Reactions of lipid hydroperoxides and how they may contribute to ferroptosis sensitivity
Bibliographic record
Abstract
The accumulation of lipid hydroperoxides (LOOHs) has long been associated with numerous pathologies and has more recently been shown to drive a specific type of cell death known as ferroptosis. In competition with their detoxification by glutathione peroxidases, LOOHs can react with both one-electron reductants and one-electron oxidants to afford radicals that initiate lipid peroxidation (LPO) chain reactions leading to more LOOH. These radicals can alternatively undergo a variety of (primarily unimolecular) reactions leading to electrophilic species that destabilize the membrane and/or react with cellular nucleophiles. While some reaction mechanisms leading to lipid-derived electrophiles have been known for some time, others have only recently been elucidated. Since LOOH (and related peroxides, LOOL) undergo these various reactions at different rates to afford distinct product distributions specific to their structures, not all LOOHs (and LOOLs) should be equivalently problematic for the cell - be it in their propensity to initiate further LPO or fragment to electrophiles, drive membrane permeabilization and eventual cell death. Herein we briefly review the fates of LOOH and discuss how they may contribute to the modulation of cell sensitivity to ferroptosis by different lipids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".