Two-Photon DNAzyme-Gold Nanoparticle Probe for Imaging Intracellular Metal Ions.

RNA-cleaving DNAzymes have been demonstrated as a promising platform for sensing metal ions. However, the poor biological imaging performance of RNA-cleaving DNAzyme-based fluorescent probes has limited their intracellular applications. Compared with traditional one-photon fluorescence imaging, two-photon (TP) fluorescent probes have shown advantages such as increased penetration depth, lower tissue autofluorescence, and reduced photodamage. Herein, for the first time, we developed an RNA-cleaving DNAzyme-based TP imaging probe (TP-8-17ES-AuNP) for Zn2+ detection in living cells by modifying a Zn2+-specific DNAzyme (8-17) with a TP fluorophore (TP-8-17ES) and using gold nanoparticles (AuNPs) for intracellular delivery. The modified TP-8-17ES exhibits good two-photon properties and excellent photostability. For the TP-8-17ES-AuNP, in the absence of Zn2+, the TP fluorophore is quenched by both AuNPs and the molecular quencher. Only in the presence of Zn2+ does the DNAzyme cleave the TP fluorophore-labeled substrate strand, resulting in fluorescence enhancement and TP imaging. Such probe shows remarkable selectivity of Zn2+ over other metal ions existing in the biological environment. Benefiting from the labeled TP fluorophore, the near-infrared (NIR) excited probe has the capability of TP imaging of Zn2+ in living cells and tissue with a deep tissue penetration up to 160 µm. This method can be generally applied to detect other metal ions in biological systems under TP imaging with higher tissue penetration ability and lower phototoxicity.

An efficient approach to the quantitative analysis of humic acid in water.

Rayleigh and Raman scatterings inevitably appear in fluorescence measurements, which make the quantitative analysis more difficult, especially in the overlap of target signals and scattering signals. Based on the grayscale images of three-dimensional fluorescence spectra, the linear model with two selected Zernike moments was established for the determination of humic acid, and applied to the quantitative analysis of the real sample taken from the Yellow River. The correlation coefficient (R(2)) and leave-one-out cross validation correlation coefficient (R(2)cv) were up to 0.9994 and 0.9987, respectively. The average recoveries were reached 96.28%. Compared with N-way partial least square and alternating trilinear decomposition methods, our approach was immune from the scattering and noise signals owing to its powerful multi-resolution characteristic and the obtained results were more reliable and accurate, which could be applied in food analyses.