Serum interferon-alpha level in first degree relatives of systemic lupus erythematosus patients: Correlation with autoantibodies titers

AbstractBackground and objectivesInterferon-α (IFN-α), a cytokine with both antiviral and immune-regulatory functions, was suggested as a useful tool which can evaluate current systemic lupus erythematosus (SLE) disease activity and identify patients who are at risk of future disease flares. In the current study, serum IFN-α levels and associated demographic, and serological features in Egyptian SLE patients and their first degree relatives (FDRs) in comparison to unrelated healthy controls (UHCs) were examined, in order to identify individuals at the greatest risk for clinical illness.MethodsIn a cross-sectional study, blood samples were drawn from 54 SLE patients, 93 of their FDRs who consented to enroll into the study and 76 UHCs. Measurement of serum IFN-α by a modified ELISA was carried out. Data were analyzed for associations of serum IFN-α levels with autoantibodies titer.ResultsMean serum IFN-α in FDRs was statistically higher than the UHCs and lower than in SLE patients (P<0.0001) and it was correlated with ANA titer (r=0.6, P<0.0001) and anti ds DNA titer (r=0.62, P<0.0001).ConclusionIFN-α is a crucial player in the complicated autoimmune changes that occur in SLE and serum IFN-α can be a useful marker identifying persons who are at risk of future disease development

Artificial immune system based neural networks for solving multi-objective programming problems

In this paper, a hybrid artificial intelligent approach based on the clonal selection principle of artificial immune system (AIS) and neural networks is proposed to solve multi-objective programming problems. Due to the sensitivity to the initial values of initial population of antibodies (Ab’s), neural networks is used to initialize the boundary of the antibodies for AIS to guarantee that all the initial population of Ab’s is feasible. The proposed approach uses dominance principle and feasibility to identify solutions that deserve to be cloned, and uses two types of mutation: uniform mutation is applied to the clones produced and non-uniform mutation is applied to the “not so good” antibodies. A secondary (or external) population that stores the nondominated solutions found along the search process is used. Such secondary population constitutes the elitist mechanism of our approach and it allows it to move towards the Pareto front

Chaotic Search-Based Salp Swarm Algorithm for Dealing with System of Nonlinear Equations and Power System Applications

The system of nonlinear equations (SNLEs) is one of the eminent problems in science and engineering, and it is still open to research. A new hybrid intelligent algorithm is presented in this research to solve SNLEs. It is a composite of the salp swarm algorithm (SSA) and chaotic search technique (CST). The proposed methodology is named chaotic salp swarm algorithm (CSSA). CSSA is designed as an optimization process, whereby feasible and infeasible solutions are updated to move closer to the optimum value. The use of this hybrid intelligent methodology aims to improve performance, increase solution versatility, avoid the local optima trap, speed up convergence and optimize the search process. Firstly, SNLEs are transformed into an optimization problem. Secondly, CSSA is used to solve this optimization problem: SSA is used to update the feasible solutions, whereas the infeasible solutions are updated by CST. One of the most significant advantages of the suggested technique is that it does not ignore infeasible solutions that are updated, because these solutions are often extremely near to the optimal solution, resulting in increased search effectiveness and effective exploration and exploitation. The algorithm&rsquo;s mathematical model is presented in detail. Finally, the proposed approach is assessed with several benchmark problems and real-world applications. Simulation results show that the proposed CSSA is competitive and better in comparison to others, which illustrates the effectiveness of the proposed algorithm. In addition, a statistical analysis by the Wilcoxon rankings test between CSSA and the other comparison methods shows that all p-values are less than 0.05, and CSSA achieves negative ranks&rsquo; sum values (R&minus;) much better than the positive ranks&rsquo; sum values (R+) in all benchmark problems. In addition, the results have high precision and show good agreement in comparison with similar methods, and they further proved the ability of CSSA to solve real-world applications

Chaotic Search-Based Salp Swarm Algorithm for Dealing with System of Nonlinear Equations and Power System Applications

The system of nonlinear equations (SNLEs) is one of the eminent problems in science and engineering, and it is still open to research. A new hybrid intelligent algorithm is presented in this research to solve SNLEs. It is a composite of the salp swarm algorithm (SSA) and chaotic search technique (CST). The proposed methodology is named chaotic salp swarm algorithm (CSSA). CSSA is designed as an optimization process, whereby feasible and infeasible solutions are updated to move closer to the optimum value. The use of this hybrid intelligent methodology aims to improve performance, increase solution versatility, avoid the local optima trap, speed up convergence and optimize the search process. Firstly, SNLEs are transformed into an optimization problem. Secondly, CSSA is used to solve this optimization problem: SSA is used to update the feasible solutions, whereas the infeasible solutions are updated by CST. One of the most significant advantages of the suggested technique is that it does not ignore infeasible solutions that are updated, because these solutions are often extremely near to the optimal solution, resulting in increased search effectiveness and effective exploration and exploitation. The algorithm’s mathematical model is presented in detail. Finally, the proposed approach is assessed with several benchmark problems and real-world applications. Simulation results show that the proposed CSSA is competitive and better in comparison to others, which illustrates the effectiveness of the proposed algorithm. In addition, a statistical analysis by the Wilcoxon rankings test between CSSA and the other comparison methods shows that all p-values are less than 0.05, and CSSA achieves negative ranks’ sum values (R−) much better than the positive ranks’ sum values (R+) in all benchmark problems. In addition, the results have high precision and show good agreement in comparison with similar methods, and they further proved the ability of CSSA to solve real-world applications

Phosphogypsum and poultry manure enhance diversity of soil fauna, soil fertility, and barley (Hordeum aestivum L.) grown in calcareous soils

Abstract Enrichment of calcareous soils with phosphogypsum and poultry manure amendments could increase nutrient availability, improve calcareous chemical characteristics, and enhance barley plant growth. In the current study, phosphogypsum (PG) and poultry manure (PM) were used to determine the effects of PG and PM application on soil fauna diversity, soil fertility, and barley yield. The pot experiment treatments were: C: control; PG1: 4.20 g kg−1 soil; PG2: 6.30 g kg−1 soil; PM1: 4.20 g kg−1 soil; PM: 6.30 g kg−1 soil, and their combinations. The results indicated that the application of PM alone or combined with PG had significant effects on the microbial biomass carbon (MBC), organic matter (OM), soil NPK availability, and yield of barley. Collembola and Prostigmata accounted for 50.0 and 43.3%, respectively, of the total number of soil fauna. Shannon and evenness indices increased significantly in the soil amended with PM alone or combined with PG. Amended soil with PG and/or PM significantly increased the yield and yield components of plants compared to the control. The PM1PG2 treatment increased the yield by 76.2% above the control

Heat transfer analysis on ferrofluid natural convection system with magnetic field

Free convection of Fe3O4-water inside the porous enclosure was investigated in the presence of magnetic fields. The SIMPLE algorithm was employed to solve the equations based on FVM. The inner wall of enclosure was considered in the constant flux and that of outer wall were at a constant temperature, respectively. Also, two other walls are thermal insulation and the radiation reflects to inner semi-annulus. An electric current coil for producing a magnetic field is wrapped around the semi-annulus. The effects of Rap=10and1000, the concentration (φAve=0,0.01and0.03), porosities (ε=0.4and0.7) and magnetic numbers (0≤Mn≤8×107) are investigated considering first laws of thermodynamics. The findings revealed that the mean Nusselt number has direct relation with the magnetic number, porosity, Rap and concentration, respectively. Moreover, increasing volume fraction from 0.01 to 0.03 in high magnetic number enhanced the Nusselt number by 32 %