Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Iwan W Schie1, Christoph Krafft2, Jürgen Popp2,3,4

  • 1Leibniz Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany. Iwan.Schie@leibniz-ipht.de.

Journal of Biophotonics
|August 10, 2016
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Chiroptical properties of bright chiral sulfur quantum dots with high-yield blue luminescence.

Chemical communications (Cambridge, England)·2026
Same author

Optical design concepts using wavelength-selective diffractive optics to enable miniaturized multimodal endoscopic imaging across separated spectral ranges.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same author

The CHI3L1 protein plays role as a protecting factor against autophagy in glioblastoma cells.

Apoptosis : an international journal on programmed cell death·2026
Same author

Effect of hybrid field coupling in nanostructured surfaces on anisotropic signal detection in nanoscale infrared spectroscopic imaging methods.

Faraday discussions·2026
Same author

Denoising and Baseline Correction of Low-Scan FTIR Spectra: A Benchmark of Deep Learning Models Against Traditional Signal Processing.

Bioengineering (Basel, Switzerland)·2026
Same author

Nanochemical Cell-Surface Evaluation in Photothermal Spectroscopic Imaging of Antimicrobial Interactions in the Model System <i>Bacillus subtilis</i> and Vancomycin.

Analytical chemistry·2025
Same journal

Evaluation of the Usefulness of Machine Learning and Artificial Intelligence on Hyperspectral Images in the Diagnosis of Myelodysplastic Syndrome.

Journal of biophotonics·2026
Same journal

Correction to "Characterization of Cerebrovascular Changes in Mice Treated With Alcohol by Photoacoustic Imaging".

Journal of biophotonics·2026
Same journal

Defining Safe Light Intensity Limits of Near-Infrared Illumination Avoiding Skin Heating in Medical Optical Diagnostic Methods.

Journal of biophotonics·2026
Same journal

Review of the SWIR Windows to Study Osteoarthritis.

Journal of biophotonics·2026
Same journal

FTIR-ATR Spectroscopy as a Tool to Differentiate Listeria monocytogenes by Geno-Serogroups, Growth Conditions and Persistence Status.

Journal of biophotonics·2026
Same journal

Utilizing Serum Fluorescence Spectra and Machine Learning Algorithms for Efficient Diagnosis of Sheep Brucellosis.

Journal of biophotonics·2026
See all related articles

Label-free Raman spectroscopy enables efficient cell classification by optimizing signal detection. Reduced spectral resolution still allows accurate identification of cancer cell lines, making it practical for clinical pathology.

Area of Science:

  • Biophotonics
  • Spectroscopy
  • Clinical Pathology

Background:

  • Cell identification is crucial for disease diagnosis and progression monitoring.
  • Fluorescent-label based methods are common, but label-free techniques like Raman spectroscopy offer alternatives.
  • A key limitation of Raman spectroscopy is low signal yield, leading to long acquisition times unsuitable for high-throughput analysis.

Purpose of the Study:

  • To investigate if reduced spectral resolution impacts the classification accuracy of eukaryotic cells using Raman spectroscopy.
  • To determine if optimizing signal detection can overcome the limitations of low signal yield in Raman spectroscopy for cell analysis.

Main Methods:

  • Raman spectroscopy was used to analyze three cancer cell lines (Jurkat, MiaPaca2, Capan1).
Keywords:
Raman spectroscopycellsclassificationresolutionsignal gain

Related Experiment Videos

  • Slit-width was varied (50 µm to 500 µm) to increase detected Raman signal.
  • Spectral resolution was reduced (8 cm⁻¹, 24 cm⁻¹, 48 cm⁻¹), simulating effects of low-diffraction gratings.
  • Support Vector Machine (SVM) was employed for cell classification.

    • Main Results:

    • Detected Raman signal from eukaryotic cells increased up to seven-fold by adjusting slit-width.
    • Cells were well-classified even with significantly reduced spectral resolution (up to six-fold reduction).
    • The characteristic Raman spectra of eukaryotic cells remained recognizable despite decreased spectral resolution.

    Conclusions:

    • High-resolution spectra are not essential for accurate cell classification using Raman spectroscopy.
    • Optimizing signal detection and accepting reduced spectral resolution can make Raman spectroscopy a more practical tool for high-throughput clinical analysis.
    • Raman spectroscopy, even with reduced resolution, shows promise for label-free cell identification in clinical pathology.