Type 2 diabetes mellitus(T2DM) is a metabolic disease that is associated with an increased risk for atherosclerosis by 2-4 folds than in non- diabetics. In general population, low IGF-1 has been associated with higher prevalence of cardiovascular disease and mortality .This study aims to find out the relationship between IGF-1 level and other biochemical markers such as Homeostasis Model Assessment insulin resistance(HOMAIR) and Body Mass Index(BMI) in type 2 diabetic patients . This study includes (82) patients (40 females and 42 males) with age range (40-75) years,(34) non obese diabetic patients and (48) obese diabetic patients. The non obese individuals considered as a controls group, all controls and patients groups with type 2 DM, ischemic heart disease and hypertension, and free from other disease by history and clinical exam .The results showed that serum IGF-1 levels were lower in obese diabetic patients than non obese.HOMAIR has been found to be significantly higher in obese than non obese diabetic patients ,there is negative correlation between IGF-1 and HOMAIR. Body mass index (BMI) was in positive correlation with HOMAIR and innegativecorrelationwithIGF-1. Conclusion of this study was the serum level of IGF-1 is significantly lower in obese than non obese type 2 DM , but HOMA IR is significantly higher in obese diabetic subjects .
Double hydrothermal method was used to prepare nano gamma alumina using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, CTAB (cetyltrimethylammonium bromide) as surfactant, and variable acids: weak acids like; citric, and acitic acids, and strong acids like; hydrochloric and nitric acids as a bridge between aluminum salts and surfactant. Different crystallization times 12, 24, 48, and 72 hrs were applied. All the batches were prepared at pH equals to 9. XRD diffraction technique was used to investigate the crystalline nano gamma alumina pure from surfactant. N2 adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the average p
... Show MoreThe (E)-4-chloro-N-(2-(dimethylamino)ethyl)-5-((8-hydroxy quinolin-5-yl)diazenyl)-2-methoxybenzamide azo ligand (L) has been synthesized through the reaction of diazonium salt for 5-amino-4-chloro-N-(2-(dimethylamino) ethyl)-2-methoxybenzamide with 8-hydroxyquinoline and identified azo ligand (L) using spectroscopic studies (FTIR, UV-Vis, 1H and 13CNMR, mass), and micro-elemental analysis (C.H.N). Metal chelates of Co(II), Ni(II), Cu(II), as well as Zn(II) have been completed as well as characterized using mass spectra, flame atomic absorption, elemental analysis (C.H.N), infrared, UV-Vis spectroscopy, as well as conductivity, magnetic measurements. The metal-to-ligand ratio in all complexes, as determined by analytical data, was 1:2 and ex
... Show MoreTwo dwarf snakes were discovered, Eirenis thospitis Schmidtler & Lanza from Sereen mountain, north east of Arbil and E. rothii Jan from Saffin mountain North of Arbil city North of Iraqi Kurdistan. Supported by description and important notes on variation. In addition summarized list for 9 species of the genus Eirenis Jan in Iraq is also presented.
KE Sharquie, AA Noaimi, AA Zeena, IOSR J Dent Med Sci, 2015 - Cited by 5
New series of imidazole[1,2-a]pyridine-sulfonamides was designed and synthesized from 2-aminopyridine, which was reacted with p-bromo phenacyl bromide in the present of MgO to produce the corresponding imidazole[1,2-a]pyridine, which was then reacted with chlorosulfonic acid to produce 2-(4-bromophenyl)imidazole[1,2-a]pyridine-3-sulfonyl chloride [2]. Following that, treatment of (2) with different amines using the grand method to generate imidazole [1,2-a] pyridine sulfonamides. All the synthesized compounds have been characterized by FTIR, 1HNMR and 13CNMR and C.H.N analysis. The DFT, POM analysis and molecular docking were carried out on for all final compounds to investigate drug like attributes, and the results revealed showed that the
... Show MoreThe current study aimed to assess the biological efficacy of the triple arbuscular mycorrhiza (AM) mixture of fungi Glomus etunicatum, G. leptotichum and Rhizophagus intraradices, and mix it with organic matter (O) and pathogenic fungi Fusarium oxysporum f.sp.lycopersici by using voyeurism in the plastic house in the growth of the tomato plant after four and eight weeks of cultivation. The results were shown after the treatment of the tomato plant in agriculture with the mixture of mycorrhiza and the pathogenic fungi and organic matter were treated with the mixture of mycorrhiza, organic matter and pathogenic fungi together. The effect of mycorrhiza and organic matter interference on the increase in the percentage of the lignin afte
... Show MoreBackground: In December 2019, an episode of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV2) was reported in Wuhan, China and has spread around the world, increasing the number of contagions. Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are common herpesviruses that can cause persistent latent infections and affect the developing immune system.The study was conducted to explore the prevalence and reactivation of CMV and EBV antibodies in COVID-19 patients group in comparison to healthy group and to investigate the association between the presence of these viruses with each of severity of disease and oral hygiene. Materials and Methods: Eighty Five subjects were participated in this case control study (5
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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