Characteristic single glucosinolates from Moringa oleifera: Induction of detoxifying enzymes and lack of genotoxic activity in various model systems
Bibliographic record
Abstract
Leaves of Moringa oleifera are used by tribes as biological cancer medicine. Scientific investigations with M. oleifera conducted so far have almost exclusively used total plant extracts. Studies on the activity of single compounds are missing. Therefore, the biological effects of the two main aromatic multi-glycosylated glucosinolates of M. oleifera were investigated in the present study. The cytotoxic effects of M. oleifera glucosinolates were identified for HepG2 cells (NRU assay), for V79-MZ cells (HPRT assay, SCE assay), and for two Salmonella typhimurium strains (Ames test). Genotoxic effects of these glucosinolates were not observed (Ames test, HPRT assay, and SCE assay). Reporter gene assays revealed a significant increase in the ARE-dependent promoter activity of NQO1 and GPx2 indicating an activation of the Nrf2 pathway by M. oleifera glucosinolates. Since both enzymes can also be induced via activation of the AhR, plasmids containing promoters of both enzymes mutated in the respective binding sites (pGL3enh-hNQO1-ARE, pGL3enh-hNQO1-XRE, pGL3bas-hGPX2-mutARE, pGL3bas-hGPX2-mutXRE) were transfected. Analyses revealed that the majority of the stimulating effects was mediated by the ARE motif, whereas the XRE motif played only a minor role. The stimulating effects of M. oleifera glucosinolates could be demonstrated both at the transcriptional (reporter gene assay, real time-PCR) and translational levels (enzyme activity) making them interesting compounds for further investigation.
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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".