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

Melatonin treatment enhanced disease resistance against Alternaria alternata of 'Korla' fragrant pear fruit via inhibiting cell wall degradation.

Plant physiology and biochemistry : PPB·2026
Same author

Tailored HER2 ECD mRNA-LNP vaccines boost CD8<sup>+</sup> T cell-mediated antitumor immunity for HER2-positive tumor suppression.

Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy·2026
Same author

[Loss of CHC1 or CHC2 in Arabidopsis compromises autophagy pathway and leads to enhanced disease resistance].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2026
Same author

Ultrasound-activated piezoelectric nanoparticles suppress glycolysis for precision therapy of stress-associated breast cancer.

Acta biomaterialia·2026
Same author

Exploring the influences of ultrasound-assisted glycosylated modification on chickpea protein isolate: insights into structural, functional, and interfacial properties.

Ultrasonics sonochemistry·2026
Same author

Factors associated with failure of hydrostatic reduction in children with ileocolic intussusception.

BMC pediatrics·2026

Related Experiment Video

Updated: Apr 21, 2026

Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues
11:54

Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues

Published on: October 20, 2019

9.9K

Artificial intelligence-driven high-content imaging decodes for NLRP7-mutant recurrent hydatidiform moles.

Jiayang Wan1, Tianliang Li2, Limeng Cai1

  • 1Department of Gynecology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Iscience
|April 20, 2026
PubMed
Summary

Recurrent hydatidiform moles (RHMs) stem from NLRP7 mutations, causing cell dysfunction. This study used AI and imaging to reveal how these mutations disrupt lysosome-mitochondria interactions, impacting embryo development.

Keywords:
Biological sciencesMachine learningMethodology in biological sciences

More Related Videos

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

4.8K
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
08:55

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Published on: November 2, 2014

13.0K

Related Experiment Videos

Last Updated: Apr 21, 2026

Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues
11:54

Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues

Published on: October 20, 2019

9.9K
Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment
13:01

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

4.8K
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
08:55

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence

Published on: November 2, 2014

13.0K

Area of Science:

  • Genetics and Genomics
  • Cell Biology
  • Reproductive Medicine

Background:

  • Recurrent hydatidiform moles (RHMs) are a severe gestational disorder.
  • Maternal-effect loss-of-function mutations in the NLRP7 gene are the primary cause of RHMs.
  • Understanding the cellular mechanisms underlying RHMs is crucial for developing therapeutic strategies.

Purpose of the Study:

  • To establish an in vitro model of NLRP7 mutation using patient-derived induced pluripotent stem cells (iPSCs).
  • To investigate mutation-induced multi-organellar dysfunction using high-content imaging (HCI) and artificial intelligence (AI).
  • To elucidate the role of NLRP7 mutations in the pathogenesis of RHMs at the organellar level.

Main Methods:

  • Generation of patient-derived iPSCs with NLRP7 mutations.
  • Application of multiparametric HCI for synchronous capture of cellular and subcellular phenotypes.
  • Development of a bio-inspired AI framework (BioVision-Segmentation) for organelle interaction quantification.

Main Results:

  • NLRP7 mutations were found to disrupt the lysosome-mitochondria crosstalk hub.
  • Significant energy metabolism dysregulation, reactive oxygen species (ROS) accumulation, and organelle spatial defects were observed.
  • Transcriptome sequencing corroborated the identified organellar dysfunctions.

Conclusions:

  • NLRP7 mutations lead to multi-organellar dysfunction, particularly affecting lysosome-mitochondria interactions.
  • This study provides novel insights into the organellar pathogenesis of RHMs.
  • The developed technological platform can aid in identifying therapeutic targets for early embryo protection.