Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture). Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size was 152. Online questionnaire by Google forms sampling method were used to collect the data which was analysed using SPSS 25. Results: The percentage of students who suffered cervical pain was (80.3%) of the 152 who participated in this study and the majority of those who suffered pain were complained from increase pain during the pandemic (72.1%). This study also showed the students recumbent on the floor 67 (44.1%) more than those who use the table and chair 62 (40.8%) during E-learning. The percentage of students who use the phone for more than 4 hours were (73.7%). Conclusion: there is a relationship between poor posture and cervical pain during E-learning in the pandemic. Most of students were suffering from neck pain with greatest percentage were in those who student in recumbent on the floor and when using chair and table.
Background: Understanding the pathogenesis and molecular basis of Oral Squamous Cell Carcinoma (OSCC) has increased rapidly over the past few years that is essential to improve patient's prognosis and treatment modalities. The purpose of this study to evaluate the Immunohistochemical expressions of AKT, ATM, AND Cyclin E in oral squamous cell carcinoma Materials and methods: This study was performed on a forty formalin-fixed paraffin-embedded blocks which histopathologically diagnosed as Oral Squamous Cell Carcinoma. All cases were collected from the Histopathological Laboratory from patients treated surgically at Maxillofacial surgery Department at Ramadi Teaching Hospital, Iraq. Results: The immunohistochemical staining of AKT showed pos
... Show MoreTo determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.
E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.
A total of 63 patients with periodontitis (case) and 35
Doxorubicin (DOX) is a chemotherapeutic agent; it is widely used in human malignancies. Its long-term use can cause neurobiological side-effects. Vitamin E and Coenzyme Q10may possess neuroprotective effects. This work was designed to investigate the effect of vitamin E and the coenzyme Q10(CoQ10) supplementation on neurotoxicity induced by doxorubicin(DOX) in rats. Forty nine adult rats of both sexes were used in this study; the animals were randomly enrolled into seven groups of 7 rats each. Group I: negative control (rats administered corn oil); Group II: Vitamin E at a dose of 100mg/kg/d for 3 weeks ; Group III: CoQ10 at a dose of 50 mg/kg/d for 3 weeks; Group IV: positive control (Doxorubicin 2
... Show MoreBack ground: Skin grafting is the most common form
of reconstructive surgery, and regeneration of
sensations in skin grafts is a complex process
influenced by many factors such as , the thickness of
the graft, the depth of the grafted bed, meshing of the
graft, the condition of the bed and the surrounding
area. So many studies performed on this subject, some
of them clinically based on subjective type of sensation
tests, and others histological to detect the presence of
nerve fibers in the grafted skin
Objectives: To detect return of sensations to split
thickness skin grafts by clinical methods.
Methods: From Oct. 1995 to Oct. 2010, a clinical
prospective study performed in Al wasity Hospital for
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreActive Learning And Creative Thinking