Fortilin potentiates the peroxidase activity of Peroxiredoxin-1 and protects against alcohol-induced liver damage in mice
Bibliographic record
Abstract
Fortilin, a pro-survival molecule, inhibits p53-induced apoptosis by binding to the sequence-specific DNA-binding domain of the tumor suppressor protein and preventing it from transcriptionally activating Bax. Intriguingly, fortilin protects cells against ROS-induced cell death, independent of p53. The signaling pathway through which fortilin protects cells against ROS-induced cell death, however, is unknown. Here we report that fortilin physically interacts with the antioxidant enzyme peroxiredoxin-1 (PRX1), protects it from proteasome-mediated degradation, and keeps it enzymatically active by blocking its deactivating phosphorylation by Mst1, a serine/threonine kinase. At the whole animal level, the liver-specific overexpression of fortilin reduced PRX1 phosphorylation in the liver, enhanced PRX1 activity, and protected the transgenic animals against alcohol-induced, ROS-mediated, liver damage. These data suggest the presence of a novel oxidative-stress-handling pathway where the anti-p53 molecule fortilin augments the peroxidase PRX1 by protecting it against degradation and inactivation of the enzyme. Fortilin-PRX1 interaction in the liver could be clinically exploited further to prevent acute alcohol-induced liver damage in humans.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".