Journal articles on the topic 'PI-RES CONTROLLER'

Power availability from renewable energy sources (RES) is unpredictable, and must be managed effectively for better utilization. The role that a hybrid energy storage system (HESS) plays is vital in this context. Renewable energy sources along with hybrid energy storage systems can provide better power management in a DC microgrid environment. In this paper, the optimal PI-controller-based hybrid energy storage system for a DC microgrid is proposed for the effective utilization of renewable power. In this model, the proposed optimal PI controller is developed using the particle swarm optimization (PSO) approach. A 72 W DC microgrid system is considered in order to validate the effectiveness of the proposed optimal PI controller. The proposed model is implemented using the MATLAB/SIMULINK platform. To show the effectiveness of the proposed model, the results are validated with a conventional PI-controller-based hybrid energy storage system.

The main objective of this paper is to allow renewable energy sources (RES) to actively participate within hybrid microgrid by proposing a new control system based on fractional order proportional integral (FOPI) controller. Fractional order proportional integral controller is a classical proportional integral (PI) in which the integral part is a fraction instead of integer numbers. The paper introduces a hybrid photovoltaic (PV), wind turbine and battery storage system connected to a three-phase grid. Three types of controller are considered and compared for a hybrid renewable energy system (HRES), namely, FOPI, PI, and the fractional order integral control (FIC). For the PV resource, maximum power point tracking (MPPT) controller was designed using the incremental conductance plus integral regulator technique. A DC/DC boost converter was utilized to connect the renewable energy resources to a point of common coupling. MATLAB/Simulink is adopted to perform the simulation results of the developed HRES. The results show that the FOPI controller outperforms other controllers under several operating conditions. The paper also includes experimental results from a prototype real scale.

Among the Unified Power Flow Controller (UPFC) tools, Flexible Alternating Current Transmission Systems (FACTS) have ability to control the transmitted power, improve transient and dynamic stability and improve the profile of the voltage and damping of the oscillations in the power system. Using the proportional-integral (PI) and proportional-integral-derivative (PID) controllers is a custom method. Selecting the PI and PID coefficients is through different methods. Also designing a resistant controller which can control the system in different points of work has been continuously considered by researchers. In this regard, in order to improve the performance of UPFC controllers, adjusting its parameters is required optimally which this matter itself would facilitate accessing to control objectives. In this project, UPFC is used for damping the oscillations of the power system. Also, in order to adjust the controller parameters optimally, evolutionary algorithms like Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Hybrid Particle Swarm Optimization (HPSO) and other algorithms are used.Bangladesh J. Sci. Ind. Res. 51(3), 231-238, 2016

In a solar power plant, a solid phase transformer and an optimization coordinated controller are utilized to improve transient responsiveness. Transient stability issues in a contemporary electrical power system represent one of the difficult tasks for an electrical engineer due to the rise in uncertain renewable energy sources (RESs) as a result of the need for green energy. The potential for terminal voltage to be adversely impacted by this greater RES raises the possibility of electrical device damage. It is possible to use a solid state transformer (SST) or smart transformer to address a transient response issue. These devices are frequently employed to interact between RES and a power grid. SST features a variety of regulated converters to maintain the necessary voltage levels. This method can therefore simultaneously lessen power fluctuations and transient responsiveness. In order to improve the quality of RES power injections and the electrical system’s transient stability, this work provides a controller design for a solar photovoltaic (SPV) system that is connected to the grid by SST. The optimization of a controller model is proposed by modifying a PI controller taken from a commercial one. With the use of IEEE 39 standard buses, the proposed controller is tested. When evaluating the effectiveness of a suggested controller, it is important to take into account a variety of solar radiation patterns as well as a time delay uncertainty that can range from 425 ms to 525 ms. According to simulation results, the proposed controller can be employed to lessen power fluctuation brought on by unpredictable RES. Additionally, the proposed coordinated regulation of SPV and SST can prevent catastrophic damage in the event of substantial disturbances like a circuit breaker collapsing to expand a power line due to a fault by inhibiting significant voltage cycles within an electronic appliance’s rated voltage limit. The results indicate that a transitory stability issue in a modern power system caused by an unforeseen increase in RES may be addressed utilizing the suggested controllers as alternatives.

In seaports, low-carbon energy systems and energy efficiency have become increasingly important as a result of the evolution of environmental and climate change challenges. In order to ensure the continued success of seaports, technological advancements must be introduced to a number of systems, such as seaport vehicles, harbor cranes, and the power sources of berthed ships. Harbor areas might need a microgrid to handle these aspects. Typically, microgrids that substitute conventional generator units with renewable energy sources (RES) suffer from system inertia problems, which adversely affect microgrid frequency stability. A load frequency controller (LFC) based on a novel modified proportional integral derivative with filter (MPIDF) is presented in this paper for enhancing the performance of marine microgrid system (MMS). The serval optimization algorithm (SOA), a recent bio-inspired optimization algorithm, is used to optimize the MPIDF controller coefficients. This controller is tested on a marine microgrid containing a number of RES such as wind turbine generators, sea wave energy, and solar generation. The efficacy of the proposed MPIDF controller is verified with respect to other controllers such as PIDF and PI. Similarly, the proposed meta-heuristic algorithm is validated as compared to other algorithms including particle swarm optimization (PSO), ant colony optimization (ACO), and jellyfish swarm optimization (JSO). This study also evaluates the robustness of the proposed controller to different perturbations in step load, changes in system parameters, and other parameter variations.

This paper presents an energy management system supported by PI Controller for a residential grid connected micro grid with renewable hybrid generation (wind and photo voltaic) and battery system. Modeling hybrid system includes non conventional energy sources given at sporadic supply conditions and dynamic energy demand, and to make conceptual energy storage with the help of battery system . Designing an appropriate scheme that dynamically changes modes of renewable integrated system based on the availability of RES power and changes in load. Wind,PV are the primary power supply of the system; battery is going to be act as a substitute.The PI controller is developed and carried out for the aimed hybrid(Wind and PV) energy system to integrate the non conventional energy sources to the serviceability either to grid or to Residential loads.main objective is improvement of transients during switching periods by using an efficient PI controller.maximum power point tracking is also other objective is energy management system designed for the residential grid connected Micro Grid. Simulations are carried out on the proposed Hybrid energy system using MATLAB/ SIMULINK.

For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly in microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects the microgrid dynamics under uncertainties, lowering the microgrid frequency stability, specifically in the islanded mode of operation. Therefore, this work aims to enhance the islanded microgrid frequency resilience using the virtual inertia frequency control concept. Additionally, optimal model predictive control (MPC) is employed in the virtual inertial control model. The optimum design of the MPC is attained using an optimization algorithm, the African Vultures Optimization Algorithm (AVOA). To certify the efficacy of the proposed controller, the AVOA-based MPC is compared with a conventional proportional–integral (PI) controller that is optimally designed using various optimization techniques. The actual data of RES is utilized, and a random load power pattern is applied to achieve practical simulation outcomes. Additionally, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability. The simulation findings show the effectiveness of AVOA-based MPC in improving the microgrid frequency resilience. Furthermore, the results secure the role of BES in improving transient responses in the time domain simulations. The simulation outcomes are obtained using MATLAB software.

