The result showed that hot water and ethanol extracts of Nigella sativa contain alkaloids ,saponins, flavonoids,tannins,glycosides,terpins and steroids. Albino mice were administered orally with 0.1 of the extract at dose of 100 mg/kg, body weight the results showed high level of white blood cell ,total and differential count of WBC,phagocytosis index, mitotic index, Arthus and delayed type hypersensitivity. The result, also showed high level of hemoglobin (Hb) and the packed cell volume (PCV) the alcoholic extract has been found more efficient than hot water extract on mice.

The present study utilised date palm fibre (DPF) waste residues to adsorb Congo red (CR) dye from aqueous solutions. The features of the adsorbent, such as its surface shape, pore size, and chemical properties, were assessed with X-ray diffraction (XRD), BET, Fourier-transform infrared (FTIR), X-ray fluorescence (XRF), and field emission scanning electron microscope (FESEM). The current study employed the batch system to investigate the ideal pH to adsorb the CR dye and found that acidic pH decolourised the dye best. Extending the dye-DPF waste mixing period at 25°C reportedly removed more dye. Consequently, the influence of the starting dye and DPF waste quantity on dye removal was explored in this study. At 5 g/L dye concentration, 48% d

T-cell activation and alteration of cytokine levels are involved in the pathogenesis of asthma. However, the profile of circulating T-lymphocyte subsets and related cytokines during asthmatic attacks is still unclear. We compared the serum concentrations of proinflammatory cytokines Interleukine-18( IL-18) and Interleukine-12(IL-12), T-helper 2 (Th2) cytokine Interleukine-13(IL-13 ) and Immunoglobuline-E ( IgE) in 27 asthmatic children and 21 sex and age matched healthy control subjects. Serum cytokines and IgE concentrations were measured by enzyme-linked immunosorbent assay. Serum IL-13 , IL-18 and IgE concentrations were significantly higher in asthmatic patients than normal control subjects ( IL-13: median 9.73 versus 4.43 pg/ml, P&l

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s