Università degli studi di Modena e Reggio Emilia

The prevalence of obesity is steadily rising, making safe and more efficient anti-obesity treatments an urgent medical need. Growing evidence correlates obesity and comorbidities, including anxiety and depression, with the development of a low-grade inflammation in peripheral and central tissues. We hypothesized that attenuating neuroinflammation might reduce weight gain and improve mood. We investigated the efficacy of a methanolic extract from Helichrysum stoechas (L.) Moench (HSE), well-known for its anti-inflammatory properties, and its main constituent arzanol (AZL). HPLC-ESI-MS2 and HPLC-UV were used to characterize the extract. HSE effects on mood and feeding behavior was assessed in mice. The mechanism of action of HSE and AZL was investigated in hippocampus samples and SH-SY5Y cells by western blotting and immunofluorescence. Oral administration of HSE for 3 weeks limited weight gain with no significant decrease in food intake. HSE produced an anxiolytic-like and antidepressant-like phenotype comparable to diazepam and amitriptyline, respectively, in the absence of locomotor and cognitive impairments and induced neuroprotective effects in glutamate-exposed SH-SY5Y cells. A dose-dependent reduction of SIRT1 expression was detected in SH-SY5Y cells and in hippocampal samples from HSE-treated mice. The inhibition of the SIRT1-FoxO1 pathway was induced in the hypothalamus. Molecular docking studies proposed a mechanism of SIRT1 inhibition by AZL, confirmed by the evaluation of inhibitory effects on SIRT1 enzymatic activity. HSE limited weight gain and comorbidities through an AZL-mediated SIRT1 inhibition. These activities indicate HSE an innovative therapeutic perspective for obesity and associated mood disorders.

The scientific interest in Cannabis sativa L. analysis has been rapidly increasing in recent years, especially for what concerns cannabinoids, plant secondary metabolites which are well known for having many biological properties. High-performance liquid chromatography (HPLC) is frequently used for both the qualitative and quantitative analysis of cannabinoids in plant extracts from C. sativa and its derived products. Many studies have been focused on the main cannabinoids, such as Delta(9)-tetrahydrocannabinolic acid (Delta(9)-THCA), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA) and their decarboxylated derivatives, such as Delta(9)-tetrahydrocannabinol (Delta(THC)-T-9), cannabidiol (CBD) and cannabigerol (CBG). In addition to the abovementioned compounds, the plant produces other metabolites of the same chemical class, and some of them have shown interesting biological activities.In the light of this, it is important to have efficient analytical methods for the simultaneous separation of cannabinoids, which is quite complex since they present similar chemical-physical characteristics. The present work is focused on the use of the Design of Experiments technique (DoE) to develop and optimise an HPLC method for the simultaneous separation of 14 cannabinoids. Experimental design optimisation was applied by using a Central Composite Face-Centered design to achieve the best resolution with minimum experimental trials. Five significant variables affecting the chromatographic separation, including ammonium formate concentration, gradient elution, run time and flow rate, were studied. A multivariate strategy, based on Principal Component Analysis (PCA) and Partial Least Squared (PLS) regression, was used to define the best operative conditions. The developed method allowed for the separation of 12 out of 14 cannabinoids. Due to co-elution phenomena, HPLC coupled with a triple quadrupole mass analyser (HPLC-ESI-MS/MS) was applied, monitoring the specific transitions of each compound in the multiple reaction monitoring (MRM) mode. Finally, the optimised method was applied to C. sativa extracts having a different cannabinoid profile to demonstrate its efficiency to real samples.The methodology applied in this study can be useful for the separation of other cannabinoid mixtures, by means of appropriate optimisation of the experimental conditions.