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

Author Correction: Ventricular assist device unloading reverses microvascular senescence in single ventricle disease.

Nature cardiovascular research·2026
Same author

Transient YAP activation uncovers the neurogenic potential of proliferative mammalian Müller glia.

PNAS nexus·2026
Same author

LATS1/2-CD38 Metabolic Rewiring Links Senescence to Intraplaque Thrombosis.

Circulation research·2026
Same author

Protocol for spatially resolved pathology scores using optimal transport on spatial transcriptomics data.

STAR protocols·2026
Same author

Validation of remote multimodal AI screening for Parkinson disease across diverse settings.

Communications medicine·2026
Same author

The heart puts pressure on cancer growth.

Science (New York, N.Y.)·2026

Related Experiment Video

Updated: Sep 19, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K

SPaSE: Spatially resolved pathology scores using optimal transport on spatial transcriptomics data.

Mohammad Nuwaisir Rahman1, Mohammed Abid Abrar2, Vikram Rakesh Shaw3

  • 1Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh; Computer Science and Engineering, Brac University, Dhaka 1212, Bangladesh.

Cell Systems
|June 6, 2025
PubMed
Summary

We developed spatially resolved pathology score (SPaSE), a new algorithm for spatial transcriptomics (ST) data. SPaSE quantifies pathological impact in diseased tissues, aiding therapeutic target identification.

Keywords:
apoptosisduchenne muscular dystrophygene expressionjensenshannon distancemyocardial infarctionoptimal transportpathological impactregularizationsenescencespatial transcriptomicssupport vector regressiontraumatic brain injuryvisium

More Related Videos

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

3.3K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.8K

Related Experiment Videos

Last Updated: Sep 19, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K
Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

3.3K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

15.8K

Area of Science:

  • Computational Biology
  • Genomics
  • Pathology

Background:

  • Pathological processes exhibit spatial heterogeneity, complicating therapeutic target identification.
  • Spatial transcriptomics (ST) offers insights into molecular mechanisms but lacks robust analytical tools.
  • Existing methods struggle to quantify localized pathological impact within tissues.

Purpose of the Study:

  • To introduce spatially resolved pathology score (SPaSE), an algorithm for analyzing ST data.
  • To quantify pathological impact at a spatial resolution within diseased tissues.
  • To facilitate the identification of therapeutic targets in spatially variable diseases.

Main Methods:

  • Developed SPaSE, an optimal transport-based algorithm for comparing ST data from diseased and control tissues.
  • Applied SPaSE to quantify pathology scores for each spatial spot in diseased samples.
  • Validated SPaSE on ST data from mouse models of myocardial infarction, traumatic brain injury, and Duchenne muscular dystrophy, as well as human post-MI data.

Main Results:

  • SPaSE successfully delineated pathological zones in post-myocardial infarction mouse hearts, aligning with expert annotations.
  • Gene expression modeling based on pathology scores identified signatures predictive of disease severity.
  • The SPaSE model demonstrated accurate cross-species prediction capabilities, performing well on human data.

Conclusions:

  • SPaSE is an effective algorithm for quantifying localized pathology in ST data.
  • The method aids in understanding spatially variable disease mechanisms and identifying potential therapeutic targets.
  • SPaSE enhances the analytical toolkit for spatial transcriptomics research across various disease models.