Comparative Anti-Obesity Potential of Cannabigerol-Dominant Cannabis sativa L. Inflorescence Extracts via Differential Regulation of Lipid Metabolism in 3T3-L1 Cells

Article type: Research Article

Keywords: cannabinoid, cannabigerol, obesity, anti-obesity

Authors: Ji-Ye Han, Osoung Kwon, Yun Jung Lee ⚬, Minji Choi, Bori Lee, Dae-Ki Kim, Soohyang Noh ⚬, Mansoo Cho, Young-Mi Lee

Affiliations: Department of Oriental Pharmacy, College of Pharmacy, and Wonkwang-Oriental Medicines Research Institute, Wonkwang University, 460 Iksan-daero, Iksan 54538, Republic of Korea; hsue0112@gmail.com (J.-Y.H.); shrons@wku.ac.kr (Y.J.L.);; The One Health Design, Iksan 54575, Republic of Korea; Department of Immunology, Medical School, Jeonbuk National University, Jeonju 54907, Republic of Korea; Graduate School of Techno Design, Kookmin University, Seoul 02707, Republic of Korea

License: © 2026 by the authors. CC BY 4.0 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

Article links: DOI: 10.3390/ijms27041747  |  PubMed: 41751885  |  PMC: PMC12941217

Relevance: Moderate: mentioned 3+ times in text

Full text: PDF (5.4 MB)

1. Introduction

Obesity is a complex, multifactorial chronic disease that has seen a sharp rise in modern society [ref. 1]. Beyond being a significant clinical concern on its own, it serves as a primary driver for the onset of metabolic complications, including type 2 diabetes and cardiovascular diseases [ref. 2]. Considerable efforts have been made to treat obesity, leading to the development of various pharmacological interventions, including cannabinoid receptor type 1 (CB1) blockers and pancreatic lipase inhibitors [ref. 3]. However, these drugs have been reported to cause severe side effects, such as depression and cardiovascular disease [ref. 4]. Furthermore, due to limitations including the long-term nature of treatment and weight regain, effective obesity therapy remains a significant challenge.

Obesity is closely linked to several lipid metabolic pathways, including adipogenesis, lipogenesis, lipolysis, and white adipose tissue (WAT) browning. While Peroxisome Proliferator-Activated Receptor gamma (PPARγ) and CCAAT/Enhancer-binding Protein alpha (C/EBPα) act as master transcriptional regulators of adipogenesis, Sterol Regulatory Element Binding Protein 1c (SREBP-1c) and Fatty Acid Synthase (FAS) primarily govern the lipogenic process [ref. 5,ref. 6]. Suppression of these factors inhibits adipogenesis and reduces subsequent lipid accumulation, effectively mitigating the progression of obesity [ref. 7]. Lipolysis is driven by Hormone-Sensitive Lipase (HSL) and Adipose Triglyceride Lipase (ATGL), while thermogenesis and WAT browning are regulated by Uncoupling Protein 1 (UCP1) and Peroxisome Gamma Coactivator 1 alpha (PGC-1α) [ref. 8,ref. 9]. The coordinated activation of these factors promotes lipolysis and energy expenditure, leading to significant anti-obesity outcomes [ref. 10].

Cannabis sativa L. has been utilized for millennia across diverse applications, including medicinal, nutritional, and industrial purposes [ref. 11,ref. 12]. The plant is reported to possess a broad spectrum of pharmacological properties, including analgesic, anti-inflammatory, anti-cancer, and anti-bacterial effects [ref. 13]. Due to these therapeutic benefits, it is currently used as a clinical treatment for diseases such as multiple sclerosis and epilepsy [ref. 14,ref. 15].

