脊髓损伤
小RNA
脊髓
计算生物学
生物信息学
医学
生物
神经科学
遗传学
基因
作者
Cai Wang,Chengcheng Wang,Weizhao Lu,Yan-Jiao Wang,Qianwen Yue,Dongyuan Xin,Baoliang Sun,Jingguo Wu,Jingyi Sun,Ying Wang
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2024-02-12
卷期号:9 (2): 736-744
被引量:1
标识
DOI:10.1021/acssensors.3c02024
摘要
The expression of microRNA (miRNA) changes in many diseases plays an important role in the diagnosis, treatment, and prognosis of diseases. Spinal cord injury (SCI) is a serious disease of the central nervous system, accompanied by inflammation, cell apoptosis, neuronal necrosis, axonal rupture, demyelination, and other pathological processes, resulting in impaired sensory and motor functions of patients. Studies have shown that miRNA expression has changed after SCI, and miRNAs participate in the pathophysiological process and treatment of SCI. Therefore, quantitative analysis and monitoring of the expression of miRNA were of great significance for the diagnosis and treatment of SCI. Through the SCI-related miRNA chord plot, we screened out miRNA-21-5p and miRNA-let-7a with a higher correlation. However, for traditional detection strategies, it is still a great challenge to achieve a fast, accurate, and sensitive detection of miRNA in complex biological environments. The most frequently used method for detecting miRNAs is polymerase chain reaction (PCR), but it has disadvantages such as being time-consuming and cumbersome. In this paper, a novel SERS sensor for the quantitative detection of miRNA-21-5p and miRNA-let-7a in serum and cerebrospinal fluid (CSF) was developed. The SERS probe eventually formed a sandwich-like structure of Fe3O4@hpDNA@miRNA@hpDNA@GNCs with target miRNAs, which had high specificity and stability. This SERS sensor achieved a wide range of detection from 1 fM to 1 nM and had a good linear relationship. The limits of detection (LOD) for miRNA-21-5p and miRNA-let-7a were 0.015 and 0.011 fM, respectively. This new strategy realized quantitative detection and long-term monitoring of miRNA-21-5p and miRNA-let-7a in vivo. It is expected to become a powerful biomolecule analysis tool and will provide ideas for the diagnosis and treatment of many diseases.
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