ABSTRACT
ObjectiveTo explore the pretreatment methods to promote the enzymatic digestion and extraction of active ingredients from Magnoliae Officinalis Cortex dregs（MOCD）， and to provide a reference basis for the utilization of resource components in MOCD. MethodLiquid chromatography-mass spectrometry（LC-MS） was used for qualitative analysis of resource components in MOCD with an Agilent C18 reversed-phase column（3.0 mm×100 mm， 2.7 µm） at the flow rate of 0.4 mL·min-1， the mobile phase was water（A）-acetonitrile（B） for gradient elution（0-3 min， 25%-48%B； 3-6 min， 48%-59%B； 6-10 min， 59%-80%B； 10-20 min， 80%-90%B； 20-25 min， 90%B）， electrospray ionization（ESI） was employed with negative ion mode scanning and scanning range of m/z 50-1 200. A high performance liquid chromatography（HPLC）， which refered to the determination in the 2020 edition of Chinese Pharmacopoeia， was used for quantitative analysis of resource components in MOCD. Four kinds of pretreatment agents were used to separate the resource components from MOCD， and the mechanism of different pretreatment agents was investigated by field emission scanning electron microscopy（FESEM）， X-ray powder diffraction（XRD） and Fourier transform infrared spectroscopy（FT-IR）. ResultMagnolol， honokiol and lignocellulose were identified as the main resource components of MOCD by qualitative and quantitative analysis. Under the conditions of 1% NaOH， reaction temperature at 80 ℃ and reaction time of 60 min， the concentration of reducing sugar produced by the enzymatic hydrolysis was 32.18 g·L-1， which was 79.8% higher than that of the untreated MOCD. After adding tween-80， the enzymatic hydrolysis time was reduced to 1/3 of the original time， the concentration of reducing sugar was increased by 102.0%. And the total recovery of magnolol and honokiol in the pretreatment solution was 69.23%. ConclusionMagnolol， honokiol and lignocellulosic components in MOCD are valuable for development and utilization， the combination of alkaline pretreatment and tween-80 can realize the recovery and utilization of these three resource components， which can provide a new idea for comprehensive utilization of resource components in MOCD.
ABSTRACT
Jianwei Xiaoshi tablets， as a common variety of Chinese patent medicine with "one product with many manufacturers"， have many manufacturers and huge market sales. However， the phenomenon about uneven quality and discrepant price is prominent. Based on this， this study was carried out for the quality evaluation of Jianwei Xiaoshi tablets by applying the high-quality evaluation criteria with the quality as core for Chinese patent medicine， which was based on the full production cycle， from the multi-dimension including raw material selection， production process， quality control， post-marketing research and so on. The evaluation results showed that the quality evaluation scores of Jianwei Xiaoshi tablets from different manufacturers varied greatly （ranging from 35 to 66）， indicating that the quality was significantly different. In the actual production， generally inadequate attention was paid to the quality of raw materials， and the quality of raw materials was insufficient with the score ratio of 43%， especially the poor consistency control of them. The role of good manufacturing practice was obvious， and the scores of production process were generally high with the average score ratio of 62%， and the maximum up to 80%. The technological advancement of the manufacturer was outstanding. The score ratio of quality control was only 31% that the internal quality standard of each manufacture almost stayed at the qualified line， which was equal to the national standard， and the consistency of products was insufficient. The post-marketing research was lacking with the score ratio of 37%. Manufacturers with high brand awareness and market share were upper scores， while the others lagged far behind. The results of this evaluation are in line with the overall prediction， which can provide a reference for the high-quality evaluation of Chinese patent medicine， and supply the scientific data for high-quality and high-price application.