Electroconvulsive shock treatment differentially modulates cortical and subcortical endocannabinoid activity
Bibliographic record
Abstract
Previous studies indicate that the endocannabinoid system is a potential target for the treatment of depression. To further examine this question we assessed the effects of electroconvulsive shock (ECS) treatment, both a single session and 10 daily sessions, on endocannabinoid content, CB(1) receptor binding parameters and CB(1) receptor-mediated [(35)S]GTPgammaS binding in the prefrontal cortex, hippocampus, hypothalamus and amygdala. A single ECS session resulted in a general reduction in the binding affinity of the CB(1) receptor in all brain regions examined, as well as reductions in N-arachidonylethanolamine (anandamide) content in the prefrontal cortex and the hippocampus, reduced hydrolysis of anandamide by fatty acid amide hydrolase (FAAH) in the prefrontal cortex and an increase in the binding site density of the CB(1) receptor in the amygdala. Following 10 ECS sessions, all these effects subsided except for the reductions in anandamide content in the prefrontal cortex, which increased in magnitude, as well as the reductions in FAAH activity in the prefrontal cortex. Additionally, repeated ECS treatment resulted in a significant reduction in the binding site density of the CB(1) receptor in the prefrontal cortex, but did not alter CB(1) receptor-mediated [(35)S]GTPgammaS binding. Repeated ECS treatment also significantly enhanced the sensitivity of CB(1) receptor-mediated [(35)S]GTPgammaS binding in the amygdala. Collectively, these data demonstrate that ECS treatment results in a down-regulation of cortical and an up-regulation of subcortical endocannabinoid activity, illustrating the possibility that the role of the endocannabinoid system in affective illness may be both complex and regionally specific.
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".