Identification and characterization of chemical components in the bioactive fractions of <i>Cynomorium coccineum</i> that possess anticancer activity
Bibliographic record
Abstract
Cynomorium coccineum has long been used as the health and medicinal plant known to induce cancer cell death.However, the bioactive compounds of C. coccineum and the underlying mechanism of their regulator in cell autophagy and cell apoptosis remain unexplored.In our previous study, we found that the ethanol extract had antitumor activity through inducing cancer cell death.In this study, by detecting the anti-tumor effect of sequence extracts from Cynomorium coccineum, the active constituents were collected in solvent ethyl acetate.A strategy based on ultra-performance liquid chromatography coupled with hybrid quadrupole-orbitrap mass spectrometry (UPLC-Q-Orbitrap/MS) was first utilized to analyze the chemical constituents of active fraction (ethyl acetate fraction, CS3).A total of 29 compounds including 8 triterpenoids, 6 flavonoids, 4 fatty acids, 8 phenolic acids, 1 anthraquinones, 1 nucleoside and 1 sterol were detected and identified or tentatively identified for the first time in Cynomorium coccineum.We found that CS3 induces cancer cell death accompanied with a great number of vacuoles in the cytoplasm.CS3-induced autophagosome formation was found and confirmed by electron microscopy and the high expression levels of microtubule-associated protein-1 light chain 3-II (LC3II), a marker protein of autophagy.We additionally demonstrated that CS3 activated and increased the pro-apoptotic mitochondrial proteins, BNIP3 and BNIP3L, in mRNA and protein levels.The constituents of CS3 down-regulated anti-apoptotic BCL2, and then releases autophagic protein Beclin-1.These finding for the first time systematically not only explore and identify the active constituents of CS3 in Cynomorium coccineum, but also examined the mechanism associated with CS3-induced cell death via cell autophagy.This active component may serve as a potential source to obtain new autophagy inducer and anti-cancer compounds for hepatocellular carcinoma.
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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 | 0.001 |
| 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".