Cannabinoids are considered the primary constituents of C. sativa. Among these, cannabidiol (CBD) exerts anti-obesity effects by inhibiting lipogenesis and promoting lipolysis in adipose tissue [ref. 16]. Furthermore, C. sativa comprises various minor cannabinoids, including cannabigerol (CBG) and cannabichromene (CBC), which interact with other cannabinoids or terpenoids to exert synergistic effects [ref. 17]. Given that these minor compounds significantly modulate the overall pharmacological profile of the plant, detailed studies on their individual and collective mechanisms are warranted. Such research is crucial for identifying novel therapeutic targets to manage complex metabolic disorders, particularly obesity.

To evaluate the anti-obesity potential of C. sativa, the 3T3-L1 cell line was employed as a widely recognized in vitro model. This cell line mimics the differentiation of preadipocytes into mature adipocytes and is primarily used to investigate the mechanisms of lipid metabolism [ref. 18]. Accordingly, the present study investigated the anti-obesity mechanisms of cannabigerol-dominant C. sativa inflorescence extracts (CEs), prepared using various ethanol concentrations, within the 3T3-L1 cell model. Furthermore, the therapeutic potential of CE as both a primary anti-obesity agent and a clinical adjuvant was evaluated.

2. Results

2.1. Quantitative Analysis of Cannabinoids in CE via UPLC

To evaluate the phytochemical characteristics of the extracts, CBG-dominant C. sativa inflorescences were extracted with four different ethanol concentrations: 30%, 50%, 70%, and 99.5%. These extracts were designated as CE30, CE50, CE70, and CE99.5, respectively. The phytochemical profiling of CEs via UPLC revealed the presence of seven distinct cannabinoids (Figure 1). Quantitative analysis identified CBG and cannabigerolic acid (CBGA) as the predominant constituents, followed by CBC. The levels of all detected cannabinoids peaked in CE99.5 (Table 1). Specifically, the total CBG content exhibited an ethanol concentration-dependent increase, with measured values of 115.35 ± 1.42, 184.13 ± 0.43, 272.76 ± 0.57, and 412.55 ± 0.46 μg/mL for CE30, CE50, CE70, and CE99.5, respectively (Table 2).

2.2. Effect of CE on the Cell Viability of 3T3-L1 Cells

Cell viability assays were performed on 3T3-L1 cells at concentrations of 2.5, 5, 10, 20, 40, and 80 µg/mL of CEs. While CE30, CE50, and CE70 preserved over 90% viability up to 40 µg/mL (Figure 2A–C), CE99.5 maintained cell viability at concentrations up to 20 µg/mL, beyond which a reduction was observed (Figure 2D).

2.3. CE Suppresses the Differentiation of 3T3-L1 Cells

A dose-dependent reduction in 3T3-L1 differentiation was demonstrated by Oil Red O (ORO) staining across all CE treatments (Figure 3A). The minimal inhibitory concentration was identified as 1 µg/mL for CE30, CE50, and CE70, whereas inhibition by CE99.5 was initiated from 0.5 µg/mL. At a concentration of 4 µg/mL, differentiation was inhibited by 26%, 35%, 47%, and 62% for CE30, CE50, CE70, and CE99.5, respectively, with the highest efficacy observed in the CE99.5-treated group (Figure 3B–E).

2.4. CE Downregulates Adipogenic and Lipogenic Gene Expression in 3T3-L1 Cells

The expression levels of PPARγ, C/EBPα, SREBP-1c, and FAS were significantly downregulated following CE treatment, with the most pronounced inhibitory effect observed in the CE99.5-treated group. Specifically, the mRNA levels of PPARγ and C/EBPα were diminished by 62% and 63%, respectively, in response to 4 µg/mL of CE99.5 compared to the differentiation control (Figure 4A,B). Furthermore, the expression of SREBP-1c and FAS was suppressed by up to 82% and 79%, respectively, under the same conditions (Figure 4C,D).

