Phytoextract of Indian mustard seeds acts by suppressing the generation of ROS against acetaminophen-induced hepatotoxicity in HepG2 cells
Bibliographic record
Abstract
CONTEXT: Indian mustard [Brassica juncea (L.) Czern. & Coss. (Brassicaceae)] is reported to possess diverse pharmacological properties. However, limited information is available concerning its hepatoprotective activity and mechanism of action. OBJECTIVE: To study the protective mechanism of mustard seed extract against acetaminophen (APAP) toxicity in a hepatocellular carcinoma (HepG2) cell line. MATERIALS AND METHODS: Hepatotoxicity models were established using APAP (2.5-22.5 mM) based on the cytotoxicity profile. An antioxidant-rich fraction from mustard seeds was extracted and evaluated for its hepatoprotective potential. The mechanism of action was elucidated using various in vitro antioxidant assays, the detection of intracellular generation of reactive oxygen species (ROS), and cell cycle analysis. The phytoconstituents isolated via HPLC-DAD were also evaluated for hepatoprotective activity. RESULTS: Hydromethanolic seed extract exhibited hepatoprotective activity in post- and pre-treatment models of 20 mM APAP toxicity and restored the elevated levels of liver indices to normal values (p < 0.05). Post-treatment suppressed the generation of ROS by 58.37% and pre-treatment effectively prevented the generation of ROS by 90.5%. The mechanism of ROS suppression was further supported by antioxidant activity (IC50) data from DPPH (103.37 ± 4.2 µg AAE/mg), FRAP (83.26 ± 1.1 µg AAE/mg), ORAC (1115 µM GAE/ml), ABTS (83.05 µg GAE/ml), and superoxide (345.22 ± 5.15 µg AAE/mg) scavenging assays and by the restoration of cell cycle alterations. HPLC-DAD analysis revealed the presence quercetin, vitamin E, and catechin, which exhibited hepatoprotective activity. DISCUSSION AND CONCLUSIONS: A phytoextract of mustard seeds acts by suppressing the generation of ROS in response to APAP toxicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".