Abstract: For ever increasing power demand and depletion of conventional energy resources, Renewable Energy Systems (RES) became an alternative source of electricity to reduce the load stress on the Power Grid. Although several control & design modifications are presented in past literature to improve reliability & performance of through Distribution Generation (DG) technologies, they always fall short in some aspects of voltage stability and Fault Ride Through (FRT) capabilities. The main aim of the project is Protecting Critical load from Grid side altercations which occur due to harmonics generated by DG’s and Short circuit faults near to load center. This project proposes the application of a Dynamic Voltage Restorer (DVR) to enhance the power quality and improve the Fault Ride Through (FRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation (DG) system. In this hybrid farm, the Photo Voltaic (PV) plant via single-stage energy conversion (DC-AC inverter) & DFIG (Doubly-Fed Induction Generator) based Wind power plant are connected to the same Point of Common Coupling (PCC). For MPPT of wind power plant, we use Pitch Angle Control (PAC) technique. This topology allows Perturb and observe (P&O) based MPPT algorithm for PV plant through connection of the DG (Distribution generation) system to the public grid through a step-up transformer. In addition, the DVR based on Artificial Neural Network (ANN) controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the sensitive Load. The efficiency of this control technique is that it enhances restoration and harmonics suppression capabilities of DVR which are far superior than that of PI controller used in existing model. Keywords: RES, DG, LVRT, FRT, PV, DFIG, PCC, MPPT, P&O, DVR, PI, ANN, THD, Voltage stability.

An intelligent control strategy is proposed in this paper which suggests the Optimum Power Quality Enhancement (OPQE) of grid-connected hybrid power systems with solar photovoltaic, wind turbines, and battery storage. Unified Power Quality Conditioner with Active and Reactive power (UPQC-PQ) is designed with Atom Search Optimization (ASO) based Fractional-order Proportional Integral Derivative (FOPID) controller in the proposed Hybrid Renewable Energy Sources (HRES) system. The main aim is to regulate voltage while reducing power loss and reducing Total Harmonic Distortion (THD). UPQC-PQ is used to mitigate the Power Quality (PQ) problems such as sag, swell, interruptions, real power, reactive power and THD reductions related to voltage/current by using ASO based FOPID controller. The developed technique is demonstrated in various modes: simultaneous to improve PQ reinforcement and RES power injection, PRES > 0, PRES = 0. The results are then compared to those obtained using previous literature methods such as PI controller, GSA, BBO, GWO, ESA, RFA, and GA and found the proposed approach is efficient. The MATLAB/Simulink work framework is used to create the model.

Hybrid microgrid optimization, integration, and control are becoming increasingly important. Renewable energy source integrations are being used more often in shipping ports, as well as on short-distance cruises and ferries. Several seaports presently lack cold ironing services, which are shore-based power stations that provide electricity to ships from the main utility grids. Furthermore, diesel engines and diesel generator-based shipboards must be continuously running and on-line when docking to provide additional loads of ships due to the absence of cold-ironing services at many ports. In this research, we analytically presented the robustness of our proposed hierarchical control design for the hybrid shipboard Microgrid system containing multiple DGs and renewable energy resource (RES) integrations. The performance comparison of the conventional proportional integral (PI) vs. Sliding Mode Controller (SMC)-based control design is validated with simulation tests under different static and dynamical load conditions for both AC and DC types of loads. We further considered multi-DGs and RES integrations into our system to validate our design’s robustness against noise and unwanted faulty load conditions. The complete system stability analysis and designing of the control law are performed. Mathematical derivations and simulation results prove the robustness of the proposed hierarchical control architecture and compare the performance characteristics of two secondary controllers designed using a MATLAB/Simulink environment.

Microgrid (MG) is a novel concept for a future distribution power system that enables renewable energy sources (RES). The intermittent RES, such as wind turbines and photovoltaic generators, can be connected to the MG via a power electronics inverter. However, the inverter interfaced RESs reduce the total inertia and damping properties of the traditional MG. Consequently, the system exhibits steeper frequency nadir and the rate of change of frequency (RoCoF), which may degrade the dynamic performance and cause the severe frequency fluctuation of the system. Smart loads such as inverter air conditioners (IACs) tend to be used for ancillary services in power systems. The power consumption of IACs can be regulated to suppress frequency fluctuation. Nevertheless, these IACs, regulating power, can cause the deviation of indoor temperature from the temperature setting. The variation in indoor temperature should be controlled to fulfill residential comfort. This paper proposes a multi-objective decentralized model predictive control (DMPC) for controlling the power consumption of IACs to reduce MG frequency fluctuation and control the variation in indoor temperature. Simulation results on the studied microgrid with the high penetration of wind and photovoltaic generator demonstrate that the proposed DMPC is able to regulate frequency deviation and control indoor temperature deviation as a user preference. In addition, the DMPC has a superior performance effect to the proportional-integral (PI) controller in terms of reducing frequency deviation, satisfying indoor temperature preferences, and being robust to the varying numbers of IACs.

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

In this article, we suggest a micro-grid methodology based on renewable energy sources (RES) in order to make more efficient use of renewable energy sources and use less energy from the traditional power grid. Off-grid, RES likes solar (generated by a photovoltaic panel) and wind can be stored in a battery and utilised to power loads. As an additional measure, a Fuzzy logic-based energy-saving method has been applied. Microgrids are used to integrate these systems in a decentralised fashion, and they provide a suite of technology solutions that facilitate communication between end users and dispersed power plants. This raises the question of how best to administer these systems. In order to guarantee that both the generating and distribution systems produce energy at low operating costs, energy management in microgrids is described as a data and monitoring network that allows the required functions. In this study, we discuss the difficulties associated with using RES and managing a microgrid. Voltage and frequency variations result from the dynamic nature of DG systems. Unpredictable dynamics result from the load's unknowability. As a result of this nonlinear dynamic, there are observable changes to the microgrid's operation. In this study, we test the efficiency of the microgrid in a variety of settings. We compare the PI controller's performance on the MATLAB/Simulink platform to that of a Fuzzy logic-based controller with various levels of complexity.

Heating, ventilation and air-conditioning (HVAC) systems constitute the majority of the demands in modern power systems for aggregated buildings. However, HVAC integrated with renewable energy sources (RES) face notable issues, such as uneven demand–supply balance, frequency oscillation and significant drop in system inertia owing to sudden disturbances in nearby generation for a longer period. To overcome these challenges, load frequency control (LFC) is implemented to regulate the frequency, maintain zero steady-state error between the generation and demand, reduce frequency deviations and balance the active power flow with neighboring control areas at a specified value. In view of this, the present paper investigates LFC with a proposed centralized single control strategy for a micro-grid (µG) system consisting of RESs and critical load of a HVAC system. The proposed control strategy includes a newly developed cascaded two-degree-of-freedom (2-DOF) proportional integral (PI) and proportional derivative filter (PDF) controller optimized with a very recent meta-heuristic algorithm—a modified crow search algorithm (mCSA)—after experimenting with the number of performance indices (PICs). The superiority of both the proposed optimization algorithm and the proposed controller is arrived at after comparison with similar other algorithms and similar controllers, respectively. Compared to conventional control schemes, the proposed scheme significantly reduces the frequency deviations, improving by 27.22% from the initial value and reducing the performance index criteria (ƞISE) control error to 0.000057. Furthermore, the demand response (DR) is implemented by an energy storage device (ESD), which validates the suitability of the proposed control strategy for the µG system and helps overcome the challenges associated with variable RESs inputs and load demand. Additionally, the improved robustness of the proposed controller for this application is demonstrated through sensitivity analysis with ±20% μG coefficient variation.