2.5. CE Upregulates Lipolytic and Brown Adipocyte-Specific Gene Expression in 3T3-L1 Cells

The mRNA levels of HSL, ATGL, UCP1, and PGC-1α were significantly downregulated upon differentiation in 3T3-L1 cells; however, these reductions were effectively reversed by CE treatment. A dose-dependent elevation in their expression was observed, with particularly marked increases induced by CE70 and CE99.5. Specifically, the expression of HSL and ATGL was promoted by CE99.5, reaching 1.86-fold and 3.4-fold higher levels than the differentiation control, respectively (Figure 5A,B). Furthermore, UCP1 and PGC-1α levels were similarly enhanced by CE99.5, with maximum increases of 7.0-fold and 3.4-fold observed (Figure 5C,D).

2.6. CE Regulates the Protein Expression of Adipogenic Factors in 3T3-L1 Cells

The protein expression levels of PPARγ and C/EBPα, which were upregulated during 3T3-L1 differentiation, were significantly attenuated by CE treatment. These adipogenic markers were dose-dependently reduced across all samples, with the inhibitory effects being particularly prominent in the CE70 and CE99.5 groups. The most potent suppression was observed in the CE99.5-treated group, resulting in a maximum reduction of 82% and 70% for PPARγ and C/EBPα, respectively (Figure 6).

2.7. CE Inhibits the Protein Expression of Lipogenic Factors in 3T3-L1 Cells

The expression levels of SREBP-1c and FAS were substantially attenuated following CE treatment. A notable suppression was observed in the CE50, CE70, and CE99.5 groups. Specifically, the protein levels of SREBP-1c and FAS were inhibited by up to 65% and 77%, respectively, by CE70. The greatest reduction was observed in the CE99.5 group, where the expression of these markers was suppressed by up to 87% and 78%, respectively (Figure 7).

2.8. CE Promotes the Protein Expression of Lipolytic Factors in 3T3-L1 Cells

The expression levels of phosphorylated HSL (p-HSL) and ATGL, which were decreased during 3T3-L1 differentiation, were significantly restored by CE treatment. These lipolytic markers were increased in a dose-dependent manner, with notable elevations observed in the CE70 and CE99.5 groups. Specifically, compared to the differentiation group, the protein levels of p-HSL and ATGL were enhanced up to 4.9-fold and 7-fold by CE70, and further increased up to 5.9-fold and 11.7-fold by CE99.5, respectively (Figure 8).

2.9. CE Promotes the Protein Expression of Brown Adipocyte-Specific Factors in 3T3-L1 Cells

The protein levels of UCP1 and PGC-1α, which were reduced following differentiation, were reversed by CE treatment. Their expression was significantly enhanced in extracts prepared with higher ethanol concentrations, with a notable increase observed in the CE70 group. The most pronounced elevation occurred in the CE99.5-treated group, where UCP1 and PGC-1α expression increased up to 8.9-fold and 4.7-fold, respectively, compared to the differentiation group (Figure 9).

3. Discussion

This study demonstrated the therapeutic potential of CBG-dominant C. sativa inflorescence in mitigating obesity by modulating the molecular pathways of adipogenesis, lipogenesis, lipolysis, and WAT browning in the 3T3-L1 cell model.

Current pharmacological strategies for obesity primarily focus on restoring energy balance through hormonal modulation, as exemplified by Glucagon-Like Peptide 1 (GLP-1) receptor agonists [ref. 19]. However, their clinical application is frequently constrained by prohibitive costs and adverse gastrointestinal effects [ref. 20]. Consequently, a comprehensive understanding of the multifaceted molecular pathways governing energy homeostasis is essential for developing sustainable and safe therapeutic approaches for weight management.

