Serum adenosine deaminase (ADA) activity was determined in 30 blood sample of type 1 diabetic individuals 30 blood sample for the type 2 and 15 normal children as a control for type 1 15 normal adults as control for type 2. The mean ADA activity and specific activity in type 1 was (8.85± 5.55 U/mg of protein) which is compared with control (32.11± 1.54 U/mg of protein) while in type 2 was (48.46±11.91 U/mg of protein) is compared with control (5.18± 2.27 U/mg of protein ). We conclude that the altered blood level of ADA activity may help in predicting immunological dysfunction in diabetic individuals and also has a prognostic value.

Arum maculatum is traditionally used for the control of many diseases and illnesses such as kidney pain, liver injury, hemorrhoids. However, the detailed biomedical knowledge about this species is still lacking. This study reports on the bioactive components and the possible mechanisms underlying the antioxidant, anti-inflammatory and cytotoxic activity of A. maculatum leaf extract. Gas chromatography-mass spectrometry (GC-MS) was used for phytochemical analysis. Assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide ) (MTT) was used to determine the cytotoxicity in the murine cell line L20B upon exposure to different extract concentrations for 24 h. Enzyme-linked immunosorbent assay (ELISA) was used to detect pro-in

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

The purpose of this research was to investigate the beneficial effects of phosphatidylcholine in reducing changes in both lipid and protein profiles in addition to atherogenic index in adult rats with fructose-induced metabolic syndrome. Thirty-six mature Wistar Albino female rats (Rattus norvegicus) (aged 12-15 weeks and weighing 200±10 g) were divided randomly into four groups (G1, G2, G3, and G4); then variable treatments were orally administered for 62 days as follows: G1 (Control group), received distilled water; G2, treated with phosphatidylcholine (PC) orally (1 g/kg BW); G3 (Fr), orally dosed with 40% fructose and 25% fructose mixed with drinking water; G4 (Fr+PC), were also intubated with 40% fr