Dr. M.G.R. Educational and Research Institute is a private deemed to be university located in Chennai, Tamil Nadu, India. It was established in the year 1988. It received its deemed to be university status in 2003.
The rapid digital transformation of microbiology has led to unprecedented laboratory automation, generating vast data and advancing analytical capabilities. However, integrating complex artificial intelligence models with high-throughput systems introduces challenges in understanding system functions, ensuring reproducibility, and maintaining trust in automated outputs. This chapter presents a framework that integrates Explainable Artificial Intelligenceand Digital Twin technologies to create intelligent microbial laboratories. Through real-time automation, sensor-based data acquisition, computational modeling, and interpretable AI methods, the system continuously monitors, simulates, and optimizes microbial experiments. This approach improves experimental reliability while supporting human decision-making in clinical microbiology. The chapter further outlines practical workflows, architectural designs, and use cases demonstrating how explainable digital twins transform automated laboratories into adaptive, transparent, and trustworthy platforms for scientific discovery.
This study reports the biological synthesis of environmentally friendly zinc oxide nanoparticles (ZnO-NPs) using the marine red alga Gracilaria corticata. The algal extract served as a natural reducing and stabilizing agent in the formation of ZnO nanoparticles (GC-ZnONPs). The synthesized nanoparticles were comprehensively characterized using UV–Vis spectroscopy, FTIR, XRD, SEM, EDX, HRTEM, DLS, zeta potential analysis, VSM, NMR and TGA/DTA. Characterization results confirmed that GC-ZnONPs possess a crystalline structure with predominantly spherical and hexagonal morphologies and a relatively uniform size distribution. The GC-ZnONPs exhibited significant antioxidant activity through inhibiting DPPH and H2O2 free radicals. Anti-inflammatory activity, evaluated using a bovine serum albumin (BSA) denaturation assay, demonstrated concentration-dependent inhibition of protein denaturation. In addition, GC-ZnONPs showed pronounced antibacterial activity against several pathogenic bacterial strains. Cytotoxicity assessment using the MTT assay revealed strong anticancer activity against AGS gastric cancer cells, with an IC₅₀ value of 53.16 µg/mL. Furthermore, molecular docking analysis demonstrated strong binding interactions between 2,4-di-tert-butylphenol, a bioactive compound isolated from G. corticata and key gastric cancer-associated proteins, including KRAS, PIK3CA, SMAD4, TP53 and CDH1, suggesting a potential multi-target therapeutic mechanism. Collectively, these findings indicate that GC-ZnONPs exhibit multifunctional biological activities, including antioxidant, anti-inflammatory, antibacterial and anticancer properties. Overall, the results highlight the promise of green nanomedicine for the development of environmentally sustainable, marine-derived nanotherapeutics for gastric cancer treatment.
Musculoskeletal injuries are among the most common causes of disability worldwide, with early detection and appropriate intervention critical to minimizing long-term complications. Infrared thermography (IRT) has emerged as a non-invasive, real-time imaging modality that captures superficial temperature changes reflecting underlying physiological processes such as inflammation and vascular alterations. This review explores the fundamental principles of medical thermography, differentiates between passive and active approaches, and outlines key technological advancements including artificial intelligence integration. The clinical utility of IRT is discussed in various contexts - ranging from acute soft tissue injuries and overuse syndromes to chronic pain and rehabilitation monitoring. Comparative insights with conventional imaging techniques such as ultrasound and magnetic resonance imaging are also presented. While IRT offers functional imaging capabilities with advantages in portability, safety, and speed, its limitations - such as lack of deep-tissue penetration and protocol standardization - remain significant barriers to broader adoption. Future directions include the integration of IRT with other imaging modalities and digital health platforms to enhance musculoskeletal assessment and injury prevention strategies.
Artificial intelligence (AI) is transforming intensive care medicine by enabling data-driven, real-time decision-making in complex and high-acuity clinical environments. However, its rapid incorporation into healthcare presents profound ethical, clinical, and professional challenges that warrant comprehensive evaluation. This structured narrative review synthesises literature published between 2015 and 2025 to explore how artificial intelligence supports diagnostic, prognostic, monitoring, and therapeutic decision-making in intensive care units (ICUs) and to assess its implications for nursing and medical practice. The findings reveal that AI enhances diagnostic precision, predictive accuracy, and workflow efficiency while improving patient safety and optimising resource utilisation. Nonetheless, ongoing concerns about interpretability, accountability, data quality, and algorithmic bias underscore the necessity for transparent governance, ethical oversight, and multidisciplinary collaboration. Distinctively, this review integrates technological, ethical, and interprofessional perspectives to present a holistic framework for understanding human-artificial intelligence collaboration in critical care. It emphasises that sustainable adoption depends on explainable, context-sensitive systems, clinician engagement, and the inclusion of AI literacy in professional training. This review advances the discourse by framing AI not as a replacement but as a transformative partner, arguing that the future of intensive care lies in harmonising computational precision with clinical empathy to deliver ethical, equitable, and patient-centred outcomes.
Excessive fructose consumption has emerged as a critical driver of obesity and metabolic dysfunction, with far-reaching implications for multiple organ systems. This review synthesizes current evidence on the biochemical and molecular pathways underlying fructose induced disease mechanisms, discussing how fructose metabolism activates the “survival switch”, promotes fat storage, and generates uric acid, mitochondrial dysfunction, and oxidative stress, thereby disrupting energy homeostasis. Key organ-specific consequences are explored, including hepatic steatosis and progression to non-alcoholic fatty liver disease, pancreatic β-cell dysfunction, renal fibrosis, intestinal barrier disruption with microbial dysbiosis, cardiometabolic impairment, pulmonary inflammation, and neurocognitive decline with relevance to Alzheimer’s disease. Moreover, mechanistic insights highlight the role of fructokinase C activation, adenosine triphosphate (ATP) depletion, leptin resistance, pro-inflammatory signaling (mechanistic target of rapamycin complex-1 (mTORC1), renin angiotensin system (RAS), Toll-like receptor 4 (TLR4)), and cross-talk between fructose metabolism and organ-specific pathophysiology. Animal and human studies consistently reinforce the central role of fructose overload in driving obesity and associated complications. Meanwhile, this review frames fructose not merely as a caloric contributor but as a metabolic disruptor, thereby underscoring the urgent need for public health interventions, dietary regulation, and mechanistic research to mitigate fructose-driven metabolic disease.
