The role of ferroptosis in iron toxicity following spinal cord injury
Bibliographic record
Abstract
Ferroptosis is a newly identified-form of programmed cell death, which is triggered by excess intracellular iron and deficient antioxidant defense, leading to iron-dependent lipid peroxidation. One molecular pathway of ferroprosis occurs through NCOA4, a shuttle protein that transports cytosolic ferritin to autophagosomes for degradation, resulting in the release of iron from ferritin, which subsequently stimulates lipid peroxidation. In spinal cord injury (SCI), one of the immediate consequences of trauma is rupture of blood vessels. Elevated level of iron due to infiltration of red blood cells to the site of injury increases the possibility that ferroptosis might be involved in secondary damage associated with SCI. However, the role of ferroptosis in SCI remains unclear. We have previously shown that iron accumulation in CD11b+ macrophages is seen rapidly after SCI. We now show increased expression of NCOA4 in the first two weeks after contusion injury in mice. NCOA4 was expressed in microglia/macrophages at the site of SCI lesions and was associated with reduced ferritin. We found that some NCOA4+ cells showed signs of cell death. In addition, protein levels of the antioxidant enzyme glutathione peroxidase 4 (GPX4) remains unchanged after SCI, indicating it may be insufficient to handle increased lipid peroxidation that causes ferroptosis. Treatment with a ferroptosis inhibitor (UAMC-3203), showed a small but significant improvement in locomotor recovery indicated by the BMS score and subscore. These findings indicate that NCOA4 may contribute to ferroptosis mediated iron toxicity in SCI.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".