Ferroptosis Sensitivity Analysis via Live-Cell Imaging and ROS Tracing

Eric Seidel's 2026 study investigates a feedback loop between cell proliferation and reactive oxygen species (ROS) regulating ferroptosis sensitivity. The research uses live-cell imaging and ROS tracing to model cellular fate, linking population growth dynamics with metabolic ROS levels. The supporting data is contained in a 2.7 MB PDF file.

Use Cases

• Analyze the relationship between cellular density and ROS levels described in the study to model ferroptosis sensitivity.
• Use the experimental findings on lipid hydroperoxide clearance and galactose-promoted OXPHOS switch to validate feedback mechanism predictions.
• Apply the mathematical model of population growth and ferroptotic cell death to predict cellular fate under varying external conditions.

Strengths

• Data originates from a peer-reviewed scientific study with a defined experimental and modeling methodology.
• The 2.7 MB PDF includes detailed textual and image data from live-cell imaging and ROS tracing experiments.
• Released under a permissive CC BY 4.0 license, enabling reuse and redistribution.

Limitations

• The dataset is a static PDF document (2.7 MB), not a structured, queryable table, limiting direct computational analysis.
• No raw numerical data or column definitions are provided, requiring manual extraction for quantitative modeling.
• The scope is limited to the specific experimental conditions and cell lines used in the underlying study.

Provenance

Source

figshare, authored by Eric Seidel.

Collection Method

Experimental data from live-cell imaging coupled with ROS tracing, combined with mathematical modeling.

Time Range

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Freshness

Last updated March 25, 2026.

Geography

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