<i>In vivo</i> Protective Efficacy of Emodin in Swiss Albino Mice Induced with Dalton Ascitic Lymphoma
Bibliographic record
Abstract
Abstract Lymphoma is a tumor that affects lymphoid tissues in the body. Treating lymphoma has become challenging because of the complexity of disease pathology, drug resistance mechanisms and side effects of existing chemo and radiation therapies. Treating cancers/tumors with plant based natural compounds is gaining interest recently because of their less toxicity profiles and efficiency in controlling the disease severity. Emodin is one such compound with such anti-cancer/tumor properties. It has immunosuppressive and anti-cancer properties through multiple ways. In this study, we have studied the therapeutic effect of emodin molecule in the DAL induced lymphoma, a well-established murine model to study and test the anti-lymphoma drugs. Our data has shown an outstanding therapeutic effect of emodin in controlling the lymphoma readouts in DAL induce Swiss Albino mice. These effects were studied in comparison with a standard drug molecule called methotrexate. Furthermore, the in-silico analysis has shown that emodin as a potential drug candidate for lymphoma based on the Lipinski’s rule of 5.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".