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A method was developed for the preparative separation of two alkaloids from the crude extract of the radix of Rauvolfia verticillata (Lour.) Baill. in a single run. The two-phase solvent system composed of petroleum ether–ethyl acetate–methanol–water (5:5:2:8, v/v), where triethylamine (40 mmol/L) was added to the upper organic phase as the stationary phase and hydrochloric acid (10 mmol/L) was added to the lower aqueous phase as the mobile phase, was selected for this separation by pH-zone-refining counter-current chromatography (PZRCCC). For the preparative separation, the apparatus was rotated at a speed 850 rpm, while the mobile phase was pumped into the column at 2 mL/min. As a result, 112 mg of reserpine and 21 mg of yohimbine were obtained from 3 g of crude extract in a single run. The analysis of the isolated compounds was determined by high-performance liquid chromatography (HPLC) at 230 nm with purities of over 91.0%, and the chemical identification was carried out by the data of electrospray ionization–mass spectrometry (ESI–MS) and nuclear magnetic resonance (NMR) spectroscopy. The technique introduced in this paper is an efficient method for preparative separation of reserpine and yohimbine from devil pepper radix. It will be beneficial to utilize medicinal materials and also useful for the separation, purification, and pharmacological study of Chinese herbal ingredients.

Open access
Journal of Behavioral Addictions
Authors: Shan-Shan Ma, Chiang-Shan R. Li, Sheng Zhang, Patrick D. Worhunsky, Nan Zhou, Jin-Tao Zhang, Lu Liu, Yuan-Wei Yao, and Xiao-Yi Fang

Abstract

Background and aims

Deficits in cognitive control represent a core feature of addiction. Internet Gaming Disorder (IGD) offers an ideal model to study the mechanisms underlying cognitive control deficits in addiction, eliminating the confounding effects of substance use. Studies have reported behavioral and neural deficits in reactive control in IGD, but it remains unclear whether individuals with IGD are compromised in proactive control or behavioral adjustment by learning from the changing contexts.

Methods

Here, fMRI data of 21 male young adults with IGD and 21 matched healthy controls (HC) were collected during a stop-signal task. We employed group independent component analysis to investigate group differences in temporally coherent, large-scale functional network activities during post-error slowing, the typical type of behavioral adjustments. We also employed a Bayesian belief model to quantify the trial-by-trial learning of the likelihood of stop signal – P(Stop) – a broader process underlying behavioral adjustment, and identified the alterations in functional network responses to P(Stop).

Results

The results showed diminished engagement of the fronto-parietal network during post-error slowing, and weaker activity in the ventral attention and anterior default mode network in response to P(Stop) in IGD relative to HC.

Discussion and conclusions

These results add to the literatures by suggesting deficits in updating and anticipating conflicts as well as in behavioral adjustment according to contextual information in individuals with IGD.

Open access