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利用光纤 Raman 光谱技术快速识别人类肌肉疾病。

Rapid identification of human muscle disease with fibre optic Raman spectroscopy.

机构信息

Sheffield Institute for Translational Neuroscience, University of Sheffield, UK.

Neuroscience Institute, University of Sheffield, UK.

出版信息

Analyst. 2022 May 30;147(11):2533-2540. doi: 10.1039/d1an01932e.

Abstract

The diagnosis of muscle disorders ("myopathies") can be challenging and new biomarkers of disease are required to enhance clinical practice and research. Despite advances in areas such as imaging and genomic medicine, muscle biopsy remains an important but time-consuming investigation. Raman spectroscopy is a vibrational spectroscopy application that could provide a rapid analysis of muscle tissue, as it requires no sample preparation and is simple to perform. Here, we investigated the feasibility of using a miniaturised, portable fibre optic Raman system for the rapid identification of muscle disease. Samples were assessed from 27 patients with a final clinico-pathological diagnosis of a myopathy and 17 patients in whom investigations and clinical follow-up excluded myopathy. Multivariate classification techniques achieved accuracies ranging between 71-77%. To explore the potential of Raman spectroscopy to identify different myopathies, patients were subdivided into mitochondrial and non-mitochondrial myopathy groups. Classification accuracies were between 74-89%. Observed spectral changes were related to changes in protein structure. These data indicate fibre optic Raman spectroscopy is a promising technique for the rapid identification of muscle disease that could provide real time diagnostic information. The application of fibre optic Raman technology raises the prospect of bedside testing for muscle diseases which would significantly streamline the diagnostic pathway of these disorders.

摘要

肌肉疾病(“肌病”)的诊断具有挑战性,需要新的疾病生物标志物来增强临床实践和研究。尽管在成像和基因组医学等领域取得了进展,但肌肉活检仍然是一种重要但耗时的检查。拉曼光谱是一种振动光谱应用,可以对肌肉组织进行快速分析,因为它不需要样品制备,并且操作简单。在这里,我们研究了使用小型化、便携式光纤拉曼系统快速识别肌肉疾病的可行性。对 27 名经最终临床病理诊断为肌病的患者和 17 名经检查和临床随访排除肌病的患者的样本进行了评估。多元分类技术的准确率在 71%-77%之间。为了探索拉曼光谱识别不同肌病的潜力,将患者分为线粒体和非线粒体肌病组。分类准确率在 74%-89%之间。观察到的光谱变化与蛋白质结构的变化有关。这些数据表明,光纤拉曼光谱是一种很有前途的快速识别肌肉疾病的技术,可以提供实时诊断信息。光纤拉曼技术的应用提出了在床边测试肌肉疾病的可能性,这将极大地简化这些疾病的诊断途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ec66/9150427/33c68c24ab7b/d1an01932e-f1.jpg

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