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Related Concept Videos

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

775
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...
775

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Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy
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Biochemical Analysis of Leukocytes after In Vitro and In Vivo Activation with Bacterial and Fungal Pathogens Using

Aikaterini Pistiki1,2, Anuradha Ramoji1,2,3, Oleg Ryabchykov1,3

  • 1Leibniz Institute of Photonic Technology Jena (a Member of Leibniz Health Technologies), Albert-Einstein-Straße 9, 07745 Jena, Germany.

International Journal of Molecular Sciences
|October 13, 2021
PubMed
Summary

Raman spectroscopy offers a label-free method to analyze activated leukocytes, identifying infection types and causes. This technique shows promise for differentiating leukocyte subtypes and detecting infections by examining cellular molecular phenotypes.

Keywords:
Candida albicansKlebsiella pneumoniaePBMCRaman microspectroscopyStaphylococcus aureusinfection modelleukocyteslymphocytemonocyteneutrophil

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Area of Science:

  • Biomedical diagnostics
  • Spectroscopy
  • Cellular immunology

Background:

  • Activated leukocytes provide crucial diagnostic information.
  • Raman spectroscopy is a label-free technique for biochemical analysis.
  • Characterizing leukocyte activation patterns is key for infection diagnostics.

Purpose of the Study:

  • To apply Raman spectroscopy for characterizing leukocyte activation patterns in an in vitro infection model.
  • To assess the potential of single-cell Raman spectroscopy for infection identification and pathogen classification.
  • To compare in vitro findings with clinical data from infected patients.

Main Methods:

  • Isolation of neutrophils, monocytes, and lymphocytes from healthy volunteers.
  • Stimulation of isolated leukocytes with Candida albicans, Staphylococcus aureus, and Klebsiella pneumoniae.
  • Analysis of single-cell Raman spectra to identify biochemical changes and classify pathogens.

Main Results:

  • Binary classification models identified infection presence in monocytes and lymphocytes.
  • The study classified infection types (bacterial/fungal) and bacterial causes (Gram-negative/positive) in leukocyte subpopulations.
  • Raman spectra from the in vitro model showed good agreement with spectra from infected patients.

Conclusions:

  • Single-cell Raman spectroscopy can differentiate leukocyte subtypes and identify infections.
  • The technique probes the molecular phenotype of leukocytes for diagnostic insights.
  • Raman spectroscopy holds significant potential for advancing infection diagnostics.