Branched-chain Amino Acid Biosensing Using Fluorescent Modified Engineered Leucine/Isoleucine/Valine Binding Protein

Abstract: A novel fluorescence sensing system for branched-chain amino acids (BCAAs) was developed based on engineered leucine/isoleucine/valine-binding proteins (LIVBPs) conjugated with environmentally sensitive fluorescence probes. LIVBP was cloned from Escherichia coli and Gln149Cys, Gly227Cys, and Gln254Cys mutants were generated by genetic engineering. The mutant LIVBPs were then modified with environmentally sensitive fluorophores. Based on the fluorescence intensity change observed upon the binding of the ligands, the MIANS-conjugated Gln149Cys mutant (Gln149Cys-M) showed the highest and most sensitive response. The BCAAs Leu, Ile, and Val can each be monitored at the sub-micromolar level using Gln149Cys-M. Measurements were also carried out on a mixture of BCAFAs and revealed that Gln149Cys-M-based measurement is not significantly affected by the change in the molar ratio of Leu, Ile and Val in the sample. Its high sensitivity and group-specific molecular recognition ability make the new sensing system ideally suited for the measurement of BCAAs and the determination of the Fischer ratio, an indicator of hepatic disease involving metabolic dysfunction

A comparative study of English and Japanese ChatGPT responses to anaesthesia-related medical questions

Background: The expansion of artificial intelligence (AI) within large language models (LLMs) has the potential to streamline healthcare delivery. Despite the increased use of LLMs, disparities in their performance particularly in different languages, remain underexplored. This study examines the quality of ChatGPT responses in English and Japanese, specifically to questions related to anaesthesiology. Methods: Anaesthesiologists proficient in both languages were recruited as experts in this study. Ten frequently asked questions in anaesthesia were selected and translated for evaluation. Three non-sequential responses from ChatGPT were assessed for content quality (accuracy, comprehensiveness, and safety) and communication quality (understanding, empathy/tone, and ethics) by expert evaluators. Results: Eight anaesthesiologists evaluated English and Japanese LLM responses. The overall quality for all questions combined was higher in English compared with Japanese responses. Content and communication quality were significantly higher in English compared with Japanese LLMs responses (both P<0.001) in all three responses. Comprehensiveness, safety, and understanding were higher scores in English LLM responses. In all three responses, more than half of the evaluators marked overall English responses as better than Japanese responses. Conclusions: English LLM responses to anaesthesia-related frequently asked questions were superior in quality to Japanese responses when assessed by bilingual anaesthesia experts in this report. This study highlights the potential for language-related disparities in healthcare information and the need to improve the quality of AI responses in underrepresented languages. Future studies are needed to explore these disparities in other commonly spoken languages and to compare the performance of different LLMs