A Hotspot-Based Nano-Integrated Smart Vascular Interface for Long-Term Local Inflammation Sensing and Therapeutic Response

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Authors: Begüm Yıldırım
Cited by: 0

Abstract

Despite major advances in vascular interventions, current stent-based therapies remain fundamentally passive, providing mechanical support without continuous insight into the evolving biological state of the vessel wall. Restenosis, thrombosis, and plaque destabilization are driven by localized inflammatory and biochemical processes that cannot be directly monitored after implantation. Here, we propose a unified experimental architecture for a smart vascular interface that integrates physical nanosensing, biochemical nanosensing, and localized drug delivery within a single stent-based platform. The system employs a hotspot-based nano-density strategy, concentrating advanced nanosensors in regions prone to restenosis and plaque activity, while maintaining low surface complexity elsewhere to reduce thrombotic risk. Long-term stability is addressed through a multi-layer special technology stack, including antifouling nano-coatings, selective permeable membranes, dual-channel reference sensing, and vessel-wall–adjacent sensor placement. Rather than claiming immediate clinical deployment, this work defines a new class of living vascular implants designed for experimental validation and future translational development. Language editing assistance was provided using an AI-based tool. Originality and AI-use statement: This work is an original research output by Begüm Yıldırım. AI tools, if used, were limited to language refinement, grammar correction, formatting, translation assistance, and clarity improvement. The conceptual framework, research direction, interpretation, models, and conclusions belong to the author. External sources, datasets, or prior works are cited where applicable.

Fields of Study & Subjects

Coronary Interventions and Diagnostics Analytical Chemistry and Sensors Tissue Engineering and Regenerative Medicine

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
11 March 2026
Language
EN
Document type
Preprint