Artificial Intelligence-Aided Massively Parallel Spectroscopy of Freely Diffusing Nanoscale Entities - Hlaváček, Antonín; Uhrová, Kateřina; Weisová, Julie; Křivánková, Jana (Analytical chemistry, 2023)
Massively parallel spectroscopy (MPS) of many single nanoparticles in an aqueous dispersion is reported. As a model system, bioconjugated photon-upconversion nanoparticles (UCNPs) with a near-infrared excitation are prepared. The UCNPs are doped either with Tm3+ (emission 450 and 802 nm) or Er3+ (emission 554 and 660 nm). These UCNPs are conjugated to biotinylated bovine serum albumin (Tm3+-doped) or streptavidin (Er3+-doped). MPS is correlated with an ensemble spectra measurement, and the limit of detection (1.6 fmol L-1) and the linearity range (4.8 fmol L-1 to 40 pmol L-1) for bioconjugated UCNPs are estimated. MPS is used for observing the bioaffinity clustering of bioconjugated UCNPs. This observation is correlated with a native electrophoresis and bioaffinity assay on a microtiter plate. A competitive MPS bioaffinity assay for biotin is developed and characterized with a limit of detection of 6.6 nmol L-1. MPS from complex biological matrices (cell cultivation medium) is performed without increasing background. The compatibility with polydimethylsiloxane microfluidics is proven by recording MPS from a 30 μm deep microfluidic channel.
Keywords: Artificial Intelligence; umělá inteligence; Spectrum Analysis; Nanoparticles; streptavidin; Streptavidin; nanočástice; spektrální analýza