Amplification-free Cas12a diagnostics with split crRNA enable rapid and programmable target recognition, yet insufficient understanding of DNA activator architecture prevents predictable control over trans-cleavage activity and sensitivity. Here we systematically map over 200 split DNA activator configurations by introducing nicks at every position across both strands. The mapping reveals that target strand nicks suppress activity with position-dependent severity, while non-target strand nicks enhance activity. Guided by these rules, we engineer an optimized split activator pair that achieves attomolar microRNA detection (LOD: 112 aM), ∼480-fold higher sensitivity than intact activators. The enhanced sensitivity supports multiplexed live-cell profiling of five miRNAs for machine learning-based cancer cell stratification, and is further generalized to non-nucleic acid targets, including APE1 enzyme (0.0073 U/L) and HClO (2.37 pM) through position-informed cleavable sites. This work provides a generalizable methodology for engineering CRISPR-Cas12a performance across diagnostic and biosensing applications.
Intelligent perception with closed-loop information acquisition, processing, and feedback is critical for humanoid robots and embodied intelligence systems. Ionochromic transistors hold great potential for on-site signal processing and visual feedback. Here, we report a bioinspir…
Cortical surface reconstruction of white matter and pial surfaces from diffusion MRI (dMRI) is critical for neuroimaging analyses, including tractography, connectomics, and multimodal data integration. However, obtaining these surfaces from dMRI data is inherently challenged by i…
Protein glycosylation, a post-translational modification involving the attachment of glycans to proteins, plays critical roles in numerous physiological and pathological cellular functions. Characterization of protein glycosylation is one of the most challenging problems due to t…
ABSTRACT Engineering the surface structure of catalysts is critical for achieving high intrinsic activity in the oxygen reduction reaction (ORR). We report a machine‐learning (ML)‐guided materials design strategy for the synthesis of support‐free, connected nanoparticle catalysts…