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Association of Higher Defensin β-4 Genomic Copy Numbers with Behçet’s Disease in Iraqi Patients
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Publication Date
Sun Aug 01 2021
Journal Name
Biochemical And Cellular Archeves
ABILITY OF CRONOBACTER SAKAZAKII FOR ADHESION AND INVASION TO SKG-GT-4 CELL LINE
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ABSTRACT : Fifteenth isolates of C. sakazakii were obtained from previous studies of the sample (infant formula, cerebrospinal fluid and blood). All isolates C. sakazakii identification based on microscopic, biochemical test and confirmed by 16SrRNA. We studied the movement of all isolates and study adhesion to polystyrene plate, adhesion and invasion to Esophageal adenocarcinoma (SKG-GT-4) for four isolates [Cerebrospinal fluid (CSF5), Bloods (B 1), Dialak (A1c), Novolac Allernova (C1)] and its cytotoxicity. Results showed that all isolates can move after 4 hours of incubation and increased after 8 hours, the isolates moved to different distances strong, medium, and weak. The results showed that the number of C. sakazakii colony adherent t

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Publication Date
Tue Aug 05 2014
Journal Name
International Journal Of Engineering Sciences & Research Technology
Synthesis and Characterization of Some New Metal Complexes 2-(4-nitrophenyl azo)-2,4- dimethylphenol.
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The Ligand 2-(4-nitrophenyl azo)-2,4-dimethylphenol derived from 4-nitroaniline and 2,4-dimethylphenol was synthesized. The prepared ligand was identified by FT-IR and UV-Vis spectroscopic techniques. Treatment of the ligand with the following metal ions ( CuII , ZnII ,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio. Characterization of these compounds has been done on the basis of FT-IR and UV-Vis, as well as magnetic susceptibility and conductivity measurements. On the basis of physicochemical data tetrahedral geometries were assigned for the complexes.

Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Synthesis and Antibacterial Screening of New Schiff Bases Based on N-(4-acetophenyl) Succinimide
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A series of nine new Schiff bases based on N-(4-acetophenyl)succinimide were synthesized via multistep synthesis. In the first step N-(4-acetophenyl)succinamic acid was prepared via reaction of succinic anhydride with 4-aminoacetophenone. The prepared amic acid was dehydrated in the second step producing N-(4-acetophenyl)succinimide. The prepared succinimide represents a modified methyl ketone bearing succinimde cycle and ready for introducing in condensation reaction thus in the third step the prepared imide was introduced in acid-catalyzed condensation reaction with a variety of primary aromatic amines affording the new target Schiff bases. The results of antibacterial screening of the newly synthesized Schiff bases indicated that they

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Synthesis and Characterization of New Mannich Bases Derived from 7-hydroxy-4-methyl Coumarin
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Coumarin is a natural substance isolated from different plants. It belonges to a group of benzobyrones which consists of a benzene ring joined to a pyrone nucleus. In the present research, a new series of coumarin derivatives were formed. Compound (1) (7-hydroxy-4-methyl Coumarin) was converted into 4-methylquinolin-2(H) derivative (2) by reaction with acetamide, and then reaction of (2) with thiosemicarbazide in ethanol leads to the synthesize of hydrazincarbothioamide derivative (3).The reaction of (3) with ethylchloroacetate in presence of sodium acetate leads to closure ring to get [(1-(5-oxo-2-thioxoimidazolidin-1-ylimino) ethyl)]quinolin-2(1H)-one (4). Mannich bases were prepared through the reaction of (4) with primary

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
The Potential of some Plant Extracts as Radical Scavengers and Dipeptidyl Peptidase-4 Inhibitors
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Seeds, beans, leaves, fruit peel and seeds of five plants (Ferula assa-foetida, Coffea robusta, Olea europaea, Punica granatum and Vitis vinifera, respectively) were extracted with four solvents (distilled water, 80% methanol, 80% acetone and a mixed solvent that included methanol, ethanol, acetone and n-butanol at proportions 7:1:1:1). Such manipulation yielded 20 extracts, which were phytochemically analyzed for total polyphenols (TP) and flavonoids (TF). The DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity (RSA) and DPP-4 (dipeptidyl peptidase-4) relative inhibition activity (RIA) were also assessed for each extract. The results revealed that mixed solvent extract of V.

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Publication Date
Thu Oct 03 2024
Journal Name
Pharmacia
Synthesis and preliminary antimicrobial evaluation of new 7-amino-4-methyl-coumarin thiazolidinone conjugates
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Abstract As a part of our ongoing project on the design and synthesis of new 4-thiazolidinone derivatives with antimicrobial activity, four new 4-thiazolidinone derivatives carrying bromo, nitro, methyl, and chloro groups on the benzene ring were synthesized by starting with the 7-amino-4-methylcoumarin moiety, linking coumarin with various phenyl isothiocynate to form the thiourea group, and then cyclizing the derivatives, characterized by IR and 1HNMR, and assayed in vitro for their antimicrobial activity against Gram positive and Gram negative bacteria and fungi. Overall, 2-(4-methyl-2-oxo-2H-chromen-3-yl)-3-(4-nitrophenyl) thiazolidin-4-one to be the most powerful individuals in the series. Based on the observed data, it can be sta

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Publication Date
Thu May 05 2022
Journal Name
Alkindy College Medical Journal
Correlation between Body Mass Index and Nonalcoholic Fatty Liver Disease
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Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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Publication Date
Thu May 05 2022
Journal Name
Al-kindy College Medical Journal
Correlation between Body Mass Index and Nonalcoholic Fatty Liver Disease
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Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.

Objectives: To assess age, sex, and body

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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