Multiplex localization of sequential peptide epitopes by use of a planar microbead chip

Machine learning implementation strategy in imaging and impedance flow cytometry

Imaging and impedance flow cytometry is a label-free technique that has shown promise as a potential replacement for standard flow cytometry. This is due to its ability to provide rich information and archive high-throughput analysis. Recently, significant efforts have been made to leverage machine learning for processing the abundant data generated by those techniques, enabling rapid and accurate analysis. Harnessing the power of machine learning, imaging and impedance flow cytometry has demonstrated its capability to address various complex phenotyping scenarios. Herein, we present a comprehensive overview of the detailed strategies for implementing machine learning in imaging and impedance flow cytometry. We initiate the discussion by outlining the commonly employed setup to acquire the data (i.e., image or signal) from the cell. Subsequently, we delve into the necessary processes for extracting features from the acquired image or signal data. Finally, we discuss how these features can be utilized for cell phenotyping through the application of machine learning algorithms. Furthermore, we discuss the existing challenges and provide insights for future perspectives of intelligent imaging and impedance flow cytometry.

A new reporter design based on DNA origami nanostructures for quantification of short oligonucleotides using microbeads

The DNA origami technique has great potential for the development of brighter and more sensitive reporters for fluorescence based detection schemes such as a microbead-based assay in diagnostic applications. The nanostructures can be programmed to include multiple dye molecules to enhance the measured signal as well as multiple probe strands to increase the binding strength of the target oligonucleotide to these nanostructures. Here we present a proof-of-concept study to quantify short oligonucleotides by developing a novel DNA origami based reporter system, combined with planar microbead assays. Analysis of the assays using the VideoScan digital imaging platform showed DNA origami to be a more suitable reporter candidate for quantification of the target oligonucleotides at lower concentrations than a conventional reporter that consists of one dye molecule attached to a single stranded DNA. Efforts have been made to conduct multiplexed analysis of different targets as well as to enhance fluorescence signals obtained from the reporters. We therefore believe that the quantification of short oligonucleotides that exist in low copy numbers is achieved in a better way with the DNA origami nanostructures as reporters.