基于表面增强的拉曼散射和人类血清的多变量分析来检测呼吸系统疾病
Yulia Khristoforova1, Lyudmila Bratchenko1, Vitalii Kupaev2
1Department of Laser and Biotechnical Systems, Samara National Research University, 34 Moskovskoe Shosse, 443086 Samara, Russia.
Diagnostics (Basel, Switzerland)
|March 28, 2025
概括
表面增强拉曼散射 (SERS) 在血清中以92%的准确度检测出呼吸道疾病. 然而,使用SERS将慢性阻塞性肺病 (COPD) 与支气管喘 (BA) 区分开来,其准确性较低,这表明存在类似的潜在机制.
科学领域:
- 生物医学工程 生物医学工程
- 分析化学 分析化学
- 肺部病理学 肺部病理学
背景情况:
- 慢性阻塞性肺病 (COPD) 是全球卫生面临的一个重大挑战.
- 早期和准确的呼吸道疾病诊断对于有效管理至关重要.
- 表面增强拉曼散射 (SERS) 提供了一个潜在的非侵入性诊断工具.
研究的目的:
- 研究SERS技术在检测呼吸道疾病,特别是COPD方面的实用性.
- 用SERS分析人类血清来区分COPD和支气管喘 (BA).
- 探索与呼吸系统疾病相关的血清中的代谢和蛋白质基因差异.
主要方法:
- 来自COPD,BA,喘-COPD重叠和慢性心力衰竭 (CHF) 患者的人类血清样本使用SERS进行了分析.
- 部分最小平方区分分析 (PLS-DA) 用于SERS光谱数据的多变量分析.
- 开发了模型来对呼吸系统疾病患者进行病理参考组 (CHF) 的分类,并区分COPD和BA患者.
主要成果:
- 在638和1051厘米-1的特定SERS光谱特征被确定为呼吸系统疾病的潜在生物标志物.
- PLS-DA模型在区分呼吸系统疾病与CHF组方面表现出高精度 (0.92),灵敏度为0.85和特异性为0.97.
- 该模型在区分COPD和BA的准确性有限 (0.61),表明这些疾病之间的微妙光谱差异.
结论:
- 呼吸系统疾病患者和病理参考组之间存在血清代谢和蛋白质组特征的显著差异.
- 区分COPD与BA的准确性有限,这表明血清成分重叠和潜在的共享致病基因机制.
- SERS在识别呼吸道疾病方面表现有前途,但需要进一步精细化,以便精确地区分COPD和BA等类似疾病.
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