Anticancer Activity of Leaf Hydro Ethanolic Extract of Aegle marmelos in Human Lung Cancer Cell Mediated through Caspase-3 and Caspase-9 mRNA Expression
Bibliographic record
Abstract
Background: Aegle marmelos (AE) is a medicinal plant that comes under the rutaceae family and the plant was used in the past for treating many diseases and illness symptoms. The plant has many effects such as anti-diarrhoeal, antimicrobial, antiviral, radioprotective, anticancer, chemopreventive, antipyretic, ulcer healing, antigenotoxic, diuretic, antifertility and anti-inflammatory properties. Aim: To know the anticancer activity of hydroethanolic leaf extract of Aegle marmelos over lung cancer cells treated with caspase 3 and caspase 9 mRNA expression. Materials and Methods: The required chemicals were collected mainly from Canada. The lung cancer cells (A549) were collected from NCCS pune and then RNA was extracted from the cells and then the study was conducted after treating it with caspase 3 and caspase 9 mRNA expression. The cells were treated with many dosage of hydroethanolic extract of Aegle marmelos and the cell viability was noted. Results: The study reported that extract of Aegle marmelos has a great anticancer activity about 1 fold change over rate of 1.7 for cells treated with caspase 3 and a fold change over of 1 in caspase 9 treated lung cancer cells. Conclusion: The study concluded an innovative finding that the hydroethanolic leaf extract of Aegle marmelos has a great anticancer activity against lung cancer cells treated with caspase 3 and caspase 9 mRNA expression.
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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) | 0.000 | 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) | 0.002 | 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".