Membrane Cholesterol But Not Putative Receptors Mediates Anandamide–Induced Hepatocyte Apoptosis
Bibliographic record
Abstract
The endogenous cannabinoid anandamide, a lipid mediator, induces various physiologic events such as vascular relaxation, inhibition of gap-junctions formation, tumor proliferation, neurologic analgesia, and apoptosis. Although increased concentration of anandamide in plasma has been implicated in pathophysiologic states including endotoxin-induced hypotension, the effects of anandamide on hepatocytes still remain unclear. In this study, we present evidence that plasma anandamide concentration is highly increased in severe hepatitis and cirrhosis patients. In addition, concentrations of anandamide within the pathophysiologic range potently induced apoptosis of hepatoma cell line (Hep G2) and primary hepatocytes, suggesting a possible link between increased anandamide level and hepatocyte damage. Anandamide-induced cell death was preceded by G0/G1 cell-cycle arrest, activation of proapoptotic signaling (i.e., p38 MAPK and JNK), and inhibition of antiapoptotic signaling (i.e., PKB/Akt) pathways. Moreover, anandamide increased susceptibility to oxidative stress-induced hepatocyte damage. In this context, methyl-beta-cyclodextrin (MCD), a membrane cholesterol depletor, or mevastatin, an HMG-CoA reductase inhibitor, or N-acetyl cysteine, an antioxidant, potently inhibited the anandamide-induced proapoptotic events and cell death, whereas putative cannabinoid receptor antagonists did not exhibit an inhibitory effect on anandamide-induced cell death. Furthermore, binding assay using polymyxin beads revealed that anandamide could interact with cholesterol. In conclusion, our data suggest that cholesterol present in the cell membrane determines the fate of hepatocytes exposed to anandamide, possibly functioning as an anandamide receptor.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".