Modulatory Effect of 4-(methylthio)butyl Isothiocyanate Isolated From Eruca Sativa Thell. on DMBA Induced Overexpression of Hypoxia and Glycolytic Pathway in Sprague-Dawley Female Rats
Bibliographic record
Abstract
Thell. In the present study, we explored the anti-cancer effect of 4-MTBITC against 7,12-dimethylbenz [a] anthracene (DMBA) induced breast cancer. Hypoxic conditions were developed using a single dose of 60 mg/kg DMBA. Hepatic and renal parameters were increased along with antioxidants in cancer-bearing rats which were lowered with the treatment of 4-MTBITC. Further, it inhibited the up-regulation of glycolytic enzymes caused by DMBA. The hypoxia pathway was evaluated using RT-PCR and it was found that the 40 mg/kg doses of 4-MTBITC statistically lowered the expression of HIF-1α. Akt/mTOR signaling pathway was one of the major pathways involved in 4-MTBITC-induced cell growth arrest by western blotting. Amino acid profiling serum-free plasma revealed the downregulation of specific amino acids required for vital components of fast-growing cancer cells. 4-MTBITC reduced the levels of serine, arginine, alanine, asparagines, and glutamic acid. Histological examination also showed neoplastic growth following DMBA doses. 4-MTBITC treated rats showed less infiltration and normal physiology. Our findings for the first time demonstrated the potential therapeutic significance of 4-MTBITC on modulation of glycolytic enzymes and hypoxia pathway in female rats.
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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 | 0.001 |
| 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".