The lncRNA H19-Derived MicroRNA-675 Promotes Liver Necroptosis by Targeting FADD
Bibliographic record
Abstract
The H19-derived microRNA-675 (miR-675) has been implicated as both tumor promoter and tumor suppressor and also plays a role in liver inflammation. We found that miR-675 promotes cell death in human hepatocellular carcinoma (HCC) cell lines. We show that Fas-associated protein with death domain (FADD), a mediator of apoptotic cell death signaling, is downregulated by miR-675 and a negative correlation exists between miR-675 and FADD expression in mouse models of HCC (p = 0.014) as well as in human samples (p = 0.017). We demonstrate in a mouse model of liver inflammation that overexpression of miR-675 promotes necroptosis, which can be inhibited by the necroptosis-specific inhibitor Nec-1/Nec-1s. miR-675 induces the level of both p-MLKL (Mixed Lineage Kinase Domain-Like Pseudokinase) and RIP3 (receptor-interacting protein 3), which are key signaling molecules in necroptosis, and enhances MLKL binding to RIP3. miR-675 also inhibits the levels of cleaved caspases 8 and 3, suggesting that miR-675 induces a shift from apoptosis to a necroptotic cellular pathway. In conclusion, downregulation of FADD by miR-675 promotes liver necroptosis in response to inflammatory signals. We propose that this regulation cascade can stimulate and enhance the inflammatory response in the liver, making miR-675 an important regulator in liver inflammation and potentially also in HCC.
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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".