Modulation of Mitochondrial and Epigenetic Targets by Polyphenols-rich Extract from Araucaria angustifolia in Larynx Carcinoma
Bibliographic record
Abstract
BACKGROUND: extract (AAE) is a polyphenol-rich extract that has gained interest as a natural anticancer agent. Recent work suggests that AAE induces oxidative damage and apoptosis through its action on decreasing complex I activity of the mitochondrial Electron Transport Chain (ETC). AIMS AND METHODS: In the present study, we aimed to further examine the specific targets by which AAE exerts proapoptotic effects in HEp-2 cancer cells. Specifically, the effect of AAE on the: 1) levels of pyruvate dehydrogenase was assessed by ELISA assay; 2) levels of mitochondrial ETC complexes, focusing on complex I at the gene transcript and protein level relevant to ROS generation was evaluated by multiplex ELISA followed by qRT-PCR and immunoblotting; 3) mitochondrial network distribution analysis was assessed by MitoTracker Red CMXRos; and 4) chemical variations on DNA was evaluated by dot-blotting in HEp-2 cells. RESULTS: Results demonstrated that AAE increased protein levels of PDH, switching energy metabolism to oxidative metabolism. Protein expression levels of complex I and III were found decreased in AAE-treated HEp-2 cells. Analyzing the subunits of complex I, changes in protein and gene transcript levels of NDUFS7 and NDUFV2 were found. Mitochondria staining after AAE incubation revealed changes in the mitochondrial network distribution. AAE was able to induce DNA hypomethylation and decreased DNA (cytosine-5)-methyltransferase 1 activity. CONCLUSION: Our data demonstrate for the first time that AAE alters expression of NDUFS7 and NDUFV2 mitochondrial subunits and induce epigenetic changes in HEp-2 cancer cells leading to a possible suppression of oncogenes.
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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".