This research demonstrates enhanced endothelial cell proliferation on polymer substrates with mesoscale patterns, implying better vascular applications.
Introduction: Mesoscopic topological cues can significantly enhance endothelialization, a critical factor in blood-contact applications. The use of polydimethylsiloxane (PDMS) substrates faces several limitations, such as slow degradation rate and surface-to-volume ratio, limited permeability, and scalability. This study introduces a hybrid fabrication method combining lithography and electrodeposition to produce large-scale, permeable, fiber-based scaffolds with mesoscale patterns designed to improve endothelial response and reduce thrombogenicity. Methods: Direct laser writing was used to ablate photoresist layers on conductive substrates, creating square, honeycomb, and microgroove patterns (60μm sides, 20μm gaps) in 1μm and 4μm thicknesses. Electrodeposition of Tecoflex60D in hexa-fluoro-2-propanol followed, forming the fibrous scaffold. Pattern fidelity was assessed via correlation-based code and CAD comparison. SEM and digital image analysis evaluated scaffold morphology and fiber alignment, quantified through the Orientation Index (OI), with values from 0.5 (random) to 1.0 (perfect alignment). Endothelial and smooth muscle cells were seeded to test proliferation and viability. Results: Pattern transfer accuracy reached 90% across all geometries. OI values varied by pattern and thickness: square (0.58–0.66), honeycomb (0.64 to 0.55), and grooves (0.57–0.63) from 1 μm to 4 μm. Cellular assays confirmed robust adhesion and proliferation on all substrates. Discussion: The hybrid method reliably replicates mesoscale patterns onto fibrous scaffolds. Thicker (4 μm) patterns improved fiber alignment in square and groove geometries, while 1 μm patterns resulted in random orientation (OI≈0.55-0.58). This proprietary technique(US2024/0016983A1) supports cellular viability and shows potential for scalable fabrication of 4×4 cm microfiber substrates suitable for vascular and organ-level applications.
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Baccarella et al. (2025) studied this question.
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