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We created 29 parallel double-crossover DNA motifs varying in hybridization pathways, domain lengths, and crossover locations, producing diverse assemblies.

 

DNA tiles serve as the fundamental building blocks for DNA self-assembled nanostructures such as DNA arrays, origami, and designer crystals. Introducing additional binding arms to DNA crossover tiles holds the promise of unlocking diverse nano-assemblies and potential applications. Here, we present one-, two-, and three-layer T-shaped crossover tiles, by integrating T junction with antiparallel crossover tiles. These tiles carry over the orthogonal binding directions from T junction and retain the rigidity from antiparallel crossover tiles, enabling the assembly of various 2D tessellations. To demonstrate the versatility of the design rules, we create 2-state reconfigurable nanorings from both single-stranded tiles and single-unit assemblies. Moreover, four sets of 4-state reconfiguration systems are constructed, showing effective transformations between ladders and/or rings with pore sizes spanning ~20 nm to ~168 nm. These DNA tiles enrich the design tools in nucleic acid nanotechnology, offering exciting opportunities for the creation of artificial dynamic DNA nanopores.

 

High-resolution albedo has the advantage of a higher spatial scale from tens to hundreds of meters, which can fill the gaps of albedo applications from the global scale to the regional scale and can solve problems related to land use change and ecosystems. The Sentinel-2 satellite provides high-resolution observations in the visible-to-NIR bands, giving possibilities to generate a high-resolution surface albedo at 10 m. This study attempted to evaluate the performance of the four data-driven machine learning algorithms (i.e., random forest (RF), artificial neural network (ANN), k-nearest neighbor (KNN), and XGBoost (XGBT)) for the generation of a Sentinel-2 albedo over flat and rugged terrain. First, we used the RossThick-LiSparseR model and the 3D discrete anisotropic radiative transfer (DART) model to build the narrowband surface reflectance and broadband surface albedo, which acted as the training and testing datasets over flat and rugged terrain. Second, we used the training and testing datasets to drive the four machine learning models, and evaluated the performance of these machine learning models for the generation of Sentinel-2 albedo. Finally, we used the four machine learning models to generate a Sentinel-2 albedo and compared them with in situ albedos to show the models’ application potentials. The results show that these machine learning models have great performance in estimating Sentinel-2 albedos at a 10 m spatial scale. The comparison with in situ albedos shows that the random forest model outperformed the others in estimating a high-resolution surface albedo based on Sentinel-2 datasets over the flat and rugged terrain, with an RMSE smaller than 0.0308 and R2 larger than 0.9472. 

Heuristic algorithms can generalize the design process of stiff and round capsule-like nanostructures made from DNA. 

DNA nanotechnology has been proven to be a powerful platform to assist the development of imaging probes for biomedical research. The attractive features of DNA nanostructures, such as nanometer precision, controllable size, programmable functions, and biocompatibility, have enabled researchers to design and customize DNA nanoprobes for bioimaging applications. However, DNA probes with low molecular weights (e.g., 10–100 nt) generally suffer from low stability in physiological buffer environments. To improve the stability of DNA nanoprobes in such environments, DNA nanostructures can be designed with relatively larger sizes and defined shapes. In addition, the established modification methods for DNA nanostructures are also essential in enhancing their properties and performances in a physiological environment. In this review, we begin with a brief recap of the development of DNA nanostructures including DNA tiles, DNA origami, and multifunctional DNA nanostructures with modifications. Then we highlight the recent advances of DNA nanostructures for bioimaging, emphasizing the latest developments in probe modifications and DNA-PAINT imaging. Multiple imaging modules for intracellular biomolecular imaging and cell membrane biomarkers recognition are also summarized. In the end, we discuss the advantages and challenges of applying DNA nanostructures in bioimaging research and speculate on its future developments. 

Over the past few decades, DNA has been recognized as a powerful self-assembling material capable of crafting supramolecular nanoarchitectures with quasi-angstrom precision, which promises various applications in the fields of materials science, nanoengineering, and biomedical science. Notable structural features include biocompatibility, biodegradability, high digital encodability by Watson–Crick base pairing, nanoscale dimension, and surface addressability. Bottom-up fabrication of complex DNA nanostructures relies on the design of fundamental DNA motifs, including parallel (PX) and antiparallel (AX) crossovers. However, paranemic or PX motifs have not been thoroughly explored for the construction of DNA-based nanostructures compared to AX motifs. In this review, we summarize the developments of PX-based DNA nanostructures, highlight the advantages as well as challenges of PX-based assemblies, and give an overview of the structural and chemical features that lend their utilization in a variety of applications. The works presented cover PX-based DNA nanostructures in biological systems, dynamic systems, and biomedical contexts. The possible future advances of PX structures and applications are also summarized, discussed, and postulated. 

Abstract: Structural DNA nanotechnology has been developed into a powerful method for creating self-assembled nanomaterials. Their compatibility with biosystems, nanoscale addressability, and programmable dynamic features make them appealing candidates for biomedical research. This review paper focuses on DNA self-assembly strategies and designer nanostructures with custom functions for biomedical applications. Specifically, we review the development of DNA self-assembly methods, from simple DNA motifs consisting of a few DNA strands to complex DNA architectures assembled by DNA origami. Three advantages are discussed using structural DNA nanotechnology for biomedical applications: (1) precise spatial control, (2) molding and guiding other biomolecules, and (3) using reconfigurable DNA nanodevices to overcome biomedical challenges. Finally, we discuss the challenges and opportunities of employing DNA nanotechnology for biomedical applications, emphasizing diverse assembly strategies to create a custom DNA nanostructure with desired functions.