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Large Language Models (LLMs) have gained attention in research and industry, aiming to streamline processes and enhance text analysis performance. Thematic Analysis (TA), a prevalent qualitative method for analyzing interview content, often requires at least two human experts to review and analyze data. This study demonstrates the feasibility of LLM-Assisted Thematic Analysis (LATA) using GPT-4 and Gemini. Specifically, we conducted semi-structured interviews with 14 researchers to gather insights on their experiences generating and analyzing Online Social Network (OSN) communications datasets. Following Braun and Clarke's six-phase TA framework with an inductive approach, we initially analyzed our interview transcripts with human experts. Subsequently, we iteratively designed prompts to guide LLMs through a similar process. We compare and discuss the manually analyzed outcomes with responses generated by LLMs and achieve a cosine similarity score up to 0.76, demonstrating a promising prospect for LATA. Additionally, the study delves into researchers' experiences navigating the complexities of collecting and analyzing OSN data, offering recommendations for future research and application designers. 

Anatomy education is an indispensable part of medical training, but traditional methods face challenges like limited resources for dissection in large classes and difficulties understanding 2D anatomy in textbooks. Advanced technologies, such as 3D visualization and augmented reality (AR), are transforming anatomy learning. This paper presents two in-house solutions that use handheld tablets or screen-based AR to visualize 3D anatomy models with informative labels and in-situ visualizations of the muscle anatomy. To assess these tools, a user study of muscle anatomy education involved 236 premedical students in dyadic teams, with results showing that the tablet-based 3D visualization and screen-based AR tools led to significantly higher learning experience scores than traditional textbook. While knowledge retention didn’t differ significantly, ethnographic and gender analysis showed that male students generally reported more positive learning experiences than female students. This study discusses the implications for anatomy and medical education, highlighting the potential of these innovative learning tools considering gender and team dynamics in body painting anatomy learning interventions. 

Although synthetic organic electrochemistry (EC) has advanced significantly, net redox neutral electrosynthesis is quite rare. Two approaches have been employed to achieve this type of electrosynthesis. One relies on turnover of the product by the reactant in a chain mechanism. The other involves both oxidation on the anode and reduction on the cathode in which the radical cation or the radical anion of the product has to migrate between two electrodes. Herein, a home-built electrochemistry/mass spectrometry (EC/MS) platform was used to generate an N -cyclopropylaniline radical cation electrochemically and to monitor its reactivity toward alkenes by mass spectrometry (MS), which led to the discovery of a new redox neutral reaction of intermolecular [3 + 2] annulation of N -cyclopropylanilines and alkenes to provide an aniline-substituted 5-membered carbocycle via direct electrolysis (yield up to 81%). A chain mechanism, involving the regeneration of the substrate radical cation and the formation of the neutral product, is shown to be responsible for promoting such a redox neutral annulation reaction, as supported by experimental evidence of EC/MS.