4.8 Article

Surface Topography-Adaptive Robotic Superstructures for Biofilm Removal and Pathogen Detection on Human Teeth

期刊

ACS NANO
卷 16, 期 8, 页码 11998-12012

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.2c01950

关键词

reconfigurable; multiscale; complex topography; shear force; antimicrobial; diagnostic sampling; antibiofilm

资金

  1. National Institute for Dental and Craniofacial Research (NIDCR), National Institutes of Health [R01DE025848, R56DE029985]
  2. Procter Gamble
  3. NIDCR [R90DE031532]
  4. Sungkyunkwan University

向作者/读者索取更多资源

Scientists have developed a magnetic field-directed self-assembling robotic superstructure called STARS, which can adapt to irregular surface topography and be used for precise removal of biofilms and diagnostic sampling. These superstructures have multiaxis motion and adjustable shape, length, and stiffness, allowing them to scrub adherent biofilms, produce antibacterial reagents, and capture pathogens and matrix components for diagnostic analysis.
The eradication of biofilms remains an unresolved challenge across disciplines. Furthermore, in biomedicine, the sampling of spatially heterogeneous biofilms is crucial for accurate pathogen detection and precise treatment of infection. However, current approaches are incapable of removing highly adhesive biostructures from topographically complex surfaces. To meet these needs, we demonstrate magnetic field-directed assembly of nanoparticles into surface topography-adaptive robotic superstructures (STARS) for precision-guided biofilm removal and diagnostic sampling. These structures extend or retract at multilength scales (micro-to-centimeter) to operate on opposing surfaces and rapidly adjust their shape, length, and stiffness to adapt and apply high-shear stress. STARS conform to complex surface topographies by entering angled grooves or extending into narrow crevices and scrub adherent biofilm with multiaxis motion while producing antibacterial reagents on-site. Furthermore, as the superstructure disrupts the biofilm, it captures bacterial, fungal, viral, and matrix components, allowing sample retrieval for multiplexed diagnostic analysis. We apply STARS using automated motion patterns to target complex three-dimensional geometries of ex vivo human teeth to retrieve biofilm samples with microscale precision, while providing toothbrushing-like and flossing-like action with antibacterial activity in real-time to achieve mechanochemical removal and multikingdom pathogen detection. This approach could lead to autonomous, multifunctional antibiofilm platforms to advance current oral care modalities and other fields contending with harmful biofilms on hard-to-reach surfaces.

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