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Based on near infrared spectroscopy and high performance liquid chromatography, this paper established the regression relationship between near infrared spectroscopy and index component content of Huoxiang Zhengqi oral liquid, so as to realize the rapid detection of index component content based on near infrared spectroscopy. Magnolol, honokiol and hesperidin were used as the quality indexes of Huoxiang Zhengqi oral liquid. After using the first derivative and normalization pretreatment method, characteristic variables were screened by CARS, and the correction model was finally established by partial least-squares regression (PLSR) method. The method accuracy was evaluated with the external validation, and the prediction results were tested for significance. The results indicated that when the near infrared spectrum was scanned through the bottle, the model's correlation coefficients of prediction (Rp) were higher than 0.99, the root mean square errors of the prediction models (RMSEP) were all less than 0.008 4, and the relative standard errors of prediction set (RSEP) were all less than 2.83%. There was no significant difference in the predicted results between these two kinds of model. The models established in the non-destructive way have good performance and high prediction accuracy. The rapid and nondestructive way has application value in the quality control of Huoxiang Zhengqi oral liquid.
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To provide the ancient literary evidence support for the clinical application and development of classical prescription based on systematical collection and analysis of the ancient Chinese medical literature containing Jinshui Liujun Jian, including its origin and development. Bibliometric analysis was used and information of Jinshui Liujun Jian in ancient Chinese medical literature was then collected for statistical analysis of formula compositions, main indications, dosage, preparation methods, etc. A total of 151 valid items of data were obtained from 48 ancient Chinese medicine books. Jinshui Liujun Jian was first recorded in Jingyue Quanshu written by ZHANG Jiebin. This prescription consisted of Rehmanniae Radix Praeparata, Angelicae Sinensis Radix, Pinelliae Rhizome, Citri Reticulatae Pericarpium, Poria and Glycyrrhizae Radix et Rhizome Praeparata cum Melle, and it was mainly used to treat the deficiency of lung and kidney, edema and excess production of phlegm, or Yin deficiency in the old, insufficient blood-qi, wind-cold evil, cough and disgusting, asthma and excessive phlegm. Doctors in later dynasties mostly followed the prescription compositions, dosages and indications in Jingyue Quanshu, and extended the clinical application of this prescription.
Assuntos
Medicamentos de Ervas Chinesas , Medicina Tradicional Chinesa , Prescrições , RizomaRESUMO
Objective: To establish HPLC fingerprints of Huagai San and identificate the characteristic peaks ion and preparations- medicinal materials peak pattern matching. Methods: Similarity on 12 batches of Huagai San was estimated, and peak pattern matching of the original medicine was conducted. Sample extraction with methanol in ultrasonic condition was carried out. HPLC- DAD methods were developed, detection wave length was set at 280 nm, HPLC mobile phase consisted of acetonitrile-0.2% phosphate acid aqueous solution, volume flow-rate was delivered at 0.6 mL/min, and column temperature was kept at 30℃. Cluster analysis of 12 batches of Huagai San was analyzed by SPSS 19.0. Results: The results showed that 26 common peaks were defined, the peaks No. 4, 5, 10, 17, 18, 20, and 21 were ephedrine hydrochloride, pseudoephedrine hydrochloride, chlorogenic acid, liquiritin, glycyrrhizic acid, narirutin, and hesperidin, respectively, and peak pattern matching showed that Huagai San had 6, 3, 6, 1, 4, and 1 matching peaks with Ephedrae Herba, Mori Cortex, Citri Reticulatae Pericarpium, Armeniacae Semen Amarum, Glycyrrhizae Radix et Rhizoma, and Perillae Fructus, respectively. The fingerprint similarity among the samples was all over 0.960. All the samples were classified into three categories. Conclusion: Similarity evaluation combined with the peak matching of fingerprint for Huagai San could provide the scientific methods for its identification and quality control.
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Objective: To optimize the preparation technology of paeoniflorin microcapsule (PM), and to study its behavior of in vitro release. Methods: Using encapsulation efficiency and drug loading as indicators, the PM were prepared by complex agglutination method, the preparation technology of PM was optimized by Doehlert design. The dissolution volume of PM within 20 h and the release curve were measured by HPLC, afterwards its morphology and particle size were studied by electron microscopy. Results: The encapsulation efficiency and drug loading were significantly related to the ratio of coating material, stirring speed, and pH value. The optimal conditions were as follows: the ratio of coating material to paeoniflorin was 4.3:1, the stirring speed was 305 r/min, and the pH value was 4.0. The obtained microcapsules were smooth round capsule-shaped, with non-adhesions and uniform particle size, the encapsulation efficiency was up to 83.81%, the drug loading was 24.24%, and the microcapsule diameter was below 200 μm, with sustained-release effect. Conclusion: The complex agglutination method is simple and reliable to prepare PM, and the product is stable. As a new formulation, microcapsule has a broad prospect for development.