applied to the neighbors, and provides essential information for the design of array actuators. In some cases, such coupling efects may lead to changes in force up to 9% compared to the reference confguration. A further coupling is also observed in the DE capacitive response, and opens up the possibility of implementing advanced and/or distributed self-sensing strategies in future applications. Conclusion By means of the conducted experiments, we clearly show that the actuation and sensing characteristics of each DE in the array are strongly infuenced by the electro-mechanical loading state of its neighbors. The coupling efects may signifcantly afect the overall cooperative system performance, if not properly accounted for during the design. In future works, the obtained results will allow developing cooperative DE systems which are robust to, and possibly take advantage of, such spatial coupling efects

Non-linear kalman filters for battery state of charge estimation and control

In this paper, two different non-linear Kalman Filters for lithium-ion battery state of charge estimation are presented and compared. Nowadays, lithium-ion batteries are extensively used for hybrid and electric vehicles; in such applications, cells are assembled in module and pack to achieve high performance. At this scope, a Battery Management Systems BMS is required to control each cell and improve the battery pack performance, safety, reliability, and lifecycle. One of the major tasks a BMS must fulfill is an accurate online estimation of the State Of Charge (SOC) of the battery pack. In this paper, the Extended Kalman Filter and Sigma Points Kalman filter are developed and compared. A battery equivalent circuit model has been chosen to have a good compromise between complexity and accuracy and model parameters have been identified from Hybrid Pulse Power Characterization (HPPC) tests carried out at different temperatures and current rates to obtain a model valid for a wide range of operating conditions. The SOC estimation strategies are developed starting from the experimental results and it is validated through different driving cycling simulations. The results show that the Sigma Points Kalman filter produces a better estimate of SOC with respect to the Extended Kalman Filter, due to its better capability to deal with system non-linearities, with comparable computational complexity

Nutritional, Functional, and Technological Characterization of a Novel Gluten- and Lactose-Free Yogurt-Style Snack Produced With Selected Lactic Acid Bacteria and Leguminosae Flours

Aiming at meeting consumers’ requirements for healthy foods, dietary needs (vegetarianism, lactose- and gluten-free), as well as the nutrition recommendations of the Health Authorities in terms of protein, fibers and bioactive compounds, the present study proposes a novel yogurt-style snack made with plant-derived ingredients. The biotechnological protocol includes the fermentation of a thermal-treated blend of cereal and legume flours by the selected lactic acid bacteria (LAB) Lactoplantibacillus plantarum DSM33326 and Levilactobacillus brevis DSM33325. The yogurt-style snack was characterized by protein and fiber concentration of 3 and 4%, respectively, and a low-fat content. Compared to the unfermented control, the yogurt-style snack was characterized by a significant higher concentration of free amino acids and lower contents of the antinutritional factors, i.e., phytic acid, condensed tannins, saponins and raffinose (up to 90%) mainly due to the LAB metabolic activity. Hence, an in-vitro protein digestibility of 79% and improvements of all the nutritional indexes related to the quality of the protein fraction (e.g., GABA) were achieved at the end of fermentation. According to the Harvard Medical School recommendations, the novel snack can be potentially classified as low-glycemic index food (53%). Antioxidant properties of the fermented snack were also improved by means of increased the total phenol content and radical scavenging activity. High survival rate of the starter LAB and a commercial probiotic (added to the snack) was found through 30 days storage under refrigerated conditions. The biotechnological protocol to make the novel snack here proposed is suitable for the large-scale application in food industry, giving a platform product with a peculiar and appreciated sensory profile

Macrophage Targeting pH Responsive Polymersomes for Glucocorticoid Therapy

Glucocorticoid (GC) drugs are the cornerstone therapy used in the treatment of inflammatory diseases. Here, we report pH responsive poly(2-methacryloyloxyethyl phosphorylcholine)–poly(2-(diisopropylamino)ethyl methacrylate) (PMPC–PDPA) polymersomes as a suitable nanoscopic carrier to precisely and controllably deliver GCs within inflamed target cells. The in vitro cellular studies revealed that polymersomes ensure the stability, selectivity and bioavailability of the loaded drug within macrophages. At molecular level, we tested key inflammation-related markers, such as the nuclear factor-κB, tumour necrosis factor-α, interleukin-1β, and interleukin-6. With this, we demonstrated that pH responsive polymersomes are able to enhance the anti-inflammatory effect of loaded GC drug. Overall, we prove the potential of PMPC–PDPA polymersomes to efficiently promote the inflammation shutdown, while reducing the well-known therapeutic limitations in GC-based therapy