4.8 Article

The Role of Dendritic Mesoporous Silica Nanoparticles' Size for Quantum Dots Enrichment and Lateral Flow Immunoassay Performance

Journal

SMALL METHODS
Volume 5, Issue 4, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/smtd.202000924

Keywords

dendritic mesoporous silica; lateral flow immunoassays; quantum dots; ultrasensitive detection

Funding

  1. ARC Linkage project
  2. Shanghai Fosun Long March Medical Science Co. Ltd.
  3. Advance Queensland Research Fellowship
  4. Ellume Limited
  5. Australian National Fabrication Facility at the Centre for Microscopy and Microanalysis, the University of Queensland
  6. Australian Microscopy and Microanalysis Research Facility at the Centre for Microscopy and Microanalysis, the University of Queensland

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This study developed a new method to prepare water-dispersible DMSNs-QDs, with the optimal size of 368 nm for the detection of C-reactive protein with high sensitivity.
Using dendritic mesoporous silica nanoparticles (DMSNs) for quantum dots (QDs) enrichment and signal amplification is an emerging strategy for improving the detection sensitivity of lateral flow immunoassay (LFIA). In this study, a new and convenient approach is developed to prepare water-dispersible DMSNs-QDs. A series of DMSNs with various diameters (138, 251, 368, and 471 nm) are studied for loading QDs and LFIA applications. The resultant water-dispersible DMSNs-QDs exhibit a high fluorescence retention of 81.8%. The increase in particle size from 138 to 471 nm results in an increase in loading capacity of QDs and a decrease in binding quantity of the DMSNs-QDs in the test line of LFIA. This trade-off leads to an optimal DMSNs-QDs size of 368 nm with a limit of detection reaching 10 pg mL(-1) (equivalent to 9.0 x 10(-14) m) for the detection of C-reactive protein, which is nearly an order of magnitude more sensitive than the literature. To the best of the authors' knowledge, this study is the first to demonstrate the distinctive role of DMSN's size for QDs enrichment and LFIA. The strategy developed from this work is useful for the rational design of high-quality QDs-based nanoparticles for ultrasensitive detection.

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