Characterization of the chemical constituents in Hongjingtian injection by liquid chromatography quadrupole time‐of‐flight mass spectrometry

Hongjingtian injection is made from Rhodiola wallichiana and used in the treatment of stable angina pectoris associated with coronary heart disease. In this study, the chemical constituents in Hongjingtian injection were comprehensively studied using liquid chromatography quadrupole time‐of‐flight mass spectrometry. A total of 49 compounds were identified or assumed, including 10 organic acids, nine phenylethanoids, 10 phenylpropanoids, two flavonoid glycosides, seven monoterpene glycosides, seven octylglycosides and four other types of compounds. The structures of seven compounds were confirmed by comparing their retention times, MS and UV spectra with the corresponding authentic standards. Amongst the 49 compounds, 35 were firstly found in R. wallichiana, while they have been reported in other species of the genus Rhodiola, including Rhodiola crenulata, Rhodiola sacra, Rhodiola rosea and Rhodiola kirilowii. The possible fragmentation pathways in the mass spectrometry of the major types of compounds are proposed and summarized. Our study demonstrates a rapid method for characterizing the chemical constituents present in the Hongjingtian injection, which could also be applied to the identification of chemical constituents in other TCM formulae containing R. wallichiana.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Modeling the Effect of Injection Molding Process Parameters on Warpage Using Neural Network Theory

A back propagation artificial neural network (BPANN) prediction model for warpage of injection-molded polypropylene was developed based on an orthogonal design method. The BPANN model was trained by the input and output data obtained from the moldflow software platform simulations. It is proved that the BPANN model can predict the warpage with reasonable accuracy. Utilizing the BPANN model, the effects of the process parameters, packing pressure (Pp), melt temperature (T_me), mold temperature (T_mo), packing time (t_p), cooling time (t_c), and fill pressure (p_f), on the warpage were investigated. The most important process parameter affecting the warpage was Pp, and the second most important was T_me. The rest of the process parameters, T_mo, t_p, t_c, and p_f, were found to be relatively less influential. Warpage increased with elevating T_mo. In contrast, an increase in Pp and T_me caused the warpage to decrease.     

Prediction of allergic reaction risk of Shenmai injection based on real-world evidence coupled with UPLC–Q-TOF-MS

The allergic reaction (AR) of Chinese herbal injection (CHI) has become one of the most noticeable focuses of public health in China. However, it still remains a considerable controversy as to whether low-molecular-weight components in CHI have potential sensitization. In this study, the relationship between AR and low-molecular-weight component profile of Shenmai injection was explored by an interdisciplinary technology integrating real-world evidence and ultra-performance liquid chromatography–quadrupole time-of-flight mass spectroscopy (UPLC–Q-TOF-MS). The AR information of hospitalized patients was obtained by comprehensively analyzing real-world evidence from January 2015 to June 2019 at two Chinese hospitals. The UPLC–Q-TOF-MS was exploited to systematically investigate the low-molecular-weight component profile with 50–1500 m/z mass range, and 3725 MS1 peaks were detected. The optimized partial least squares discriminant analysis model was established to map the influence of low-molecular-weight components on AR. The results of this study showed that high levels of organic acids administered intravenously might be a potential risk factor for inducing AR. By using this method, Shenmai injection with high AR risk could be recognized precisely with 100% accuracy before clinical use.     

基于B3PyMPM∶Cs高效叠层OLED器件的制备

以B 3 PyMPM∶Cs/Al/HAT-CN作为电荷生成单元制备高效叠层绿色磷光有机电致发光器件,叠层器件的最大电流效率和最大流明效率分别为172.2 cd/A和111.0 lm/W,在5 mA/cm^2电流密度下,叠层器件的电压和亮度分别为传统器件的2.04倍和2.84倍.为了探究叠层器件性能优于传统器件的原因,研究了电荷生成单元内的电荷产生和注入过程,以及薄层铝对电子注入特性和电荷生成单元稳定性的影响.实验结果表明,电荷能够有效地在电荷生成单元内产生并顺利注入电子传输层中,B3PyMPM∶Cs和HAT-CN间Al薄层的插入能够进一步提高电子注入效率及器件结构的稳定性.     

