Protective effect of essential oil of <i>Cinnamomum verum</i> bark on hepatic and renal toxicity induced by carbon tetrachloride in rats
Bibliographic record
Abstract
The inner bark of cinnamon (Cinnamomum verum) is widely used as a spice. Cinnamon plants are also a valuable source of essential oil used for medicinal purposes. The present study aimed to investigate the composition and in vitro antioxidant activity of essential oil of C. verum bark (CvEO) and its protective effects in vivo on CCl4-induced hepatic and renal toxicity in rats. Groups of animals were pretreated for 7 days with CvEO (70 or 100 mg/kg body weight) or received no treatment and on day 7 a single dose of CCl4 was used to induce oxidative stress. Twenty-four hours after CCl4 administration, the animals were euthanized. In the untreated group, CCl4 induced an increase in serum biochemical parameters and triggered oxidative stress in both liver and kidneys. CvEO (100 mg/kg) caused significant reductions in CCl4-elevated levels of alanine transaminase, aspartate transaminase, alkaline phosphatase, γ-glutamyl transferase, lactate dehydrogenase, total cholesterol, triglycerides, low-density lipoprotein, urea, and creatinine and increased the level of high-density lipoprotein compared with the untreated group. Moreover, pretreatment with CvEO at doses of 70 and 100 mg/kg before administration of CCl4 produced significant reductions in thiobarbituric acid reactive substances and protein carbonyl levels in liver and kidney tissues compared with the untreated group. The formation of pathological hepatic and kidney lesions induced by the administration of CCl4 was strongly prevented by CvEO at a dose of 100 mg/kg. Overall, this study suggests that administration of CvEO has high potential to quench free radicals and alleviate CCl4-induced hepatorenal toxicity in 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) | 0.001 | 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".