Osteoporosis is related to the loss of bone mass that occurs as part of the natural process of aging and in menopausal women. The aim of this study is to evaluate the levels of interleukin-35 in menopausal women with osteoporosis, that may be used as an early predicted marker of osteoblastic and osteoclastic activity in osteoporosis patients in relation with other diagnostic parameters. Fasting blood samples were obtained from forty Iraqi menopausal women with mean age of (61.06±6.59)years who were newly diagnosed of osteoporosis by physicians at Baghdad Teaching Hospital as patients group(G1). In addition to , twenty two healthy women were included in the study as a control group(G2) with mean age(60.75±6.35). Serum samples were used for determination of Rheumatoid Factor (RF), Alkaline Phosphatase(ALP), Calcium(Ca+2), Phosphate(PO4-3) and Interleukin-35(IL-35),while blood sample was used for determination of Erythrocyte Sedimentation Rate (ESR). The results revealed a highly significant increase in IL-35 level in patients group(G1) compared to the control group(G2) while there are no significant differences in ALP, Ca+2 and PO4-3 levels between G1 and G2. The correlation between serum levels of IL-35 and ALP ,Ca+2 and PO4-3 in menopausal osteoporosis patients was calculated; A significant positive correlation between IL-35 and ALP was found (r=0.277,P<0.05), while there was no significant correlation between IL-35 and each of Ca+2 and PO4-3 levels (r=0.191,P>0.05),(r=0.124,P>0.05) respectively. The conclusion obtained from this study that IL-35 may be used as an additional biomarker in predicting osteoporosis in postmenopausal women.
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Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local
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Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and La
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Fifteen samples were collected from recent sediments grouping at 80 km east Samawa City, southern Iraq. Three selected samples for grain size analysis and twelve samples for chemical and biofacies analysis. Grain size analysis indicated that the sediment is mainly composed of the silt and clay with a small amount of sand. Most of the samples considered to be as clayey silt. The dominated non clay minerals are Quartz, Calcite, and Dolomite, while the clay minerals are composed of mixed Montmorillonite- Chlorite, Palygorskite, Illite and Kaolinite. Chemical analysis showed that all samples have high concentrations of SiO2 and CaO in comparison with Al2O3, MgO, Fe2O3, K2O and N2O. The identified fauna
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Luminescent solar concentrator (LSC) are used to enhance photoresponsivity of solar cell. The Quantumdots luminescent solar concentrator (QDLSC) consists of CdSe/CdS core/shell nanoparticles embedded in polyacrylamide polymer matrix positioned on the top surface of the silicon solar cell. This procedure improves the conversion efficiency of the bare silicon solar cell. The conversion efficiency of the solar cell has increased from 7.3% to 10.3%. this improvement is referred to the widening of the response spectral region window of the a- Si. Solar cell.
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In this work, monitoring of monthly variation (from May 2016 to October 2016) in the concentration of the metals (Co, Zn, Cd, Pb, Ni and Fe) from Al-Diwaniya city of Iraq. Investigation about the pollution with these metals was achieved from five selected sites locate in study area by flame atomic absorption spectroscopy. The results showed a wide variation in the levels of heavy metals from site to site and from month to month. A total of 180 surface soil samples were analyzed to detecting the pollution with selected samples. The resultsshowed that the highest concentration with Ni was 6.290 mg kg-1 while the lowest concentration detected with Ni was 0.080 mg kg-1. The results of pollution index (enrichment factor, contamination factor, po
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