Ferroptosis in liver diseases: Fundamental mechanism and clinical implications
Bibliographic record
Abstract
. Our research focuses on p53's regulatory mechanism for controlling ferroptosis, as well as the intricate connection between ferroptosis and liver diseases. Ferroptosis is a specific form of programmed cell death that is de-pendent on iron and displays unique features in terms of morphology, biology, and genetics, distinguishing it from other forms of cell death. Ferroptosis can affect the liver, which is a crucial organ responsible for iron storage and meta-bolism. Mounting evidence indicates a robust correlation between ferroptosis and the advancement of liver disorders. P53 has a dual effect on ferroptosis through various distinct signaling pathways. However, additional investigations are required to clarify the regulatory function of p53 metabolic targets in this complex association with ferroptosis. In the future, researchers should clarify the mechanisms by which ferroptosis and other forms of programmed cell death contribute to the progression of liver diseases. Identifying and controlling important regulatory factors associated with ferroptosis present a promising therapeutic strategy for liver disorders.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".