Publications by authors named "S Al Kassab"
Purpose: To create tridimensional (3D) anatomical models of diaphyseal fractures in dogs (3D AMDFD) and to evaluate the models from their radiographs.
Methods: The study consisted of six stages: preparation of femur from a healthy dog cadaver; digitalization of the bone through a 3D scanner and creation of the base model; creation of a 3D AMDFD based on the image of the base model, 3D modeling carried out to reproduce five different types of diaphyseal fractures; printing the models produced on a 3D printer with a thermoplastic material; insertion of neodymium magnets in the fracture line to allow the assembly and disassembly of the parts; and radiography of 3D AMDFD in lateromedial and craniocaudal positions.
Results: The base model and 3D AMDFD had high precision in the replication of bone structures, like the bone in natura.
Background: Sociocultural competence is essential for health professions education (HPE) students. However, the relationships between university campus environment, sense of belonging, and sociocultural engagement of HPE students remain unclear. We hypothesized that a university environment promoting students' participation in social activities enhances their sociocultural engagement, which is mediated through the students' sense of belonging, ultimately increasing their satisfaction with university experience.
View Article and Find Full Text PDFBackground: This research explores the relationships between the educational environment, student engagement, and academic achievement in Health Professions Education (HPE) , specifically examining the mediating role of engagement.
Methods: The study used cross-sectional design, and data were collected from 554 HPE students via self-report questionnaires. The Dundee Ready Education Environment Measure (DREEM) assessed the educational environment while the University Student Engagement Inventory measured learning engagement across the behavioral, emotional, and cognitive dimensions.
Article Synopsis
- Proteolysis Targeting Chimeras (PROTACs) are innovative tools in targeted protein degradation (TPD) that hold promise for drug development, but predicting their effectiveness is challenging.
- This study introduces an AI-powered PROTAC Activity Prediction Tool (AI-DPAPT) that leverages machine learning and molecular fingerprinting techniques to accurately predict PROTAC activity based on chemical structures.
- The research demonstrated strong performance across various machine learning classifiers, with the Random Forest model yielding an impressive area under the curve score of 0.97, enhancing the understanding of structure-activity relationships in TPD and potentially accelerating drug development processes.
Purpose: To develop and assess three-dimensional models of physeal fractures in dog femurs (3D MPFDF) using radiographic imaging.
Methods: The study was conducted in three phases: development of 3D MPFDF; radiographic examination of the 3D MPFDF; and comparative analysis of the anatomical and radiographic features of the 3D MPFDF.
Results: The base model and the 3D MPFDF achieved high fidelity in replicating the bone structures, accurately maintaining the morphological characteristics and dimensions such as length, width, and thickness, closely resembling natural bone.