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Chao, J.

Publications and source records attributed to Chao, J..

20 records · Page 2Linked to original sources

Designer DNA architecture offers precise and multivalent spatial pattern-recognition for viral sensing and inhibition

DNA, when folded into nanostructures of customizable shapes, is capable of spacing and arranging external ligands in a desired geometric pattern with nanometer-precision. This allows DNA to serve as an excellent, biocompatible scaffold for complex spatial pattern-recognizing displays. In this report, we demonstrate that a templated designer DNA nanostructure achieves multi-ligand display with precise spatial pattern-recognition, representing a unique strategy in synthesizing potent viral sensors and inhibitors. Specifically, a star-shaped DNA architecture, carrying five molecular beacon-like motifs, was constructed to display ten dengue virus envelope protein domain-III (ED3)-binding aptamers into a 2D pattern precisely matching the pentagonal arrangement of ED3 clusters on the dengue viral surface. The resulting spatial pattern recognition and multivalent interactions achieve high dengue-binding avidity, conferring direct, highly-sensitive, facile, low-cost, and rapid sensing as well as potent viral inhibition capability. Our molecular-platform design strategy could be adapted to detect and combat other disease-causing pathogens, including bacteria and microbial-toxins, by generating the requisite ligand patterns on customized DNA nanoarchitectures.

bioengineering↗

Intensity-based axial localization approaches for multifocal plane microscopy

Multifocal plane microscopy (MUM) can be used to visualize biological samples in three dimensions over large axial depths and provides for the high axial localization accuracy that is needed in applications such as the three-dimensional tracking of single particles and superresolution microscopy. This report analyzes the performance of intensity-based axial localization approaches as applied to MUM data using Fisher information calculations. In addition, a new non-parametric intensity-based axial location estimation method, Multi-Intensity Lookup Algorithm (MILA), is introduced that, unlike typical intensity-based methods that make use of a single intensity value per data image, utilizes multiple intensity values per data image in determining the axial location of a point source. MILA is shown to be robust against potential bias induced by differences in the sub-pixel location of the imaged point source. The method's effectiveness on experimental data is also evaluated.

biophysics↗