Protective effect of Garcinia against renal oxidative stress and biomarkers induced by high fat and sucrose diet

<p>Abstract</p> <p>Background</p> <p>Obesity became major health problem in the world, the objective of this work was to examine the effect of high sucrose and high fat diet to induce obesity on antioxidant defense system, biochemical changes in blood and tissue of control, non treated and treated groups by administration of Garcinia cambogia, and explore the mechanisms that link obesity with altered renal function</p> <p>Methods</p> <p>Rats were fed a standard control diet for 12 week (wk) or a diet containing 65% high sucrose (HSD) or 35% fat (HFD) for 8 wk and then HFD group divided into two groups for the following 4 wks. One group was given <it>Garcinia</it>+HFD, the second only high fat, Also the HSD divided into two groups, 1^stHSD+<it>Garcinia </it>and 2^ndHSD. Blood and renal, mesenteric, Perirenal and epididymal adipose tissues were collected for biochemical assays.</p> <p>Results</p> <p>HFD and HSD groups of rats showed a significant increase in feed intake, Body weight (BW) and body mass index (BMI). Also there were significant increases in weights of mesenteric, Perirenal and epididymal adipose tissues in HFD and HSD groups.</p> <p>HFD and HSD affect the kidney by increasing serum urea and creatinine levels and decreased level of nitric oxide (NO) and increased blood glucose, low density lipoproteins (LDL), triacylglycerol (TG), total cholesterol (TC) and malondialdehyde (MDA). Glucose 6-phosphate dehydrogenase (G6PD) activities were significantly decreased in HFD while there were significant increases in HSD and HSD+G groups p ≤ 0.05 compared with control. Moreover, renal catalase activities and MDA levels were significantly increased while NO level was lowered. These changes improved by <it>Garcinia </it>that decreased the oxidative stress biomarkers and increased NO level.</p> <p>There were significant positive correlations among BMI, kidney functions (Creatinine and urea), TG and Oxidative markers (renal MDA and catalase).</p> <p>Conclusions</p> <p>Rats fed a diet with HFD or HSD showed, hypertriglyceridemia, increased LDL production, increased oxidative stress and renal alteration. Moreover, suggesting association between lipid peroxidation, obesity and nephropathy, while <it>Garcinia </it>ameliorated the damaging effects of the HFD or HSD and decreased feed intake, MDA level and decreased oxidative stress in renal tissues.</p

The relation of high fat diet, metabolic disturbances and brain oxidative dysfunction: modulation by hydroxy citric acid

<p>Abstract</p> <p>Aims</p> <p>This study aimed to examine the effect of high fat diet (HFD) to modulate brain dysfunction, and understand the linkages between obesity, metabolic disturbances and the brain oxidative stress (BOS) dysfunction and modulation with hydroxyl citric acid of <it>G. Cambogia</it>.</p> <p>Methods</p> <p>Rats were divided into 3 groups; 1^stcontrol, maintained on standard normal rat chow diet, 2^ndHFD, maintained on high fat diet along 12 week and 3^rdHFD+G, administered <it>G. Cambogia </it>for 4 weeks and each group include 8 rats. Blood, brain and abdominal fat were collected for biochemical measurements.</p> <p>Results</p> <p>HFD group showed significant increase in energy intake, final BW and BW gain. Also significant increase in weight of abdominal fat in HFD group. HFD induce metabolic disturbance through increasing the lipid profile (LDL, TG, TC), γGT and α-amylase activity, uric acid level and hyperglycemia, while decreasing creatine kinase (CK) activity.</p> <p>These changes associated with lowering in brain nitric oxide (NO) level and rising in serum butyrylcholinesterase (BChE), brain catalase activity and MDA levels as oxidative stress markers. These alterations improved by <it>G. Cambogia </it>that decrease BOS and increased NO level.</p> <p>Conclusions</p> <p>Rats fed HFD showed, metabolic disturbances produce hyperglycemia, hypertriglyceridemia, hypercholesterolemia and increased LDL associated with increased BOS. Involvement of BuChE, NO and oxidative stress associated with metabolic disturbances in the pathophysiological progression in brain, suggesting association between obesity, metabolic disorders and brain alteration while, using <it>G. Cambogia</it>, ameliorate the damaging effects of the HFD via lowering feed intake and BOS.</p

Sinteza, protuupalno, analgetsko i antikonvulzivno djelovanje 1,8-dihidro-1-aril-8-alkil pirazolo(3,4-b)indola

