Repeated Administration of a Full-Spectrum Cannabidiol Product, Not a Cannabidiol Isolate, Reverses the Lipopolysaccharide-Induced Depressive-Like Behavior and Hypolocomotion in a Rat Model of Low-Grade Subchronic Inflammation
Bibliographic record
Abstract
Background: Mounting evidence suggests that the phytocannabinoid cannabidiol (CBD) holds promise as an antidepressant agent in conditions underlined by inflammation. Full-spectrum CBD extracts might provide greater behavioral efficacy than CBD-only isolates and might require lower doses to achieve the same outcomes due to the presence of other cannabinoids, terpenes, and flavonoids. However, investigations in this area remain limited. Methods: We evaluated the behavioral response to the administration for 7 days of 15 and 30 mg/kg of a CBD isolate and a full-spectrum CBD product in a rat model of subchronic lipopolysaccharide (LPS, 0.5 mg/kg/day/7 days, intraperitoneal)-induced depressive-like and sickness behavior. The forced swim test was used to assess depressive-like behavior, the open field test (OFT) to assess locomotion, and the elevated plus maze to assess anxiety-like behavior. Results: The full-spectrum CBD extract at both doses, but not the CBD isolate, reversed the LPS-induced depressive-like behavior in the forced swim test. Moreover, the full-spectrum CBD extract at the higher dose but not the CBD isolate restored the subchronic LPS-induced hypolocomotion in the OFT. Repeated administration of both formulations elicited an anxiogenic-like trend in the elevated plus maze. Conclusion: Full-spectrum CBD products might have greater therapeutic efficacy in resolving inflammation-induced depressive and sickness behavior compared to a CBD-only isolate.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".