基于Voigt峰值补偿的自适应拉曼光谱分离方法,用于对细胞生化成分的定量分析
Xiang Chen1,2, Ping Tang1,2, Jianhui Wan1,2
1Key Laboratory of Photonics Technology for Integrated Sensing and Communication of Ministry of Education, Guangdong University of Technology, Guangzhou 510006, China.
Biomedical optics express
|March 20, 2025
概括
这项研究引入了一种新的拉曼光谱法,使用沃伊格特函数进行准确的细胞生化分析. 这种先进的技术改善了光谱分离,使得细胞过程中分子变化的可靠量化成为可能.
科学领域:
- 生物医学光学 生物医学光学
- 频谱学是一种光谱学.
- 细胞生物学 细胞生物学
背景情况:
- 拉曼光谱通过检测分子振动提供无标签,非侵入性的细胞生化分析.
- 细胞组件的准确量化受到重叠的光谱信号的阻碍,需要有效的光谱分离.
- 现有的不混合方法在解释性 (无监督) 或对环境变化 (监督) 的敏感性方面存在困难.
研究的目的:
- 为细胞分析中的拉曼光谱学开发了一种改进的光谱分离算法.
- 提高细胞定量生物化学分析的准确性和可靠性.
- 解决传统不混合方法在处理光谱扭曲和环境变化方面的局限性.
主要方法:
- 将参数化的Voigt函数纳入线性光谱混合模型以进行元素光谱补偿.
- 代最小平方优化的应用,用于自适应性分离和定量分析.
- 通过模拟验证和从Hela细胞亡和诱导多能干细胞 (iPSCs) 分化中对拉曼光谱的应用.
主要成果:
- 在模拟中,Voigt补偿脱混合算法证明了更好的光谱适配精度和稳定性.
- 该方法成功地跟踪了Hela细胞亡期间的生物化学分子变化.
- 在iPSCs分化过程中实现了生物化学变化的精确监测.
结论:
- 开发的算法为使用拉曼光谱学进行定量生物化学分析提供了一个精确,可靠和多功能工具.
- 这种方法增强了拉曼光谱的深入细胞研究能力.
- 该方法克服了复杂生物样本光谱分离的关键挑战.
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