Identification of a novel fatty acid binding protein-5-CB2 receptor-dependent mechanism regulating anxiety behaviors in the prefrontal cortex
Bibliographic record
Abstract
The endocannabinoid (eCB) system represents a promising neurobiological target for novel anxiolytic pharmacotherapies. Previous clinical and preclinical evidence has revealed that genetic and/or pharmacological manipulations altering eCB signaling modulate fear and anxiety behaviors. Water-insoluble eCB lipid anandamide requires chaperone proteins for its intracellular transport to degradation, a process that requires fatty acid-binding proteins (FABPs). Here, we investigated the effects of a novel FABP-5 inhibitor, SBFI-103, on fear and anxiety-related behaviors using rats. Acute intra-prelimbic cortex administration of SBFI-103 induced a dose-dependent anxiolytic response and reduced contextual fear expression. Surprisingly, both effects were reversed when a cannabinoid-2 receptor (CB2R) antagonist, AM630, was co-infused with SBFI-103. Co-infusion of the cannabinoid-1 receptor antagonist Rimonabant with SBFI-103 reversed the contextual fear response yet showed no reversal effect on anxiety. Furthermore, in vivo neuronal recordings revealed that intra-prelimbic region SBFI-103 infusion altered the activity of putative pyramidal neurons in the basolateral amygdala and ventral hippocampus, as well as oscillatory patterns within these regions in a CB2R-dependent fashion. Our findings identify a promising role for FABP5 inhibition as a potential target for anxiolytic pharmacotherapy. Furthermore, we identify a novel, CB2R-dependent FABP-5 signaling pathway in the PFC capable of strongly modulating anxiety-related behaviors and anxiety-related neuronal transmission patterns.
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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 | 0.000 | 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".