Bioreactor-Based Suspension Cultures of <i>Cannabis sativa</i> for Enhanced Production of Anti-Inflammatory Cannabinoid Derivatives
Bibliographic record
Abstract
Cannabis sativa synthesizes diverse cannabinoids with significant pharmacological value, but existing suspension cultures show low metabolite yields and limited scalability. This study establishes bioreactor-based cell suspension system to enhance cannabinoid biosynthesis in C. sativa . Petiole explants cultured on MS medium with 4 mg/L BAP and 0.01 mg/L NAA produced 95.83 ± 0.74% friable callus. Suspension cultures accumulated 352.29 ± 3.90 g/L fresh biomass in 28 days, showing 22.4-fold increase upon scale-up in stirred-tank bioreactor. Methanolic extracts (60 °C) showed strong anti-inflammatory activity, reducing TNF-α and IL-6 by 88.40 ± 0.87 and 92.03 ± 1.55% at 30 μg mL –1 without cytotoxicity. Metabolomic profiling identified putative cannabinoid derivatives, with THCA-C1 (0.05%) exhibiting highest binding affinity (−8.4 kcal/mol) to inflammatory targets based on docking and dynamics analyses. Overall, these results provide the first evidence for scalable cannabinoid biosynthesis in bioreactor-grown C. sativa cell suspensions, underscoring their potential for sustainable production of anti-inflammatory therapeutics.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".