Background: The COVID-19 virus outbreak had a massive effect on many parts of people's lives, as they were advised to quarantine and lockdown to prevent the virus from spreading, which had a big impact on people's mental health, anxiety, and stress. Many internal and external factors lead to stress. This negatively influences the body's homeostasis. As a result, stress may affect the body's capacity to use energy to defend against pathogens. Many recent investigations have found substantial links between human mental stress and the production of hormones, prohormones, and/or immunological chemicals. some of these researches have verified the link between stress and salivary cortisol levels. The aim of this study is to measure salivary cortisol as a stress biomarker as well as a total viable count of salivary bacterial microbiome among COVID-19 patients. Materials and methods: a sample of 84 adults patients was collected who were divided into two groups: the COVID-19 group consists of 42 patients and the COVID-19 free group which consists of 42 subjects. All subjects undergo a PCR test to confirm their health status. The collection of Un-stimulated saliva was done. Laboratory investigations were carried out to measure the total viable count of the salivary bacterial microbiome by culturing on Brain Heart Infusion Agar and to evaluate the salivary cortisol level using cortisol kit (Elecsys Cortisol II). Results: SPSS version 21 was used for statistical analysis. According to the statistical analysis, the salivary cortisol and total viable count of salivary bacterial microbiome values were substantially greater in the COVID-19 group than in the COVID-19 free group. Conclusion: A positive association was found between salivary cortisol and the total viable count of the salivary bacterial microbiome. So, when the concentration of salivary cortisol is elevated in the COVID-19 group, the level of the total viable count of the salivary bacterial microbiome is also elevated.
Background: Pleomorphic adenoma of the minor salivary gland is a rare benign tumor. It commonly occurs in the hard and soft palates. Treatment by surgical excision achieved success in improving the patient’s health. Objective: To evaluate the recurrence rate after surgical treatment of pleomorphic adenoma in minor salivary glands. Methods: This retrospective study included patients who attended the Maxillofacial Surgery Unit in Ghazi Al-Hariri Hospital, Baghdad, from 2019 to 2021, complaining of soft tissue lumps involving the soft and hard palate, buccal mucosa, and upper lip. After the provisional diagnosis of these lesions, a total surgical excision of the tumor with a safe margin of 1 mm was performed, and the biopsy was sent
... Show MoreBackground: Pleomorphic adenoma of the minor salivary gland is a rare benign tumor. It commonly occurs in the hard and soft palates. Treatment by surgical excision achieved success in improving the patient’s health. Objective: To evaluate the recurrence rate after surgical treatment of pleomorphic adenoma in minor salivary glands. Methods: This retrospective study included patients who attended the Maxillofacial Surgery Unit in Ghazi Al-Hariri Hospital, Baghdad, from 2019 to 2021, complaining of soft tissue lumps involving the soft and hard palate, buccal mucosa, and upper lip. After the provisional diagnosis of these lesions, a total surgical excision of the tumor with a safe margin of 1 mm was performed, and the biopsy was sent for hist
... Show MoreThe study aims to identify the degree of appreciation for the level of digital citizenship of a sample of Palestinian university students in the governorates of Gaza, and its relationship to the level of health awareness about the emerging coronavirus (covid-19). To achieve the objectives of the study, the researcher followed a descriptive approach by applying two questionnaires; the first, which consists of 30 items, was used to measure the level of digital citizenship. The second, which consists of 19 items, was used to measure the level of health awareness. Both questionnaires were applied on a sample of 367 students who were electronically selected using the manner simple randomness. Results have shown that the degr
... Show MoreBackground: Manuka honey (MH) is a mono-floral honey derived from the Manuka tree (Leptospermum scoparium). MH is a highly recognized for its non-peroxide antibacterial activities, which are mostly related to its unique methylglyoxal content (MGO) in MH. The beneficial phytochemicals in MH is directly related to their favorable health effects, which include wound healing, anticancer, antioxidant, and anti-inflammatory properties. Aims: The purpose of this study was to evaluate the effect of MH on pro-inflammatory cytokines (IL-8 and TNF-α) in patients with gingivitis and compare it with chlorhexidine (CHX) and distilled water (DW). Materials and Methods: This study was a randomized, double blinded, and parallel clinical trial. Forty-fiv
... Show MoreBackground: Smoking is the major environmental risk factor that has been associated with the pathogenesis and progression of periodontal diseases. Interleukin-8 (IL-8), has been associated with the immunopathology of periodontitis. Objectives: To determine the influence of smoking on salivary Interleukin-8 level from smokers and non-smokers with periodontitis and periodontally healthy control subjects.
Materials and Methods: Un-stimulated saliva samples were collected of 90 participants: 30 smokers and 30 non-smokers with chronic periodontitis, as well as 30 periodontally healthy control subjects. The clinical parameters such as the pocket depth, clinical attachment loss, plaque index, and gingiv
... Show MoreCOVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in