Unveiling the Phenolic Profiling of Moroccan <i>Ferula communis</i> L. Fruits: A Combination of <i>In Silico</i> and <i>In Vivo</i> Protective Effect Against Methotrexate‐Induced Hepato‐Renal Dysfunction
Bibliographic record
Abstract
Background: Methotrexate (MTX) is associated with several side effects, including hepatic and renal toxicities, which limit its effectiveness as an anticancer medication. These toxicities can lead to hepatotoxicity, nephrotoxicity, and potential liver and kidney failure. On the other hand, the fruit of the giant fennel plant ( Ferula communis ) contains bioactive compounds with proven antioxidant and anti‐inflammatory properties, as demonstrated in previous studies. These compounds have protective effects against various diseases. Aim of the Study: The current study combines in silico ADMET prediction and in vivo evaluation of hepatorenal toxicity of MTX in rats to predict potential effects in humans. Materials: Chemical constituents of FC were identified using HPLC‐DAD analysis. In silico pharmacokinetics, ADMET predictions, and Egan’s boiled egg model were employed. For the in vivo experiments, 32 rats were divided into four groups to investigate the impact of FC extract (FC‐Ext) on MTX‐induced hepatorenal toxicity. The rats were pretreated with FC‐Ext (250 mg/kg, body mass, dissolved in distilled water) from days 1 to 21 and administered MTX (25 mg/kg) on day 7. Various parameters, including body and organ masses, serum toxicity biomarkers (such as albumin, ALT, AST, BUN, creatinine, uric acid, and total protein), hematological parameters, and tissue histopathology, were evaluated to assess MTX‐induced hepato‐renal damage. Results: The analysis of FC revealed the presence of various phenolic acids, with 15 compounds identified using HPLC‐DAD. ADMET prediction provided assurance regarding the safety of the phytochemical compounds from FC concerning liver injury. Experimental validation in vivo confirmed that MTX‐induced hepato‐renal damage led to increased levels of AST, ALT, BUN, and creatinine in blood serum. Hemoglobin, total protein, albumin, and uric acid levels decreased following exposure to MTX. However, co‐treatment with a hydro‐ethanolic extract of FC significantly mitigated these changes, restored kidney and liver functions, and preserved tissue architecture. Conclusion: FC‐Ext shows promise in managing liver and renal diseases and mitigating the hematological toxicity induced by MTX. These findings suggest potential applications for humans in preventing MTX‐induced renal, hepatic, and hematological toxicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".