Determination of sulfa antibiotic residues in river and particulate matter by field-amplified sample injection-capillary zone electrophoresis

In the present research, field-amplified sample injection–CZE (FASI–CZE) coupled with a diode array detector was established to determine trace level sulfa antibiotic. Sulfathiazole, sulfadiazine, sulfamethazine, sulfadimethoxine, sulfamethoxazole, and sulfisoxazole were selected as analytes for the experiments. The background electrolyte solution consisted of 70.0 mmol/L borax and 60.0 mmol/L boric acid (including 10% methanol, pH 9.1). The plug was 2.5 mmol/L borax, which was injected into the capillary at a pressure of 0.5 psi for 5 s. Then the sample was injected into the capillary at an injection voltage of –10 kV for 20 s. The electrophoretic separation was carried out under a voltage of +19 kV. The capillary temperature was maintained at 20˚C throughout the analysis, and six sulfonamides were completely separated within 35 min. Compared with pressure injection-CZE, the sensitivity of FASI-CZE was increased by 6.25–10.0 times, and the LODs were reduced from 0.2–0.5 to 0.02–0.05 μg/mL. The method was applied to the determination of sulfonamides in river water and particulate matter samples. The recoveries were 78.59–106.59%. The intraday and interday precisions were 2.89–7.35% and 2.77–7.09%, respectively. This provides a simpler and faster method for the analysis of sulfa antibiotic residues in environmental samples.     

Amperometric detection of indapamide on glassy carbon electrode

This work describes the development of a fast, precise and reliable voltammetric method for the quantification of indapamide, an orally active diuretic sulfonamide used for hypertensive treatment. This compound acts inhibiting sodium reabsorption and increasing the elimination of water. This characteristic was responsible for its banishment by the International Olympic Committee since 1999. The study begins by finding an adequate potential range (−0.20 to 0.30 V) to avoid poisoning the working glassy carbon electrode (GCE) in phosphate buffer 0.10 mol L⁻¹ (pH=12.0). Utilizing flow injection analysis, linear responses between 2.0 × 10⁻⁶ mol L⁻¹ to 2.5 × 10⁻⁵ mol L⁻¹ of indapamide (R²=0.995), and detection limit (LOD) 3.0 × 10⁻⁷ mol L⁻¹ were obtained. This method was applied for the quantification of indapamide in tablets and in synthetic urine. The same flow system was used for the analysis of commercial drugs and the response obtained corresponded to 98 % of the concentration indicated on the drug label. These tablets were also analyzed by high performance liquid chromatography (HPLC), obtaining a recovery of 103 % and LOD 4.0 × 10⁻⁷ mol L⁻¹. The velocity of analysis using flow methods compares advantageously to the classical chromatographic methods. For synthetic urine, linear responses were obtained in samples spiked in the region from 5.0 × 10⁻⁶ mol L⁻¹ to 30 × 10⁻⁶ mol L⁻¹ (R²=0.991) and LOD 3.0 × 10⁻⁷ mol L⁻¹.     

流动注射法同时测定海水中氨氮和磷酸盐

采用流动注射法同时测定海水中氨氮和磷酸盐的含量。在优化的试验条件下,氨氮和磷酸盐的线性范围分别为0.25 mg·L-1和0.30 mg·L-1以内,检出限(3S/N)分别为0.42μg·L-1和0.56μg·L-1。氨氮和磷酸盐加标回收率分别在85.0%~103%和86.7%~103%之间,测定值的相对标准偏差(n=6)分别在0.43%~5.3%和0~4.1%之间。方法用于分析标准物质,测定结果与分光光度法的结果一致。     

流动注射在线分离富集-火焰原子吸收光谱法测定水中镍(Ⅱ)

应用D412螯合树脂作为富集柱填充物,将在线分离富集装置与火焰原子吸收光谱法联用测定水中镍(Ⅱ)的含量。优化的试验条件如下:1富集柱采用干法填充;2吸附介质的p H为6;3进样速率为5 m L·min-1;4 3 mol·L-1硝酸溶液(洗脱剂)用量为2.5 m L;5洗脱速率为7.5 m L·min-1。镍的质量浓度在50μg·L-1以内与其吸光度呈线性关系,检出限(3s)为0.35μg·L-1。方法用于自来水和河水样品的分析,加标回收率在96.0%~101%之间,测定值的相对标准偏差(n=7)在2.5%~3.1%之间。