SUMMARY: Flavokawain C inhibited the growth of HT-29 human colon adenocarcinoma cellsFlavokawain C induced apoptosis in HT-29 cells, associated with an increase in reactive oxygen species and a decrease in SOD activityFlavokawain C induced cell cycle arrest at the G1 and G2/M phases via upregulation of p21 and p27 in HT-29 cellsHT-29 cells treated with flavokawain C caused downregulation of XIAP, c-IAP1, and c-IAP2, and upregulation of GADD153. Abbreviations used: FKC: Flavokawain C; SRB: Sulforhodamine B; ROS: Reactive oxygen species; SOD: Superoxide dismutase; PARP: Poly(ADP-ribose) polymerase; ER: Endoplasmic reticulum; IAPs: Inhibitor of apoptosis proteins; TUNEL: Transferase dUTP nick end labeling; Annexin V-FITC: Annexin V conjugated with fluorescein isothicyanate.
METHODS: A qualitative case study was conducted with medical students who were in the early phases of their training. Purposive sampling was employed to select the study participants. Data collection was carried out using semi-structured interviews. The interviews were recorded and transcribed verbatim, and they were later analysed using NVivo 10 software and employing open coding, axial coding and selective coding techniques. Nine medical students participated in the study. To ensure trustworthiness of the data, member checks, an audit trail, the Cohen kappa index, and peer checking were utilized.
RESULTS: Based on thematic analysis, four themes and seven categories were identified. Themes include soft skills, an academic overview, social skills and motivation from mentors. Categories include time management, study skills, communication skills, social adjustment, social activities, moral support and personal support.
CONCLUSION: Results indicate that mentoring is essential to medical students in developing their identity and professional maturity. The effectiveness of the mentoring programme is supported by several factors that, as a whole, lead to the development of a professional graduate.
AIM: This systematic review aimed to investigate the performance of AI systems in identifying dental anomalies in paediatric dentistry and compare it with human performance.
DESIGN: A systematic search of Scopus, PubMed and Google Scholar was conducted from 2012 to 2022. Inclusion criteria were based on problem/patient/population, intervention/indicator, comparison and outcome scheme and specific keywords related to AI, DL, paediatric dentistry, dental anomalies, supernumerary and mesiodens. Six of 3918 initial pool articles were included, assessing nine DL sub-systems that used panoramic radiographs or cone-beam computed tomography. Article quality was assessed using QUADAS-2.
RESULTS: Artificial intelligence systems based on DL algorithms showed promising potential in enhancing the speed and accuracy of dental anomaly detection, with an average of 85.38% accuracy and 86.61% sensitivity. Human performance, however, outperformed AI systems, achieving 95% accuracy and 99% sensitivity. Limitations included a limited number of articles and data heterogeneity.
CONCLUSION: The potential of AI systems employing DL algorithms is highlighted in detecting dental anomalies in paediatric dentistry. Further research is needed to address limitations, explore additional anomalies and establish the broader applicability of AI in paediatric dentistry.
METHODS: A cross-sectional study was conducted with 241 medical students. Validated questionnaires were administered to measure burnout, psychological distress, emotional intelligence, personality traits, and academic stress, respectively. A structural equation modelling analysis was performed by AMOS.
RESULTS: The results suggested a structural model with good fit indices, in which psychological distress and academic stress were noted to have direct and indirect effects on burnout. The burnout levels significantly increased with the rise of psychological distress and academic stress. Neuroticism was only found to have significant indirect effects on burnout, whereby burnout increased when neuroticism increased. Emotional intelligence had a significant direct effect on lowering burnout with the incremental increase of emotional intelligence, but it was significantly reduced by psychological distress and neuroticism.
CONCLUSION: This study showed significant effects that psychological distress, emotional intelligence, academic stress, and neuroticism have on burnout. Academic stress and neuroticism significantly increased psychological distress, leading to an increased burnout level, while emotional intelligence had a significant direct effect on reducing burnout; however, this relationship was compromised by psychological distress and neuroticism, leading to increased burnout. Several practical recommendations for medical educators, medical students, and medical schools are discussed.