Frataxin deficiency promotes endothelial senescence in pulmonary hypertension
Bibliographic record
Abstract
The dynamic regulation of endothelial pathophenotypes in pulmonary hypertension (PH) remains undefined. Cellular senescence is linked to PH with intracardiac shunts; however, its regulation across PH subtypes is unknown. Since endothelial deficiency of iron-sulfur (Fe-S) clusters is pathogenic in PH, we hypothesized that a Fe-S biogenesis protein, frataxin (FXN), controls endothelial senescence. An endothelial subpopulation in rodent and patient lungs across PH subtypes exhibited reduced FXN and elevated senescence. In vitro, hypoxic and inflammatory FXN deficiency abrogated activity of endothelial Fe-S-containing polymerases, promoting replication stress, DNA damage response, and senescence. This was also observed in stem cell-derived endothelial cells from Friedreich's ataxia (FRDA), a genetic disease of FXN deficiency, ataxia, and cardiomyopathy, often with PH. In vivo, FXN deficiency-dependent senescence drove vessel inflammation, remodeling, and PH, whereas pharmacologic removal of senescent cells in Fxn-deficient rodents ameliorated PH. These data offer a model of endothelial biology in PH, where FXN deficiency generates a senescent endothelial subpopulation, promoting vascular inflammatory and proliferative signals in other cells to drive disease. These findings also establish an endothelial etiology for PH in FRDA and left heart disease and support therapeutic development of senolytic drugs, reversing effects of Fe-S deficiency across PH subtypes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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) | 0.000 | 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".