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获取还是不获取:评估生物拉曼光谱中的压缩感知技术

To Acquire or Not to Acquire: Evaluating Compressive Sensing for Raman Spectroscopy in Biology.

作者信息

Raj Piyush, Wu Lintong, Kim Jeong Hee, Bhatt Raj, Glunde Kristine, Barman Ishan

机构信息

Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States.

Hackensack Meridian School of Medicine, Nutley, New Jersey 07110, United States.

出版信息

ACS Sens. 2025 Jan 24;10(1):175-184. doi: 10.1021/acssensors.4c01732. Epub 2024 Dec 20.

Abstract

Raman spectroscopy has revolutionized the field of chemical biology by providing detailed chemical and compositional information with minimal sample preparation. Despite its advantages, the technique suffers from low throughput due to the weak Raman effect, necessitating long acquisition times and expensive equipment. This limitation is particularly acute in time-sensitive applications like bioprocess monitoring and dynamic studies. Compressive sensing offers a promising solution by reducing the burden on measurement hardware, lowering costs, and decreasing measurement times. It allows for the collection of sparse data, which can be computationally reconstructed later. This paper explores the practical application of compressive sensing in spontaneous Raman spectroscopy across various biological samples. We demonstrate its benefits in scenarios requiring portable hardware, rapid acquisition, and minimal storage, such as skin hydration prediction and cellular studies involving drug molecules. Our findings highlight the potential of compressive sensing to overcome traditional limitations of Raman spectroscopy, paving the way for broader adoption in biological research and clinical diagnostics.

摘要

拉曼光谱通过最少的样品制备就能提供详细的化学和成分信息,从而彻底改变了化学生物学领域。尽管具有这些优势,但由于拉曼效应较弱,该技术存在通量低的问题,需要较长的采集时间和昂贵的设备。在生物过程监测和动态研究等对时间敏感的应用中,这一限制尤为突出。压缩感知提供了一个有前景的解决方案,它可以减轻测量硬件的负担,降低成本,并减少测量时间。它允许收集稀疏数据,这些数据随后可以通过计算进行重建。本文探讨了压缩感知在各种生物样品的自发拉曼光谱中的实际应用。我们展示了它在需要便携式硬件、快速采集和最少存储的场景中的优势,例如皮肤水合预测和涉及药物分子的细胞研究。我们的研究结果突出了压缩感知克服拉曼光谱传统局限性的潜力,为其在生物研究和临床诊断中的更广泛应用铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d56a/11773570/989c81bfbf10/se4c01732_0001.jpg

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