Mitochondrial dysfunction contributes to the senescent phenotype of <scp>IPF</scp> lung fibroblasts
Bibliographic record
Abstract
Increasing evidence highlights that senescence plays an important role in idiopathic pulmonary fibrosis (IPF). This study delineates the specific contribution of mitochondria and the superoxide they form to the senescent phenotype of lung fibroblasts from IPF patients (IPF-LFs). Primary cultures of IPF-LFs exhibited an intensified DNA damage response (DDR) and were more senescent than age-matched fibroblasts from control donors (Ctrl-LFs). Furthermore, IPF-LFs exhibited mitochondrial dysfunction, exemplified by increases in mitochondrial superoxide, DNA, stress and activation of mTORC1. The DNA damaging agent etoposide elicited a DDR and augmented senescence in Ctrl-LFs, which were accompanied by disturbances in mitochondrial homoeostasis including heightened superoxide production. However, etoposide had no effect on IPF-LFs. Mitochondrial perturbation by rotenone involving sharp increases in superoxide production also evoked a DDR and senescence in Ctrl-LFs, but not IPF-LFs. Inhibition of mTORC1, antioxidant treatment and a mitochondrial targeting antioxidant decelerated IPF-LF senescence and/or attenuated pharmacologically induced Ctrl-LF senescence. In conclusion, increased superoxide production by dysfunctional mitochondria reinforces lung fibroblast senescence via prolongation of the DDR. As part of an auto-amplifying loop, mTORC1 is activated, altering mitochondrial homoeostasis and increasing superoxide production. Deeper understanding the mechanisms by which mitochondria contribute to fibroblast senescence in IPF has potentially important therapeutic implications.
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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 | 0.001 |
| 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".