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Nucleases present a formidable barrier to the application of nucleic acids in biology, significantly reducing the lifetime of nucleic acid-based drugs. Here, we develop a novel methodology to protect DNA and RNA from nucleases by reconfiguring their supramolecular structure through the addition of a nucleobase mimic, cyanuric acid. In the presence of cyanuric acid, polyadenine strands assemble into triple helical fibers known as the polyA/CA motif. We report that this motif is exceptionally resistant to nucleases, with the constituent strands surviving for up to 1 month in the presence of serum. The conferred stability extends to adjacent non-polyA sequences, albeit with diminishing returns relative to their polyA sections due to hypothesized steric clashes. We introduce a strategy to regenerate stability through the introduction of free polyA strands or positively charged amino side chains, enhancing the stability of sequences of varied lengths. The proposed protection mechanism involves enzyme failure to recognize the unnatural polyA/CA motif, coupled with the motif’s propensity to form long, bundling supramolecular fibers. The methodology provides a fundamentally new mechanism to protect nucleic acids from degradation using a supramolecular approach and increases lifetime in serum to days, weeks, or months.

We developed Significant Latent Factor Interaction Discovery and Exploration (SLIDE), an interpretable machine learning approach that can infer hidden states (latent factors) underlying biological outcomes. These states capture the complex interplay between factors derived from multiscale, multiomic datasets across biological contexts and scales of resolution.

Summary: Researchers unveiled a pioneering technology capable of real-time human emotion recognition, promising transformative applications in wearable devices and digital services.

The system, known as the personalized skin-integrated facial interface (PSiFI), combines verbal and non-verbal cues through a self-powered, stretchable sensor, efficiently processing data for wireless communication.

This breakthrough, supported by machine learning, accurately identifies emotions even under mask-wearing conditions and has been applied in a VR “digital concierge” scenario, showcasing its potential to personalize user experiences in smart environments. The development is a significant stride towards enhancing human-machine interactions by integrating complex emotional data.

How Does The Neutral Atom Approach Compare

The neutral atom approach is a well-known and extensively investigated approach to quantum computing. The approach offers numerous advantages, especially in terms of scalability, expense, error mitigation, error correction, coherence, and simplicity.

Neutral atom quantum computing utilizes individual atoms, typically alkali atoms like rubidium or cesium, suspended and isolated in a vacuum and manipulated using precisely targeted laser beams. These atoms are not ionized, meaning they retain all their electrons and do not carry an electric charge, which distinguishes them from trapped ion approaches. The quantum states of these neutral atoms, such as their energy levels or the orientation of their spins, serve as the basis for qubits. By employing optical tweezers—focused laser beams that trap and hold the atoms in place—arrays of atoms can be arranged in customizable patterns, allowing for the encoding and manipulation of quantum information.

A team of researchers has found that Neanderthals crafted stone tools using a sophisticated multi-component glue. This discovery, the oldest known example of such an advanced adhesive in Europe, indicates that these early human relatives possessed a greater degree of intellectual and cultural sophistication than was earlier believed.

The work, reported in the journal Science Advances, included researchers from New York University, the University of Tübingen, and the National Museums in Berlin.