A series of 1,8-dihydro-1-aryl-8-alkyl pyrazolo(3,4-b)indoles 4a-j, 5a-j and 6a-j has been synthesized and tested for their anti-inflammatory and anticonvulsant activities. Formation of the pyrazoloindole derivatives was achieved by treating arylhydrazones of N-alkyl indole-3-carboxaldehydes 1a-j, 2a-j and 3a-j with ten times their mass of polyphosphoric acid as a condensing agent. The newly synthesized compounds were evaluated for their anti-inflammatory, analgesic and anticonvulsant activities compared to indomethacin, flufenamic acid and diazepam as positive controls. Detailed synthesis, spectroscopic and toxicity data are reported.Serija 1,8-dihidro-1-aril-8-alkil pirazolo(3,4-b)indola 4a-j, 5a-j i 6a-j sintetizirana je i testirana na protuupalno i antikonvulzivno djelovanje. Pirazolindol derivati pripravljeni su reakcijom arilhidrazona N-alkil indol-3-karboksaldehida 1a-j, 2a-j i 3a-j s deset puta većom masom polifosforne kiseline kao sredstva za kondenzaciju. Novosintetizirani spojevi testirani su na protuupalno, analgetsko i antikonvulzivno djelovanje i uspoređeni s djelovanjem indometacina, flufenaminske kiseline i diazepama. U radu su dati detaljni sintetski, spektroskopski i toksikološki podaci

Robust Parameters Tuning of Different Power System Stabilizers Using a Quantum Artificial Gorilla Troops Optimizer

Electrical power system abnormalities may have several negative consequences on its stable operation. As a result, preserving its stability under such operational states has become an ongoing challenge for power engineers. PSSs are created as auxiliary controllers to address the instability issues produced upon disturbances. They dampen the oscillations induced by the disturbances by giving the system the necessary damping torque. This research aims at presenting a comprehensive study for the optimum tuning of power system stabilizer (PSS) of different structures. This aim is accomplished with the help of a novel modified optimization algorithm called Quantum Artificial Gorilla Troops Optimizer. The modified optimizer\u27s validation is first investigated with the well-known benchmark optimization functions and shows superiority over Gorilla Troops Optimizer and competitive algorithms. The research is extended to the application of the optimum tuning of various PSS structures of the single machine to the infinite bus model. The proposed optimization algorithm shows fast convergence over investigated optimization algorithms. Moreover, the Tilt-integral-derivative based PSS shows better performance characteristics in terms of lower settling time and lower maximum and undershoot values over the conventional lead-lag PSS, dual input PSS, and fractional-order proportional-integral-derivative based PSS

Detection and tracking of discrete phenomena in sensor-network databases

This paper introduces a framework for Phenomena Detection and Tracking (PDT, for short) in sensor network databases. Examples of detectable phenomena include the propagation over time of a pollution cloud or an oil spill region. We provide a crisp definition of a phenomenon that takes into consideration both the strength and the time span of the phenomenon.We focus on discrete phenomena where sensor readings are drawn from a discrete set of values, e.g., item numbers or pollutant IDs, and we point out how our work can be extended to handle continuous phenomena. The challenge for the proposed PDT framework is to detect as much phenomena as possible, given the large number of sensors, the overall high arrival rates of sensor data, and the limited system resources. Our proposed PDT framework uses continuous SQL queries to detect and track phenomena. Execution of these continuous queries is performed in three phases; the joining phase, the candidate selection phase, and the grouping/output phase. The joining phase employs an in-memory multi-way join algorithm that produces a set of sensor pairs with similar readings. The candidate selection phase filters the output of the joining phase to select candidate join pairs, with enough strength and time span, as specified by the phenomenon definition. The grouping/ output phase constructs the overall phenomenon from the candidate join pairs. We introduce two optimizations to increase the likelihood of phenomena detection while using less system resources. Experimental studies illustrate the performance gains of both the proposed PDT framework and the proposed optimizations

An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks

This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system’s voltage profile and energy losses. DG penetration in the power systems is one approach that has several advantages such as peak savings, loss lessening, voltage profile amelioration. It also intends to increase system reliability, stability, and security. The main goal of optimal distributed generation (ODG) is a guarantee to achieve the benefits mentioned previously to increase the overall system efficiency. For extremely vast and complicated systems, analytical approaches are not suitable and insufficient. Therefore, several meta-heuristic techniques are favored to obtain better performance from were convergence and accuracy for large systems. In this paper, an Improved Wild Horse Optimization algorithm (IWHO) is proposed as a novel metaheuristic method for solving optimization issues in electrical power systems. IWHO is devised with inspirations from the social life behavior of wild horses. The suggested method is based on the horse’s decency. To assess the efficacy of the IWHO, it is implemented on the 23 benchmark functions Reliability amelioration is the most things superb as a result of DGs incorporation. Thus, in this research, a customer-side reliability appraisal in the DS that having a DG unit was carried out by a Monte Carlo Simulation (MCS) approach to construct an artificial history for each ingredient across simulation duration. For load flow calculations, the backward Forward Sweep (BFS) technique has been employed as a simulation tool to assess the network performance considering the power handling restrictions. The proposed IWHO method has been measured on IEEE 33 69 and 119 buses to ascertain the network performing in the presence of the optimal DG and the potential benefits of the suggested technique for enhancing the tools used by operators and planners to maintain the system reliability and efficiency. The results proved that IWHO is an optimization method with lofty performance regarding the exploration–exploitation balance and convergence speed, as it successfully handles complicated problems

