Determination of chemical components of the endemic species Allium turcicum L. plant extract by LC-MS/MS and evaluation of medicinal potentials
Bibliographic record
Abstract
L. (Zuzubak) plant as a cultivated vegetable have various health benefits and consumed as a food. Due to the shortcoming evidence in literature and the importance of this plant in folk medicine, in the present study, for the first time, we evaluated the bioactive profile of components (using LC-MS/MS), cytotoxicity, anticancer, antioxidant, and antibacterial prospectives of Zuzubak methanol extract. Reported results show that the extract is rich in bioactive compounds and has anticancer activity with breast cancer cells (MCF-7), human prostate cancer cells (DU-145), and Human osteosarcoma cancer Cell lines of (IC50) in dose dependent manner in the concentration range of 31.25 μg/mL and 2000 μg/mL for 24 and 48 h. Western blotting results determined that the extract significantly suppressed the growth of U2OS, MCF-7, and DU-145 cancer cells by down expression of Ang-1 (angiogenic protein) and Beclin-1 (autophagy protein) and overexpression of Bax (a proapoptotic protein). The oxidative stress indices showed a reduction in RPE-1 and MCF-7 cells and an upsurge in U2OS and DU-145 cells. Additionally, the antimicrobial assay showed suppression of the growth of various pathogenic microorganisms in 4.00-8.00 μg/concentrations of Zuzubak extract using the microdilution method. The phytochemicals identified showed promising anticancer, antioxidant effects, and antimicrobial properties, representing a valuable herbal source for drug development studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".