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With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researchers in literature review, abstract screening, and manuscript drafting. However, these models also present the attendant challenge of providing ethically questionable scientific information. Our study provides a snapshot of global researchers' perception of current trends and future impacts of LLMs in research. Using a cross-sectional design, we surveyed 226 medical and paramedical researchers from 59 countries across 65 specialties, trained in the Global Clinical Scholars' Research Training certificate program of Harvard Medical School between 2020 and 2024. Majority (57.5%) of these participants practiced in an academic setting with a median of 7 (2,18) PubMed Indexed published articles. 198 respondents (87.6%) were aware of LLMs and those who were aware had higher number of publications (p < 0.001). 18.7% of the respondents who were aware (n = 37) had previously used LLMs in publications especially for grammatical errors and formatting (64.9%); however, most (40.5%) did not acknowledge its use in their papers. 50.8% of aware respondents (n = 95) predicted an overall positive future impact of LLMs while 32.6% were unsure of its scope. 52% of aware respondents (n = 102) believed that LLMs would have a major impact in areas such as grammatical errors and formatting (66.3%), revision and editing (57.2%), writing (57.2%) and literature review (54.2%). 58.1% of aware respondents were opined that journals should allow for use of AI in research and 78.3% believed that regulations should be put in place to avoid its abuse. Seeing the perception of researchers towards LLMs and the significant association between awareness of LLMs and number of published works, we emphasize the importance of developing comprehensive guidelines and ethical framework to govern the use of AI in academic research and address the current challenges., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Gitelman syndrome is an autosomal recessive inherited salt-losing tubulopathy. It has a prevalence of around 1 in 40,000 people, and heterozygous carriers are estimated at approximately 1%, although the exact prevalence is unknown. We estimated the predicted prevalence of Gitelman syndrome based on multiple genome databases, HGVD and jMorp for the Japanese population and gnomAD for other ethnicities, and included all 274 pathogenic missense or nonsense variants registered in HGMD Professional. The frequencies of all these alleles were summed to calculate the total variant allele frequency in SLC12A3. The carrier frequency and the disease prevalence were assumed to be twice and the square of the total allele frequency, respectively, according to the Hardy-Weinberg principle. In the Japanese population, the total carrier frequencies were 0.0948 (9.5%) and 0.0868 (8.7%) and the calculated prevalence was 0.00225 (2.3 in 1000 people) and 0.00188 (1.9 in 1000 people) in HGVD and jMorp, respectively. Other ethnicities showed a prevalence varying from 0.000012 to 0.00083. These findings indicate that the prevalence of Gitelman syndrome in the Japanese population is higher than expected and that some other ethnicities also have a higher prevalence than has previously been considered., (© 2021. The Author(s).)

X-linked Alport syndrome (XLAS) is a congenital renal disease caused by mutations in COL4A5. In XLAS cases suspected of being caused by aberrant splicing, transcript analysis needs to be conducted to determine splicing patterns and assess the pathogenicity. However, such analysis is not always available. We conducted a functional splicing assay using a hybrid minigene for seven COL4A5 intronic mutations: one was identified by us and six were found in the Human Gene Mutation Database. The minigene assay revealed exon skipping in four variants, exon skipping and a 10-bp insertion in one variant, and no change in one variant, which appeared not to be pathogenic. For one variant, our assay did not work. The results of all three cases for which transcript data were available were consistent with our assay results. Our findings may help to increase the accuracy of genetic test results and clarify the mechanisms causing aberrant splicing.