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

EPS and iPS Cells in Disease Research01:21

EPS and iPS Cells in Disease Research

2.8K
Embryonic and induced pluripotent stem cells are excellent models for disease research because of their ability to self-renew and differentiate into most cell types. Somatic cells from a patient are isolated and reprogrammed into induced pluripotent stem cells or iPSCs. These iPSCs are later differentiated into the desired cell type, which mirrors the diseased cell of the patient. In this way, disease models have been created for investigating diseases such as Down syndrome, type I diabetes,...
2.8K

You might also read

Related Articles

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

Sort by
Same author

Characterization of chemical composition and prebiotic effect of a dietary medicinal plant Penthorum chinense Pursh.

Food chemistry·2020
Same author

Natural killer cells as a double-edged sword in cancer immunotherapy: A comprehensive review from cytokine therapy to adoptive cell immunotherapy.

Pharmacological research·2020
Same author

STAT3 activates MSK1-mediated histone H3 phosphorylation to promote NFAT signaling in gastric carcinogenesis.

Oncogenesis·2020
Same author

Ubiquitin-specific protease 14 regulates ovarian cancer cisplatin-resistance by stabilizing BCL6 oncoprotein.

Biochemical and biophysical research communications·2020
Same author

CD8 expression in anaplastic large cell lymphoma correlates with noncommon morphologic variants and T-cell antigen expression suggesting biological differences with CD8-negative anaplastic large cell lymphoma.

Human pathology·2020
Same author

Comprehensive understanding of B7 family in gastric cancer: expression profile, association with clinicopathological parameters and downstream targets.

International journal of biological sciences·2020
Same journal

Editorial: Innovative approaches in glioma therapy: exploring new therapeutic frontiers, volume II.

Frontiers in molecular neuroscience·2026
Same journal

Neurotransmitter co-transmission: synaptic architectures, functional logic, and emerging tools.

Frontiers in molecular neuroscience·2026
Same journal

Sex differences in plasma endocannabinoids and related lipids before and after single and repeated mTBI: an exploratory study of endolipid plasma biomarkers.

Frontiers in molecular neuroscience·2026
Same journal

Editorial: Emerging mechanisms in neurodegenerative disease pathogenesis: vertebrate and invertebrate model organisms.

Frontiers in molecular neuroscience·2026
Same journal

Extracellular vesicles as nanocarriers in glioblastoma: implications for chemoresistance and immune evasion.

Frontiers in molecular neuroscience·2026
Same journal

Proline-directed phosphorylation and prolyl isomerization oppose each other to regulate PSD-95 ubiquitination and excitatory synaptic plasticity.

Frontiers in molecular neuroscience·2026
See all related articles

Related Experiment Video

Updated: Aug 4, 2025

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons
09:21

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

1.6K

Machine learning-based predictive models and drug prediction for schizophrenia in multiple programmed cell death

Yu Feng1,2, Jing Shen3

  • 1The University of New South Wales, Kensington, NSW, Australia.

Frontiers in Molecular Neuroscience
|March 30, 2023
PubMed
Summary
This summary is machine-generated.

This study identifies 10 key genes and develops a diagnostic model for schizophrenia, a common mental illness. Findings also suggest potential therapeutic drugs, offering new avenues for schizophrenia research and treatment.

Keywords:
apoptosisautophagydiagnostic modelingdrug predictionferroptosismachine learningprogrammed cell deathschizophrenia

More Related Videos

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
09:53

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

7.3K
Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

645

Related Experiment Videos

Last Updated: Aug 4, 2025

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons
09:21

Author Spotlight: Generating Neuronal Phenotypic Profiles - A Protocol to Culture and Image Human Midbrain Dopaminergic Neurons

Published on: July 7, 2023

1.6K
Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
09:53

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Published on: August 16, 2020

7.3K
Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

645

Area of Science:

  • Genetics
  • Immunology
  • Computational Biology

Background:

  • Schizophrenia (SC) is a prevalent mental illness with unknown genetic causes and treatments.
  • Programmed cell death (PCD) is implicated in immune diseases and may serve as a diagnostic indicator for schizophrenia.

Purpose of the Study:

  • To identify key genes and develop a diagnostic model for schizophrenia using machine learning.
  • To investigate immune cell dysregulation in schizophrenia.
  • To identify potential therapeutic drugs for schizophrenia.

Main Methods:

  • Utilized Gene Expression Omnibus (GEO) datasets for schizophrenia.
  • Applied Limma analysis for differential gene expression and functional enrichment.
  • Employed LASSO regression, PPI networks, ANN, and consensus clustering for gene selection and model validation.
  • Analyzed immune cell infiltration and collected drug information via Network Analyst.

Main Results:

  • Identified 263 overlapping genes between differentially expressed genes (DEGs) and PCD-related genes.
  • Selected 10 candidate hub genes, including DPF2, ATG7, and GSK3A, to build a diagnostic prediction model.
  • The model demonstrated high diagnostic accuracy (AUC 0.91-0.94) in training and validation groups.
  • Revealed significant differences in Cytotoxic and NK cells in schizophrenia patients.

Conclusions:

  • Successfully identified 10 candidate hub genes crucial for schizophrenia.
  • Developed a robust diagnostic prediction model with high accuracy.
  • Identified potential therapeutic drugs, including Valproic Acid and Epigallocatechin gallate, for schizophrenia treatment.