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Weilin Luo

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Review Jul 2026

Strategic Design and Engineering of CRISPR/Cas-Powered Sensing Platforms for Enhanced Nucleic Acid Detection.

Rapid and accurate nucleic acid detection is fundamental to effective disease management. While PCR remains the gold standard, its requirement for sophisticated instrumentation limits its application in point-of-care settings. CRISPR-Cas systems have emerged as a disruptive diagnostic technology, leveraging the programmable specificity and unique trans-cleavage activity of Cas effectors to revolutionize biosensing. This review systematically evaluates the evolution of CRISPR-Cas-powered sensing platforms, categorized by their signal transduction modalities. We first discuss the expanding biochemical landscape of Cas nucleases, highlighting recent discoveries where conventional boundaries of Cas9, Cas12, and Cas13 have been transcended to enable versatile DNA/RNA targeting. Subsequently, we provide a comprehensive analysis of four primary sensing architectures: (1) Fluorescence-based platforms, exploring diverse strategies from target and signal amplification with dual-labeled ssDNA probes to nanomaterial-based probes; (2) Naked-eye visual platforms, encompassing both solid-phase lateral flow assays and solution-phase colorimetric strategies that facilitate rapid, instrument-free screening; (3) Electrochemical biosensors, which transduce biological recognition events into measurable electrical parameters, offering high sensitivity and seamless integration with miniaturized electronics; and (4) Electronic and Optoelectronic systems, including field-effect transistors and plasmonic sensors, which offer high-sensitivity, label-free detection. Despite significant progress, the translation of CRISPR-Dx from laboratory proof of concepts to clinical reality faces several bottlenecks. We critically analyze current challenges, including the need for integrated "sample-to-answer" workflows, high-throughput multiplexing, and digital quantification. Finally, we envision future trends such as AI-assisted signal processing and wearable sensing interfaces. By bridging the gap between molecular biology and advanced engineering, CRISPR-powered platforms are poised to make precision molecular diagnostics universally accessible.

Songkuan Zhuang, Weilin Luo, Beiyi Lan et al. · 0 citations
Conference Open access 2026

Exploration-Exploitation Reshaping towards Efficient Reasoning for Large Language Models

While excelling at solving complex problems, Large Reasoning Models (LRMs) are still constrained by the overthinking issue. Most current studies rely on reward shaping in Rein-forcement Learning (RL) to shorten the Chain-of-Thought (CoT) of LRMs, remaining sample-inefficient and non-robust due to the absence of prioritized exploitation and guided exploration. To address these issues, we propose a novel policy optimization framework with S elf-I mitation and self-G uidance M ech A nisms (SIGMA), which reshapes the exploration and exploitation through two core components: (i) self-imitation exploitation , which enables the prioritized exploitation of high-value prompts and rollouts by introducing a self-imitation loss and a dynamic sampling strategy based on compression rate; (ii) self-guidance exploration , which provides a preference-aware exploration guidance through diverse and pluggable self-rewriting strategies. Experiments across various datasets indicate that our method achieves superior reasoning efficiency without compromising, and even facilitating, the overall accuracy. Furthermore, ablation studies show that the proposed mechanisms can provide flexible control interfaces for the tradeoff between the reasoning accuracy and efficiency of LRMs.

Yufeng Shi, Weilin Luo, Yuxiang Zhang et al. · 0 citations