Suppressor of Cytokine Signaling-3 (SOCS-3) induces Proprotein Convertase Subtilisin Kexin Type 9 (PCSK9) expression in hepatic HepG2 cell line

The suppressor of cytokine signaling (SOCS) proteins are negative regulators of the JAK/STAT pathway activated by proinflammatory cytokines, including the tumor necrosis factor (TNF-\u3b1). SOCS3 is also implicated in hypertriglyceridemia associated to insulin resistance. Proprotein convertase subtilisin kexin type 9 (PCSK9) levels are frequently found to be positively correlated to insulin resistance and plasma very low density lipoprotein (VLDL) triglycerides concentrations. The present study aimed to investigate the possible role of TNF-\u3b1 and JAK/STAT pathway on de novo lipogenesis and PCSK9 expression in HepG2 cells. TNF-\u3b1 induced both SOCS3 and PCSK9 in a concentration-dependent manner. This effect was inhibited by transfection with siRNA anti-STAT3, suggesting the involvement of the JAK/STAT pathway. Retroviral overexpression of SOCS3 in HepG2 cells (HepG2SOCS3) strongly inhibited STAT3 phosphorylation and induced PCSK9 mRNA and protein, with no effect on its promoter activity and mRNA stability. Consistently, siRNA anti-SOCS3 reduced PCSK9 mRNA levels, whereas an opposite effect was observed with siRNA anti- STAT3. In addition, HepG2SOCS3 express higher mRNA levels of key enzymes involved in the de novo lipogenesis, such as fattyacid synthase, stearoyl-CoA desaturase (SCD)-1, and apoB. These responses were associated with a significant increase of SCD-1 protein, activation of sterol regulatory element-binding protein-1c (SREBP-1), accumulation of cellular triglycerides, and secretion of apoB. HepG2SOCS3 show lower phosphorylation levels of insulin receptor substrate 1 (IRS-1) Tyr896 and Akt Ser473 in response to insulin. Finally, insulin stimulation produced an additive effect with SOCS3 overexpression, further inducing PCSK9, SREBP-1, fatty acid synthase, and apoB mRNA. In conclusion, our data candidate PCSK9 as a gene involved in lipid metabolism regulated by proinflammatory cytokine TNF- in a SOCS3-dependent manner

High Density Lipoproteins Inhibit Oxidative Stress-Induced Prostate Cancer Cell Proliferation

Recent evidence suggests that oxidative stress can play a role in the pathogenesis and the progression of prostate cancer (PCa). Reactive oxygen species (ROS) generation is higher in PCa cells compared to normal prostate epithelial cells and this increase is proportional to the aggressiveness of the phenotype. Since high density lipoproteins (HDL) are known to exert antioxidant activities, their ability to reduce ROS levels and the consequent impact on cell proliferation was tested in normal and PCa cell lines. HDL significantly reduced basal and H2O2-induced oxidative stress in normal, androgen receptor (AR)-positive and AR-null PCa cell lines. AR, scavenger receptor BI and ATP binding cassette G1 transporter were not involved. In addition, HDL completely blunted H2O2-induced increase of cell proliferation, through their capacity to prevent the H2O2-induced shift of cell cycle distribution from G0/G1 towards G2/M phase. Synthetic HDL, made of the two main components of plasma-derived HDL (apoA-I and phosphatidylcholine) and which are under clinical development as anti-atherosclerotic agents, retained the ability of HDL to inhibit ROS production in PCa cells. Collectively, HDL antioxidant activity limits cell proliferation induced by ROS in AR-positive and AR-null PCa cell lines, thus supporting a possible role of HDL against PCa progression

Scalable model for industrial coffee roasting chamber

Abstract The temperature profile of the coffee beans during the roasting phase determines the colour, aroma and flavour of the coffee. In order to reproduce these desired characteristics, the control of the coffee beans temperature has a key role in the roasting process. A proper model of the plant is required to design an intelligent control. Recently, several physical models that share the main physical equations have been proposed, but they have physical parameters specific of each process. In such scenario, each plant requires an ad hoc identification of the model parameters. This work proposes a model of the roasting chamber that can be used on plants of different sizes by scaling only geometrical parameters directly measurable on the roasting plant. The proposed model was identified on a 120 kg plant and then applied to a 360 kg one. The obtained results show in both cases similar accuracy (FIT = 75.49%, MPE=4.66%)

Evaluating the Potential Contribution of District Heating to the Flexibility of the Future Italian Power System

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat– electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in terms of performance. The case study analyzed is the future Italian energy system, which is simulated through the unit commitment and optimal dispatch model Dispa-SET. Results show that DH coupled with heat pumps and CHP units could enable both costs and emissions related to the heat–electricity sector to be reduced by up to 50%. DH systems also proved to be a promising solution to grant the flexibility and resilience of power systems with high shares of renewables by significantly reducing the curtailment of renewables and cost-optimally providing up to 15% of the total upward reserve requirements

Optimization of γ-PGA biosynthesis supported by synthetic biology and metabolic engineering strategies

