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Investigating The Environmental And Molecular Dependence Of Single-Molecule Blinking-Based Multiplexing
DeSalvo, Grace
DeSalvo, Grace
Abstract
Visualizing nanoscale biological systems allows us to uncover their detailed structure and functions, which have major implications in the biomedical field. Super-resolution microscopy is a powerful tool for fluorescence imaging because, by overcoming the diffraction limit of light, it accesses structural detail with unprecedented spatial resolution. Although multicolor super-resolution imaging has been successfully implemented in many experiments, its efficiency is limited by reliance on spectral measurement for emitter identification, which limits the combinations of compatible probes to be used together. Blinking-based multiplexing (BBM) is a novel approach that circumvents the need for spectrally-distinct emitters by instead exploiting the intrinsic differences in their blinking dynamics, or the stochastic fluctuations in emissive and nonemissive intensities of single-molecules under continuous photoexcitation. We find that BBM is most efficiently carried out using multinomial logistic regression (LR) to classify hundreds blinking dynamics obtained through single-molecule spectroscopy (SMS). Blinking dynamics are captured for three emitters—quantum dots (QD), rhodamine 6G (R6G), and pyrromethene 605 (PM605)— both on glass substrate and in complex poly(vinyl alcohol) (PVA) matrix for analysis with LR. Our results show that LR rapidly generates highly accurate predictive models for a variety of emitter systems under many experimental conditions.
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2023-01-01
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Chemistry
DOI
https://dx.doi.org/10.21220/s2-sam6-a089