Emerging Technologies for Exploring the Cellular Mechanisms in Vascular Diseases

Published Abstract (Verbatim Bibliographic Record)

Vascular diseases (VDs) and cardiovascular diseases (CVDs) are the leading causes of morbidity and mortality worldwide. Current diagnostic and therapeutic approaches are limited by insufficient resolution and a lack of mechanistic understanding at the cellular level. Traditional imaging and clinical assays do not fully capture the dynamic molecular and structural complexities underlying vascular pathology. Recent technological innovations, including single-cell and spatial transcriptomics, super-resolution and photoacoustic imaging, microfluidic organ-on-chip platforms, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-based gene editing, and artificial intelligence (AI), have created new opportunities for investigating the cellular and molecular basis of VDs. These techniques enable high-resolution mapping of cellular heterogeneity and functional alterations, facilitating the integration of large-scale data for biomarker discovery, disease modeling, and therapeutic development. This review focuses on evaluating the translational readiness, limitations, and potential clinical applications of these emerging technologies. Understanding the cellular and molecular mechanisms of VDs is essential for developing targeted therapies and precise diagnostics. Integrating single-cell and multiomics approaches highlights disease-driving cell types and gene programs. Optogenetics and organ-on-chip platforms allow for controlled manipulation and physiologically relevant modeling, while AI enhances data integration, risk prediction, and clinical interpretability. Future efforts should prioritize multi-center, large-scale validation studies, harmonization of assay protocols, and integration with clinical datasets and human samples. Multi-omics approaches and computational modeling hold promise for unraveling disease complexity, while advances in regulatory science and digital simulation (such as digital twins) may further accelerate personalized medicine in vascular disease research and treatment.

Bibliographic Metadata

Journal / Book

International Journal of Molecular Sciences

Publication Date / Volume

2025;27(1):164

Digital Object Identifier (DOI)

https://doi.org/10.3390/ijms27010164

PubMed ID (PMID)

41516041

Leadership Authorship

First Author (Debasis Sahu, PhD) · ORCID 0000-0003-1720-2680