Medical imaging is considered a suitable alternative testing method for the detection of lung diseases. Many researchers have been working to develop various detection methods that have aided in the prevention of lung diseases. To better understand the condition of the lung disease infection, chest X-Ray and CT scans are utilized to check the disease’s spread throughout the lungs. This study proposes an automated system for the detection multi lung diseases in X-Ray and CT scans. A customized convolutional neural network (CNN) and two pre-trained deep learning models with a new image enhancement model are proposed for image classification. The proposed lung disease detection comprises two main steps: pre-processing, and deep learning classification. The new image enhancement algorithm is developed in the pre-processing step using k-symbol Lerch transcendent functions model which enhancement images based on image pixel probability. While, in the classification step, the customized CNN architecture and two pre-trained CNN models Alex Net, and VGG16Net are developed. The proposed approach was tested on publicly available image datasets (CT, and X-Ray image dataset), and the results showed classification accuracy, sensitivity, and specificity of 98.60%, 98.40%, and 98.50% for the X-Ray image dataset, respectively, and 98.80%, 98.50%, 98.40% for the CT scans dataset, respectively. Overall, the obtained results highlight the advantages of the image enhancement model as a first step in processing.

Aluminum is the most abundant metal that can get admission to the human through several means that include our food, drinking water, cans, drugs, and deodorants, causing neurodegenerative diseases such as Alzheimer’s disease (AD). The present study aims to evaluate the role of quercetin nanoemulsion (QCNE) in attenuating neuronal dysfunction in aluminum chloride (AlCl₃)-induced experimental AD. All animals were classified into six groups including negative control group (I): received a vehicle; QC group: received intraperitoneal (IP) injection of QC; Alzheimer’s group: received AlCl₃ orally; treated group (I): received AlCl₃ orally and IP injection of QC; treated group (II): received AlCl₃ orally and QC orally; and treated group (III): received AlCl₃ orally and IP injection of QCNE. At the end of the experimental period (30 days), the brain was used to study biochemical parameters (measurement of neurotransmitters (serotonin, dopamine, and norepinephrine), oxidant/antioxidant parameters (reduced glutathione, malondialdehyde, superoxide dismutase, and advanced oxidation protein product), and inflammatory markers (adiponectin, interleukin 1β, and plasma tumor necrosis factor-alpha)), while another part was for brain immune-histochemical analysis (study cyclooxygenases (COX-1 and COX-2)). Results showed that the mean value of oxidative stress markers was significantly increased in the AD group as well as the inflammatory biomarkers and all the study neurotransmitters, whereas these parameters were attenuated in treated groups, especially those that received QCNE. The immunohistochemistry findings confirm our results. Both approaches (QC and QCNE) succeeded in retracting the negative impact of AlCl₃. Meanwhile, the effect of QCNE is more potent in mitigating the impact mediated by AlCl₃ in treated animals. In conclusion, the treatment mainly by QCNE has huge potential in protecting against AlCl3-induced neuronal dysfunction, as shown in our results by the elevation of brain antioxidant/anti-inflammatory activities and neurotransmitter levels as well as mending of the histopathological changes in animal models.

Background: While online education is by no means a new concept, it was recently thrust into the spotlight after school campuses all over the world were forced to close because of the COVID-19 pandemic. The sudden need to shift revealed emerging challenges to online teaching, both logistic and personal. One important challenge is the ability to assess the readiness of educators for online teaching, so that appropriate and specific feedback/training can be offered to those in need. This study aims at developing, validating, and implementing a tool to measure the teachers’ readiness for online teaching in three medical schools from three different countries. Methods: This was a multi-center, cross-sectional study that involved developing a survey through review of literature and previous studies, item development and revision, and pilot testing. The survey was then distributed electronically to a convenient sample of 217 teaching faculty members of different academic ranks from three medical schools in Egypt, Saudi Arabia, and Bahrain. Exploratory factor analysis and reliability study were performed. Descriptive statistics were applied, and the statistical significance level was set at 0.05. Results: Factor analysis produced the following five factors: “Online Teaching and Course Design Skills”, “Digital Communication”, “Basic Computer Skills”, “Advanced Computer Skills” and “Using Learning Management Systems”. The tool showed high reliability (alpha = 0.94). Survey results showed highest mean scores for Basic Computer Skills with lower scores for Online Teaching and Course Design Skills and Using Learning Management Systems. ANOVA revealed statistically significant differences between the three studied schools regarding Digital Communication (F=5.13; p=0.007) and Basic Computer Skills (F=4.47; p=0.012) factors. Conclusion: The tool proved to be reliable and valid. Results indicated an overall acceptable readiness in the three involved schools, with a need for improvement in “Online Teaching and Course Design” and Using Learning Management Systems.

Background: Recent reports suggest that faculty development (FD) programs need a structured framework to design training and assess improvement in teaching performance of participants. Entrustable professional activities (EPAs) can serve as a novel framework to plan and conduct structured FD programs, and to assess the proficiency of small group facilitators after training. Objective: The researchers aimed to develop an EPAs framework for small group facilitators. Design: In March 2019, three workshops were organized to develop the EPAs framework by using a participatory action design approach. An orientation workshop was conducted to train the participating students and teachers. Then, a design workshop was conducted to develop the EPA framework, where data were collected from three sources: scribe notes, audio recordings, and field charts. Thematic analysis was performed, and consensus was sought from participants on the extracted professional tasks and competencies in the consensus workshop. In the third workshop, the participants also mapped professional tasks with relevant competencies. Results: A total of 15 teachers and 15 studentsf participated in the co-design process. Through a robust thematic analysis of multisource data, 57 professional tasks and 52 competencies emerged, which were converged into 11 tasks and 17 competencies after removing duplicating and non-qualifying professional tasks and competencies. Finally, a consensus was achieved on nine tasks and 12 competencies. Conclusions: The proposed EPAs framework can serve as a road map for longitudinal training and entrustment of small group facilitators. It can also guide small group facilitators in their continuous professional development and in building their teaching portfolios.

The effect of smoking on cognition as measured by Cambridge Neuropsychological Test Automated Battery (CATNAB) and brain-derived neurotrophic factor plasma levels