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Related Concept Videos

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

251
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...
251
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

272
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...
272

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Related Experiment Video

Updated: May 16, 2025

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects
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Using Single-Cell Raman Microspectroscopy to Profile Human Peripheral Blood Mononuclear Cells.

Elizabeth Gan1, Megan Stoker1, Edie Guo1

  • 1Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK.

Methods in Molecular Biology (Clifton, N.J.)
|May 15, 2025
PubMed
Summary

A new Raman microspectroscopy method analyzes peripheral blood mononuclear cells (PBMCs) to aid chronic disease diagnosis. This technique, combined with machine learning, helps differentiate patient groups and identify metabolic differences for disease research.

Keywords:
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)Peripheral blood mononuclear cells (PBMC’s)Raman spectroscopySingle cells

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Area of Science:

  • Biomedical Engineering
  • Spectroscopy
  • Computational Biology

Background:

  • Chronic conditions require reliable diagnostic tools for effective treatment and research.
  • Current diagnostic methods for heterogeneous disorders often lack specificity.
  • Peripheral blood mononuclear cells (PBMCs) are crucial for understanding disease mechanisms.

Purpose of the Study:

  • To present Raman microspectroscopy as a method for analyzing PBMC biology.
  • To demonstrate the application of machine learning for interpreting spectroscopic data.
  • To explore the potential for early diagnosis and disease mechanism discovery in chronic conditions.

Main Methods:

  • Isolation of PBMCs from human blood samples.
  • Acquisition of Raman spectra from PBMCs.
  • Application of machine learning algorithms to analyze spectral data and classify samples.

Main Results:

  • Demonstrated ability to differentiate between patient and control groups using Raman spectroscopy data.
  • Potential to identify subgroups within patient cohorts.
  • Identification of intracellular metabolite differences indicative of disease mechanisms.

Conclusions:

  • Raman microspectroscopy offers a promising, label-free approach for studying PBMCs.
  • Machine learning enhances the diagnostic and research potential of Raman spectroscopy for chronic diseases.
  • This integrated approach can advance the understanding and treatment of complex, heterogeneous disorders.