Similar and Additive Effects of Ovariectomy and Diabetes on Insulin Resistance and Lipid Metabolism

Type 2 diabetes mellitus (T2DM) is among the leading causes of death in postmenopausal women. The disruption of ovarian function may contribute to the incidence of T2DM. The purpose of this study was to investigate the effects of ovariectomy and T2DM on glucose and lipid homeostasis, perilipin levels in adipose tissues, as a lipolytic regulator, and levels of certain adipokines. Ovariectomized (OVX) rats were used as a model for postmenopausal women. The study was performed on sham, OVX, sham diabetic, and OVX diabetic female rats. The results indicated that ovariectomy alters adipose tissue metabolism through reducing perilipin content in white adipose tissue (WAT); however it has no effect on perilipin level in brown adipose tissue (BAT). OVX diabetic females suffer from serious metabolic disturbances, suggested by exacerbation of insulin resistance in terms of disrupted lipid profile, higher HOMA-IR, hyperinsulinemia, higher leptin, and lower adiponectin concentrations. These metabolic derangements may underlie the predisposition for cardiovascular disease in women after menopause. Therefore, for efficient treatment, the menopausal status of diabetic female should be addressed, and the order of events is of great importance because ovariectomy following development of diabetes has more serious complications compared to development of diabetes as result of menopause

Hierarchical distributed framework for optimal dynamic load management of electric vehicles with vehicle-to-grid technology

The tendency towards carbon dioxide reduction greatly stimulates the popularity of electric vehicles against conventional vehicles. However, electric vehicle chargers represent a huge electric burden, which affects the performance and stability of the grid. Various optimization methodologies have been proposed in literature to enhance the performance of the distribution grids. However, existing techniques handle the raised issues from individual perspectives and/or with limited scopes. Therefore, this paper aims to develop a distributed controller-based coordination scheme in both medium and low voltage networks to handle the electric vehicles’ charging impact on the power grid. The scope of this work covers improving the network voltage profile, reducing the total active and reactive power, reducing the load fluctuations and total charging cost, while taking into consideration the random arrivals/departures of electric vehicles and the vehicle owners’ preferred charging time zones with vehicle-to-grid technology. Simulations are carried out to prove the success of the proposed method in improving the performance of IEEE 31-bus 23 kV system with several 415 V residential feeders. Additionally, the proposed method is validated using Controller Hardware-in-the-Loop. The results show that the proposed method can significantly reduce the issues that appear in the electric power grid during charging with minor changes in the existing grid. The results prove the successful implementation of different types of charging, namely, ultra-fast, fast, moderate, normal and vehicle-to-grid charging with minimum charging cost to enhance the owner’s satisfaction level

The mR scheme to the shallow water equation with horizontal density gradients in one and two dimensions

In this work, we consider the model of shallow water equation with horizontal density gradients. We develop the modified Rusanov (mR) scheme to solve this model in one and two dimensions. Predictor and corrector are the two stages of the suggested scheme. The predictor stage is dependent on a local parameter $(\alpha^n_{i+\frac{1}{2}})$ that allows for diffusion control. The balance conservation equation is recovered in the corrector stage. The proposed approach is well-balanced, conservative, and straightforward. Several 1D and 2D test cases are produced after presenting the shallow water model and the numerical technique. In the 1D case, we compared the proposed scheme with the Rusanov scheme, mR with constant $\alpha$ and analytical solutions. The numerical simulation demonstrates the mR's great resolution and attests to its capacity to produce accurate simulations of the shallow water equation with horizontal density gradients. Our results demonstrate that the mR technique is a highly effective instrument for solving a variety of equations in applied science and developed physics

An efficient electric charged particles optimization algorithm for numerical optimization and optimal estimation of photovoltaic models

The electric charged particles optimization (ECPO) technique is inspired by the interaction (exerted forces) between electrically charged particles. A developed version of ECPO called MECPO is suggested in this article to enhance the capability of searching and balancing the exploitation and exploration phases of the conventional ECPO. To let the search agent jumps out from the local optimum and avoid stagnation in the local optimum in the proposed MECPO, three different strategies in the interaction between ECPs are modified in conjunction with the conventional ECPO. Therefore, the convergence rate is enhanced and reaches rapidly to the optimal solution. To evaluate the effectiveness of the MECPO, it is executed on the test functions of the CEC’17. Furthermore, the MECPO technique is suggested to estimate the parameters of different photovoltaic models, such as the single-diode model (SDM), the double-diode model (DDM), and the triple-diode model (TDM). The simulation results illustrate the validation and effectiveness of MECPO in extracting parameters from photovoltaic models