解码方法
计算生物学
计算机科学
小RNA
适体
下调和上调
传感器融合
生物
信号(编程语言)
信号处理
细胞
衰老
核糖核酸
系统生物学
化学
仿形(计算机编程)
生物信息学
细胞生物学
编码(内存)
融合
融合蛋白
人工智能
作者
Haonan Chang,Yunfeng Feng,B Zhang,Yadong Xue,Jianwei Jiao,Yuna Guo
出处
期刊:JACS Au
[American Chemical Society]
日期:2026-04-27
卷期号:6 (5): 3027-3038
标识
DOI:10.1021/jacsau.6c00378
摘要
We have developed a multimodal biosensing platform for the in situ monitoring of exosomal RNAs without cell lysis. This system employs a cascade of aptamer recognition, rolling circle amplification (RCA), and G-quadruplex/hemin signal transduction. Electrochemical and colorimetric outputs are seamlessly integrated using an inverse-variance-weighted data fusion algorithm, achieving ultrasensitive and precise detection. Applying this method to oxidative stress-induced cellular senescence, we successfully constructed a comprehensive RNA dynamic map. This analysis revealed time-resolved molecular logic: miRNA-21 displayed transient early upregulation as an adaptive response, while miRNA-29c and miRNA-34a accumulated progressively at later stages, driving irreversible senescence. Clinical validation further demonstrated the platform's efficacy in staging Alzheimer's disease (AD), where the integrated trimodal signals effectively distinguished between mild cognitive impairment (MCI) and progressive AD stages. Detailed statistical analysis identified exosomal miRNA-21 and miRNA-34a as significant independent risk factors, establishing a robust molecular signature for precision AD diagnostics. This work establishes an amplified, multimodal biosensing framework for profiling exosomal RNA communication during aging, offering a powerful tool for stage-resolved biomolecular mapping in precision geroscience.
科研通智能强力驱动
Strongly Powered by AbleSci AI