Effect of Aegle Marmelos Hydroethanolic Leaf Extract on Expression of Antiapoptotic Markers in Human Melanoma Cells
Bibliographic record
Abstract
Background: Aegle marmelos commonly known as Bael is a herbal plant. Itis from a family called Rutaceae. It has many medicinal uses: anti-diarrheal, anti- microbial, anti-viral, anti-cancer, chemo-preventive, Ulcer healing and many others. Aim: To study the effect of Aegle marmelos hydroethanolic leaf extract on expression of antiapoptotic markers in human melanoma cells. Objective: The present study investigated the effect of Aegle marmelos hydroethanolic leaf extract on expression of antiapoptotic markers in human melanoma cells. Materials and Methods: DMSO and MTT chemicals were purchased from Sigma chemical Pvt Ltd. Trypsin EDTA, FBS, RPMI 1640 medium and PBS, Real time PCR kit was purchased from Canada. Human melanoma cell line (A375) was purchased from NCCS, Pune, India. Results: The data was analysed statistically by ANOVA and Duncan’s multiple range test with a computer based software (Graph Pad Prism version 5). The percentage of cell viability decreases with the increase in dosage of Aegle marmelos leaf extract. Conclusion: The study concluded that Aegle marmelos hydro ethanolic leaf extract a novel and innovative herbal drug has a significant effect on the expression of antiapoptotic markers in human melanoma cell lines.
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) | 0.000 | 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".