General Objectives

Non-communicable diseases (NCDs) are a significant global health concern, posing substantial challenges to healthcare systems worldwide. The ten most common NCDs include cancer, chronic respiratory diseases, cardiovascular diseases, diabetes, Alzheimer’s and other dementias, kidney diseases, liver diseases, musculoskeletal disorders, mental health disorders, and oral diseases, with cancer, chronic respiratory diseases, cardiovascular diseases, and diabetes accounting for over two-thirds of global deaths. The European Commission’s initiatives, such as “Healthier Together – EU NCDs Initiative” and “Europe’s Beating Cancer Plan,” aim to reduce the burden of major NCDs and improve citizens’ health and well-being. These initiatives emphasize better knowledge and data, screening and early detection, diagnosis and treatment management, and improved quality of life for patients. Early detection and accurate monitoring of NCDs are critical for effective management and improved patient outcomes. Conventional biomarkers and imaging techniques have limitations, necessitating innovative biomarkers that can provide more precise and timely information. Mechanical biomarkers, utilizing the mechanical properties of tissues and cells coupled with optical readouts, are emerging as a promising approach for NCD detection and monitoring. The proposed research aims to develop novel MechanoOptical Biomarkers to revolutionize diagnostics by enabling mechanical characterization and high-resolution imaging of diseased tissues with enhanced sensitivity and specificity. This project will focus on assessing the MechanoOptical fingerprints (MOFPs) of NCDs, specifically cancer (desmoplastic tumors, like breast and melanoma) and pulmonary fibrosis. The hypothesis is that supplementary information from different microscopes (Brillouin and Atomic Force Microscope-AFM) can be used to develop novel MechanoOptical biomarkers for NCD diagnosis, treatment monitoring, and prognosis. Cutting-edge technologies and experimental approaches will be leveraged to study, design, and optimize these biomarkers.