Citations

The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.

Abstract Recent times have witnessed an upsurge in the incidence of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, Huntington's disease, Prion disease, and amyotrophic lateral sclerosis. The treatment of the same remains a daunting challenge due to the limited access of therapeutic moieties across the blood–brain barrier. Engineered nanoparticles with a size less than 100 nm provide multifunctional abilities for solving these biomedical and pharmacological issues due to their unique physico‐chemical properties along with capability to cross the blood–brain barrier. Needless to mention, there is a scarcity of review articles summarizing recent developments of various nanomaterials including liposomes, polymeric nanoparticles, metal nanoparticles, and bio‐nanoparticles toward the therapeutic and theranostics applications for various neurodegenerative disorders. Here, a broad spectrum of nanomedicinal approaches to eradicate neurodegenerative disorders is provided, along with a brief account of neuroprotection and neuronal tissue regeneration, current clinical status, issues related to safety, toxicity, challenges, and future outlook.