Role of the endocannabinoid system in stress resilience and depression: a master regulator of neurovascular health
Bibliographic record
Abstract
Only 30 to 50% of major depressive disorder (MDD) patients completely remit, making it a leading cause of disability worldwide. This lack of efficacy suggests that current neuron-centric treatments do not address important biological factors. Chronic stress, the main environmental risk for MDD development, has been known to trigger a whole-body response including neuroimmune and neurovascular adaptations. We recently reported that chronic social stress causes a detrimental increase in blood-brain barrier (BBB) permeability, promoting infiltration of circulating inflammatory mediators and development of depressive-like behaviours in mice. Those pathological changes have been confirmed in brain samples of MDD patients. However, biological mechanisms underlying these molecular changes in response to stress remain elusive. Interestingly, the endocannabinoid system (ECS) is a crucial regulator of stress responses. Moreover, ECS was shown to regulate BBB permeability under homeostatic and pathological conditions. Here we combine molecular, cellular and morphological analyzes to behavioral studies and show that the ECS is actively involved in stress resilience to chronic social defeat stress, a mouse model of depression, in a sex- and brain region-specific manner. Based on those results, we propose that stress-induced increased in BBB permeability could be due to pathological changes in the ECS system, enabling release of inflammatory signals into the circulation, vascular dysfunction and establishment of depressive behaviours.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".