The aim of this study is to determine the organic and inorganic components of bile and gallstones in Iraqi patients. Forty seven patients were included in this study with mean age (53+7) years and BMI (30.82+4.18) Kg/m2. Bile was classified according to its corresponding stones into: Bile of Mixed stones and Bile of pigment stones. IR spectra were studied for both types of stones and their bile in addition to biochemical analysis for organic and inorganic components. The organic components include: (cholesterol, bilirubin, bile salts, and phospholipids), while inorganic components include salts of: (calcium, phosphorus, iron, cupper and magnesium). The results reveal to there was significant low levels (p<0.005) of bile salts and phospholipids in bile of patients with mixed stones in comparison to their levels in bile of pigment stones ( p<0.001). There is significant increase in the salts levels of calcium, phosphorus, iron, cupper, magnesium, and bilirubin, in bile of pigment stones as compared to their levels in mixed stones bile. It was concluded that most types of stones that are formed in Iraqi patients are mixed stones when cholesterol is the main component and pigment stones are more less incidence to occur when bilirubin salts form their main component and they are mostly tend to occur in hemolytic diseases such as: sickle cell anemia, thalassaemia and so on .
Case Report.
To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.
A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli
In solar-thermal adsorption/desorption processes, it is not always possible to preserve equal operating times for the adsorption/desorption modes due to the fluctuating supply nature of the source which largely affects the system’s operating conditions. This paper seeks to examine the impact of adopting unequal adsorption/desorption times on the entire cooling performance of solar adsorption systems. A cooling system with silica gel–water as adsorbent-adsorbate pair has been built and tested under the climatic condition of Iraq. A mathematical model has been established to predict the system performance, and the results are successfully validated via the experimental findings. The results show that, the system can be operational
... Show MoreFG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2
The data presented in this paper are related to the research article entitled “Novel dichloro(bis{2-[1-(4-methylphenyl)-1H-1,2,3-triazol-4-yl-κN3 ]pyridine-κN})metal(II) coordination compounds of seven transition metals (Mn, Fe, Co, Ni, Cu, Zn and Cd)” (Conradie et al., 2018) [1]. This paper presents characterization and structural data of the 2-(1-(4-methyl-phenyl)-1H-1,2,3-triazol-1-yl)pyridine ligand (L2 ) (Tawfiq et al., 2014) [2] as well as seven dichloro(bis{2- [1-(4-methylphenyl)-1H-1,2,3-triazol-4-yl-κN3 ]pyridine-κN})metal (II) coordination compounds, [M(L2 )2Cl2], all containing the same ligand but coordinated to different metal ions. The data illustrate the shift in IR, UV/VIS, and NMR (for diamagnetic complexes) peaks wh
... Show MoreThe meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
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