Striving for the suppression of greenhouse emissions, the modern power network is facing fundamental changes with the utilization of renewable energies (REs) for the future carbon-free society. The utilization of intermittent renewable-green power needs a better power management system and virtual power plant (VPP) can be a vital candidate that meets this demand. This study investigates a coordinated control grid integrated virtual power plant (VPP) in the presence of Central Receiver Solar Thermal System (CRSTS), Wind Turbine Generator (WTG), and Electric Vehicle (EV). To this end, CRSTS employed with thermal storage acts as a dispatchable renewable generating unit and coordinated control of the system units are achieved using the available control strategy on interconnected microgrids in the modified form, employing communication time delay. The proposed control strategy employs the proportional-integral (PI) and PI-derivative (PID) controller. Coordinated power control with real-time communication delay in grid integrated VPP in presence of CRSTS, WTG, and EV is a novel approach. Genetic algorithm (GA), Particle Swarm Optimization (PSO), Slap Swarm Algorithm (SSA), and recent Butterfly Optimization Algorithm (BOA) are used for tuning the necessary control parameters. The results establish the superiority of the BOA over SSA and PSO in suppressing system frequency deviations and tie line power deviation. The analysis of the dynamic response reveals that the consideration of the communication delay in the system expressively impedes the stable operation of the power system.

Decarbonization of power systems has put Renewable Energy Sources (RES) at the forefront when it comes to electric power generation. The increasing shares of converter-connected renewable generation cause a decrease of the rotational inertia of the Electric Power System (EPS), and consequently deteriorate the system capability to withstand large load-generation imbalances. Low-inertia systems are subjected to fast and large frequency changes in case of in-feed loss, where the traditional primary frequency control is not sufficient to preserve the frequency stability and to maintain the frequency above the critical value. One possible solution to this rising problem is seen in Fast Frequency Response (FFR) provided by the High-Voltage Direct-Current (HVDC)-based systems. This paper presents the adaptive FFR control of HVDC-based systems for frequency stability enhancement in the low-inertia system. The EPS is considered as a “black box” and the HVDC response is determined only using the locally measured frequency change. Sliding Mode Control (SMC) of the Modular Multilevel Converter (MMC) was developed and demonstrated to provide faster and more appropriate frequency response compared to the PI controller. The described adaptive HVDC control considers the size of disturbance and the inertia of the power system, and it is verified by simulations on the IEEE 39 bus test system implemented in MATLAB/Simulink for different system configurations and different sizes of disturbance.

DC microgrids have shown to be a good approach for better accommodating stochastic renewable energy sources (RES) and for the charging of electric vehicles (EVs) at the distribution level. For this, fast-acting energy storage units (ESSs) are essential. This requires that both the bi-directional power converter topology and the control scheme present the right set of features. The ESS discussed in this paper consists of a new DC-DC converter based on a tapped inductor (TI) for a higher voltage gain at moderate duty cycles. The direction of the current in its intermediate inductor does not need to be reversed for power flow reversal, leading to a faster action. Moreover, it can employ a multi-state and multi-variable modulation scheme that eliminates the right half-plane (RHP) zero, common in boost-type converters. In order to achieve good dynamic performance across a wide range of operating points, a control scheme based on feedback linearization is developed. This paper presents the modeling of the five-switch DC-DC converter operating in the tri-state buck–boost mode. A systematic approach for deriving control laws for the TI current and output voltage based on exact state feedback linearization is discussed. The performance of the proposed control scheme is verified by simulation for a supercapacitor (SC)-based ESS. It is compared to that of a conventional control scheme for a dual-state buck–boost mode with cascaded PI controllers designed based on small-signal models. The results show that both control schemes work similarly well at the operating point that the conventional control scheme was designed for. However, only the proposed scheme allows the SC-based ESS to control the current injected into the DC microgrid with the voltage of the SC varying between the expected range of rated to half-rated.

A paradigm shift in power engineering transforms conventional fossil fuel-based power systems gradually into more sustainable and environmentally friendly systems due to more renewable energy source (RES) integration. However, the control structure of high-level RES integrated system becomes complex, and the total system inertia is reduced due to the removal of conventional synchronous generators. Thus, such a system poses serious frequency instabilities due to the high rate of change of frequency (RoCoF). To handle this frequency instability issue, this work proposes an optimized fractional-order proportional integral (FOPI) controller-based superconducting magnetic energy storage (SMES) approach. The proposed FOPI-based SMES technique to support virtual inertia is superior to and more robust than the conventional technique. The FOPI parameters are optimized using the particle swarm optimization (PSO) technique. The SMES is modeled and integrated into the optimally designed FOPI to support the virtual inertia of the system. Fluctuating RESs are considered to show the effectiveness of the proposed approach. Extensive time-domain simulations were carried out in MATLAB Simulink with different load and generation mismatch levels. Systems with different inertia levels were simulated to guarantee the frequency stability of the system with the proposed FOPI-based SMES control technique. Several performance indices, such as overshoot, undershoot, and settling time, were considered in the analysis.

Electric vehicles (EVs) are gradually becoming an integral part of the drive to accomplish sustainable energy standards. Due to their limited onboard battery capacity, EVs’ expanding popularity creates a need for widespread charging stations. However, fast charging stations, particularly Extreme Fast Charging (EFC), may impose a hassle on the electrical system due to overload during peak hours, frequent power gaps, and voltage sag. To flatten the power supply, the photovoltaic (PV) Hybrid Energy Storage Systems (HESS) and the uncertain and variable nature of PV systems always include solar and hybrid energy storage systems (HESS) such as batteries and supercapacitors. This research suggests a multi-port DC-DC converter (MPC) with a bidirectional DC-DC converter for battery ESS-integrated PV systems. The MPC can regulate the majority of active power through PV to a battery, PV to an EV charging station, HESS to an EV charging station, and PV to AC grid. Additionally, a PI controller is used for the MPC, taking both the PV and battery voltage variations into account. Therefore, the presented configuration can achieve the key benefits of greater integration, more efficiency, and reduced cost. Simulation results show the advantages of this multiport EV charging circuit with PV-HESS and design in different modes.

With high penetrations of renewable energy sources (RES), distributed battery systems (DBS) are widely adopted in standalone DC microgrids to stabilize the bus voltages by balancing the active power. This paper presents an Adaptive Differential Evolution (ADE)-based hierarchical control for DBS to achieve online distribution power loss mitigation as well as bus voltage regulations in standalone DC microgrids. The hierarchical control comprises two layers, i.e., ADE for the secondary layer and local proportional-integral (PI) control for the primary layer. The secondary layer control provides the bus voltage references for the primary control by optimizing the fitness function, which contains the parameters of the bus voltage deviations and the power loss on the distribution lines. Simultaneously, the state-of-charge (SoC) of the battery packs are controlled by local controllers to prevent over-charge and deep-discharge. Case studies using a Real-Time Digital Simulator (RTDS) validate that the proposed ADE-based hierarchical control can effectively reduce the distribution power loss and regulate the bus voltages within the tolerances in DC microgrids.