Poly-γ-glutamate (γ-PGA) is a natural polymer composed by glutamic acid residues, synthesized by the pgs operon of Bacillus subtilis. γ-PGA has a wide range of applications as food, cosmetic and pharmaceutical additive. However, to increase its industrial attractiveness, it is necessary to cut production costs utilizing cost-competitive feedstocks for fermentation. A low-cost by-product that can be used as feedstock is raw glycerol, that accounts for 10% (w/w) of the total biodiesel production. To achieve cost-competitive γ-PGA production from glycerol a multifaceted approach has been set up that includes: 1) improvement of pgs expression; 2) accumulation of γ-PGA precursors by metabolic engineering; 3) enhancement of glycerol metabolism. 1) The strength of the pgs operon regulatory elements has been analysed both by a synthetic biology approach, exploiting the well-characterized expression operating unit (EOU) inserted in amyE, and by a classical in-locus transcriptional fusion. Results from the two settings will be compared. These data will be then used to finely tune pgs expression and optimize γ-PGA yield. To this end, an inducible pgs operon has been constructed. 2) A genome-scale metabolic model was used to identify suitable targets for enhancing central carbon pathway flux toward γ-PGA synthesis. The first two B. subtilis strains, engineered following this analysis, showed enhanced polymer production. Other target genes are currently under investigation. 3) B. subtilis tolerance to raw glycerol obtained from a biodiesel plant (from both vegetable and animal origin) was verified. Further investigations are underway to improve glycerol uptake and consumption

Towards a Model-Based Field-Frequency Lock for Fast-Field Cycling NMR

Fast-field cycling nuclear magnetic resonance (FFC NMR) relaxometry allows to investigate molecular dynamics of complex materials. FFC relaxometry experiments require the magnetic field to reach different values in few milliseconds and field oscillations to stay within few ppms during signal acquisition. Such specifications require the introduction of a novel field-frequency lock (FFL) system. In fact, control schemes based only on current feedback may not guarantee field stability, while standard FFLs are designed to handle very slow field fluctuations, such as thermal derives, and may be ineffective in rejecting faster ones. The aim of this work is then to propose a methodology for the synthesis of a regulator that guarantees rejection of field fluctuations and short settling time. Experimental trials are performed for both model validation and evaluation of the closed-loop performances. Relaxometry experiments are performed to verify the improvement obtained with the new FFL. The results highlight the reliability of the model and the effectiveness of the overall approach

Improvement of manufacturing technologies through a modelling approach: an air-steam sterilization case-study

Abstract A milestone of Industry 4.0 is the improvement of the design procedures requiring models of complex processes. Models can be used to simulate the process, being accurate even if complex, and to predict process behaviour for control action, requiring simplicity and stability. In the last years, machine learning approaches came up alongside of the standard identification techniques for prediction purposes. In this work we propose two models of an industrial autoclave to describe the evolution of temperature and pressure. The first model (PhM) involves a physical structure with data-driven adaptation of the parameters, the second one is a Long Short-Term Memory network (LSTM), trained ensuring Input-to-State stability. Both models obtained good performance: FIT of 94.26% (91.55%) for the temperature (pressure) with PhM; 84.59% (78.31 %) for the temperature (pressure) with the LSTM. Future developments involve the synthesis of an MPC based on the LSTM to be tested in simulation via PhM

Assessment of the Contribution of Power-To-Hydrogen to the Flexibility of the Future European Energy System

peer reviewedThe European Commission is planning to become climate-neutral by 2050. At the power sector level, this implies turning to renewable sources such as PV panels and wind turbines. However, the intermittence of variable renewable sources is making this task more complex and putting at risk the power sector security of supply. Coupling sectors is a solution to that problem. In particular, power-to-hydrogen is getting more and more attention. This is about using electricity when it is abundant to synthesize hydrogen which can then be used for various purposes. The first goal of this work was to add the power-to-hydrogen sector into the unit-commitment and power dispatch model Dispa-SET. The second objective was to soft-link Dispa-SET with the long-term investment model JRC-EU-TIMES and investigate the benefits of this sector in terms of curtailment, total costs, CO2 emissions, etc. The linking between JRC-EU-TIMES and Dispa-SET allowed to observe the importance of power-to-hydrogen in using the extra renewable production and avoiding curtailment. Indeed, 20% of the total renewable production is used to produce hydrogen. This highlights the importance of sector coupling in future energy systems. Moreover, the results showed that hydrogen storage is not seasonal. Finally, the importance of validating system feasibility provided by long-term planing models was demonstrated as TIMES overestimates renewable production by 15% compared to Dispa-SET

Modelling the Integration of Residential Heat Demand and Demand Response in Power Systems with High Shares of Renewables

The EU aims to become the world\’s first climate-neutral continent by 2050. In order to meet this target, the integration of high shares of Renewable Energy Sources (RESs) in the energy system is of primary importance. Nevertheless, the large deployment of variable renewable sources such as wind and photovoltaic power will pose important challenges in terms of power management. For this reason, increasing the system flexibility will be crucial to ensure the security of supply in future power systems. This work investigates the flexibility potential obtainable from the diffusion of Demand Response (DR) programmes applied to residential heating for different renewables penetration and power system configuration scenarios. To that end, a bottom-up model for residential heat demand and flexible electric heating systems (heat pumps and electric water heaters) is developed and directly integrated into Dispa-SET, an existing unit commitment optimal dispatch model of the power system. The integrated model is calibrated for the case of Belgium and different simulations are performed varying the penetration and type of residential heating technologies, installed renewables capacity and capacity mix. Results show that, at country level, operational cost could be reduced up to 35 million and curtailment up to 1 TWh per year with 1 million flexible electric heating systems installed. These benefits are significantly reduced when nuclear power plants (non-flexible) are replaced by gas-fired units (flexible) and grow when more renewable capacity is added. Moreover, when the number of flexible heating systems increases, a saturation effect of the flexibility is observed.Peer reviewe