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Related Concept Videos

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

311
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...
311

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Updated: Jun 7, 2025

Author Spotlight: Oral Candida Diagnosis to Advance Clinical Treatment Regimen for pSS Patients
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Author Spotlight: Oral Candida Diagnosis to Advance Clinical Treatment Regimen for pSS Patients

Published on: March 1, 2024

861

Raman Spectroscopic Algorithms for Assessing Virulence in Oral Candidiasis: The Fight-or-Flight Response.

Giuseppe Pezzotti1,2,3,4,5,6,7, Tetsuya Adachi3,4,8,9, Hayata Imamura1,4

  • 1Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, Kyoto 606-8585, Japan.

International Journal of Molecular Sciences
|November 9, 2024
PubMed
Summary
This summary is machine-generated.

Raman spectroscopy effectively characterized physiological stress and virulence in oral candidiasis using clinical samples. This technique offers potential for rapid, bedside analysis of Candida species.

Keywords:
Raman spectroscopybedside analysismorphogenic stateoral candidiasisvirulence

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Area of Science:

  • Biophotonics
  • Microbiology
  • Spectroscopy

Background:

  • Oral candidiasis is a common fungal infection.
  • Accurate characterization of Candida species' virulence and stress is crucial for effective treatment.
  • Current diagnostic methods can be time-consuming.

Purpose of the Study:

  • To evaluate Raman spectroscopy for characterizing physiological stress and virulence in clinical Candida isolates.
  • To explore the potential of Raman spectroscopy for rapid bedside diagnostics.

Main Methods:

  • Raman spectroscopy was performed on eight clinical isolates of Candida.
  • Samples were analyzed in their native state and after culture, with data correlated to microscopy and chromogenic assays.
  • Statistical analysis of Raman spectra was used to identify key parameters.

Main Results:

  • Despite sample complexity (biofilms, commensals), three Raman algorithms successfully classified Candida cells.
  • Classifications were based on physiological stress, morphogenic state, membrane permeability, and virulence.
  • A "fight or flight" response pattern was observed in Candida cells.

Conclusions:

  • Raman spectroscopy shows promise for analyzing Candida virulence and stress in clinical samples.
  • The study highlights challenges and proposes solutions for using Raman spectroscopy in point-of-care settings.
  • This technique could enable faster, more accurate diagnosis and management of oral candidiasis.