In this article, the problem of voltage and frequency stability in a hybrid multi-area power system including renewable energy sources (RES) and electric vehicles has been investigated. Fractional order systems have been used to design innovative controllers for both load frequency control (LFC) and automatic voltage regulator (AVR) based on the combination of fractional order proportional-integral and proportional-integral-derivative plus double derivative (FOPI–PIDD2). Here, the dandelion optimizer (DO) algorithm is used to optimize the proposed FOPI–PIDD2 controller to stabilize the voltage and frequency of the system. Finally, the results of simulations performed on MATLAB/Simulink show fast, stable, and robust performance based on sensitivity analysis, as well as the superiority of the proposed optimal control strategy in damping frequency fluctuations and active power, exchanged between areas when faced with step changes in load, the changes in the generation rate of units, and the uncertainties caused by the wide changes of dynamic values.

The multi-modular converter (MMC) technology is becoming the preferred option for the increased deployment of variable renewable energy sources (RES) into electrical power systems. MMC is known for its reliability and modularity. The fast adjustment of the MMC’s active/reactive powers, within a few milliseconds, constitutes a major research challenge. The solution to this challenge will allow accelerated integration of RES, without creating undesirable stability issues in the future power system. This paper presents a variant of model predictive control (MPC) for the grid-connected MMC. MPC is defined using a Laguerre function to reduce the computational burden. This is achieved by reducing the number of parameters of the MMC cost function. The feasibility and effectiveness of the proposed MPC is verified in the real-time digital simulations. Additionally, in this paper, a comparison between an accurate mathematical and real-time simulation (RSCAD) model of an MMC is given. The comparison is done on the level of small-signal disturbance and a Mean Absolute Error (MAE). In the MMC, active and reactive power controls, AC voltage control, output current control, and circulating current controls are implemented, both using PI and MPC controllers. The MPC’s performance is tested by the small and large disturbance in active and reactive powers, both in an offline and online simulation. In addition, a sensitivity study is performed for different variables of MPC in the offline simulation. Results obtained in the simulations show good correspondence between mathematical and real-time analytical models during the transient and steady-state conditions with low MAE. The results also indicate the superiority of the proposed MPC with the stable and fast active/reactive power support in real-time simulation.

Objectives The purpose of this study was to create a novel ex vivo organ culture model for evaluating the effects of static and dynamic load on cartilage. Methods The metatarsophalangeal joints of 12 fresh cadaveric bovine feet were skinned and dissected aseptically, and cultured for up to four weeks. Dynamic movement was applied using a custom-made machine on six joints, with the others cultured under static conditions. Chondrocyte viability and matrix glycosaminoglycan (GAG) content were evaluated by the cell viability probes, 5-chloromethylfluorescein diacetate (CMFDA) and propidium iodide (PI), and dimethylmethylene blue (DMMB) assay, respectively. Results Chondrocyte viability in the static model decreased significantly from 89.9% (sd 2.5%) (Day 0) to 66.5% (sd 13.1%) (Day 28), 94.7% (sd 1.1%) to 80. 9% (sd 5.8%) and 80.1% (sd 3.0%) to 46.9% (sd 8.5%) in the superficial quarter, central half and deep quarter of cartilage, respectively (p < 0.001 in each zone; one-way analysis of variance). The GAG content decreased significantly from 6.01 μg/mg (sd 0.06) (Day 0) to 4.71 μg/mg (sd 0.06) (Day 28) (p < 0.001; one-way analysis of variance). However, with dynamic movement, chondrocyte viability and GAG content were maintained at the Day 0 level over the four-week period without a significant change (chondrocyte viability: 92.0% (sd 4.0%) (Day 0) to 89.9% (sd 0.2%) (Day 28), 93.1% (sd 1.5%) to 93.8% (sd 0.9%) and 85.6% (sd 0.8%) to 84.0% (sd 2.9%) in the three corresponding zones; GAG content: 6.18 μg/mg (sd 0.15) (Day 0) to 6.06 μg/mg (sd 0.09) (Day 28)). Conclusion Dynamic joint movement maintained chondrocyte viability and cartilage GAG content. This long-term whole joint culture model could be of value in providing a more natural and controlled platform for investigating the influence of joint movement on articular cartilage, and for evaluating novel therapies for cartilage repair. Cite this article: Y-C. Lin, A. C. Hall, A. H. R. W. Simpson. A novel organ culture model of a joint for the evaluation of static and dynamic load on articular cartilage. Bone Joint Res 2018;7:205–212. DOI: 10.1302/2046-3758.73.BJR-2017-0320.

