Introduction: ChatGPT is a Large Language Model (LLM) which allows for natural language processing and interactions with users in a conversational style. Since its release in 2022, it has had a significant impact in many occupational fields, including medical education. We sought to gain insight into the extent and type of usage of ChatGPT at a Caribbean medical school, the American University of Antigua College of Medicine (AUA). Methods: We administered a questionnaire to 87 full-time faculty at the school via email. We quantified and made graphical representations of the results via Qualtrics Experience Management software (QualtricsXM, Qualtrics, Provo, UT). Survey results were investigated using bar graph comparisons of absolute numbers and percentages for various categories related to ChatGPT usage, and descriptive statistics for Likert scale questions. Results: We found an estimated 33% of faculty were currently using ChatGPT. There was broad acceptance of the program by those who were using it and most believed it should be an option for students. The primary task ChatGPT was being used for was multiple choice question (MCQ) generation. The primary concern faculty had was incorrect information being included in ChatGPT output. Conclusion: ChatGPT has been quickly adopted by a subset of the college faculty, demonstrating its growing acceptance. Given the level of approval expressed about the program, we believe ChatGPT will continue to form an important and expanding part of faculty workflows at AUA and in medical education in general.

Next-generation sequencing (NGS) has emerged as a promising tool for diagnosing fungal infections. It enables the identification of a wide range of fungal species and provides more accurate and rapid results than traditional diagnostic methods. NGS-based approaches involve the sequencing of DNA or RNA from clinical samples, which can be used to detect and identify fungal pathogens in complex clinical samples. The development of targeted gene panels and whole-genome sequencing has allowed for identifying genetic markers associated with antifungal drug resistance, enabling clinicians to tailor patient treatment options. NGS can also provide insights into the pathogenesis of fungal infections and aid in discovering novel drug targets. Although NGS has some limitations, such as cost and data analysis, it can potentially revolutionize the future diagnosis and treatment of fungal infections.

Next-generation sequencing (NGS) and the technique of DNA metabarcoding have provided more efficient and comprehensive options for testing water quality compared to traditional methods. Recent studies have shown the efficacy of DNA metabarcoding in characterizing the bacterial microbiomes of varied sources of drinking water, including rivers, reservoirs, wells, tanks, and lakes. We asked whether DNA metabarcoding could be used to characterize the microbiome of different private sources of stored freshwater on the Caribbean Island nation of Antigua and Barbuda. Two replicate water samples were obtained from three different private residential sources in Antigua: a well, an above-ground tank, and a cistern. The bacterial microbiomes of different freshwater sources were assessed using 16S rRNA metabarcoding. We measured both alpha diversity (species diversity within a sample) and beta diversity (species diversity across samples) and conducted a taxonomic analysis. We also looked for the presence of potentially pathogenic species. Major differences were found in the microbiome composition and relative abundances depending on the water source. A lower alpha diversity was observed in the cistern sample compared to the others, and distinct differences in the microbiome composition and relative abundance were noted between the samples. Notably, pathogenic species, or genera known to harbor such species, were detected in all the samples. We conclude that DNA metabarcoding can provide an effective and comprehensive assessment of drinking water quality and has the potential to identify pathogenic species overlooked using traditional methods. This method also shows promise for tracing the source of disease outbreaks due to waterborne microorganisms. This is the first study from small island countries in the Caribbean where metabarcoding has been applied for assessing freshwater water quality.