Monoacylglycerol lipase inhibitors produce pro- or antidepressant responses via hippocampal CA1 GABAergic synapses
Bibliographic record
Abstract
The probability of suffering the mood disorder depression is up to 30% in women and 15% in men during their life span. Pharmacological options for depression are limited: conventional antidepressants have low efficacy and a delayed onset of action (several weeks). Here we investigate the antidepressant actions of inhibitors of monoacylglycerol lipase (MAGL), the major degradative enzyme of the endocannabinoid 2-arachidonoylglycerol. A low-dose of MAGL inhibitors produces antidepressant effects on acute stress-exposed mice, through glutamatergic synaptic long-term depression (LTD), without significant effects on chronic corticosterone-exposed mice. In contrast, a high-dose of MAGL inhibitors produces pro- or antidepressant effects on acute stress- or chronic corticosterone-exposed mice, respectively, through GABAergic synaptic disinhibition. In the hippocampus, in vivo inhibition of MAGL induces a CB1 cannabinoid receptor (CB1R)-dependent suppression of inhibitory GABAergic synapses and an in vivo LTD of excitatory glutamatergic synapses. LTD induction requires CB1R in astroglial cells (but not in GABAergic or glutamatergic neurons) and postsynaptic glutamate receptors. The conventional antidepressant fluoxetine produces rapid or delayed antidepressant effects in acute stress- or chronic corticosterone-exposed mice, respectively. We propose that depression-like behavior of animals in response to acute stress is the normal behavioral response, and thus, MAGL inhibitors, which produce antidepressant effects in chronic corticosterone-exposed animals through GABAergic synaptic disinhibition, represent a new class of rapidly-acting and long-lasting antidepressants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".