Publications by authors named "Mohammed Nahid"

There is a growing interest in studying natural products for the identification of novel lead compounds for drug development for treating inflammatory diseases. Although some studies have focused anti-inflammatory activity of benzophenones and xanthones, exploring additional targets such as enzymes and cytokines, involved in their inflammatory response could provide more comprehensive understanding of the compounds' anti-inflammatory effects. In this study, four xanthones ananixanthone (), smeathxanthone A (), smeathxanthone B (), and 1,3,5,8-tetrahydroxy-2-(3-methybut-2-enyl)-4-(3,7-dimethyloct-2,6-dienyl) xanthone (); and three benzophenones guttiferone O (), guttiferone M (), and aristophenone A () from (Planch.

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Background: Student-centered learning strategy increases the likelihood of graduation of competent, self-dependent, and problem-solving physicians. The University of Bisha, College of Medicine (UBCOM) adopted self-directed learning (SDL) represented by problem-based learning (PBL), and directed self-learning (DSL) represented by team-based learning (TBL).

Aim: To compare the students' performance in SDL and DSL among UBCOM students.

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Accumulating evidence suggests that dysregulation of FOXO3a plays a significant role in the progression of various malignancies, including hepatocellular carcinoma (HCC). FOXO3a inactivation, driven by oncogenic stimuli, can lead to abnormal cell growth, suppression of apoptosis, and resistance to anticancer drugs. Therefore, FOXO3a emerges as a potential molecular target for the development of innovative treatments in the era of oncology.

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Liver fibrosis is a progressive condition characterized by the build-up of fibrous tissue resulting from long-term liver injury. Although there have been advancements in research and treatment, there is still a need for effective antifibrotic medication. HSP90 plays a crucial role in the development of fibrosis.

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Introduction: The circumstances of the COVID-19 lockdown offered an opportunity to develop remote educational strategies in medical education.

Objectives: To assess medical students' experiences with online e-learning (OeL) satisfaction, intellectual environment, and communication during the COVID-19 pandemic.

Methods: A cross-sectional study was conducted at the College of Medicine, University of Bisha, Saudi Arabia.

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This work aims to improve EEG signal binary and multiclass classification for real-time BCI applications. Therefore, our paper discusses the results of a new real-time approach that was integrated into a complete prediction system, where we proposed a new trick to eliminate the effect of EEG's non-stationarity nature. This improvement can increase the accuracy from 50% using raw EEG to the order of 90% after preprocessing step in the binary case and from 28% to 78% in the multiclass case.

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