Phlorotannins are a group of phenolic secondary metabolites isolated from a variety of brown algal species belonging to the Fucaceae, Sargassaceae, and Alariaceae families. The isolation of phlorotannins from various algal species has received a lot of interest owing to the fact that they have a range of biological features and are very biocompatible in their applications. Phlorotannins have a wide range of therapeutic biological actions, including antimicrobial, antidiabetic, antioxidant, anticancer, anti-inflammatory, anti-adipogenesis, and numerous other biomedical applications. The current review has extensively addressed the application of phlorotannins, which have been extensively investigated for the above-mentioned biological action and the underlying mechanism of action. Furthermore, the current review offers many ways to use phlorotannins to avoid certain downsides, such as low stability. This review article will assist the scientific community in investigating the greater biological significance of phlorotannins and developing innovative techniques for treating both infectious and non-infectious diseases in humans.

The increased interest in nanomedicine and its applicability for a wide range of biological functions demands the search for raw materials to create nanomaterials. Recent trends have focused on the use of green chemistry to synthesize metal and metal-oxide nanoparticles. Bioactive chemicals have been found in a variety of marine organisms, including invertebrates, marine mammals, fish, algae, plankton, fungi, and bacteria. These marine-derived active chemicals have been widely used for various biological properties. Marine-derived materials, either whole extracts or pure components, are employed in the synthesis of nanoparticles due to their ease of availability, low cost of production, biocompatibility, and low cytotoxicity toward eukaryotic cells. These marine-derived nanomaterials have been employed to treat infectious diseases caused by bacteria, fungi, and viruses as well as treat non-infectious diseases, such as tumors, cancer, inflammatory responses, and diabetes, and support wound healing. Furthermore, several polymeric materials derived from the marine, such as chitosan and alginate, are exploited as nanocarriers in drug delivery. Moreover, a variety of pure bioactive compounds have been loaded onto polymeric nanocarriers and employed to treat infectious and non-infectious diseases. The current review is focused on a thorough overview of nanoparticle synthesis and its biological applications made from their entire extracts or pure chemicals derived from marine sources.

Foodborne pathogens remain a significant public health concern, necessitating the development of rapid, sensitive, and reliable detection methods for various food matrices. Traditional biosensors, while effective in many contexts, often face limitations related to complex sample environments, signal interpretation, and on-site usability. The integration of artificial intelligence (AI) into biosensing platforms offers a transformative approach to address these challenges. This review critically examines recent advancements in AI-assisted biosensors for detecting foodborne pathogens in various food samples, including meat, dairy products, fresh produce, and ready-to-eat foods. Emphasis is placed on the application of machine learning and deep learning to improve biosensor accuracy, reduce detection time, and automate data interpretation. AI models have demonstrated capabilities in enhancing sensitivity, minimizing false results, and enabling real-time, on-site analysis through innovative interfaces. Additionally, the review highlights the types of biosensing mechanisms employed, such as electrochemical, optical, and piezoelectric, and how AI optimizes their performance. While these developments show promising outcomes, challenges remain in terms of data quality, algorithm transparency, and regulatory acceptance. The future integration of standardized datasets, explainable AI models, and robust validation protocols will be essential to fully harness the potential of AI-enhanced biosensors for next-generation food safety monitoring.

Biofilms are complex microbial communities encased within a self-produced extracellular matrix, which plays a critical role in chronic infections and antimicrobial resistance. These enhance pathogen survival and virulence by protecting against host immune defenses and conventional antimicrobial treatments, posing substantial challenges in clinical contexts such as device-associated infections and chronic wounds. Secondary metabolites derived from medicinal plants, such as alkaloids, tannins, flavonoids, phenolic acids, and essential oils, have gained attention as promising agents against biofilm formation, microbial virulence, and antibiotic resistance. These natural compounds not only limit microbial growth and biofilm development but also disrupt communication between bacteria, known as quorum sensing, which reduces their ability to cause disease. Through progress in nanotechnology, various nanocarriers such as lipid-based systems, polymeric nanoparticles, and metal nanoparticles have been developed to improve the solubility, stability, and cellular uptake of phytochemicals. In addition, the synergistic use of plant-based metabolites with conventional antibiotics or antifungal drugs has shown promise in tackling drug-resistant microorganisms and revitalizing existing drugs. This review comprehensively discusses the efficacy of pure secondary metabolites from medicinal plants, both as individuals and in nanoformulated forms or in combination with antimicrobial agents, as alternative strategies to control biofilm-forming pathogens. The molecular mechanisms underlying their antibiofilm and antivirulence activities are discussed in detail. Lastly, the current pitfalls, limitations, and emerging directions in translating these natural compounds into clinical applications are critically evaluated.

Mycotoxin contamination of foods is a major concern for food safety and public health worldwide. The contamination of agricultural commodities employed by humankind with mycotoxins (toxic secondary metabolites of fungi) is a major risk to the health of the human population. Common methods for mycotoxin detection include chromatographic separation, often combined with mass spectrometry (accurate but time-consuming to prepare the sample and requiring skilled technicians). Artificial intelligence (AI) has been introduced as a new technique for mycotoxin detection in food, providing high credibility and accuracy. This review article provides an overview of recent studies on the use of AI methods for the discovery of mycotoxins in food. The new approach demonstrated that a variety of AI technologies could be correlated. Deep learning models, machine learning algorithms, and neural networks were implemented to analyze elaborate datasets from different analytical platforms. In addition, this review focuses on the advancement of AI to work concomitantly with smart sensing technologies or other non-conventional techniques such as spectroscopy, biosensors, and imaging techniques for rapid and less damaging mycotoxin detection. We question the requirement for large and diverse datasets to train AI models, discuss the standardization of analytical methodologies, and discuss avenues for regulatory approval of AI-based approaches, among other top-of-mind issues in this domain. In addition, this research provides some interesting use cases and real commercial applications where AI has been able to outperform other traditional methods in terms of sensitivity, specificity, and time required. This review aims to provide insights for future directions in AI-enabled mycotoxin detection by incorporating the latest research results and stressing the necessity of multidisciplinary collaboration among food scientists, engineers, and computer scientists. Ultimately, the use of AI could revolutionize systems monitoring mycotoxins, improving food safety and safeguarding global public health.

Nisin is a naturally occurring bioactive small peptide produced by Lactococcus lactis subsp. lactis and belongs to the Type A (I) lantibiotics. Due to its potent antimicrobial activity, it has been broadly employed to preserve various food materials as well as to combat a variety of microbial pathogens. The present review discusses the antimicrobial properties of nisin and different types of their derivatives employed to treat microbial pathogens with a detailed underlying mechanism of action. Several alternative strategies such as combination, conjugation, and nanoformulations have been discussed in order to address several issues such as rapid degradation, instability, and reduced activity due to the various environmental factors that arise in the applications of nisin. Furthermore, the evolutionary relationship of many nisin genes from different nisin-producing bacterial species has been investigated. A detailed description of the natural and bioengineered nisin variants, as well as the underlying action mechanisms, has also been provided. The chemistry used to apply nisin in conjugation with natural or synthetic compounds as a synergetic mode of antimicrobial action has also been thoroughly discussed. The current review will be useful in learning about recent and past research that has been performed on nisin and its derivatives as antimicrobial agents.