Advancements in Engineering Tetrahedral Framework Nucleic Acids for Biomedical Innovations.

Tetrahedral framework nucleic acids (tFNAs) are renowned for their controllable self-assembly, exceptional programmability, and excellent biocompatibility, which have led to their widespread application in the biomedical field. Beyond these features, tFNAs demonstrate unique chemical and biological properties including high cellular uptake efficiency, structural bio-stability, and tissue permeability, which are derived from their distinctive 3D structure. To date, an extensive range of tFNA-based nanostructures are intelligently designed and developed for various biomedical applications such as drug delivery, gene therapy, biosensing, and tissue engineering, among other emerging fields.

Active Clustering Ensemble With Self-Paced Learning.

A clustering ensemble provides an elegant framework to learn a consensus result from multiple prespecified clustering partitions. Though conventional clustering ensemble methods achieve promising performance in various applications, we observe that they may usually be misled by some unreliable instances due to the absence of labels. To tackle this issue, we propose a novel active clustering ensemble method, which selects the uncertain or unreliable data for querying the annotations in the process of the ensemble.