The Endocannabinoid System, Aggression, and the Violence of Synthetic Cannabinoid Use, Borderline Personality Disorder, Antisocial Personality Disorder, and Other Psychiatric Disorders
Bibliographic record
Abstract
Endogenous and exogenous cannabinoids bind to central cannabinoid receptors to control a multitude of behavioral functions, including aggression. The first main objective of this review is to dissect components of the endocannabinoid system, including cannabinoid 1 and cannabinoid 2 receptors; the endogenous cannabinoids anandamide and 2-arachidonoylglycerol; and the indirect cannabinoid modulators fatty acid amide hydrolase and monoacylglycerol lipase; that have shown abnormalities in basic research studies investigating mechanisms of aggression. While most human research has concluded that the active ingredient of marijuana, Δ9-tetrahydrocannabinol, tends to dampen rather than provoke aggression in acute doses, recent evidence supports a relationship between the ingestion of synthetic cannabinoids and emergence of violent or aggressive behavior. Thus, another objective is to evaluate the emerging clinical data. This paper also discusses the relationship between prenatal and perinatal exposure to cannabis as well as use of cannabis in adolescence on aggressive outcomes. A final objective of the paper is to discuss endocannabinoid abnormalities in psychotic and affective disorders, as well as clinically aggressive populations, such as borderline personality disorder and antisocial personality disorder. With regard to the former condition, decreased anandamide metabolites have been reported in the cerebrospinal fluid, while some preliminary evidence suggests that fatty acid amide hydrolase genetic polymorphisms are linked to antisocial personality disorder and impulsive-antisocial psychopathic traits. To summarize, this paper will draw upon basic and clinical research to explain how the endocannabinoid system may contribute to the genesis of aggressive behavior.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".