Cannabinoid Receptor 1 and 2 Signaling Pathways Involved in Sepsis
Bibliographic record
Abstract
ABSTRACT: Sepsis is defined as a life-threatening organ dysfunction, caused by a dysregulated host response to an infection and can progress to septic shock, which represents a major challenge in critical care with a high mortality rate. Currently, there is no definitive treatment available for the dysregulated immune response in sepsis. Therefore, a better understanding of the pathophysiological mechanisms may be useful for elucidating the molecular basis of sepsis and may contribute to the development of new therapeutic strategies. The endocannabinoid system is an emerging research topic for the modulation of the host immune response under various pathological conditions. Cannabinoid receptors include the cannabinoid type 1 receptor (CB1) and the cannabinoid type 2 receptor (CB2). This review addresses the main functionality of CB1 and CB2 in sepsis, which can contribute to a better understanding about the pathophysiology of sepsis. Specifically, we discuss the role of CB1 in the cardiovascular system which is one of the biological systems that are strongly affected by sepsis and septic shock. We are also reviewing the role of CB2 in sepsis, specially CB2 activation, which exerts anti-inflammatory activities with potential benefit in sepsis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".