Recruitment of Prefrontal Cortical Endocannabinoid Signaling by Glucocorticoids Contributes to Termination of the Stress Response
Bibliographic record
Abstract
The mechanisms subserving the ability of glucocorticoid signaling within the medial prefrontal cortex (mPFC) to terminate stress-induced activation of the hypothalamic-pituitary-adrenal (HPA) axis are not well understood. We report that antagonism of the cannabinoid CB(1) receptor locally within the mPFC prolonged corticosterone secretion following cessation of stress in rats. Mice lacking the CB(1) receptor exhibited a similar prolonged response to stress. Exposure of rats to stress produced an elevation in the endocannabinoid 2-arachidonoylglycerol within the mPFC that was reversed by pretreatment with the glucocorticoid receptor antagonist RU-486 (20 mg/kg). Electron microscopic and electrophysiological data demonstrated the presence of CB(1) receptors in inhibitory-type terminals impinging upon principal neurons within layer V of the prelimbic region of the mPFC. Bath application of corticosterone (100 nm) to prefrontal cortical slices suppressed GABA release onto principal neurons in layer V of the prelimbic region, when examined 1 h later, which was prevented by application of a CB(1) receptor antagonist. Collectively, these data demonstrate that the ability of stress-induced glucocorticoid signaling within mPFC to terminate HPA axis activity is mediated by a local recruitment of endocannabinoid signaling. Endocannabinoid activation of CB(1) receptors decreases GABA release within the mPFC, likely increasing the outflow of the principal neurons of the prelimbic region to contribute to termination of the stress response. These data support a model in which endocannabinoid signaling links glucocorticoid receptor engagement to activation of corticolimbic relays that inhibit corticosterone secretion.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".