Attitudes of Egyptian and Saudi University Youth towards the Effectiveness of Media Campaigns on Social Networking Sites in Raising Awareness of the Coronavirus. (Comparative Study)

The research aims to identify the rate of exposure of Egyptian and Saudi university youth to media campaigns on social media sites to raise awareness of the Coronavirus and to monitor the trend of young people towards the information provided about the Coronavirus. The research used the survey method in its field apartment on a sample of Egyptian and Saudi university youth, as well as the comparative approach to identify the similarities and differences in the study sample. The most important results: The (We Are All Responsible) campaign ranked first in terms of media campaigns preferred by Saudi university youth with a relative importance of (97.5%), while the "Protect Yourself, Protect Your Nation” campaign ranked first in terms of media campaigns preferred by Egyptian university youth with relative importance. The amount of (91.83%) and the Egyptian and Saudi university youth agreed to choose because it provides information about the Coronavirus and how to prevent it in the first place with a relative importance of (95.17%) in the motives for following up on media campaigns, and there are no differences between the sample members at the three socio-economic levels on a scale The trend towards the effectiveness of campaigns in raising awareness of the Coronavirus as a total degree, where the value of (t) was not significant at the 0.05. level. © 2023 DSR Publishers/ The University of Jordan.

Premenstrual Symptoms and Cycle Regularity: A Cross-sectional Study among Iraqi University Students during the COVID-19 Pandemic

Evidence suggests that the stressor factors faced by women of childbearing age during the COVID-19 pandemic are related to changes in menstrual cycles. The present study was conducted to explore the premenstrual symptoms (PMS), menstrual regularity, and their negative impact on academic performance and interpersonal relationships among Iraqi female university students during the COVID-19 pandemic. A cross-sectional study was conducted on 1270 Iraqi university students in Baghdad, Iraq. An online questionnaire was created to collect data about the menstrual cycle, PMS, and academic performance during the COVID 19 pandemic. The majority of the participants (76.6%) reported PMS. Depressed mood (69.6%) and flatulence (56.1%) were the most commonly reported PMS. The majority of participants (36.9%) suffered from moderate PMS. Moreover, (26.3%) and (18.3%) of the respondents reported worsening PMS and exacerbating menstrual pain, respectively. Among the respondents, (8.5%) reported a change in menstrual cycle length, and (50%) mentioned the lack of concentration. The study found that PMS was significantly (P<0.005) associated with the students’ age, age of menarche, and dysmenorrhea. Furthermore, PMS was highly significantly (P<0.001) associated with poor academic performance, poor interpersonal relationships, and COVID-19 infection. The findings of the present study reveal that during the COVID-19 pandemic, PMS was significantly increased in Iraqi university students and was associated with poorer academic performance and interpersonal relationships. © 2023 by SPC (Sami Publishing Company)

Dysmenorrhea among Female University Students during the COVID-19 Pandemic

Dysmenorrhea is the most common gynecological symptom among adolescent girls and young women. It can have a significant impact on females' quality of life. The study aims to investigate the prevalence and impact of dysmenorrhea among Iraqi university students during the COVID-19 pandemic. A cross-sectional study was conducted across different universities, including (College of Medicine, Pharmacy, and Dentistry) in Baghdad/Iraq, from March to May 2021. The data was collected through a self-questionnaire of 1312 Iraqi female university students. Dysmenorrhea was reported by (51.5%) of university students. Nearly one-third (32.1%) of participants rating dysmenorrhea as mild, (13.3%) moderate, and (6.1%) severe. Approximately (18.1%) of participants reported worsening of their menstrual pain, (21.3%) reported irregular menstrual cycles, (35.5%) reported increasing in learning difficulties, and (13.4%) reported increasing in the medication used to treat dysmenorrhea during the pandemic. The results revealed that there was a significant relationship between dysmenorrhea and the age of students, menstrual irregularity, medication use, and students who had Covid-19 infection (p-value <0.005). In addition, there was a highly significantly relationship between dysmenorrhea and learning disabilities as well as poor interpersonal relationships among Iraqi university students during the COVID-19 pandemic (p-value <0.001). According to the findings, dysmenorrhea has a negative impact on students' attendance, academic performance, and their interpersonal interactions during the COVID 19 pandemic. Future studies need to focus on improving pain management strategies to reduce the effects of dysmenorrhea so that young women can optimize their educational and future life opportunities. © 2022 Sami Publishing Company. All rights reserved.

The forgotten oral microbial transplantation for improving the outcomes of COVID-19.

Ever since the uncovering of the severe discrepancy of COVID-19 manifestations, irrespective of viral load, scientists have raced to locate and manage factors contributing to the genesis of a critical state. Recent evidence delineates the role of oral dysbiosis in the development of low-grade inflammation, characterized by the increase of inflammatory cytokines common to those fundamental to the development of severe COVID. Furthermore, high periodontopathic bacteria were recorded in severe acute respiratory syndrome in COVID patients, as well as its common provoking comorbidities such as diabetes and hypertension. This can be explained by the immigration and elimination of oral bacteria into the airways, which, in the context of an injured lung, allows for their preferential overgrowth familiar to that, causing the progression to advanced lung diseases. This is why we indicate the promising usage of oral microbiome transplantation as a treatment of oral microbial dysbiosis, not only associated with the worst outcomes of COVID-19 but also in other disorders of low-grade inflammation.

COVIDz: Deep learning for coronavirus disease detection

The severe damage caused by COVID-19 has become a reality, and there is no longer a way to save humanity from this epidemic except diagnose and prevention, especially with emergence delay and lack of vaccine recognized by the World Health Organization. Without therapeutic treatment or explicit restorative immunizations for COVID-19, it is fundamental to diagnose the disease at an early stage and quickly seclude patients contaminated with the virus. This study aims at estimating the damage via consistency of chest imaging, which is not always feasible or possible. Here, an application is proposed to solve the problem via a WEB Predictor ‘COVIDz” and a program exploiting deep learning, so as emergency care will be able to systematically bring chest X-ray images and predict the percentage of the absence or presence of COVID-19. The proposed approach (custom VGG model) and our WEB site “COVIDz” objective validation of the suggested solution obtained the best classification efficiency of 99.64%, F-score of 99.2%, precision of 99.28%, MCC of 99.28%, recall of 99.28%, and a specificity value of 100%. © Springer Nature Switzerland AG 2021.

WEB Predictor COVIDz: Deep Learning for COVID-19 Disease Detection from chest X-rays

While writing these words, the number of COVID-19 infected persons exceeded 20 730 456 and caused 751 154 deaths across the world as reported by WHO (World Health Organization) statistics [1]. The matter has become a reality and the damage is very severe, there is no longer any way to save humanity from this epidemic except diagnose and prevention, especially with the delay in the emergence of any vaccine recognized by the World Health Organization so far. Without therapeutic treatment or explicit restorative immunizations for COVID-19, it is fundamental to distinguish the malady at a beginning phase and to have the option to quickly seclude a contaminated patient. This study, therefore, looked at the diagnostic value and consistency of chest imaging. Access to imaging is not always possible, accessible, or feasible. Our application solves this problem and from a WEB Predictor COVIDz and a program with deep learning we will be able to systematically bring the chest X-ray image and predict the percentage of absence or presence of COVID-19. The proposed approach (Custom VGG model) and our WEB site COVIDz objective validation of the suggested solution obtained the best classification efficiency 99,64%, F -score of 99,2%, Precision of 99,28%, MCC of 99,28%, recall of 99,28%, and a Specificity value of 100%. © 2020 IEEE.