Expression of the leukocyte-associated ig-like receptor-1 on B lymphocytes from systemic lupus erythematosus patients

Background The leukocyte-associated immunoglobulin (Ig)-like receptor-1 (LAIR-1) is a transmembrane molecule belonging to the Ig superfamily. In B cells, LAIR-1 cross-linking leads to downregulation of Ig and cytokine production. Aim of the work The aim of the present study was to assess the expression of LAIR-1 on peripheral blood B lymphocyte from systemic lupus erythematosus (SLE) patients, and its correlation with disease manifestations. Patients and methods Twenty-two SLE female patients and 16 matched healthy controls were included in the study. Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score was assessed. The expression of LAIR-1 was determined by using flow cytometry. Results The 22 SLE patients had a mean age of 25.59±4.22 years and disease duration of 5–24 months. The mean SLEDAI was 8±1.5. The percentage of CD19+ B lymphocytes lacking LAIR-1 was markedly increased in SLE patients (27.8±10.9%) compared with healthy controls (16.2±4.4%) (P<0.001). The mean fluorescent intensity ratio (MFIR) of LAIR-1 expression on CD19+ B cells was strongly decreased in SLE patients (44.1±12.6) compared with healthy controls (58.9±7.7) (P<0.001). The percentage of CD19+ LAIR-1− B cells significantly correlated with the complement (C4) (r=0.45, P=0.03) and the serum creatinine level (r=0.47, P=0.02), and negatively with the serum albumin level (r=−0.57, P=0.005). The MFIR of LAIR-1 significantly correlated with the serum albumin level (r=0.74, P<0.001) and negatively correlated with the serum creatinine level (r=−0.43, P=0.041). There was no significant association of LAIR− (%) or the MFIR with the clinical manifestations of the patients. Conclusion This study points out that the lack of LAIR-1 expression on B cells from SLE patients could be a trigger for the dysregulation of antibody production in SLE, and is associated with the degree of renal affection as evidenced by the significant correlation with serum creatinine levels and negative correlation with the levels of serum albumin

Operation of Grid-Connected PV System With ANN-Based MPPT and an Optimized LCL Filter Using GRG Algorithm for Enhanced Power Quality

The expanding use of photovoltaics (PV) as a green energy resource has been rising in these years, mostly due to the possibility of being incorporated with traditional power systems, to meet the world&#x2019;s energy needs and reduce carbon emissions. However, providing green electricity from this renewable generator is frequently vulnerable to power quality (PQ) disruptions resulting from the PV&#x2019;s intermittent nature and other factors associated with the electric grid, power converters, and linked loads. These disruptions need to be reduced to keep the investigated system&#x2019;s PQ from deteriorating. The investigated system includes PV, DC-DC, and DC-AC converters, filter, power grid, and control schemes. If the DC-DC converter is not managed, a deviation from the maximum power point (MPP) extrapolated from the PV system will take place. In order to maximize the energy harvested from the PV system by managing the DC-DC converter, this research developed two MPP tracking (MPPT) algorithms: artificial neural networks (ANN) and cuckoo search (CS). Additionally, a design and implementation for a shunt active power filter (LCL) using genetic algorithm and GRG is provided to lower the injected total harmonic distortion (THD) and thereby enhance the PQ. To achieve the smallest size of the LCL components, the generalized reduced gradient (GRG) was the best compared to genetic algorithms GA. The results of the simulation showed that ANN performed better at tracking maximum power than CS. With the designed LCL, the THD is reduced by 99.78&#x0025; compared to without a filter. To verify the simulation&#x2019;s findings, a practical configuration is implemented