Cannabinoids, their cellular receptors, and effects on the invasive phenotype of carcinoma and metastasis
Bibliographic record
Abstract
BACKGROUND: The morbidity and mortality of cancer are significantly impacted by the invasive and metastatic potential of particular subgroups of malignant cells within a tumor. The particular pre-metastatic properties of cancerous cells are thus a critical target for novel therapeutics in the oncology field. Cannabinoid molecules have been investigated in recent years in the context of invasion and metastasis of various malignancies, with varying effects reported in the literature. RECENT FINDINGS: There was substantial variability in the findings reported by the literature of the effects of cannabinoid molecules on cancer cell invasion and metastasis. These effects varied depending on which ligand and which of the CB1, CB2, or GPR55 receptors were investigated. These findings suggest a role for the phenomenon of biased signaling in explaining the diversity of effects of cannabinoid molecules on cancer cell invasion. CONCLUSION: While substantially more investigation is required into the effects of cannabinoid molecules on cancer cell invasion and metastasis, we describe in this review the significant diversity in the responses of cancer cells to cannabinoid molecules in terms of their invasive and metastatic capacities.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".