C. sativa serves as a promising candidate for obesity treatment, as its diversity of bioactive compounds allows for a multifaceted therapeutic approach that targets various metabolic pathways simultaneously. Its therapeutic potential is attributed not only to the major cannabinoids, typically represented by tetrahydrocannabinol (THC) and CBD, but also to the synergistic actions of various minor cannabinoids that modulate multiple metabolic pathways [ref. 21]. A thorough understanding of minor cannabinoids—including CBG, CBC, and cannabinol (CBN)—is required to appreciate the multifaceted pharmacological value of C. sativa [ref. 22]. These compounds contribute significantly to the “entourage effect,” wherein the holistic interaction of all plant constituents produces enhanced therapeutic benefits compared to single-agent treatments [ref. 23,ref. 24]. Their unique pharmacological profiles enable both individual bioactivity and synergistic contributions through complex interactions with other components [ref. 25]. In this regard, the CBG-dominant C. sativa extract serves as an appropriate sample to investigate the synergy of multiple cannabinoids, with CBG representing a major constituent that contributes to the functional profile of this complex mixture.

To determine the optimal extraction conditions for maximizing anti-obesity efficacy, the bioactivity of CE prepared with various ethanol concentrations (30%, 50%, 70%, and 99.5%) was evaluated using the 3T3-L1 cell model. While all CEs exhibited significant anti-obesity potential, the most profound effects were observed in the CE99.5 group. The superior bioactivity observed in CE99.5 may be attributed to the chemical properties of its primary constituents [ref. 26]. Cannabinoids, including CBD, THC, and CBG, possess a hydrophobic nature, which facilitates their optimal solubility in high-concentration ethanol. The chemical analysis confirmed a direct correlation between the ethanol concentration and the total cannabinoid content (Figure 1; Table 1 and Table 2).

Adipogenesis and lipogenesis represent essential targets of obesity [ref. 27]. In this study, these metabolic processes were significantly inhibited by CE70 and CE99.5 in 3T3-L1 cells, as evidenced by the marked downregulation of key transcription factors and enzymes, such as PPARγ, C/EBPα, SREBP-1c, and FAS (Figure 3, Figure 4, Figure 6 and Figure 7). These findings suggest that CE effectively suppresses adipocyte hypertrophy and hyperplasia by impeding the initial stages of lipid formation.

The activation of lipolysis and WAT browning is a crucial therapeutic strategy for obesity, as these processes actively promote energy expenditure and limit lipid accumulation [ref. 28,ref. 29]. Our results demonstrate that CE significantly enhances these metabolic pathways, addressing the core challenges of energy imbalance. Specifically, the substantial upregulation of key lipolytic enzymes (HSL and ATGL) and thermogenesis markers (UCP1 and PGC-1α) indicates that CE does not merely reduce lipid accumulation but actively transforms adipocytes into a more metabolically active state. This regulatory effect was observed in a dose-dependent manner, with CE99.5—characterized by the highest ethanol concentration—exhibiting the most potent activity (Figure 5,Figure 8 and Figure 9). Collectively, these findings suggest that CE offers a comprehensive metabolic benefit by simultaneously accelerating lipid lysis and enhancing thermogenic energy loss, marking it as a sophisticated multi-targeted agent for obesity management.

While the anti-obesity effects of CBD have been extensively studied, research focusing on the therapeutic potential of CBG remains relatively limited [ref. 16,ref. 30]. This study addresses the current limited understanding of CBG by demonstrating that CBG-dominant C. sativa extracts possess the potential to effectively regulate lipid metabolism. While these effects arise from the synergy of the complex mixture, CBG acts as the predominant functional constituent in this multi-targeted approach. Furthermore, our findings corroborate previous reports indicating that CBG exerts inhibitory effects on obesity and insulin resistance-related metabolic dysregulation [ref. 31]. Indeed, recent studies emphasize that the structural properties and spatial conformation of CBG play a critical role in determining its functional efficacy [ref. 32].

Despite these promising in vitro findings, further in vivo studies are warranted to fully elucidate the long-term safety and metabolic pharmacokinetics of CE in complex biological systems. Additionally, while this study emphasizes the collective impact of the CBG-dominant C. sativa extracts, the precise contribution of each minor cannabinoid and their potential synergistic interactions—often referred to as the entourage effect—remain to be fully characterized. To address this, further research utilizing isolated single cannabinoids is required to elucidate the specific functional role of each constituent and to validate the underlying mechanisms behind their therapeutic efficacy. In conclusion, these results suggest that CE acts as a safe and effective therapeutic agent by simultaneously regulating adipogenesis, lipogenesis, lipolysis, and WAT browning.

