MFSD7C protects hemolysis-induced lung impairments by inhibiting ferroptosis
Bibliographic record
Abstract
Hemolysis drives susceptibility to lung injury and predicts poor outcomes in diseases, such as malaria and sickle cell disease (SCD). However, the underlying pathological mechanism remains elusive. Here, we report that major facilitator superfamily domain containing 7 C (MFSD7C) protects the lung from hemolytic-induced damage by preventing ferroptosis. Mechanistically, MFSD7C deficiency in HuLEC-5A cells leads to mitochondrial dysfunction, lipid remodeling and dysregulation of ACSL4 and GPX4, thereby enhancing lipid peroxidation and promoting ferroptosis. Furthermore, systemic administration of MFSD7C mRNA-loaded nanoparticles effectively prevents lung injury in hemolytic mice, such as HbSS-Townes mice and PHZ-challenged 7 C−/− mice. These findings present the detailed link between hemolytic complications and ferroptosis, providing potential therapeutic targets for patients with hemolytic disorders. Hemolysis heightens susceptibility to lung injury and predicts poor outcomes in hemolytic disorders. Here, the authors show that MFSD7C shields the lung from hemolysis-related ferroptosis by stabilizing mitochondrial function and regulating GPX4 and ACSL4 expression to prevent lipid peroxidation.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".