Background: Recently increasing number of people are using mouthwashes for general and oral care while the primary appeal of a mouthwash is an aid to breath freshness and cleansing the mouth, the majority of mouthwashes also claim to have antiseptic properties. The aim of this study is to determine the antimicrobial effectiveness of eight types of mouthwashes against Streptococcus mutans, Staphylococcus aureus and Candida albicans in vitro. Materials and methods: Agar diffusion technique was used to evaluate the antimicrobial activity of eight types of mouthwashes against Streptococcus mutans, Staphylococcus aureus and Candida albicans isolated from the oral cavities of patients attending dental clinics at college of dentistry - Baghdad University. Results: Al-Mansour mouthwash emerged as the most effective mouthwash giving the maximum mean diameter of inhibition zones against Staphylococcus aureus (26 mm), Candida albicans (25 mm) and Streptococcus mutans (20 mm) followed by corsodyl mouthwash, emoform mouthwash and zac mouthwash all of them had excellent levels of antimicrobial activity also Breath, close up, sensodyne and aquafresh had good antimicrobial activity Conclusion: All the mouthwashes used revealed antimicrobial activity against the three microorganisms used even when these mouthwashes were diluted but the concentrated mouthwash had the strongest antimicrobial activity. Al-Mansour mouthwash an Iraqi mouthwash was the best one according to the results of this study.
Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio
In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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This case series aims to evaluate patients affected with post COVID‐19 mucormycosis from clinical presentation to surgical and pharmacological treatment to improve the disease prognosis.
This case series was conducted at a specialized surgery hospital in Baghdad Medical City for over 10 months. Fifteen cases who had mild to severe COVID‐19 infections followed by symptoms similar to aggressive periodontitis, such as mobility and bone resorption around the multiple maxillary teeth, were included in this case series.
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