Abstract Abstract 2170 Poster Board II-147 We have previously published that NIH 3T3 cells, which are known to be resistant to Bcr-Abl transformation, are greatly stimulated to undergo Bcr-Abl oncogenic transformation by forced expression of the α and β chains of the human IL-3 receptor (Tao et al., Oncogene 2008). These studies further showed that expression of the receptor chains enhanced activation of Jak2 but had little effect on the ability of Bcr-Abl to activate STAT5, which readily occurred by expression of only Bcr-Abl. Recently we have shown (see Abstract by Samanta et al.) that treatment of Bcr-Abl+ 32D cells with the validated Jak2 inhibitor TG101209 (TargeGen, Inc.) and also with a new Jak2 inhibitor WP1193 for 60-120 min: a) reduced phosphorylation of Tyr 177 of Bcr-Abl and the total level of pTyr Bcr-Abl; b) Bcr-Abl protein levels were rapidly decreased; c) total Ras-GTP, pGab2, pShc and pSTAT5 levels were reduced. These results suggest that major functions attributed to Bcr-Abl are actually controlled by Jak2. However, important questions need to be addressed: a) how is Jak2 regulated in Bcr-Abl+ cells; b) whether activation of Jak2 requires Bcr-Abl only; c) or whether it requires Bcr-Abl associated with IL-3 α and β chains together; and finally d) whether our observations in Bcr-Abl+ mouse hematopoietic cell lines can be reproduced in the Bcr-Abl+, IL-3 receptor+ NIH 3T3 fibroblastic cell line. We observed that NIH 3T3 cells expressing the IL-3 receptor and Bcr-Abl have increased Jak2 activity and increased ability to phosphorylate Tyr 177 of Bcr-Abl compared to NIH 3T3 cells expressing Bcr-Abl only. Phosphorylation of Tyr 177 of Bcr-Abl is needed to activate the Ras and PI-3 kinase pathways. Phosphorylation of Gab2 on Tyr YxxM, which depends on Jak2 kinase activity (Samanta et al., Can Res 2006), plays a critical role in activating the PI-3 kinase pathway. Inhibition of Jak2 with the highly specific Jak2 inhibitor TG101209 and the newly discovered Janus kinase inhibitor WP1193 rapidly reduced phosphorylation of Tyr 177 of Bcr-Abl in Bcr-Abl+ NIH 3T3 cells expressing the IL-3 receptor chains. In Bcr-Abl+ 32D cells Jak2 inhibitors but not imatinib mesylate (IM) inhibited phosphorylation of Bcr-Abl Tyr 177 (see Abstract by Samanta et al.). The lack of IM inhibition of phosphorylation of Tyr 177 supports the conclusion that Bcr-Abl does not autophosphorylate Tyr 177 but Tyr 177 is a target of Jak2. Soft agar clones of NIH 3T3 cells that had expressed both the IL-3 receptor chains and Bcr-Abl in cell culture surprisingly had a strong preference for expressing only the β chain of the IL-3 receptor as agar clones. Five of six clones expressed only the β chain whereas the remaining clone expressed only the α chain. All of these clones expressed Bcr-Abl. The β clones generally had higher levels of activated Jak2 kinase than the α chain clone. Cells expressing the β chain had high levels of pTyr 177 Bcr-Abl. Since the levels of activated Jak2 in NIH 3T3 cells expressing only Bcr-Abl were quite low compared to the cells expressing the IL-3 receptor chains and Bcr-Abl, and since cells expressing β chain only together with Bcr-Abl had higher levels of activated Jak2 compared to the α chain only clone, we propose that the β chain is a critical component utilized by Bcr-Abl to activate Jak2. In this scenario, we hypothesize that the β chain would bind a molecule of Jak2 and Bcr-Abl would bind another molecule of Jak2 (see Xie et al. Oncogene 2001), and furthermore the association of the β chain with Bcr-Abl would facilitate cross phosphorylation of Jak2 at Tyr 1007, resulting in activation of Jak2. Disclosures: No relevant conflicts of interest to declare.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) is the most lethal disease and the leading cause of cancer death worldwide. The survival rate of patients with this form of cancer is about 8%. The physiological barrier of the tumor microenvironment composed of a dense stroma and disorganized blood vessels creates a barrier for early identification and treatment of this deadly disease. In recent years, nanoparticle-based controlled delivery systems were developed to exploit the pathophysiology of biological systems such as acidic tumor microenvironment or the altered tumor-specific enzymes to improve the diagnosis and treatment efficacy. Here, we demonstrate the collagenase IV-mediated tumor site-selective release of the IR-780 imaging probe from the M-Ge-SDC1 nanoparticles, revealing the feasibility of the collagenase IV (MMP-9) responsive target specificity for diagnosing pancreatic cancer by multispectral optoacoustic tomography (MSOT) imaging. Methods: Mesoporous silica nanoparticles (MSN) with wormhole pore topology were synthesized and were characterized by dynamic light scattering (DLS) and transmission electron microscopy (TEM). The surface of MSN was conjugated with Gelatin-A to obtain M-Ge. The M-Ge particles were loaded with propidium Iodide (PI) or IR780 infrared imaging dye. The M-Ge surface was further conjugated with Syndecan-1 (SDC1) to improve the target specificity to release imaging cargo from the nanoparticles. Female athymic mice were orthotopically implanted with S2VP10 tumor cells. After a week of tumor implantation, mice were intravenously injected with M-Ge-SDC1 nanoparticles containing IR780 dye and were imaged with MSOT and AMI. Results: In the current study, Mesoporous silica nanoparticles with 27 nm diameter were synthesized. The Gelatin-A crosslinking on the surface of MSN particles as a gatekeeper was developed that could degrade upon contact with collagenase IV in the tumor microenvironment. The conjugation of SDC1 further improved the tumor specificity. The athymic mice orthotopically implanted with S2VP10 cells closely resemble human PDAC. Our results demonstrated that intravenous delivery of M-Ge-SDC1 nanoparticles could enzymatically degrade (MMP-9) and release IR780 at the tumor site and conjugation of SDC1 further improved the tumor specificity to detect the orthotopically implanted pancreatic tumors (p&lt;0.0001,n=5). Conclusion: Due to the lack of effective screening tools, PDAC has the lowest survival rate and limited therapeutic efficacy for current FDA-approved drugs compared to other malignancies. Innovative technologies to develop engineered nanoparticles with active targeting moiety and dynamic imaging technology can overcome these limitations. Implementing such systems can enhance PDAC detection that can be translated into the clinic to improve health care. Citation Format: Abhilash Samykutty, Molly McNally, William M. MacCuaig, Jordan Hagood, Girish Mishra, Barish H. Edil, William E. Grizzle, Lacey R. McNally. Matrix metalloproteinase-9 responsive active targeted silica nanoparticles for pancreatic cancer detection by multispectral optoacoustic tomography [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 300.

Abstract Among the main aberrations occurring in GBM, those in MEK/ERK and PI3K/akt/mTOR pathways predominate and confer GBM Stem-like Cells (GSCs) sustained proliferation and resistance to therapy. A panel of eight patient-derived primary GSCs lines have been screened for their sensitivity to a small kinase MEK inhibitor (MEKi) with AnnexinV/PI staining. Among these, five display a sensitive phenotype with at least 50% reduction on cell viability after 72 hours of treatment. Then, four cell lines, two MEKi-sensitive (ICH001 and ICH003) and two MEKi-resistant (ICH013 and ICH027) were selected for a deeper molecular characterization based on MGMT methylation status, mesenchymal index and main hotspot mutations associated with GBM pathology MEKi incubation on GSC caused a prompt phospho-ERK reduction already after 3 hours. Of note, we report a concomitant activation of AKT and downstream molecules pointing to an ERK-mTOR redundant activity. To this end, we combined MEKi to PI3K/akt/mTOR inhibitor and we observed an increased cell death even in GSCs displaying moderate sensitivity to MEKi as single-agent (MEKi: 90% vs MEKi-PI3K/akt/mTOR inhibitor: 30% cell viability). Then, MEKi ability to cross the Blood Brain Barrier (BBB) and target GBM cells was investigated using a transwell BBB in vitro model. The PI3K/akt/mTOR pathway inhibitor, known from the literature to readily cross the BBB, was included as positive control. Obtained results showed MEKi inability to efficiently cross the BBB, thus limiting its utility as GBM therapy. These results suggest the need for a specific drug delivery strategy in the brain that might be therapeutically effective. Recently our laboratory has provided proof-of-concept of a combination strategy based on radiation and adjuvant drug-loaded liposomes (LPs) conjugated with a modified Apolipoprotein E-derived peptide (mApoE), known to facilitate BBB crossing. To strengthen therapeutic efficacy and to lower off-target effects, we implemented mApoE-LPs with a matrix metalloproteinases 2 and 9 sensitive lipopeptide (M2-9SLP) that allows controlled payload release only in the tumor microenvironment rich in MMPs. To this end, MEKi was encapsulated into the M2-9SLP/mApoE-LPs, and its capacity to promote cell death was evaluated. M2-9SLP/mApoE-MEKi-LPs caused in all the sensitive cell lines GSCs proliferation inhibition and induction of apoptosis upon 72h in vitro treatment indicating that the encapsulation process did not alter drug efficacy. In conclusion, our in vitro results support MEKi encapsulation into M2P/mApoE-LP as nanotherapeutic strategy that could guarantee specific delivery of MEKi in a MMP2-enriched tumor microenvironment without altering its capacity to inhibit GSC proliferation and survival. Funding by FRRB grant NEVERMIND (CP2_16/2018) Citation Format: Milena Mattioli, Elisabetta Stanzani, Valentino Ribecco, Marco Pizzocri, Eliana Lauranzano, Margherita Maria Ravanelli, Simone Olei, Maria Pia Tropeano, Pierfausto Seneci, Francesca Re, Federico Pessina, Michela Matteoli, Lorena Passoni. Smart encapsulation of a MEK inhibitor into M2-9SLP/mApoE-liposomes for specific GBM targeting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2711.

