OBJECTIVE:To prepare borneol-puerarin liposomes,and to investigate its brain-targeting. METHODS:Film dis-persion ultrasonic method was used to prepare borneol-puerarin liposomes. The morphology of liposomes was observed by TEM;the particle size and Zeta potential were measured by laser particle size analyzer;the entrapment efficiency were measured by sepha-dex gel filtration method. Compared with Puerarin injection,brain-targeting of borneol-puerarin liposomes and puerarin liposomes via intravenous injection of mice tail was studied with relative intake rate and peak concentration ratio. RESULTS:Borneol-puerarin liposomes were spherical or quasi-circular;its mean particle size,polydispersity index and Zeta potential were 226 nm,0.263 and-21.3 mV respectively. The entrapment efficiency were(65.32±2.13)%. Compared with Puerarin injection,relative intake rate of puerarin liposome and borneol-puerarin liposome were 1.68 and 2.58,and peak concentration ratio were 1.15 and 1.42. CONCLU-SIONS:Brain-targeted borneol-puerarin liposomes are prepared successfully.

OBJECTIVE:To optimize the formulation of Dimemorfan phosphate tablets. METHODS:Using 60 min dissolution rate of dimemorfan phosphate as index,L9(34) orthogonal test was used to optimize the amount of starch,microcrystalline cellu-lose,croscarmellose sodium and concentration of HPMC E5 solution. The friability,hardness,60 min dissolution rate and main component were detected. The similarity of dissolution curves of Dimemorfan phosphate tablets was compared with that of imported tablets in 0.1 mol/L hydrochloric acid,pH 6.8 phosphate buffer,water and pH 4.0 acetate buffer. RESULTS:The optimized formu-lation of Dimemorfan phosphate tablet(1 000 tablets)was composed of dimemorfan phosphate 10 g,starch 60 g,microcrystalline cellulose 40 g,10% HPMC E5 solution and croscarmellose sodium 25 g. The friability,hardness,60 min dissolution rate and main component of 3 batches of Dimemorfan phosphate tablets prepared by optimized prescription were 0.42%-0.58%,9.8-10.5 kg,94.89%-96.21% and 99.21%-99.52%,respectively. In 4 dissolution mediums,similar factors f2 of dissolution curves between prepared tablets and imported tablets were above 50. CONCLUSIONS:Dimemorfan phosphate tablets were prepared successfully. The optimized formulation is rational. The dissolution behavior of prepared tablets is similar to that of imported tablets in vitro.

Objective:To determine the content of chloroform, ethyl acetate and DMF in dimemorfan phosphate by gas chromatog-raphy (GC). Methods:The capillary gas chromatography was used with a PEG-20M column, programmed temperature, water as the solvent and FID as the detector. Results:The three organic solvents were separated and showed good linear relationship (r>0. 999 0). The detection limit of chloroform, ethyl acetate and DMF was 0. 63,0. 60 and 8. 92μg·ml-1 , respectively. The residues of the organ-ic solvents in three batches of the samples all met with the requirements of ICH. Conclusion: The method is sensitive, accurate and reliable, and can be used in the quality control of dimemorfan phosphate.

Objective To establish a gas chromatograph method for determing Chloroform, ethyl acetate and N, N-dimethyl formamide in butoconazole nitrate. Methods The samples was detected by Headspace Gas Chromatography. Temperature programming method was adpoted and FID was used as detector. The injector temperature was 200 ℃, and the detector temperature was reach 250 ℃. Nitrogen was used as carrier gas in the experiment. Results In the mentioned chromatographic conditions, Chloroform, ethyl acetate and N, N-dimethyl formamide had good linear relationships in the ranges of 0. 066-0. 588,0. 062-0. 556 and 0. 896-8. 061 μg·mL-1 respectively. The average recoveries were 99. 18%,102. 84% and 98. 71%. RSD were 3. 87%,4. 33% and 3. 71%. Conclusion The detection method is sensitive, accurate, reliable, and can be used as a quality control for butoconazole nitrate.

Objective:To establish a method for the determination of dichloromethane, methanol and ethanol in fenticonazole ni-trate. Methods:The samples were detected by headspace GC. The column was OV-1301(30 m × 0. 53 mm,3. 0 μm), the detector was FID with nitrogen as the carrier gas, the detector temperature was 250 ℃ and the injector temperature was 200 ℃. Results:The linear range of dichloromethane, methanol and ethanol was 2. 436-21. 924(r=0. 998 8), 12. 268-110. 412(r=0. 999 5) and 20. 052-180. 468 μg·ml-1(r=0. 996 9) with the average recovery of 99. 30% (RSD=2. 36%), 100. 21%(RSD=1. 07%) and 100. 15%(RSD=1. 21%)(n=9), respectively. Conclusion:The detection method is sensitive, accurate and reliable, and can be used in the quality control of fenticonazole nitrate.

Objective:To investigate the impact on image quality of a new deep learning image reconstruction (DLIR) algorithm in dynamic CT myocardial perfusion imaging (CTP) and to explore whether the algorithm affects the quantification of myocardial blood flow (MBF) in swine.Methods:Dynamic CTP imaging was performed in five anesthetized domestic swine [body weight (58.6±1.9) kg], at both rest and stress state. The tube voltages were fixed at 100 kV, and the low-dose and high-dose scanning tube currents were set as 150 mA and 300 mA, respectively. The low-dose (LD) scan data were reconstructed with filtered back projection (FBP) and three different DLIR strengths (low, medium, and high). High-dose (HD) scan data were reconstructed with filtered back projection (FBP) only. Subjective (5-point scale) image quality was evaluated, and objective evaluations included image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) was performed. Linear regression was used to test the linear trend between DLIR algorithm strength and image quality. Data sets normality was determined by the Shapiro-Wilk test. Comparisons between groups were performed using Student′s t test for normally distributed data or the Wilcoxon rank-sum test for non-normally distributed data. Results:The mean effective radiation dose was 7.2 and 3.8 mSv for the HD protocol and the LD protocol, respectively, with statistically significant difference found between two protocols ( t=282.50, P<0.001). The image noise of the images obtained at LD protocol gradually decreased and the image SNR and CNR gradually increased with DLIR algorithm strength increased ( F=60.10,35.87,41.41; P for trend were all<0.001). As for DLIR-high strength (LD) and FBP (HD) images, the image noise values were (31.7±3.1) and (38.2±1.2) HU; SNR were 16.6±2.0 and 13.8±0.8; CNR were 14.5±1.7, 11.6±0.9, respectively, with significant differences found between two groups ( t=5.70, 4.15, 5.68; all P<0.05). The subjective scores of DLIR-high strength (LD) and FBP (HD) images were significantly different (4.8±0.4 and 4.2±0.6, Z=2.12, P<0.05). No significant differences were found between the MBF calculated from FBP (LD) and from DLIR-high strength (LD), with the values as (81.3±17.3) ml·100 ml -1·min -1 vs. (79.9±18.3)ml·100 ml -1·min -1 at rest state; and (99.4±24.9)ml·100 ml -1·min -1 vs. (100.7±27.3) ml·100 ml -1·min -1 at stress state ( t=1.10, 0.89; P>0.05). Conclusion:DLIR-high strength can improve image quality of myocardial CTP in swine, and can reduce radiation dose without influencing the MBF calculation.