4. Materials and Methods

4.1. Preparation and Extraction of C. sativa Inflorescences

CBG-dominant C. sativa ‘Sativa G’ inflorescences were obtained from Nongboomind (Accession number: NBM-F02-250304, Andong, Republic of Korea). Their authenticity and cannabinoid profiles were verified by the Gyeongbuk Institute for Bio Industry (GIB, Daegu, Republic of Korea) according to the GIB-KQI-203 quantitative analysis protocol. Dried C. sativa inflorescences were subjected to ultrasonic extraction (40 kHz, 40 °C) with ethanol at various concentrations (30%, 50%, 70%, and 99.5%) using a solid-to-solvent ratio of 1:15 (w/v). The extraction was performed in triplicate for 30 min each. The resulting extracts were filtered through 6 μm filter paper (ADVANTEC, Tokyo, Japan) and concentrated under reduced pressure using a rotary vacuum evaporator (EYELA N-1110, Tokyo, Japan) at 40 °C. Subsequently, the extracts were lyophilized at −80 °C to obtain a powder (CE). The final extraction yields for the 30%, 50%, 70%, and 99.5% ethanol concentrations were 20.77%, 31.80%, 26.04%, and 19.50% (w/w), respectively. The CE was stored at -20 °C until further use. For cellular treatment, all extracts were dissolved in DMSO, with the final concentration of DMSO maintained below 0.1% (v/v) to ensure no cytotoxic effects.

4.2. Quantitative Analysis of Cannabinoids

The cannabinoid contents in the CE were determined using an ACQUITY UPLC H-Class system (Waters, Milford, MA, USA) equipped with an ACQUITY UPLC BEH C18 Column (1.7 µm, 2.1 × 100 mm) and a VanGuard Pre-column (1.7 µm, 2.1 × 5 mm). Cannabinoid standards were purchased from Cayman Chemical (Ann Arbor, MI, USA), Absolute Standards (Hamden, CT, USA), and U.S. Pharmacopeia (Rockville, MD, USA). Before analysis, samples and standards were filtered through a 0.2 µm polytetrafluoroethylene syringe filter (Hyundai Micro, Seoul, Republic of Korea). The mobile phases consisted of (A) 0.1% formic acid in water, (B) 0.1% formic acid in methanol, and (C) 0.1% formic acid in acetonitrile. A multi-step gradient elution was applied as detailed in Supplementary Table S1. The column temperature, flow rate, and injection volume were maintained at 30 °C, 0.3 mL/min, and 2 µL, respectively, with detection at 230 nm.

4.3. Cell Culture

The 3T3-L1 (mouse preadipocyte) cells were acquired from the Korean Cell Line Bank (KCLB, Seoul, Republic of Korea). These cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% calf serum (Thermo Fisher Scientific, Waltham, MA, USA), 10 mM HEPES (WelGENE, Daegu, Republic of Korea), and 1% penicillin–streptomycin. The cells were maintained in a humidified incubator at 37 °C with 5% CO₂.

4.4. Adipocyte Differentiation of 3T3-L1 Cells

3T3-L1 preadipocytes were grown to confluence and induced to differentiate using a standard MDI cocktail (0.5 mM IBMX, 1 μM dexamethasone, and 1 μg/mL insulin in DMEM with 10% FBS) for 3 days. The medium was then replaced with maintenance medium (DMEM with 10% FBS and 1 μg/mL insulin) for 3 days, followed by incubation in DMEM supplemented with 10% FBS until day 9. CE was co-administered during each medium change every 2 days throughout the process. FBS was purchased from Thermo Fisher Scientific (Waltham, MA, USA), and other reagents were from Sigma-Aldrich (St. Louis, MO, USA).

