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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Sesamin attenuates atherosclerosis by alleviating vascular endothelial ferroptosis-related injury <i>via</i> m<sup>6</sup>A-dependent regulation of SREBF1 expression.

Frontiers in cell and developmental biology·2026
Same author

Identification of Dopamine D2 Receptor as a Direct Target of Salidroside and Tyrosol by Integrated Transcriptomic and Biophysical Approaches.

Pharmaceuticals (Basel, Switzerland)·2026
Same author

Tripartite motif-containing protein 28 promotes drug resistance to bortezomib in gastric cancer through proteasome activity regulation.

CytoJournal·2026
Same author

Reinvigorating CD8<sup>+</sup> T cells through ADRB1 blockade using copper-propranolol nanoparticles for enhanced immune checkpoint blockade therapy.

Journal of nanobiotechnology·2026
Same author

Vertically Aligned, Highly Ordered BiFeO<sub>3</sub>-BaTiO<sub>3</sub> Micropillars Supported by a Flexible P(VDF-TrFE) Layer for Harvesting Mechanical Energy and Sensing Applications.

ACS applied materials & interfaces·2025
Same author

Development and characterization of a dual-fiber Raman probe for accurate and rapid endometrial carcinoma detection.

Biomedical optics express·2025

Related Experiment Video

Updated: May 16, 2025

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
10:57

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Published on: February 1, 2022

3.0K

Deciphering Metabolic Alterations Associated with Glioma Grading Using Hyperspectral Stimulated Raman Scattering

Le Xin1, Wei Zheng1, Kan Lin1

  • 1Optical Bioimaging Laboratory, Department of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117576, Singapore.

Analytical Chemistry
|April 4, 2025
PubMed
Summary
This summary is machine-generated.

Hyperspectral stimulated Raman scattering (SRS) imaging reveals metabolic shifts in brain tumors. This label-free technique accurately detects and grades gliomas, offering new avenues for precision cancer treatment.

More Related Videos

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion
09:09

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Published on: April 12, 2020

6.8K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.2K

Related Experiment Videos

Last Updated: May 16, 2025

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
10:57

Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis

Published on: February 1, 2022

3.0K
Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion
09:09

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Published on: April 12, 2020

6.8K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.2K

Area of Science:

  • Neuro-oncology
  • Metabolomics
  • Biophotonics

Background:

  • Metabolic dysregulation is a hallmark of cancer, influencing tumor development and treatment response.
  • Understanding metabolic changes in brain tumors is crucial for improving patient outcomes.
  • Current methods for analyzing tumor metabolism often require labeling and can be time-consuming.

Purpose of the Study:

  • To investigate metabolic diversity in gliomas using label-free hyperspectral stimulated Raman scattering (SRS) imaging.
  • To identify unique molecular and histological signatures associated with different glioma grades.
  • To develop a diagnostic classifier for accurate brain tumor detection and grading.

Main Methods:

  • Utilized hyperspectral SRS imaging combined with biochemical spectral modeling for label-free histopathology.
  • Employed multivariate curve resolution analysis to study lipid profiles and demyelination.
  • Applied non-negative least-squares regression spectral modeling for quantitative metabolite analysis.
  • Developed a neural network classifier trained on SRS spectra from patients with pilocytic astrocytoma (PA) and glioblastoma (GBM).

Main Results:

  • Uncovered significant changes in lipid profiles and neuron demyelination across glioma grades.
  • Observed increased cellular proteins, DNA, and cholesterol, with a reduced redox ratio (flavin adenine dinucleotide (FAD)/nicotinamide adenine dinucleotide (NADH)) in glioblastoma (GBM) compared to pilocytic astrocytoma (PA) and healthy tissues.
  • Achieved 99.6% accuracy in detecting and grading brain tumors using a neural network classifier trained on SRS data.

Conclusions:

  • Hyperspectral SRS imaging provides rapid, label-free, and spatially resolved metabolic analysis of human gliomas.
  • The findings demonstrate the potential for identifying metabolic heterogeneity and its link to malignancy.
  • This technique offers a promising approach for developing metabolome-targeted therapies in precision brain tumor treatment.