Evaluation of Antitumor and Antioxidant Potential of a Polyherbal Extract on Ehrlich’s Ascites Carcinoma Xenografted Mice
Bibliographic record
Abstract
Objective: Indigenous herbs alone or in combination are widely used in Indian system of medicine to treat innumerable ailments since time immemorial. Many strategies has been adopted to enhance anticarcinogenic responses and to establish therapeutic benefits. Poly herbal extracts (PHE), one of the emerging trends of modern medicine, where the assorted active principles work vibrantly to produce a maximum therapeutic activity with minimal toxicity by virtue of its additive, potentative, synergistic, agonistic or antagonistic effects. Though, Withania somnifera, Oroxylum indicum and Calotropis gigentia are independently established as potent antineoplastic agents, their antitumor and antioxidant perspective in combination is yet to be studied. The proposed study ascertains the assorted antineoplastic and antioxidant potential of the said potent herbs in PHE.Method: The antitumor potency of the PHE at a dose of 400 mg/kg body weight was screened on Ehrlich’s ascites carcinoma (EAC) xenografted swiss albino mice. The in-vivo anti-oxidant activity was investigated on the basis of hepatic anti-oxidant enzymes’ levels.Result: The PHE at the aforementioned dose showed a restoring effect on altered hematological parameters (***P< 0.05 considered to be significant), down turn in ascitic tumor volume and increase in mean survival time. A significant improvement in biochemical parameters (Enzymic antioxidants) was too observed.Conclusion:The study epitomizes the PHE (400 mg/kg body weight) as a potent anti tumor and anti-oxidant preparation with synergistic effects on EAC bearing mice.
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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 | 0.002 | 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 | 0.000 |
| 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".