4.5. Cell Viability Assay

Cell viability was assessed via the MTT assay. MTT was obtained from Sigma-Aldrich (St. Louis, MO, USA). 3T3-L1 cells were exposed to CE at concentrations of 2.5, 5, 10, 20, 40, and 80 μg/mL for 24 h. After the treatment, the cells were incubated for 4 h with MTT solution at a final concentration of 50 μg/mL. The generated formazan crystals were dissolved in DMSO for 30 min, and absorbance was measured at 540 nm using a SpectraMAX 190 microplate reader (Molecular Devices, San Jose, CA, USA).

4.6. Oil Red O Staining

ORO was purchased from Sigma-Aldrich (St. Louis, MO, USA). Differentiated 3T3-L1 cells were fixed with 10% neutral buffered formalin for 30 min and subsequently incubated with ORO working solution for 1 h at room temperature. After rinsing with distilled water to remove background staining, lipid droplets were visualized and imaged using an EVOS XL Core microscope (Invitrogen, Carlsbad, CA, USA). For quantitative analysis, the stained ORO was eluted with 100% isopropanol for 5 min, and the absorbance was measured at 492 nm using a SpectraMAX 190 microplate reader (Molecular Devices, San Jose, CA, USA).

4.7. Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR)

Total RNA was extracted using RiboEX reagent (GeneAll Biotechnology, Seoul, Republic of Korea), and its concentration and purity were assessed with a BioSpectrometer (Eppendorf, Hamburg, Germany). For cDNA synthesis, the HelixCript Easy cDNA Synthesis kit (NanoHelix, Daejeon, Republic of Korea) was utilized in a SimpliAmp Thermal Cycler (Applied Biosystems, Foster City, CA, USA). Quantitative real-time PCR was performed using the RealHelix Premier qPCR kit (NanoHelix, Daejeon, Republic of Korea) on a StepOnePlus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). Relative gene expression levels were calculated after normalization to GAPDH. The specific primer sequences utilized for RT-qPCR are provided in Supplementary Table S2.

4.8. Western Blot Analysis

Proteins were extracted using RIPA buffer (ELPIS-Bioech, Daejeon, Republic of Korea) with Halt™ protease inhibitors (Thermo Fisher Scientific, Waltham, MA, USA) and quantified via Bradford assay (Bio-Rad, Hercules, CA, USA). Samples were denatured in 5X Laemmli buffer at 100 °C for 5 min, separated by 10% SDS-PAGE, and transferred to PVDF membranes. Following blocking with 5% non-fat milk, membranes were incubated with primary antibodies overnight at 4 °C, then with HRP-conjugated secondary antibodies for 1 h. Protein bands were visualized using ECL reagent (Kindle Biosciences, Greenwich, CT, USA) on a ChemiDoc system (Bio-Rad, Hercules, CA, USA). Antibodies are listed in Supplementary Table S3.

4.9. Statistical Analysis

Data are presented as mean ± SD. Statistical significance was determined by one-way ANOVA followed by Tukey’s post hoc test using GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, USA). Differences were considered significant at a p-value of <0.05, with p-values indicated as follows: * p < 0.05, ** p < 0.01, and *** p < 0.001.

