AIM OF REVIEW: This review aims to explain the application of the metabolomics approach in the study of anti-diabetes and anti-obesity activity of Malaysian herbs to identify the stand-up point for future advancement in using these herbs as a primary source for drug exploration.
KEY SCIENTIFIC CONCEPTS OF REVIEW: This review provides an overview of using metabolomics technique in studying the anti-diabetes and anti-obesity activity of Malaysian herbs. Specific emphasis is given to the changed metabolites in both in vivo and in vitro treatment of Malaysia herbs that might be future drugs for treating diabetes and obesity.
METHODS: Data were collected from 10 researchers from 10 different countries (Australia, China, the UK, Brazil, Pakistan, Bangladesh, Iran, Nigeria, Trinidad and Tobago, and Turkiye) using semi-structured interviews. NVivo was employed for data analysis.
RESULTS: Based on the responses, five themes about the influence of ChatGPT on academic and research writing were generated, i.e., opportunity, human assistance, thought-provoking, time-saving, and negative attitude. Although the researchers were mostly positive about it, some feared it would degrade their writing skills and lead to plagiarism. Many of them believed that ChatGPT would redefine the concepts, parameters, and practices of creativity and plagiarism.
DISCUSSION: Creativity may no longer be restricted to the ability to write, but also to use ChatGPT or other large language models (LLMs) to write creatively. Some suggested that machine-generated text might be accepted as the new norm; however, using it without proper acknowledgment would be considered plagiarism. The researchers recommended allowing ChatGPT for academic and research writing; however, they strongly advised it to be regulated with limited use and proper acknowledgment.
METHODS: A systematic literature search was conducted using PubMed, Google Scholar, Web of Science, Scopus, and Embase, focusing on studies published in the last fifteen years from 2009 to 2023. Keywords included "uveitis," "infectious uveitis," "viral uveitis," and others. Rigorous inclusion and exclusion criteria were applied, and data were synthesized thematically. Gene symbols related to infectious uveitis were analyzed using protein-protein interaction (PPI) networks and pathway analyses to uncover molecular mechanisms associated with infectious uveitis.
RESULTS: The search from different databases yielded 97 eligible studies. The review identified a significant rise in publications on infectious uveitis, particularly viral uveitis, over the past fifteen years. Infectious uveitis prevalence varies geographically, with high rates in developing regions due to systemic infections and limited diagnostic resources. Etiologies include viruses (39%), bacteria (17%), and other pathogens, substantially impacting adults aged 20-50 years. Pathogenesis involves complex interactions between infectious agents and the ocular immune response, with key roles for cytokines and chemokines. The PPI network highlighted IFNG, IL6, TNF, and CD4 as central nodes. Enriched pathways included cytokine-cytokine receptor interaction and JAK-STAT signaling. Clinical manifestations range from anterior to posterior uveitis, with systemic symptoms often accompanying ocular signs. Diagnostic strategies encompass clinical evaluation, laboratory tests, and imaging, while management involves targeted antimicrobial therapy and anti-inflammatory agents.
CONCLUSION: This review underscores the complexity of infectious uveitis, driven by diverse pathogens and influenced by various geographical and systemic factors. Molecular insights from PPI networks and pathway analyses provide a deeper understanding of its pathogenesis. Effective management requires comprehensive diagnostic approaches and targeted therapeutic strategies.