Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Autophagy

Autophagy

Autophagy is a self-digesting process by which a cell protects itself from threats both within and outside the cell, ranging from abnormal proteins to invading bacteria. In this process, obsolete components of the cell and invading microbes are degraded by hydrolytic enzymes active in an acidic environment of the lysosomal lumen.
An autophagic pathway consists of a series of signaling events activated in response to diverse stress and physiological conditions such as food deprivation,...

Delivery Pathways to the Lysosome

Delivery Pathways to the Lysosome

Eukaryotic cells use different mechanisms to eliminate toxic waste obsolete and worn-out substances. Lysosomes play a pivotal role in this, and hence, these substances are carried to the lysosome from other parts of the cell and extracellular space through different pathways. The most elaborately studied pathways to the lysosome are the endocytic pathways.
Endocytosis
In endocytosis, the cell membrane takes up macromolecules and particles from the surrounding medium. Clathrin-mediated...

Autophagic Cell Death

Autophagic Cell Death

Christian de Duve discovered “autophagy,” a process in which cellular components are engulfed by membrane-bound organelles called autophagosomes. The autophagosomes then fuse with lysosomes to digest the enclosed contents. Autophagy is generally activated in cells to prevent cell death. However, cell death is triggered when the damage is beyond repair.
Autophagy and Apoptosis
Autophagy can activate apoptosis. In normal conditions, the autophagy activating protein Beclin-1 and...

You might also read

Related Articles

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

Sort by

Same author

Synthetic data generation: challenges and perspectives for gastrointestinal medicine.

Nature reviews. Gastroenterology & hepatology·2026

Same author

A multi-center study on the consistency of drug sensitivity testing in patients with acute myeloid leukemia.

NPJ precision oncology·2026

Same author

Systematic interrogation of drug sensitivities in melanoma reveals potent synergistic and antagonistic drug combinations with translational potential.

Communications medicine·2026

Same author

AutoDRY: a genome-wide resource revealing phase-specific control of autophagy activation, amplitude, and termination.

Autophagy·2026

Same author

Interaction of HS1BP3 with cortactin modulates TKS5 localisation, cell secretion and cancer malignancy.

Molecular oncology·2026

Same author

Reliability, Accuracy, and Timeliness of Autism Telehealth Evaluations by Pediatricians.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association·2026

Search research articles

Related Experiment Video

Updated: Jul 11, 2025

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Published on: May 3, 2013

CELLULAR, A Cell Autophagy Imaging Dataset.

Amani Al Outa^1,2,3, Steven Hicks⁴, Vajira Thambawita⁵

¹Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway. a.a.outa@medisin.uio.no.

Scientific Data

|November 17, 2023

Summary

This summary is machine-generated.

This study introduces CELLULAR, an open dataset for analyzing autophagy in cells using machine learning. It provides annotated images to overcome bottlenecks in high-content screening for autophagy research.

More Related Videos

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Published on: July 27, 2013

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Published on: July 21, 2017

Related Experiment Videos

Last Updated: Jul 11, 2025

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Published on: May 3, 2013

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

Published on: July 27, 2013

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry

Published on: July 21, 2017

Area of Science:

Cell Biology
Biotechnology
Bioinformatics

Background:

Cells maintain homeostasis through dynamic responses to environmental changes.
Autophagy is crucial for cellular material turnover and stress response, but its deregulation is linked to diseases like cancer.
Efficient image analysis for autophagy studies, particularly in high-content screening, presents a significant challenge.

Purpose of the Study:

To introduce CELLULAR, a novel open dataset for autophagy research.
To provide annotated cell images for machine learning-based analysis of autophagy.
To establish a baseline for future research using the CELLULAR dataset.

Main Methods:

Development of the CELLULAR dataset, comprising images of cells expressing the mRFP-EGFP-Atg8a autophagy reporter.
Generation of cell-specific segmentation masks for each image.
Annotation of each cell into categories: basal autophagy, activated autophagy, or unknown.

Main Results:

The CELLULAR dataset is now available as an open resource.
The dataset includes images with precise cell segmentation and autophagy status annotations.
Preliminary experiments demonstrate the dataset's utility for machine learning applications.

Conclusions:

The CELLULAR dataset addresses the bottleneck in autophagy image analysis.
Machine learning can be effectively applied to autophagy research using this dataset.
This resource facilitates a deeper understanding of autophagy dynamics and its role in health and disease.