Hamsters were exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days. Equal amounts of proteins from urinary bladder or liver extracts of control and arsenic-treated hamsters were labeled with Cy3 and Cy5 dyes, respectively. After differential in gel electrophoresis and analysis by the DeCyder software, several protein spots were found to be down-regulated and several were up regulated. Our experiments indicated that in the bladder tissues of hamsters exposed to arsenite, transgelin was down-regulated and GST-pi was up-regulated. The loss of transgelin expression has been reported to be an important early event in tumor progression and a diagnostic marker for cancer development [29-32]. Down-regulation of transgelin expression may be associated with the carcinogenicity of inorganic arsenic in the urinary bladder. In the liver of arsenite-treated hamsters, ornithine aminotransferase was up-regulated, and senescence marker protein 30 and fatty acid binding protein were down-regulated. The volume ratio changes of these proteins in the bladder and liver of hamsters exposed to arsenite were significantly different than that of control hamsters. Introduction Chronic exposure to inorganic arsenic can cause cancer of the skin, lungs, urinary bladder, kidneys, and liver [1-6]. The molecular mechanisms of the carcinogenicity and toxicity of inorganic arsenic are not well understood [7-9). Humans chronically exposed to inorganic arsenic excrete MMA(V), DMA(V) and the more toxic +3 oxidation state arsenic biotransformants MMA(III) and DMA (III) in their urine [10, 11], which are carcinogen [12]· After injection of mice with sodium arsenate, the highest concentrations of the very toxic MMA(III) and DMA(III) were in the kidneys and urinary bladder tissue, respectively, as shown by experiments of Chowdhury et al [13]. Many mechanisms of arsenic toxicity and carcinogenicity have been suggested [1, 7, 14] including chromosome abnormalities [15], oxidative stress [16, 17], altered growth factors [18], cell proliferation [19], altered DNA repair [20], altered DNA methylation patterns [21], inhibition of several key enzymes [22], gene amplification [23] etc. Some of these mechanisms result in alterations in protein expression. Methods for analyzing multiple proteins have advanced greatly in the last several years. In particularly, mass spectrometry (MS) and tandem MS (MS/MS) are used to analyze peptides following protein isolation using two-dimensional (2-D) gel electrophoresis and proteolytic digestion [24]. In the present study, Differential In Gel Electrophoresis (DIGE) coupled with Mass Spectrometry (MS) has been used to study some of the proteomic changes in the urinary bladder and liver of hamsters exposed to sodium arsenite in their drinking water. Our results indicated that transgelin was down-regulated and GST-pi was up-regulated in the bladder tissues. In the liver tissues ornithine aminotransferase was up-regulated, and senescence marker protein 30, and fatty acid binding protein were down-regulated. Materials and Methods Chemicals Tris, Urea, IPG strips, IPG buffer, CHAPS, Dry Strip Cover Fluid, Bind Silane, lodoacetamide, Cy3 and Cy5 were from GE Healthcare (formally known as Amersham Biosciences, Uppsala, Sweden). Thiourea, glycerol, SDS, DTT, and APS were from Sigma-Aldrich (St. Louis, MO, USA). Glycine was from USB (Cleveland, OH, USA). Acrylamide Bis 40% was from Bio-Rad (Hercules, CA, USA). All other chemicals and biochemicals used were of analytical grade. All solutions were made with Milli-Q water. Animals Male hamsters (Golden Syrian), 4 weeks of age, were purchased from Harlan Sprague Dawley, USA. Upon arrival, hamsters were acclimated in the University of Arizona animal care facility for at least 1 week and maintained in an environmentally controlled animal facility operating on a 12-h dark/12-h light cycle and at 22-24°C. They were provided with Teklad (Indianapolis, IN) 4% Mouse/Rat Diet # 7001 and water, ad libitum, throughout the acclimation and experimentation periods. Sample preparation and labelling Hamsters were exposed to sodium arsenite (173 mg) in drinking water for 6 days and the control hamsters were given tap water. On the 6th day hamsters were decapitated rapidly by guillotine. Urinary bladder tissues and liver were removed, blotted on tissue papers (Kimtech Science, Precision Wipes), and weighed. Hamster urinary bladder or liver tissues were homogenized in lysis buffer (30mMTris, 2M thiourea, 7M urea, and 4% w/w CHAPS adjusted to pH 8.5 with dilute HCI), at 4°C using a glass homogenizer and a Teflon coated steel pestle; transferred to a 5 ml acid-washed polypropylene tube, placed on ice and sonicated 3 times for 15 seconds. The sonicate was centrifuged at 12,000 rpm for 10 minutes at 4°C. Small aliquots of the supernatants were stored at -80°C until use (generally within one week). Protein concentration was determined by the method of Bradford [25] using bovine serum albumin as a standard. Fifty micrograms of lysate protein was labeled with 400 pmol of Cy3 Dye (for control homogenate sample) and Cy5 Dye (for arsenic-treated urinary bladder or liver homogenate sample). The samples containing proteins and dyes were incubated for 30 min on ice in the dark. To stop the labeling reaction, 1uL of 10 mM lysine was added followed by incubation for 10 min on ice in the dark. To each of the appropriate dye-labeled protein samples, an additional 200 ug of urinary bladderor liver unlabeled protein from control hamster sample or arsenic-treated hamster sample was added to the appropriate sample. Differentially labeled samples were combined into a single Microfuge tube (total protein 500 ug); protein was mixed with an equal volume of 2x sample buffer [2M thiourea, 7M urea, pH 3-10 pharmalyte for isoelectric focusing 2% (v/v), DTT 2% (w/v), CHAPS 4% (w/v)]; and was incubated on ice in the dark for 10 min. The combined samples containing 500 ug of total protein were mixed with rehydration buffer [CHAPS 4% (w/v), 8M urea, 13mM DTT, IPG buffer (3-10) 1% (v/v) and trace amount of bromophenol blue]. The 450 ul sample containing rehydration buffer was slowly pipetted into the slot of the ImmobilinedryStripReswelling Tray and any large bubbles were removed. The IPG strip (linear pH 3-10, 24 cm) was placed (gel side down) into the slot, covered with drystrip cover fluid (Fig. 1), and the lid of the Reswelling Tray was closed. The ImmobillineDryStrip was allowed to rehydrate at room temperature for 24 hours. First dimension Isoelectric focusing (IEF) The labeled sample was loaded using the cup loading method on universal strip holder. IEF was then carried out on EttanIPGphor II using multistep protocol (6 hr @ 500 V, 6 hr @ 1000 V, 8 hr @ 8000 V). The focused IPG strip was equilibrated in two steps (reduction and alkylation) by equilibrating the strip for 10 min first in 10 ml of 50mM Tris (pH 8.8), 6M urea, 30% (v/v) glycerol, 2% (w/v) SDS, and 0.5% (w/v) DTT, followed by another 10 min in 10 ml of 50mM Tris (pH 8.8), 6M urea, 30% (v/v) glycerol, 2% (w/v) SDS, and 4.5% (w/v) iodoacetamide to prepare it for the second dimension electrophoresis. Second dimension SDS-PAGE The equilibrated IPG strip was used for protein separation by 2D-gel electrophoresis (DIGE). The strip was sealed at the top of the acrylamide gel for the second dimension (vertical) (12.5% polyacrylamide gel, 20x25 cm x 1.5 mm) with 0.5% (w/v) agarose in SDS running buffer [25 mMTris, 192 mM Glycine, and 0.1% (w/v) SDS]. Electrophoresis was performed in an Ettan DALT six electrophoresis unit (Amersham Biosciences) at 1.5 watts per gel, until the tracking dye reached the anodic end of the gel. Image analysis and post-staining The gel then was imaged directly between glass plates on the Typhoon 9410 variable mode imager (Sunnyvale, CA, USA) using optimal excitation/emission wavelength for each DIGE fluor: Cy3 (532/580 nm) and Cy5 (633/670 nm). The DIGE images were previewed and checked with Image Quant software (GE Healthcare) where all the two separate gel images could be viewed as a single gel image. DeCyde v.5.02 was used to analyze the DIGE images as described in the Ettan DIGE User Manual (GE Healthcare). The appropriate up-/down regulated spots were filtered based on an average volume ratio of ± over 1.2 fold. After image acquisition, the gel was fixed overnight in a solution containing 40% ethanol and 10% acetic acid. The fixed gel was stained with SyproRuby (BioRad) according to the manufacturer protocol (Bio-Rad Labs., 2000 Alfred Nobel Drive, Hercules, CA 94547). Identification of proteins by MS Protein spot picking and digestion Sypro Ruby stained gels were imaged using an Investigator ProPic and HT Analyzer software, both from Genomic Solutions (Ann Arbor, MI). Protein spots of interest that matched those imaged using the DIGE Cy3/Cy5 labels were picked robotically, digested using trypsin as described previously [24] and saved for mass spectrometry identification. Liquid chromatography (LC)- MS/MS analysis LC-MS/MS analyses were carried out using a 3D quadrupole ion trap massspectrometer (ThermoFinnigan LCQ DECA XP PLUS; ThermoFinnigan, San Jose, CA) equipped with a Michrom Paradigm MS4 HPLC (MichromBiosources, Auburn, CA) and a nanospray source, or with a linear quadrupole ion trap mass spectrometer (ThermoFinnigan LTQ), also equipped with a Michrom MS4 HPLC and a nanospray source. Peptides were eluted from a 15 cm pulled tip capillary column (100 um I.D. x 360 um O.D.; 3-5 um tip opening) packed with 7 cm Vydac C18 (Vydac, Hesperia, CA) material (5 µm, 300 Å pore size), using a gradient of 0-65% solvent B (98% methanol/2% water/0.5% formic acid/0.01% triflouroacetic acid) over a 60 min period at a flow rate of 350 nL/min. The ESI positive mode spray voltage was set at 1.6 kV, and the capillary temperature was set at 200°C. Dependent data scanning was performed by the Xcalibur v 1.3 software on the LCQ DECA XP+ or v 1.4 on the LTQ [27], with a default charge of 2, an isolation width of 1.5 amu, an activation amplitude of 35%, activation time of 50 msec, and a minimal signal of 10,000 ion counts (100 ion counts on the LTQ). Global dependent data settings were as follows: reject mass width of 1.5 amu, dynamic exclusion enabled, exclusion mass width of 1.5 amu, repeat count of 1, repeat duration of a min, and exclusion duration of 5 min. Scan event series were included one full scan with mass range of 350-2000 Da, followed by 3 dependent MS/MS scans of the most intense ion. Database searching Tandem MS spectra of peptides were analyzed with Turbo SEQUEST, version 3.1 (ThermoFinnigan), a program that allows the correlation of experimental tandem MS data with theoretical spectra generated from known protein