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Abstract We introduce a new class of chemical probes for activity‐based sensing of proteases, termed cleavable, locked initiator probes (CLIPs). CLIPs contain a protease‐cleavable peptide linked between two programmable DNA strands—an “initiator” DNA and a shorter “blocking” DNA. These DNA sequences are designed to hybridize, creating a “locked” hairpin‐like structure. Upon proteolytic cleavage, the initiator strand is released, triggering the activation of CRISPR‐Cas12a enzymes and producing an amplified fluorescence response. CLIPs generate more than 20‐fold turn‐on signals at room temperature (25 °C), significantly outperforming commercial probes by yielding ∼40‐fold lower limits of detection (LOD) at 100‐fold lower concentrations. Their versatility enables the detection of various disease‐relevant proteases—including the SARS‐CoV‐2 main protease, caspase‐3, matrix metalloproteinase‐7, and cathepsin B—simply by altering the peptide sequence. Importantly, CLIPs detect cathepsin B in four different colorectal cancer cell lines, highlighting their clinical potential. Taken together, the sensitivity (LOD: ∼88 pM), selectivity, and rapid assay time (down to 35 min), combined with the ability to operate in complex biological media with minimal sample preparation, position CLIPs as powerful chemical tools for activity‐based sensing of functional enzymes. 

Genetically encoded fluorescent protein and fluorogenic RNA sensors are indispensable tools for imaging biomolecules in cells. To expand the toolboxes and improve the generalizability and stability of this type of sensor, we report herein a genetically encoded fluorogenic DNA aptamer (GEFDA) sensor by linking a fluorogenic DNA aptamer for dimethylindole red with an ATP aptamer. The design enhances red fluorescence by 4-fold at 650 nm in the presence of ATP. Additionally, upon dimerization, it improves the signal-to-noise ratio by 2–3 folds. We further integrated the design into a plasmid to create a GEFDA sensor for sensing ATP in live bacterial and mammalian cells. This work expanded genetically encoded sensors by employing fluorogenic DNA aptamers, which offer enhanced stability over fluorogenic proteins and RNAs, providing a novel tool for real-time monitoring of an even broader range of small molecular metabolites in biological systems. 

Neural mechanisms and underlying directionality of signaling among brain regions depend on neural dynamics spanning multiple spatiotemporal scales of population activity. Despite recent advances in multimodal measurements of brain activity, there is no broadly accepted multiscale dynamical models for the collective activity represented in neural signals. Here we introduce a neurobiological-driven deep learning model, termedmultiscale neuraldynamicsneuralordinarydifferentialequation (msDyNODE), to describe multiscale brain communications governing cognition and behavior. We demonstrate that msDyNODE successfully captures multiscale activity using both simulations and electrophysiological experiments. The msDyNODE-derived causal interactions between recording locations and scales not only aligned well with the abstraction of the hierarchical neuroanatomy of the mammalian central nervous system but also exhibited behavioral dependences. This work offers a new approach for mechanistic multiscale studies of neural processes.