Purpose: To explore whether baseline matrix metalloproteinase (MMP)-8 level in gingival crevicular fluid (GCF) (exposure) can predict the outcome (reduction in probing pocket depth (PPD) (outcome)) of nonsurgical periodontal therapy (NSPT) (manual or ultrasonic or both) in patients with periodontitis (population/problem) after 3 months. Methods: Six databases (PubMed, Cochrane library, ProQuest, Ovid, Scopus, EBSCO) were searched for relevant articles published until 30 July 2021. Retrieved articles were passed through a three-phase filtration process on the basis of the eligibility criteria. The primary outcome was the change in PPD after 3 months. Quality of the selected articles was assessed using Cochrane Risk of Bias tool (RoB2) and Risk of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tools. Results: From 1306 articles, five were selected for analysis. The results showed high variations in the level of GCF MMP-8 level at baseline. The average amount of reduction in PPD was 1.20 and 2.30 mm for pockets with initial depth of 4–6 mm and >6 mm, respectively. Conclusion: On the basis of available evidence, it was not possible to reach a consensus on the ability of baseline GCF MMP-8 to forecast the outcome of NSPT. This could have been due to variation in clinical and laboratory techniques used. However, consistency in mean PPD reduction after 3 months was shown.
In this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.
PVC membrane sensor for the selective determination of Mefenamic acid (MFA) was constructed. The sensor is based on ion association of MFA with Dodecaphospho molybdic acid (PMA) and Dodeca–Tungstophosphoric acid(PTA) as ion pairs. Nitro benzene (NB) and di-butyl phthalate (DBPH) were used as plasticizing agents in PVC matrix membranes. The specification of sensor based on PMA showed a linear response of a concentration range 1.0 × 10–2 –1.0 × 10–5 M, Nernstian slopes of 17.1-18.86 mV/ decade, detection limit of 7 × 10-5 -9.5 × 10 -7M, pH range 3 – 8 , with correlation coefficients lying between 0.9992 and 0.9976, respectively. By using the ionphore based on PTA gives a concentration range of 1.0 × 10–4 –1.0 × 10–5 M,
... Show MoreThis study aimed to explore the relationship between cyberbullying and levels of pessimism and optimism among female university students, emphasizing the significance of these variables in students' psychological well-being. The research problem was identified in the increasing rates of cyberbullying among female students and its negative impact on optimism and pessimism, alongside the lack of effective counseling programs addressing this issue. The study sample consisted of 30 third-year students from the College of Physical Education and Sports Sciences for Women during the academic year 2023--2024. The participants were deliberately selected through a lottery method. The researchers employed the descriptive survey method as it suited the
... Show MoreExposure of reinforced concrete buildings to an accidental fire may result in cracking and loss in the bearing capacity of their major components, columns, beams, and slabs. It is a challenge for structural engineers to develop efficient retrofitting techniques that enable RC slabs to restore their structural integrity, after being exposed to intense fires for a long period of time. Experimental
investigation was carried out on twenty one slab specimens made of self compacting concrete, eighteen of them are retrofitted with CFRP sheets after burning and loading till failure while three of them (which represent control specimens) are retrofitted with CFRP sheet after loading till failure without burning. All slabs had been tested in a
Introduction to Medical Physics for Pharmacy Students and Medical Groups - ISBNiraq.org
Background: Gastro oesophageal reflux disease (GERD) is characterized by diverse symptoms. There is an evidence for a genetic component to Gastro oesophageal reflux disease as supported by familial aggregation of this disease. Aim of the study was to investigate whether certain human leucocyte antigen genes HLA-DRB1 are associated with (GERD).Methods: Patients and controls were prospectively recruited from GIT center at Al-Kindy Teaching Hospital (Baghdad-Iraq) between January 2014 and July 2016. Sixty Iraqi Arab Muslim patients with a history of heartburn and dyspepsia were compared with 100 Iraqi Arab Muslims controls. All study patients and control groups underwent upper gastrointestinal endoscopic examinations and their serums were anal
... Show MoreAbstract
Objectives: To assess patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention, and to find out the relationship between patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention
Methodology: A descriptive design was carried out at Al- Nasiriyah Heart Center in Thi-Qar Governorate for the period between May 19th, 2022 to October 25th, 2022. A non-probability sampling was used among (50) patients after their Percutaneous Coronary Intervention. The study instrument that used to collect data was composed of three parts namely: sociodemographic charac
... Show MoreSelf-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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