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Abstract β-Branched aromatic α-amino acids are valuable building blocks in natural products and pharmaceutically active compounds. However, their chemical or enzymatic synthesis is challenging due to the presence of two stereocenters. We design phenylalanine ammonia lyases (PAL) variants for the direct asymmetric synthesis of β-branched aromatic α-amino acids. Based on extensive computational analyses, we unravel the enigma behind PAL’s inability to accept β-methyl cinnamic acid (β-MeCA) as substrate and achieve the synthesis of the corresponding amino acids of β-MeCA and analogs using a double (PcPAL-L256V-I460V) and a triple mutant (PcPAL-F137V-L256V-I460V). The reactions are scaled-up using an optimized E. coli based whole-cell biotransformation system to produce ten β-branched phenylalanine analogs with high diastereoselectivity (dr > 20:1) and enantioselectivity (ee > 99.5%) in yields ranging from 41-71%. Moreover, we decipher the mechanism of PcPAL-L256V-I460V for the acceptance of β-MeCA and converting it with excellent stereoselectivity by computational simulations. Thus, this study offers an efficient method for synthesizing β-branched aromatic α-amino acids.

This viewpoint article first explores the ethical challenges associated with the future application of large language models (LLMs) in the context of medical education. These challenges include not only ethical concerns related to the development of LLMs, such as artificial intelligence (AI) hallucinations, information bias, privacy and data risks, and deficiencies in terms of transparency and interpretability but also issues concerning the application of LLMs, including deficiencies in emotional intelligence, educational inequities, problems with academic integrity, and questions of responsibility and copyright ownership. This paper then analyzes existing AI-related legal and ethical frameworks and highlights their limitations with regard to the application of LLMs in the context of medical education. To ensure that LLMs are integrated in a responsible and safe manner, the authors recommend the development of a unified ethical framework that is specifically tailored for LLMs in this field. This framework should be based on 8 fundamental principles: quality control and supervision mechanisms; privacy and data protection; transparency and interpretability; fairness and equal treatment; academic integrity and moral norms; accountability and traceability; protection and respect for intellectual property; and the promotion of educational research and innovation. The authors further discuss specific measures that can be taken to implement these principles, thereby laying a solid foundation for the development of a comprehensive and actionable ethical framework. Such a unified ethical framework based on these 8 fundamental principles can provide clear guidance and support for the application of LLMs in the context of medical education. This approach can help establish a balance between technological advancement and ethical safeguards, thereby ensuring that medical education can progress without compromising the principles of fairness, justice, or patient safety and establishing a more equitable, safer, and more efficient environment for medical education.

For the lack of command and control modeling principles and mechanisms in the current end-to-end campaign tactical level simulation for unmanned air combat, this paper systematically combs and studies the recent research in unmanned air campaign tactical simulation. Combined with the relevant research, this paper explored the principles and methods of different C2 modeling at different simulation levels and established a C2 simulation system suitable for the characteristics of CISE in unmanned air combat. Further, theoretical and practical guidance is provided for innovative demonstration and evaluation methods of CISE through the effectiveness evaluation support of unmanned air combat tasks.

AbstractThis viewpoint article explores the transformative role of large language models (LLMs) in the field of medical education, highlighting their potential to enhance teaching quality, promote personalized learning paths, strengthen clinical skills training, optimize teaching assessment processes, boost the efficiency of medical research, and support continuing medical education. However, the use of LLMs entails certain challenges, such as questions regarding the accuracy of information, the risk of overreliance on technology, a lack of emotional recognition capabilities, and concerns related to ethics, privacy, and data security. This article emphasizes that to maximize the potential of LLMs and overcome these challenges, educators must exhibit leadership in medical education, adjust their teaching strategies flexibly, cultivate students’ critical thinking, and emphasize the importance of practical experience, thus ensuring that students can use LLMs correctly and effectively. By adopting such a comprehensive and balanced approach, educators can train health care professionals who are proficient in the use of advanced technologies and who exhibit solid professional ethics and practical skills, thus laying a strong foundation for these professionals to overcome future challenges in the health care sector.

Abstract Carboxylic ester hydrolases with the capacity to degrade polyesters are currently highly sought after for their potential use in the biological degradation of PET and other chemically synthesized polymers. Here, we describe MarCE, a carboxylesterase family protein identified via genome mining of a Maribacter sp. isolate from the marine sponge Stelligera stuposa. Based on phylogenetic analysis, MarCE and its closest relatives belong to marine‐associated genera from the Cytophaga–Flavobacterium–Bacteroides taxonomic group and appear evolutionarily distinct to any homologous carboxylesterases that have been studied to date in terms of structure or function. Molecular docking revealed putative binding of BHET, a short‐chain PET derivative, onto the predicted MarCE three‐dimensional structure. The synthetic ester‐degrading activity of MarCE was subsequently confirmed by MarCE‐mediated hydrolysis of 2 mM BHET substrate, indicated by the release of its breakdown products MHET and TPA, which were measured, respectively, as 1.28 and 0.12 mM following 2‐h incubation at 30°C. The findings of this study provide further insight into marine carboxylic ester hydrolases, which have the potential to display unique functional plasticity resulting from their adaptation to complex and fluctuating marine environmentsw.