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The Impact of Chronic Periodontitis on Mother-Infant Bonding Status in Relation to Salivary Tumor Necrosis Factor Alpha and Interleukin-6
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Background: Chronic periodontitis is a bacterial infection that result in bone destruction associated with the increasing level of salivary tumor necrosis alpha and interleukin6 that affect Mother-infant bonding status. The aim of the present study was to assess the relationship between the Mother-infant bonding status in mothers with chronic periodontitis in relation to Salivary Tumor necrosis factor alpha and Salivary Interleukin6. Materials and Methods: The selected sample consisted of mothers with chronic periodontitis compared with mothers with healthy periodontium in postpartum period, their age ranged between 30-40 years. Both groups were subjected to postpartum Bonding Questionnaire (PBQ). Periodontal health status was assessed for control group like plaque index and gingival index in order to obtain control group with healthy periodontium, while measuring probing pocket depth and clinical attachment level in addition to plaque and gingival index for study group. Salivary Tumor necrosis factor alpha and Interleukin6 measure in saliva by enzyme-linked immune sorbent assay (ELISA). Results: The mean values of Salivary Tumor necrosis factor alpha and Interleukin 6 were found to be higher among mothers with chronic periodontitis than mothers with normal bonding relationship, and the percentage of disorder mother-infant bonding relation was higher in study group than in control group. Conclusion: Mother-infant bondings affected by chronic periodontitis as the patient have higher Salivary Tumor necrosis factor alpha and Salivary Interleukin6 than mothers with healthy periodontal condition.

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Science
Study of Corrosion Inhibition for Some New Schiff Bases Synthesized from Quinazolinone Derivative
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In this work, new Schiff bases of quinazolinone derivatives (Q1-Q5) were synthesized from methyl anthranilate. The synthesis involved three steps. In the first step, methyl anthranilate was reacted with isothiocyanatobenzene, producing the thiourea derivative K1. The second step entailed reacting K1 with hydrazine hydrate, synthesizing 3-amino-2-(phenylamino) quinazolin-4(3H)-one (K2). The third step involved reaction of K2 with various aromatic aldehydes, yielding the Schiff bases derivatives Q1-Q5. The chemical structures of these compounds were identified by FT-IR,1H NMR and 13C NMR spectroscopy. The newly synthesized derivatives (Q1-Q5) were subjected to rigorous evaluation to assess their efficacy as corrosion inhibitors for ca

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Publication Date
Tue Nov 01 2016
Journal Name
Renewable Energy
Biodiesel production by esterification of oleic acid over zeolite Y prepared from kaolin
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Publication Date
Tue Jan 01 2019
Journal Name
Optical And Quantum Electronics
Photocatalytic activity of anatase titanium dioxide nanostructures prepared by reactive magnetron sputtering technique
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Publication Date
Fri Mar 01 2019
Journal Name
Optical Fiber Technology
Highly sensitive measurement of surrounding refractive index using tapered trench–assisted multicore fiber
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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology & Applied Science Research
Post-Fire Behavior of Non-Prismatic Beams with Multiple Rectangular Openings Monotonically Loaded
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

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Publication Date
Fri Jul 19 2019
Journal Name
Communications Chemistry
Positive functional synergy of structurally integrated artificial protein dimers assembled by Click chemistry
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Abstract<p>Construction of artificial higher order protein complexes allows sampling of structural architectures and functional features not accessible by classical monomeric proteins. Here, we combine in silico modelling with expanded genetic code facilitated strain promoted azide-alkyne cycloaddition to construct artificial complexes that are structurally integrated protein dimers and demonstrate functional synergy. Using fluorescent proteins sfGFP and Venus as models, homodimers and heterodimers are constructed that switched ON once assembled and display enhanced spectral properties. Symmetrical crosslinks are found to be important for functional enhancement. The determined molecular structure of one artific</p> ... Show More
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Publication Date
Thu Sep 10 2020
Journal Name
Diyala Journal Of Engineering Sciences
Finite Element Analysis of Seepage for Hemrin Earth Dam Using Geo-Studio Software
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Finite Element Approach is employed in this research work to solve the governing differential equations related to seepage via its foundation's dam structure. The primary focus for this reason is the discretization of domain into finite elements through the placement of imaginary nodal points and the discretization of governing equations into an equation system; An equation for each nodal point or part, and unknown variables are solved. The SEEP / W software (program) is a sub-program of the Geo-Studio software, which is used by porous soil media to compensate for the problems of seepage. To achieve the research goals, a study was carried out on Hemrin dam, which located in the Diyala River 100 km northeast of Baghdad, Iraq. Thus, o

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Thu Mar 01 2018
Journal Name
Materials Today Communications
Improved mechanical properties of sol-gel derived ITO thin films via Ag doping
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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology, Monitoring & Management
Boosted visible-light-driven photocatalytic degradation of lomefloxacin over α-Ag2WO4/NiSx nanocomposites
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