Protective role of thymoquinone against liver damage induced by tamoxifen in female rats
Bibliographic record
Abstract
One of the major reasons for terminating a clinical trial is the liver toxicity induced by chemotherapy. Tamoxifen (TAM) is an anti-estrogen used in the treatment and prevention of hormone-dependent breast cancer. Tamoxifen therapy may cause hepatic injury. The seeds of Nigella sativa, which contain the active ingredient thymoquinone (TQ), have been used in folk medicine for diverse ailments. TQ is reported to possess anticancer and hepatoprotective effects. In this study, the protective effects of TQ against TAM-induced hepatotoxicity in female rats were evaluated. Four groups of rats were used: control; TAM; TQ; TAM+TQ. TAM (45 mg·(kg body mass)(-1)·day(-1), by intraperitoneal injection (i.p.), for 10 consecutive days) resulted in elevated serum levels of alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, lactate dehydrogenase, total bilirubin, and gamma glutamyl transferase, as well as depletion of reduced glutathione in the liver and accumulation of lipid peroxides. Also, TAM treatment inhibited the hepatic activity of superoxide dismutase. Further, it raised the levels of tumor necrosis factor alpha in the liver and induced histopathological changes. Pretreatment with TQ (50 mg·(kg body mass)(-1)·day(-1); orally, for 20 consecutive days, starting 10 days before TAM injection) significantly prevented the elevation in serum activity of the assessed enzymes. TQ significantly inhibited TAM-induced hepatic GSH depletion and LPO accumulation. Consistently, TQ normalized the activity of SOD, inhibited the rise in TNF-α and ameliorated the histopathological changes. In conclusion, TQ protects against TAM-induced hepatotoxicity.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".