Endogenous cannabinoid signaling is essential for stress adaptation
Bibliographic record
Abstract
Secretion of glucocorticoid hormones during stress produces an array of physiological changes that are adaptive and beneficial in the short term. In the face of repeated stress exposure, however, habituation of the glucocorticoid response is essential as prolonged glucocorticoid secretion can produce deleterious effects on metabolic, immune, cardiovascular, and neurobiological function. Endocannabinoid signaling responds to and regulates the activity of the hypothalamic-pituitary-adrenal (HPA) axis that governs the secretion of glucocorticoids; however, the role this system plays in adaptation of the neuroendocrine response to repeated stress is not well characterized. Herein, we demonstrate a divergent regulation of the two endocannabinoid ligands, N-arachidonylethanolamine (anandamide; AEA) and 2-arachidonoylglycerol (2-AG), following repeated stress such that AEA content is persistently decreased throughout the corticolimbic stress circuit, whereas 2-AG is exclusively elevated within the amygdala in a stress-dependent manner. Pharmacological studies demonstrate that this divergent regulation of AEA and 2-AG contribute to distinct forms of HPA axis habituation. Inhibition of AEA hydrolysis prevented the development of basal hypersecretion of corticosterone following repeated stress. In contrast, systemic or intra-amygdalar administration of a CB(1) receptor antagonist before the final stress exposure prevented the repeated stress-induced decline in corticosterone responses. The present findings demonstrate an important role for endocannabinoid signaling in the process of stress HPA habituation, and suggest that AEA and 2-AG modulate different components of the adrenocortical response to repeated stressor exposure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".