Rapid antidepressant effects of the psychedelic ayahuasca in treatment-resistant depression: a randomized placebo-controlled trial

Background Recent open-label trials show that psychedelics, such as ayahuasca, hold promise as fast-onset antidepressants in treatment-resistant depression. Methods To test the antidepressant effects of ayahuasca, we conducted a parallel-arm, double-blind randomized placebo-controlled trial in 29 patients with treatment-resistant depression. Patients received a single dose of either ayahuasca or placebo. We assessed changes in depression severity with the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating scale at baseline, and at 1 (D1), 2 (D2), and 7 (D7) days after dosing. Results We observed significant antidepressant effects of ayahuasca when compared with placebo at all-time points. MADRS scores were significantly lower in the ayahuasca group compared with placebo at D1 and D2 (p = 0.04), and at D7 (p < 0.0001). Between-group effect sizes increased from D1 to D7 (D1: Cohen's d = 0.84; D2: Cohen's d = 0.84; D7: Cohen's d = 1.49). Response rates were high for both groups at D1 and D2, and significantly higher in the ayahuasca group at D7 (64% v. 27%; p = 0.04). Remission rate showed a trend toward significance at D7 (36% v. 7%, p = 0.054). Conclusions To our knowledge, this is the first controlled trial to test a psychedelic substance in treatment-resistant depression. Overall, this study brings new evidence supporting the safety and therapeutic value of ayahuasca, dosed within an appropriate setting, to help treat depression. This study is registered at http://clinicaltrials.gov (NCT02914769)

COLAB:módulo LTE de sensoriamento colaborativo e radio cognitivo para o simulador de redes ns-3

Resumo O crescimento exponencial de dispositivos sem fio conectados à internet e a limitação do espectro electromagnético disponível requer a otimização do escalonamento de recursos e reuso de frequências para prover uma melhor qualidade de serviço. As novas aplicações oriundas da evolução das redes sem fio, principalmente a rede 5G, consideram o uso de rádios cognitivos e o sensoreamento do espectro como elementos fundamentais no seu desenvolvimento. O avanço e desenvolvimento de novas tecnologias depende de ambientes de simulação que facilitem e integrem ferramentas para avaliar as diversas aplicações das redes 5G. Este artigo apresenta um módulo de sensoriamento colaborativo e um escalonador de recursos cognitivo para o módulo LTE do simulador de rede ns-3.Abstract The exponential growth of wireless devices connected to the Internet and the limitation of the available electromagnetic spectrum requires the optimization of resource scheduling and frequency reuse to provide a better quality of service. New applications from the evolution of wireless networks, especially the 5G network, consider the use of cognitive radios and the sensing of the spectrum as fundamental elements in its development. The advance and development of new technologies depends on simulation environments that facilitate and integrate tools to evaluate the various applications and scenarios of 5G networks. This article presents a collaborative sensing module and a cognitive resource scheduler for the LS module of the ns-3 network simulator