Type 2 diabetes mellitus (DM2) is a chronic metabolic disease. Silver nanoparticles (AgNPs) show promise in their treatment. This study assessed the potential of AgNPs as DM2 treatment agent using in vitro, in vivo, and machine learning approaches. M...
The escalating global crisis of multidrug-resistant (MDR) bacteria demands innovative strategies that bypass conventional antibiotic limitations. This study introduced a multifunctional Au@CuSe core-shell nanoplatform integrating artificial intellige...
Urinary glucose, creatinine, and uric acid are vital biomarkers for diabetes and kidney disease management. However, multiplex point-of-care detection faces challenges due to insufficient sensitivity in complex urine matrices and signal cross-talk fr...
Pathogenic bacteria pose serious threats to public health and environmental safety. Conventional colony counting, a standard method for bacterial detection, is time-consuming and unsuitable for rapid on-site detection. In this work, a flexible ACH/Ag...
Proceedings of the National Academy of Sciences of the United States of America
Nov 24, 2025
Cryoelectron tomography (cryo-ET) enables three-dimensional visualization of molecular structures within tissue and intact cells, providing a powerful tool for studying the spatial organization of biological components at nanometer resolution. Realiz...
Journal of materials science. Materials in medicine
Nov 21, 2025
Metal oxide nanomaterials play a central role in biomedical applications due to their unique physicochemical properties. In particular, various treatment methods such as drug delivery, hyperthermia therapy, radiation, and chemotherapy are used for th...
The overused quinolone antibiotics in animal husbandry and clinical medicine pose a growing threat for global health as they enter ecosystem via agricultural discharge and medical wastewater. Consequently, risk assessment for environmental and human ...
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...
Recently, the severe side effects related to the widespread consumption of antidepressants (ADs) have alarmingly created a global challenge for clinics and forensic laboratories. This study introduces a machine learning-empowered multicolor fluoresce...
Signature-based protein detection coupled with machine learning algorithms has revolutionized traditional sensing methods, providing rapid, inexpensive, and selectivity-driven detection without the use of specialized equipment. This strategy leverage...
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