The cannabinoid WIN55,212-2 protects against oxidized LDL-induced inflammatory response in murine macrophages
Bibliographic record
Abstract
The endocannabinoid system has recently been attracted interest for its anti-inflammatory and anti-oxidative properties. In this study, we investigated the role of the endocannabinoid system in regulating the oxidized low-density lipoprotein (oxLDL)-induced inflammatory response in macrophages. RAW264.7 mouse macrophages and peritoneal macrophages isolated from Sprague-Dawley (SD) rats were exposed to oxLDL with or without the synthetic cannabinoid WIN55,212-2. To assess the inflammatory response, reactive oxygen species (ROS) and tumor necrosis factor alpha (TNF- alpha) levels were determined, and activation of the mitogen-activated protein kinase (MAPK) and nuclear factor (NF)-kappa B signaling pathways were assessed. We observed that: i) oxLDL strongly induced ROS generation and TNF- alpha secretion in murine macrophages; ii) oxLDL-induced TNF- alpha and ROS levels could be lowered considerably by WIN55,212-2 via inhibition of MAPK (ERK1/2) signaling and NF-kappa B activity; and iii) the effects of WIN55212-2 were attenuated by the selective CB2 receptor antagonist AM630. These results demonstrate the involvement of the endocannabinoid system in regulating the oxLDL-induced inflammatory response in macrophages, and indicate that the CB2 receptor may offer a novel pharmaceutical target for treating atherosclerosis.
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) | 0.001 | 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 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".