St. Dominic College of Asia

Biofilms are organized groups of microbes surrounded by an extracellular polymeric substance (EPS) matrix. This structure helps microbes survive, creates metabolic differences, and makes them less sensitive to antimicrobial treatments. Because biofilms can block antimicrobials and help microbes adapt, they often cause chronic and recurring infections that are hard to treat with standard methods. Most current diagnostic and antimicrobial testing methods focus on free-floating (planktonic) microbes and do not reflect the complex structure and behavior of mature biofilms. This gap often leads to ongoing treatment failures and poor predictions of treatment outcomes. Recently, artificial intelligence (AI) and computational modeling have shown promise for improving biofilm research. These tools can help with automated detection, structural analysis, computational phenotyping, and predicting how biofilms will respond to treatments. This review examines current and emerging AI-based methods in biofilm biology, focusing on computational analysis, prediction of antimicrobial responses, and AI-supported antibiofilm therapies. It also discusses challenges such as dataset differences, limited real-world testing, difficulty understanding models, and a lack of models for clinically important mixed-species biofilms. Overall, this review shows how AI could help improve the accuracy, integration, and tailoring of biofilm research and antimicrobial management.

Southeast Asia faces a substantial burden of antimicrobial resistance (AMR), creating increasing interest in bacteriophage-based antimicrobial strategies. However, the regional development, contributors, collaboration patterns, and evolving research priorities of this field remain insufficiently characterized. This study conducted a bibliometric analysis of Scopus-indexed publications on bacteriophage-based antimicrobial research affiliated with Southeast Asian countries from 1981 to 2025. Bibliometrix/Biblioshiny and VOSviewer were used to evaluate scientific production, citation patterns, leading contributors, collaboration networks, and conceptual and thematic development. A total of 862 publications were analyzed, with scientific output accelerating markedly after 2019 and reaching its highest level in 2025. Thailand emerged as the dominant regional contributor, with Vongkamjan (n = 21) and Surachat (n = 20) as the two most prolific authors. Mahidol University (n = 182), Prince of Songkla University (n = 142), and Universiti Putra Malaysia (n = 139) were the leading institutions, demonstrating a concentration of research capacity in Thailand and Malaysia. Scientific Reports was the most productive journal (30 publications), whereas Frontiers in Microbiology recorded the highest citation count among the leading sources (963 citations). Collaboration mapping revealed increasingly interconnected regional and international research networks. Thematic analyses demonstrated a transition from foundational and pathogen-specific investigations toward AMR, bacteriophage therapy, biofilm control, aquaculture, genomic and comparative genomic analysis, wastewater and public-health applications, and One Health-oriented research. Emerging topics included endolysins, quorum sensing, CRISPR-associated approaches, metagenomics, and genome-informed phage characterization. These findings demonstrate the rapid expansion and thematic diversification of bacteriophage-based antimicrobial research in Southeast Asia while highlighting persistent geographic concentration and the need for stronger regional infrastructure, collaboration, and translational capacity.

IntroductionPleurotus spp. have attracted significant scientific interest for their diverse bioactive compounds and broad pharmacological potential. Despite the rapid growth of the literature, a comprehensive scientometric synthesis of this research landscape remains limited.MethodsThis study used a systematic scientometric approach to analyze global research trends in Pleurotus bioactivity from 2000 to 2025. Key analyses included publication productivity, citation dynamics, co-authorship and country-level collaboration networks, keyword co-occurrence mapping, and thematic evolution.ResultsThe results reveal relatively stable publication output accompanied by a marked increase in citation impact after 2012, indicating growing intellectual consolidation and global recognition of the field. China and India dominate research productivity, whereas citation influence is more widely distributed, highlighting disparities between output and impact. Thematic evolution shows a shift from early studies on cultivation and compositional profiling toward advanced research in molecular bioactivity, gut microbiota modulation, enzymatic biotechnology, and circular bioeconomy applications. Emerging directions include precision nutraceutical development, optimization of extraction and fermentation processes, and agro-industrial waste valorization. Despite increasing interdisciplinary integration and strong preclinical evidence, collaboration networks remain partially fragmented, and translation into clinical and industrial applications remains limited.DiscussionThese findings indicate that while research on Pleurotus has reached a stage of disciplinary maturity, significant gaps persist in standardization, clinical validation, and scalability. Addressing these challenges will require integrative omics approaches, strengthened global collaboration, and translational frameworks to bridge the gap between laboratory discoveries and real-world applications.

Methicillin-resistant Staphylococcus aureus (MRSA) remains a significant multidrug-resistant pathogen, frequently associated with persistent infections and biofilm formation, underscoring the urgent need for alternative antimicrobial strategies. Bioactive compounds derived from fungi have attracted considerable attention due to their structural diversity and demonstrated antibacterial activity against MRSA. This study employed a scientometric approach to assess global research trends, thematic evolution, and collaborative networks concerning fungi-derived anti-MRSA compounds. Bibliographic data were collected from the Scopus database, and a total of 1666 English-language articles and reviews published up to 2025 were analyzed using Bibliometrix/Biblioshiny and VOSviewer. The findings indicate a marked increase in research output after 2010, reflecting heightened scientific interest in fungal natural products for MRSA management. China and the United States emerged as leading contributors in terms of publication volume and international collaboration. Thematic analysis revealed a shift from broad antimicrobial screening to more specialized investigations, including antibiofilm activity, secondary metabolites, endophytic fungi, molecular docking, and antimicrobial resistance. Nonetheless, several challenges persist, such as insufficient mechanistic validation, limited toxicity and pharmacokinetic assessments, and a lack of clinically relevant in vivo studies. Overall, the field is increasingly multidisciplinary, integrating microbiology, natural product chemistry, and computational methodologies to advance the discovery of anti-MRSA agents.

Antimicrobial resistance and persistent biofilm-associated infections have renewed interest in bacteriophages as alternatives or complements to conventional antibiotics. However, broader therapeutic adoption remains constrained by slow phage discovery, incomplete genome characterization, narrow host range, complex therapeutic matching, and manufacturing variability. Artificial intelligence (AI) offers computational approaches that may help address several of these limitations. This comprehensive narrative review discusses current AI applications across the bacteriophage pipeline, including metagenomic phage discovery, genome annotation, phage-host interaction prediction, personalized phage selection, cocktail optimization, and phage-antibiotic combination design. The review also examines AI-assisted synthetic biology approaches, including receptor-binding protein redesign, CRISPR-enabled engineering, generative genome design, and biosafety screening, as well as emerging applications in bioprocess optimization, yield prediction, purification analytics, quality assurance, and supply-chain management. Current evidence suggests that AI may accelerate phage identification, improve host-range prediction, support therapeutic optimization, and strengthen manufacturing consistency, potentially facilitating the transition of phage therapy from individualized rescue interventions toward more scalable antimicrobial platforms. Nevertheless, major limitations remain, including fragmented, taxonomically biased datasets; limited external validation; restricted interpretability; privacy concerns; biosafety oversight; and evolving regulatory frameworks. Future progress will depend on standardized datasets, multimodal validation, scalable manufacturing systems, experimental and clinical verification, and coordinated regulatory development.