References

1. G.B.D.O. Collaborators, A. Afshin, C.J.L. Murray. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N. Engl. J. Med., 2017. [DOI | PubMed]
2. A. Kabir, A. Karimi Behnagh. Prevalence patterns of overweight and obesity in the world: An age-period-cohort analysis. PLoS ONE, 2025. [DOI | PubMed]
3. T.D. Muller, M. Bluher, M.H. Tschop, R.D. DiMarchi. Anti-obesity drug discovery: Advances and challenges. Nat. Rev. Drug Discov., 2022. [DOI | PubMed]
4. L. Liu, Z. Li, W. Ye, P. Peng, Y. Wang, L. Wan, J. Li, M. Zhang, Y. Wang, R. Liu. Safety and effects of anti-obesity medications on weight loss, cardiometabolic, and psychological outcomes in people living with overweight or obesity: A systematic review and meta-analysis. EClinicalMedicine, 2025. [DOI | PubMed]
5. R.H. Lustig, D. Collier, C. Kassotis, T.A. Roepke, M.J. Kim, E. Blanc, R. Barouki, A. Bansal, M.C. Cave, S. Chatterjee. Obesity I: Overview and molecular and biochemical mechanisms. Biochem. Pharmacol., 2022. [DOI | PubMed]
6. H. Park, U. Ju, J. Park, J. Song, D. Shin, K. Lee, L. Jeong, J. Yu, H. Lee, J. Cho. PPARγ neddylation essential for adipogenesis is a potential target for treating obesity. Cell Death Differ., 2016. [DOI | PubMed]
7. L. He, Z. Su, S. Wang. The anti-obesity effects of polyphenols: A comprehensive review of molecular mechanisms and signal pathways in regulating adipocytes. Front. Nutr., 2024. [DOI | PubMed]
8. C. Desgrouas, T. Thalheim, M. Cerino, C. Badens, N. Bonello-Palot. Perilipin 1: A systematic review on its functions on lipid metabolism and atherosclerosis in mice and humans. Cardiovasc. Res., 2024. [DOI | PubMed]
9. C.F. Cheng, H.C. Ku, H. Lin. PGC-1alpha as a Pivotal Factor in Lipid and Metabolic Regulation. Int. J. Mol. Sci., 2018. [DOI | PubMed]
10. P. Morigny, J. Boucher, P. Arner, D. Langin. Lipid and glucose metabolism in white adipocytes: Pathways, dysfunction and therapeutics. Nat. Rev. Endocrinol., 2021. [DOI | PubMed]
11. P. Kumar, D.K. Mahato, M. Kamle, R. Borah, B. Sharma, S. Pandhi, V. Tripathi, H.S. Yadav, S. Devi, U. Patil. Pharmacological properties, therapeutic potential, and legal status of Cannabis sativa L.: An overview. Phytother. Res., 2021. [DOI | PubMed]
12. M. Balant, A. Gras, M. Ruz, J. Valles, D. Vitales, T. Garnatje. Traditional uses of Cannabis: An analysis of the CANNUSE database. J. Ethnopharmacol., 2021. [DOI | PubMed]
13. A. Stasiłowicz-Krzemień, W. Nogalska, Z. Maszewska, M. Maleszka, M. Dobroń, A. Szary, A. Kępa, M. Żarowski, K. Hojan, M. Lukowicz. The use of compounds derived from Cannabis sativa in the treatment of epilepsy, painful conditions, and neuropsychiatric and neurodegenerative disorders. Int. J. Mol. Sci., 2024. [DOI | PubMed]
14. O. Devinsky, J.H. Cross, L. Laux, E. Marsh, I. Miller, R. Nabbout, I.E. Scheffer, E.A. Thiele, S. Wright. Trial of cannabidiol for drug-resistant seizures in the Dravet syndrome. N. Engl. J. Med., 2017. [DOI | PubMed]
15. Y.Y. Syed, K. McKeage, L.J. Scott. Delta-9-tetrahydrocannabinol/cannabidiol (Sativex®): A review of its use in patients with moderate to severe spasticity due to multiple sclerosis. Drugs, 2014. [DOI | PubMed]
