Thujone inhibits lung metastasis induced by B16F-10 melanoma cells in C57BL/6 mice
Bibliographic record
Abstract
The antimetastatic potential of thujone, a naturally occurring monoterpene, was evaluated. Metastasis was induced in C57BL/6 mice by injecting highly metastatic B16F-10 melanoma cells through the lateral tail vein. Administration of thujone (1 mg·(kg body weight)(-1)), prophylactically and simultaneously with tumor induction, inhibited tumor nodule formation in the lungs by 59.45% and 57.54%, respectively, with an increase in the survival rate (33.67% and 32.16%) of the metastatic tumor bearing animals. These results correlated with biochemical parameters such as lung collagen hydroxyproline, hexosamine and uronic acid contents, serum sialic acid and γ-glutamyl transpeptidase levels, and histopathological analysis. Treatment with thujone downregulated the production of proinflammatory cytokines such as tumor necrosis factor-α, interleukin (IL)-1β, IL-6, and granulocyte-monocyte colony-stimulating factor. Thujone administration downregulated the expression of matrix metalloproteinase (MMP)-2, MMP-9, extracellular signal-regulated kinase (ERK)-1, ERK-2, and vascular endothelial growth factor (VEGF) and also upregulated the expression of nm-23, tissue inhibitor of metalloproteinase (TIMP)-1, and TIMP-2 in the lung tissue of metastasis-induced animals. Treatment with thujone inhibited the activity of MMP-2 and MMP-9 in gelatin zymographic analysis. Thujone treatment significantly inhibited the invasion of B16F-10 melanoma cells across the collagen matrix in a Boyden chamber. Thujone also inhibited the adhesion of tumor cells to collagen-coated microtire plate wells and the migration of B16F-10 melanoma cells across a polycarbonate filter in vitro. These results indicate that Thujone can inhibit the lung metastasis of B16F-10 cells through inhibition of tumor cell proliferation, adhesion, and invasion, as well as by regulating expression of MMPs, VEGF, ERK-1, ERK-2, TIMPs, nm23, and levels of proinflammatory cytokines and IL-2 in metastatic animals.
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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 | 0.000 | 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) | 0.001 | 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".