Proapoptotic and Antiangiogenic Activities of <i>Arctium Lappa</i> L. on Breast Cancer Cell Lines
Bibliographic record
Abstract
In this study, the bioactivity-guided fractionation was conducted on the aerial parts of Arctium lappa L. and then the extracts were tested in vitro on breast cancer (MCF-7), colorectal cancer (HCT-116), and normal cells (EA.hy926). The n-hexane fraction (EHX) of the ethanolic extract showed strong activity against both MCF-7 and EA.hy926 cell lines (IC50 values: 14.08 ± 3.64 and 27.25 ± 3.45 μg/mL, respectively). The proapoptotic activity of EHX was assessed using MCF-7. Morphological alterations were visualized using Hoechst staining and a transmission electron microscope. Cancer cell signal transduction pathways were investigated, and EHX significantly upregulated p53, TGF-β, and NF-κB. Furthermore, EHX was found to disrupt the metastatic cascade of breast cancer cells by the inhibition of cell proliferation, migration, invasion, and colonization. The antiangiogenic activity of EHX fraction showed potent inhibition of rat aorta microvessels with IC50 value: 4.34 ± 1.64 μg/mL. This result was supported by the downregulation of VEGF-A expression up to 54%. Over 20 compounds were identified in EHX using GC-MS, of which stigmasterol, ß-sitosterol, and 3-O-acetyllupeol are the major active compounds. Phytochemical analysis of EHX showed higher phenolic and flavonoid contents with a substantial antioxidant activity. In conclusion, this work demonstrated that A. lappa has valuable anticancer activity and antiangiogenic properties that might be useful in breast cancer therapy.
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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 | 0.000 |
| 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".