Shikonin exerts antitumor activity by causing mitochondrial dysfunction in hepatocellular carcinoma through PKM2–AMPK–PGC1α signaling pathway
Bibliographic record
Abstract
, exhibits broad-spectrum antitumor activity via different molecular mechanisms. In this study, we investigated the effect of shikonin on mitochondrial dysfunction in hepatocellular carcinoma (HCC). Our results showed that shikonin inhibited the proliferation, migration, and invasiveness of HCCLM3 cells, and promoted cell apoptosis in a dose-dependent manner. More importantly, shikonin affected mitochondrial function by disrupting mitochondrial membrane potential and oxidative stress (OS) status. Furthermore, shikonin decreased the oxygen consumption rate of HCCLM3 cells, as well as the levels of ATP and metabolites involved in the tricarboxylic acid cycle (TCA cycle). We also investigated the molecular mechanisms underlying the regulation of mitochondrial function by shikonin as an inhibitor of PKM2. Shikonin decreased the expression of PKM2 in the mitochondria and affected other metabolic pathways (AMPK and PGC1α pathways), which aggravated the oxidative stress and nutrient deficiency. Our results indicate a novel role of shikonin in triggering mitochondria dysfunction via the PKM2-AMPK-PGC1α signaling pathway and provide a promising therapeutic approach for the treatment of HCC.
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 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".