Delving into the death signaling pathway of hemp oil and gamma radiation in solid tumor bearing mice
Bibliographic record
Abstract
Many studies reported the diverse therapeutic potential of essential oils. They have a crucial role in cancer prevention and treatment. Antioxidant, antimutagenic, and antiproliferative are mechanisms involved. Also, essential oils may enhance immune function and surveillance, induce enzymes, enhance detoxification, and modulate multidrug resistance. Hemp oil, obtained from Cannabis sativaL. seeds, is known for its health-enhancing properties and bioactivity. Adult female Swiss albino mice were injected with viable Ehrlich ascites carcinoma cells (2.5 × 106 cells/mouse), and then administered with hemp oil (20 mg/kg) daily for 10 consecutive days pre-, and then 10 days post-exposure to 6 Gy whole-body gamma irradiation. Hemp oil significantly increased Beclin1, VMP1, LC3, cytochrome c, and Bax. More interestingly, Hemp oil showed a significant decrease in Bcl2 and P13k either alone or in combination with γ radiation. Finally, this study documented the possible role of hemp oil in inducing two cell death types, autophagy and apoptosis, as it may be applied as an adjuvant in cancer treatment.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".