RESUMO
Background: Preclinical studies indicate that cannabidiol (CBD), the primary nonaddictive component of cannabis, has a wide range of reported pharmacological effects such as analgesic and anxiolytic actions; however, the exact mechanisms of action for these effects have not been examined in chronic osteoarthritis (OA). Similar to other chronic pain syndromes, OA pain can have a significant affective component characterized by mood changes. Serotonin (5-HT) is a neurotransmitter implicated in pain, depression, and anxiety. Pain is often in comorbidity with mood and anxiety disorders in patients with OA. Since primary actions of CBD are analgesic and anxiolytic, in this first in vivo positron emission tomography (PET) imaging study, we investigate the interaction of CBD with serotonin 5-HT1A receptor via a combination of in vivo neuroimaging and behavioral studies in a well-validated OA animal model. Methods: The first aim of this study was to evaluate the target involvement, including the evaluation of modulation by acute administration of CBD, or a specific target antagonist/agonist intervention, in control animals. The brain 5-HT1A activity/availability was assessed via in vivo dynamic PET imaging (up to 60 min) using a selective 5-HT1A radioligand ([18F]MeFWAY). Tracer bindings of 17 ROIs were evaluated based on averaged SUVR values over the last 10 min using CB as the reference region. We subsequently examined the neurochemical and behavioral alterations in OA animals (induction with monosodium iodoacetate (MIA) injection), as compared to control animals, via neuroimaging and behavioral assessment. Further, we examined the effects of repeated low-dose CBD treatment on mechanical allodynia (von Frey tests) and anxiety-like (light/dark box tests, L/D), depressive-like (forced swim tests, FST) behaviors in OA animals, as compared to after vehicle treatment. Results: The tracer binding was significantly reduced in control animals after an acute dose of CBD administered intravenously (1.0 mg/kg, i.v.), as compared to that for baseline. This binding specificity to 5-HT1A was further confirmed by a similar reduction of tracer binding when a specific 5-HT1A antagonist WAY1006235 was used (0.3 mg/kg, i.v.). Mice subjected to the MIA-induced OA for 13-20 days showed a decreased 5-HT1A tracer binding (25% to 41%), consistent with the notion that 5-HT1A plays a role in the modulation of pain in OA. Repeated treatment with CBD administered subcutaneously (5 mg/kg/day, s.c., for 16 days after OA induction) increased 5-HT1A tracer binding, while no significant improvement was observed after vehicle. A trend of increased anxiety or depressive-like behavior in the light/dark box or forced swim tests after OA induction, and a decrease in those behaviors after repeated low-dose CBD treatment, are consistent with the anxiolytic action of CBD through 5HT1A receptor activation. There appeared to be a sex difference: females seem to be less responsive at the baseline towards pain stimuli, while being more sensitive to CBD treatment. Conclusion: This first in vivo PET imaging study in an OA animal model has provided evidence for the interaction of CBD with the serotonin 5-HT1A receptor. Behavioral studies with more pharmacological interventions to support the target involvement are needed to further confirm these critical findings.
RESUMO
We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy andscope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners.
