The Implications of Cannabinoid-Induced Metabolic Dysregulation for Cellular Differentiation and Growth
Bibliographic record
Abstract
The endocannabinoid system (ECS) governs and coordinates several physiological processes through an integrated signaling network, which is responsible for inducing appropriate intracellular metabolic signaling cascades in response to (endo)cannabinoid stimulation. This intricate cellular system ensures the proper functioning of the immune, reproductive, and nervous systems and is involved in the regulation of appetite, memory, metabolism, and development. Cannabinoid receptors have been observed on both cellular and mitochondrial membranes in several tissues and are stimulated by various classes of cannabinoids, rendering the ECS highly versatile. In the context of growth and development, emerging evidence suggests a crucial role for the ECS in cellular growth and differentiation. Indeed, cannabinoids have the potential to disrupt key energy-sensing metabolic signaling pathways requiring mitochondrial-ER crosstalk, whose functioning is essential for successful cellular growth and differentiation. This review aims to explore the extent of cannabinoid-induced cellular dysregulation and its implications for cellular differentiation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".