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Label-Free Single Nanoparticle Identification and Characterization in Demanding Environment, Including Infectious Emergent Virus.
Nguyen, Minh-Chau; Bonnaud, Peter; Dibsy, Rayane; Maucort, Guillaume; Lyonnais, Sébastien; Muriaux, Delphine; Bon, Pierre.
Affiliation
  • Nguyen MC; UMR 7252, CNRS, XLIM, Université de Limoges, Limoges, F-87000, France.
  • Bonnaud P; UMR 7252, CNRS, XLIM, Université de Limoges, Limoges, F-87000, France.
  • Dibsy R; UMR 9004 CNRS, IRIM (Institut de Recherche en Infectiologie de Montpellier), Université de Montpellier, Montpellier, F-34293, France.
  • Maucort G; Laboratoire Photonique Numérique et Nanosciences, University of Bordeaux, Talence, F-33400, France.
  • Lyonnais S; LP2N UMR 5298, Institut d'Optique Graduate School, CNRS, Talence, F-33400, France.
  • Muriaux D; UAR 3725 CNRS, CEMIPAI, Université de Montpellier, Montpellier, F-34000, France.
  • Bon P; UMR 9004 CNRS, IRIM (Institut de Recherche en Infectiologie de Montpellier), Université de Montpellier, Montpellier, F-34293, France.
Small ; 20(16): e2304564, 2024 Apr.
Article in En | MEDLINE | ID: mdl-38009767
Unknown particle screening-including virus and nanoparticles-are keys in medicine, industry, and also in water pollutant determination. Here, RYtov MIcroscopy for Nanoparticles Identification (RYMINI) is introduced, a staining-free, non-invasive, and non-destructive optical approach that is merging holographic label-free 3D tracking with high-sensitivity quantitative phase imaging into a compact optical setup. Dedicated to the identification and then characterization of single nano-object in solution, it is compatible with highly demanding environments, such as level 3 biological laboratories, with high resilience to external source of mechanical and optical noise. Metrological characterization is performed at the level of each single particle on both absorbing and transparent particles as well as on immature and infectious HIV, SARS-CoV-2 and extracellular vesicles in solution. The capability of RYMINI to determine the nature, concentration, size, complex refractive index and mass of each single particle without knowledge or model of the particles' response is demonstrated. The system surpasses 90% accuracy for automatic identification between dielectric/metallic/biological nanoparticles and ≈80% for intraclass chemical determination of metallic and dielectric. It falls down to 50-70% for type determination inside the biological nanoparticle's class.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Viruses / Holography / Nanoparticles / Metal Nanoparticles Language: En Journal: Small Journal subject: ENGENHARIA BIOMEDICA Year: 2024 Type: Article Affiliation country: France

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Viruses / Holography / Nanoparticles / Metal Nanoparticles Language: En Journal: Small Journal subject: ENGENHARIA BIOMEDICA Year: 2024 Type: Article Affiliation country: France