sequences. All spectra were searched against the latest version of the non redundant protein database from the National Center for Biotechnology Information (NCBI 2006; at that time, the database contained 3,783,042 entries). Statistical analysis The means and standard error were calculated. The Student's t-test was used to analyze the significance of the difference between the control and arsenite exposed hamsters. P values less than 0.05 were considered significant. The reproducibility was confirmed in separate experiments. Results Analysis of proteins expression After DIGE (Fig. 1), the gel was scanned by a Typhoon Scanner and the relative amount of protein from sample 1 (treated hamster) as compared to sample 2 (control hamster) was determined (Figs. 2, 3). A green spot indicates that the amount of protein from sodium arsenite-treated hamster sample was less than that of the control sample. A red spot indicates that the amount of protein from the sodium arsenite-treated hamster sample was greater than that of the control sample. A yellow spot indicates sodium arsenite-treated hamster and control hamster each had the same amount of that protein. Several protein spots were up-regulated (red) or down-regulated (green) in the urinary bladder samples of hamsters exposed to sodium arsenite (173 mg As/L) for 6 days as compared with the urinary bladder of controls (Fig. 2). In the case of liver, several protein spots were also over-expressed (red) or under-expressed (green) for hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days (Fig. 3). The urinary bladder samples were collected from the first and second experiments in which hamsters were exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days and the controls were given tap water. The urinary bladder samples from the 1st and 2nd experiments were run 5 times in DIGE gels on different days. The protein expression is shown in Figure 2 and Table 1. The liver samples from the 1st and 2nd experiments were also run 3 times in DIGE gels on different days. The proteins expression were shown in Figure 3 and Table 2. The volume ratio changed of the protein spots in the urinary bladder and liver of hamsters exposed to arsenite were significantly differences than that of the control hamsters (Table 1 and 2). Protein spots identified by LC-MS/MS Bladder The spots of interest were removed from the gel, digested, and their identities were determined by LC-MS/MS (Fig. 2 and Table 1). The spots 1, 2, & 3 from the gel were analyzed and were repeated for the confirmation of the results (experiments; 173 mg As/L). The proteins for the spots 1, 2, and 3 were identified as transgelin, transgelin, and glutathione S-transferase Pi, respectively (Fig. 2). Liver We also identified some of the proteins in the liver samples of hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days (Fig. 3). The spots 4, 5, & 6 from the gels were analyzed and were repeated for the confirmation of the results. The proteins for the spots 4, 5, and 6 were identified as ornithine aminotransferase, senescence marker protein 30, and fatty acid binding protein, respectively (Fig. 3) Discussion The identification and functional assignment of proteins is helpful for understanding the molecular events involved in disease. Weexposed hamsters to sodium arsenite in drinking water. Controls were given tap water. DIGE coupled with LC-MS/MS was then used to study the proteomic change in arsenite-exposed hamsters. After electrophoresis DeCyder software indicated that several protein spots were down-regulated (green) and several were up-regulated (red). Our overall results as to changes and functions of the proteins we have studied are summarized in Table 3. Bladder In the case of the urinary bladder tissue of hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days, transgelin was down-regulated and GST-pi was up-regulated. This is the first evidence that transgelin is down-regulated in the bladders of animals exposed to sodium arsenite. Transgelin, which is identical to SM22 or WS3-10, is an actin cross linking/gelling protein found in fibroblasts and smooth muscle [28, 29]. It has been suggested that the loss of transgelin expression may be an important early event in tumor progression and a diagnostic marker for cancer development [30-33]. It may function as a tumor suppressor via inhibition of ARA54 (co-regulator of androgen receptor)-enhanced AR (androgen receptor) function. Loss of transgelin and its suppressor function in prostate cancer might contribute to the progression of prostate cancer [30]. Down-regulation of transgelin occurs in the urinary bladders of rats having bladder outlet obstruction [32]. Ras-dependent and Ras-independent mechanisms can cause the down regulation of transgelin in human breast and colon carcinoma cell lines and patient-derived tumorsamples [33]. Transgelin plays a role in contractility, possibly by affecting the actin content of filaments [34]. In our experiments loss of transgelin expression may be associated or preliminary to bladder cancer due to arsenic exposure. Arsenite is a carcinogen [1]. In our experiments, LC-MS/MS analysis showed that two spots (1 and 2) represent transgelin (Fig. 2 and Table 1). In human colonic neoplasms there is a loss of transgelin expression and the appearance of transgelin isoforms (31). GST-pi protein was up-regulated in the bladders of the hamsters exposed to sodium arsenite. GSTs are a large family of multifunctional enzymes involved in the phase II detoxification of foreign compounds [35]. The most abundant GSTS are the classes alpha, mu, and pi classes [36]. They participate in protection against oxidative stress [37]. GST-omega has arsenic reductase activity [38]. Over-expression of GST-pi has been found in colon cancer tissues [39]. Strong expression of GST-pi also has been found in gastric cancer [40], malignant melanoma [41], lung cancer [42], breast cancer [43] and a range of other human tumors [44]. GST-pi has been up-regulated in transitional cell carcinoma of human urinary bladder [45]. Up-regulation of glutathione – related genes and enzyme activities has been found in cultured human cells by sub lethal concentration of inorganic arsenic [46]. There is evidence that arsenic induces DNA damage via the production of ROS (reactive oxygen species) [47]. GST-pi may be over-expressed in the urinary bladder to protect cells against arsenic-induced oxidative stress. Liver In the livers of hamsters exposed to sodium arsenite, ornithine amino transferase was over-expressed, senescence marker protein 30 was under-expressed, and fatty acid binding protein was under-expressed. Ornithine amino transferase has been found in the mitochondria of many different mammalian tissues, especially liver, kidney, and small intestine [48]. Ornithine amino transferase knockdown inhuman cervical carcinoma and osteosarcoma cells by RNA interference blocks cell division and causes cell death [49]. It has been suggested that ornithine amino transferase has a role in regulating mitotic cell division and it is required for proper spindle assembly in human cancer cells [49]. Senescence marker protein-30 (SMP30) is a unique enzyme that hydrolyzes diisopropylphosphorofluoridate. SMP30, which is expressed mostly in the liver, protects cells against various injuries by stimulating membrane calcium-pump activity [50]. SMP30 acts to protect cells from apoptosis [51]. In addition it protects the liver from toxic agents [52]. The livers of SMP30 knockout mice accumulate phosphatidylethanolamine, cardiolipin, phosphatidyl-choline, phosphatidylserine, and sphingomyelin [53]. Liver fatty acid binding protein (L-FABP) also was down- regulated. Decreased liver fatty acid-binding capacity and altered liver lipid distribution hasbeen reported in mice lacking the L-FABP gene [54]. High levels of saturated, branched-chain fatty acids are deleterious to cells and animals, resulting in lipid accumulation and cytotoxicity. The expression of fatty acid binding proteins (including L-FABP) protected cells against branched-chain saturated fatty acid toxicity [55]. Limitations: we preferred to study the pronounced spots seen in DIGE gels. Other spots were visible but not as pronounced. Because of limited funds, we did not identify these others protein spots. In conclusion, urinary bladders of hamsters exposed to sodium arsenite had a decrease in the expression of transgelin and an increase in the expression of GST-pi protein. Under-expression of transgelin has been found in various cancer systems and may be associated with arsenic carcinogenicity [30-33). Inorganic arsenic exposure has resulted in bladder cancer as has been reported in the past [1]. Over-expression of GST-pi may protect cells against oxidative stress caused by arsenite. In the liver OAT was up regulated and SMP-30 and FABP were down regulated. These proteomic results may be of help to investigators studying arsenic carcinogenicity. The Superfund Basic Research Program NIEHS Grant Number ES 04940 from the National Institute of Environmental Health Sciences supported this work. Additional support for the mass spectrometry analyses was provided by grants from NIWHS ES06694, NCI CA023074 and the BIOS Institute of the University of Arizona. Acknowledgement The Author wants to dedicate this paper to the memory of his former supervisor Dr. H. VaskenAposhian who passed away in September 6, 2019. He was an emeritus professor of the Department of Molecular and Cellular Biology at the University of Arizona. 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In power industry due to fast industrialization the generation system has upswing towards strongly procuring energy from various non-conventional energy sources (RES). Persistent work is carried out in order to use additional energy obtained from the renewable sources and limiting the dependence on the conventional energy sources. The amalgamation of various Hybrid Renewable Energy Sources (HRES) i.e. Solar, Wind and Fuel cell including load forms a Micro grid, the realistic management of energy from these renewable sources to accommodate the demand at the consumer end with proper efficiency is necessary. This paper proposes a hybrid system comprising of three energy sources PV, Wind and Fuel Cell and is connected to the grid by using power electronic converters using MATLAB/SIMULINK. A control circuit is designed by using PI controller and fuzzy logic based controller for providing gate signals to the inverter. The voltage profile when connected to a load by using various controllers is studied. A comparison study and behavior of source voltage, source current, load voltage and load current is studied by using PI controller and fuzzy logic controller.