16. P. Bielawiec, E. Harasim-Symbor, A. Chabowski. Phytocannabinoids: Useful drugs for the treatment of obesity? Special focus on cannabidiol. Front. Endocrinol., 2020. [DOI]
17. J.E. LaVigne, R. Hecksel, A. Keresztes, J.M. Streicher. Cannabis sativa terpenes are cannabimimetic and selectively enhance cannabinoid activity. Sci. Rep., 2021. [DOI | PubMed]
18. S.P. Poulos, M.V. Dodson, G.J. Hausman. Cell line models for differentiation: Preadipocytes and adipocytes. Exp. Biol. Med. (Maywood), 2010. [DOI | PubMed]
19. A.M. Jastreboff, R.F. Kushner. New Frontiers in Obesity Treatment: GLP-1 and Nascent Nutrient-Stimulated Hormone-Based Therapeutics. Annu. Rev. Med., 2023. [DOI | PubMed]
20. D.J. Drucker. Efficacy and Safety of GLP-1 Medicines for Type 2 Diabetes and Obesity. Diabetes Care, 2024. [DOI | PubMed]
21. N. Shalev, M. Kendall, S.M. Anil, S. Tiwari, H. Peeri, N. Kumar, E. Belausov, A.C. Vinayaka, H. Koltai. Phytocannabinoid compositions from cannabis act synergistically with PARP1 inhibitor against ovarian cancer cells in vitro and affect the Wnt signaling pathway. Molecules, 2022. [DOI | PubMed]
22. F.Z. Laaboudi, M. Rejdali, H. Amhamdi, A. Salhi, A. Elyoussfi, M. Ahari. In the weeds: A comprehensive review of cannabis; its chemical complexity, biosynthesis, and healing abilities. Toxicol. Rep., 2024. [DOI | PubMed]
23. R. Andre, A.P. Gomes, C. Pereira-Leite, A. Marques-da-Costa, L. Monteiro Rodrigues, M. Sassano, P. Rijo, M.D.C. Costa. The Entourage Effect in Cannabis Medicinal Products: A Comprehensive Review. Pharmaceuticals, 2024. [DOI | PubMed]
24. H. Koltai, D. Namdar. Cannabis Phytomolecule ‘Entourage’: From Domestication to Medical Use. Trends Plant Sci., 2020. [DOI | PubMed]
25. F.T. Chacon, W.M. Raup-Konsavage, K.E. Vrana, J.J. Kellogg. Secondary Terpenes in Cannabis sativa L.: Synthesis and Synergy. Biomedicines, 2022. [DOI | PubMed]
26. T. Gulck, B.L. Moller. Phytocannabinoids: Origins and Biosynthesis. Trends Plant Sci., 2020. [DOI | PubMed]
27. S. Kersten. Peroxisome proliferator activated receptors and obesity. Eur. J. Pharmacol., 2002. [DOI | PubMed]
28. S.-M. An, S.-H. Cho, J.C. Yoon. Adipose tissue and metabolic health. Diabetes Metab. J., 2023. [DOI | PubMed]
29. G.F. Grabner, H. Xie, M. Schweiger, R. Zechner. Lipolysis: Cellular mechanisms for lipid mobilization from fat stores. Nat. Metab., 2021. [DOI | PubMed]
30. E.K.F.F. Cavalheiro, A.B. Costa, D.H. Salla, M.R.d. Silva, T.F. Mendes, L.E.d. Silva, C.d.R. Turatti, R.M.d. Bitencourt, G.T. Rezin. Cannabis sativa as a treatment for obesity: From anti-inflammatory indirect support to a promising metabolic re-establishment target. Cannabis Cannabinoid Res., 2022. [DOI | PubMed]
31. P. Bielawiec, L. Swierkot, K. Konstantynowicz-Nowicka, A. Chabowski, A. Błachnio-Zabielska, E. Harasim-Symbor. Cannabigerol—A potent regulator of insulin sensitivity in rat’s skeletal muscle via targeting the sphingolipid metabolism and PI3K/Akt/mTOR pathway?. Int. J. Biochem. Cell Biol., 2025. [DOI | PubMed]
32. M. Salha, H. Adenusi, J.H. Dupuis, E. Bodo, B. Botta, I. McKenzie, R.Y. Yada, D.H. Farrar, J. Magolan, K.V. Tian. Bioactivity of the cannabigerol cannabinoid and its analogues—The role of 3-dimensional conformation. Org. Biomol. Chem., 2023. [DOI | PubMed]