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Purpose <p>Endothelial cells lining blood vessels continuously experience hemodynamic forces that profoundly influence cardiovascular health and disease. This article investigates how these mechanical stimuli are detected at the molecular level and converted into biological responses that either protect against or promote atherosclerosis. The primary objective is to elucidate the complete signalling architecture from initial force detection to functional outcomes and therapeutic opportunities.</p> Methods <p>We synthesized evidence from experimental approaches spanning molecular biology, live-cell imaging, genetic manipulation, biomechanical testing, and clinical studies. Key methodologies include controlled flow exposure systems, high-resolution microscopy of cellular dynamics, genome editing for functional validation, proteomic and transcriptomic profiling, hemodynamic simulation tools, and analysis of patient vascular specimens.</p> Results <p>Endothelial mechanosensing involves coordinated activity of surface glycoproteins, cell-cell junction proteins, force-sensitive ion channels, and cell-matrix attachment sites. Laminar flow triggers protective programs including nitric oxide generation and anti-inflammatory gene activation. Disturbed flow activates inflammatory pathways, adhesion molecule expression, and barrier disruption. Calcium signalling dynamics differ markedly between flow patterns, encoding distinct downstream transcriptional outputs. Patient-derived cells demonstrate substantial individual variation in mechanosensitive responses, explaining differential disease susceptibility.</p> Conclusions <p>Mechanotransduction knowledge is being translated into hemodynamically-optimized tissue constructs, force-targeted pharmaceuticals, and individualized risk stratification based on personal vascular geometry and cellular responsiveness. Next-generation technologies combining machine learning, spatial molecular mapping, and physiologically-accurate three-dimensional models will enable predictive cardiovascular medicine based on mechanical phenotyping.</p> Graphical Abstract <p></p>

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Endothelial Mechanotransduction: Integrating Hemodynamic Forces, Molecular Signalling, and Bioengineering Platforms for Cardiovascular Precision Medicine

  • 期刊论文

  • 发表日期：

    2026年6月22日

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  • Polu Picheswara Rao,
  • Shubham Mishra,
  • Jaya Gupta

摘要

Purpose

Endothelial cells lining blood vessels continuously experience hemodynamic forces that profoundly influence cardiovascular health and disease. This article investigates how these mechanical stimuli are detected at the molecular level and converted into biological responses that either protect against or promote atherosclerosis. The primary objective is to elucidate the complete signalling architecture from initial force detection to functional outcomes and therapeutic opportunities.

Methods

We synthesized evidence from experimental approaches spanning molecular biology, live-cell imaging, genetic manipulation, biomechanical testing, and clinical studies. Key methodologies include controlled flow exposure systems, high-resolution microscopy of cellular dynamics, genome editing for functional validation, proteomic and transcriptomic profiling, hemodynamic simulation tools, and analysis of patient vascular specimens.

Results

Endothelial mechanosensing involves coordinated activity of surface glycoproteins, cell-cell junction proteins, force-sensitive ion channels, and cell-matrix attachment sites. Laminar flow triggers protective programs including nitric oxide generation and anti-inflammatory gene activation. Disturbed flow activates inflammatory pathways, adhesion molecule expression, and barrier disruption. Calcium signalling dynamics differ markedly between flow patterns, encoding distinct downstream transcriptional outputs. Patient-derived cells demonstrate substantial individual variation in mechanosensitive responses, explaining differential disease susceptibility.

Conclusions

Mechanotransduction knowledge is being translated into hemodynamically-optimized tissue constructs, force-targeted pharmaceuticals, and individualized risk stratification based on personal vascular geometry and cellular responsiveness. Next-generation technologies combining machine learning, spatial molecular mapping, and physiologically-accurate three-dimensional models will enable predictive cardiovascular medicine based on mechanical phenotyping.

Graphical Abstract