Renewable energy source (RES)-based electricity generating plants are expensive and complicated, requiring controls to deal with the energy input's intermittent renewables and fluctuation. If the grid interface of these devices is not monitored and maintained within the norms, it presents a problem of providing electricity to the utilities. Thus researchers have discusses several grid interface and control strategies for RES-based generators. This paper discusses the technique of improving power quality by using UPFC (Unified Power Flow Control) having PI controller.

Renewable energy source (RES)-based electricity generating plants are expensive and complicated, requiring controls to deal with the energy input's intermittent renewables and fluctuation. If the grid interface of these devices is not monitored and maintained within the norms, it presents a problem of providing electricity to the utilities. Thus researchers have discusses several grid interface and control strategies for RES-based generators. This paper discusses the technique of improving power quality by using UPFC (Unified Power Flow Control) having PI controller.

This paper bestows 3-phase grid interfaced solar-wind hybrid renewable energy system (RES), feeding three-phase loads. The proposed system includes solar photovoltaic, permanent magnet based synchronous generator (PMSG), DC-DC converter, maximum power point tracker (MPPT) based on incremental conductance, three phases IGBT based voltage source converter (VSC), with a third order generalized integrator (TOGI) control technique. This control technique bestows multifunctional capabilities as harmonic mitigations, load balancing, and reactive power compensation. A fundamental component of load current is extracted by TOGI based controller, and further it is utilized to provide switching pulses to VSC for power quality enrichment. The fuzzy logic-based controller is used for loss computation of VSC as well as for maintaining DC link voltage. Moreover, fuzzy logic provides better dynamic performance compared to conventional PI controller. The results are presented in many aspects for linear and nonlinear loads such as, intermittent nature of solar and wind as well as disturbances in the system. A comparative analysis between proposed TOGI based controller and conventional control algorithm has been presented. Test results are performed by using MATLAB/ Simulink environment and demonstrate, AC-grid current is maintained within the IEEE-519 standard.