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Abstract Background The chatbot application Bennie and the Chats was introduced due to the outbreak of COVID-19, which is aimed to provide substitution for teaching conventional clinical history-taking skills. It was implemented with DialogFlow with preset responses, which consists of a large constraint on responding to different conversations. The rapid advancement of artificial intelligence, such as the recent introduction of ChatGPT, offers innovative conversational experiences with computer-generated responses. It provides an idea to develop the second generation of Bennie and the Chats. As the epidemic slows, it can become an assisting tool for students as additional exercise. In this work, we present the second generation of Bennie and the Chats with ChatGPT, which provides room for flexible and expandable improvement. Methods The objective of this research is to examine the influence of the newly proposed chatbot on learning efficacy and experiences in bedside teaching, and its potential contributions to international teaching collaboration. This study employs a mixed-method design that incorporates both quantitative and qualitative approaches. From the quantitative approach, we launched the world’s first cross-territory virtual bedside teaching with our proposed application and conducted a survey between the University of Hong Kong (HKU) and the National University of Singapore (NUS). Descriptive statistics and Spearman’s Correlation were applied for data analysis. From the qualitative approach, a comparative analysis was conducted between the two versions of the chatbot. And, we discuss the interrelationship between the quantitative and qualitative results. Results For the quantitative result, we collected a questionnaire from 45 students about the evaluation of virtual bedside teaching between territories. Over 75% of the students agreed that teaching can enhance learning effectiveness and experience. Moreover, by exchanging patients cases, 82.2% of students agreed that it helps to gain more experiences with diseases that may not be prevalent in their own locality. For the qualitative result, the new chatbot provides better usability and flexibility. Conclusion Virtual bedside teaching with chatbots has revolutionized conventional bedside teaching by its advantages and allowing international collaborations. We believe that the training of history taking skills by chatbot will be a feasible supplementary teaching tool to conventional bedside teaching.

Abstract This study employed large eddy simulation (LES) with the wall-adapting local eddy-viscosity (WALE) model to investigate transitional flow characteristics in an idealized model of a healthy thoracic aorta. The OpenFOAM solver pimpleFoam was used to simulate blood flow as an incompressible Newtonian fluid, with the aortic walls treated as rigid boundaries. Simulations were conducted for 30 cardiac cycles and ensemble averaging was employed to ensure statistically reliable results. Main hemodynamic parameters, such as velocity fields, turbulence intensity turbulent kinetic energy (TKE), oscillatory shear index (OSI) and wall shear stress (WSS), were analyzed throughout the circulatory system. Through 3D computational fluid dynamics (CFD) visualization, we explained the transition from laminar to turbulent flow and its development throughout the cardiac cycle. The results demonstrated that turbulence originates in the aortic arch following the peak systole phase and further develops in the aortic arch and descending aorta during the mid-deceleration and end-systole phases, with the maximum turbulence intensity exceeding 25%. WSS reached up to 30 Pa during the peak systole, with an average WSS of 6.5 Pa across the cardiac cycle. Low and oscillatory WSS were observed during diastole which can potentially contribute to the development of vascular diseases including, aortic dissection and atherosclerosis.

Abstract We investigate the bulk reconstruction of AdS black hole spacetime emergent from quantum entanglement within a machine learning framework. Utilizing neural ordinary differential equations alongside Monte-Carlo integration, we develop a method tailored for continuous training functions to extract the general isotropic bulk metric from entanglement entropy data. To validate our approach, we first apply our machine learning algorithm to holographic entanglement entropy data derived from the Gubser-Rocha and superconductor models, which serve as representative models of strongly coupled matters in holography. Our algorithm successfully extracts the corresponding bulk metrics from these data. Additionally, we extend our methodology to many-body systems by employing entanglement entropy data from a fermionic tight-binding chain at half filling, exemplifying critical one-dimensional systems, and derive the associated bulk metric. We find that the metrics for a tight-binding chain and the Gubser-Rocha model are similar. We speculate this similarity is due to the metallic property of these models.

The cryptochromes are flavoproteins that either individually or synergistically respond to light and magnetic field directionality as well as are implicated in circadian rhythm entrainment and development. Single brief exposures (10 min) to low energy (1.5 mT) pulsed electromagnetic fields (PEMFs) were previously shown to enhance myogenesis by stimulating transient receptor potential canonical 1 (TRPC1)-mediated Ca2+ entry, whereby downwardly directed fields produced greater myogenic enhancement than upwardly directed fields. Here, we show that growth in the dark results in myoblasts losing their sensitivity to both magnetic field exposure and directionality. By contrast, overexpressing or silencing cryptochrome circadian regulator 2 (CRY2) in myoblasts enhances or reduces PEMF responses, respectively, under conditions of ambient light. Reducing cellular flavin adenine dinucleotide (FAD) content by silencing riboflavin kinase (RFK) attenuated responsiveness to PEMFs and inhibited selectivity for magnetic field direction. The upregulation of TRPC1 and cell cycle regulatory proteins typically observed in response to PEMF exposure was instead attenuated by upwardly directed magnetic fields, growth in the darkness, magnetic shielding, or the silencing of CRY2 or RFK. A physical interaction between CRY2 and TRPC1 was detected using coimmunoprecipitation and immunofluorescence, revealing their co-translocation into the nucleus after PEMF exposure. These results implicate CRY2 in an identified TRPC1-dependent magnetotransduction myogenic cascade.