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相关概念视频

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

291
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
291
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

270
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
270

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相关实验视频

Updated: May 21, 2025

Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry
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利用表面增强的拉曼光谱技术用于基于呼吸的诊断

Ivan A Lujan-Cabrera1, Eden Morales-Narváez1

  • 1Biophotonic Nanosensors Laboratory, Centro de Física Aplicada y Tecnología Avanzada (CFATA), Universidad Nacional Autónoma de México (UNAM), Querétaro 76230, Mexico.

Analytical chemistry
|May 9, 2025
PubMed
概括

人类呼吸分析使用生物标志物进行非侵入性诊断. 表面增强的拉曼光谱为个性化和预防医学下一代传感器提供了强大的平台.

科学领域:

  • 生物医学工程 生物医学工程
  • 分析化学 分析化学
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 人类呼吸中含有众多挥发性有机化合物 (VOC) 和其他分析物.
  • 这些呼吸分析剂可以作为各种健康状况的非侵入性生物标志物.
  • 当前的诊断方法往往需要侵入性手术.

研究的目的:

  • 探索呼吸分析在下一代诊断中的潜力.
  • 突出表面增强拉曼光谱 (SERS) 作为呼吸分析的关键技术.
  • 将呼吸分析定位为个性化医疗保健和预防医学的工具.

主要方法:

  • 使用表面增强拉曼光谱法 (SERS) 进行呼吸分析.
  • 在人类呼吸中识别特定的分子指纹.
  • 开发基于SERS的敏感和选择性传感器平台.

主要成果:

  • 证明了SERS在人类呼吸中检测和识别各种分析物的能力.
  • 建立SERS作为一种非侵入性获得分子指纹的方法.
  • 展示了基于SERS的传感器在医疗保健应用中的潜力.

结论:

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  • 呼吸分析是一种有前途的非侵入性诊断方法.
  • 塞尔斯为开发先进的呼吸传感器提供了一个强大的平台.
  • 这项技术支持个性化和预防性医学的进步.