Orally consumed cannabinoids: the effect of carrier oil on acute tissue distribution in male C57BL/6 mice
Bibliographic record
Abstract
BACKGROUND: Fundamental gaps in knowledge exist in understanding the tissue distribution of cannabinoids, cannabidiol (CBD) and tetrahydrocannabinol (THC), following oral ingestion. CBD and THC are lipid-soluble and oral bioavailability is increased when combined with long-chain fatty acid carrier oils prior to oral ingestion. Oils with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) confer positive health benefits and have yet to be examined as a carrier oil for oral cannabinoid delivery thus, examination is warranted. METHODS: This study investigated the acute tissue distribution of cannabinoids in serum, adipose, brain, liver, heart, and muscle of male C57BL/6 mice at 1, 2, and 3 h (H) post oral ingestion. Mice were gavaged with CBD (5 mg/kg) and THC (1 mg/kg) combined with either sesame (SES), mixed EPA/DHA, or DHA enriched (DHA) oil as a carrier. With assistance of the Analytical Facility for Bioactive Molecules (Toronto, Canada), tissue concentration of cannabinoids was quantified using liquid chromatography with tandem mass spectrometry. RESULTS: SES oil resulted in a significantly greater concentration of CBD and THC (p < 0.05) across all tissues and times compared to the n-3 polyunsaturated fatty acid (PUFA) oils. The ratio of EPA:DHA in the carrier oils modestly affected distribution of cannabinoids to tissues, notably, DHA oil resulted in a greater concentration of CBD in the brain. Heart tissue had the highest concentration of CBD at 1 and 2H post-oral gavage, and adipose tissue had the highest concentration at 3H which was consistent across all three carrier oils. CONCLUSIONS: This study profiled the greatest number of tissues to-date for the acute distribution of CBD and THC following oral consumption with a lipid carrier in mice which demonstrated a non-uniform distribution to tissues over time. SES oil proved to be far more effective as a carrier oil at delivering orally consumed cannabinoids to tissues compared to two different n-3 PUFA containing oils. Further developing our fundamental understanding of cannabinoid distribution across tissues following their consumption from foods and pharmaceuticals are necessary to establish specific pharmacokinetic profiles to aid oral dosing strategies and maximize the bioactive potential of cannabinoids.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".