Lipid peroxidation increases membrane tension, Piezo1 gating, and cation permeability to execute ferroptosis
Bibliographic record
Abstract
The ongoing metabolic and microbicidal pathways that support and protect cellular life generate potentially damaging reactive oxygen species (ROS). To counteract damage, cells express peroxidases, which are antioxidant enzymes that catalyze the reduction of oxidized biomolecules. Glutathione peroxidase 4 (GPX4) is the major hydroperoxidase specifically responsible for reducing lipid peroxides; this homeostatic mechanism is essential, and its inhibition causes a unique type of lytic cell death, ferroptosis. The mechanism(s) that lead to cell lysis in ferroptosis, however, are unclear. We report that the lipid peroxides formed during ferroptosis accumulate preferentially at the plasma membrane. Oxidation of surface membrane lipids increased tension on the plasma membrane and led to the activation of Piezo1 and TRP channels. Oxidized membranes thus became permeable to cations, ultimately leading to the gain of cellular Na + and Ca 2+ concomitant with loss of K + . These effects were reduced by deletion of Piezo1 and completely inhibited by blocking cation channel conductance with ruthenium red or 2-aminoethoxydiphenyl borate (2-APB). We also found that the oxidation of lipids depressed the activity of the Na + /K + -ATPase, exacerbating the dissipation of monovalent cation gradients. Preventing the changes in cation content attenuated ferroptosis. Altogether, our study establishes that increased membrane permeability to cations is a critical step in the execution of ferroptosis and identifies Piezo1, TRP channels, and the Na + /K + -ATPase as targets/effectors of this type of cell death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".