Rapid and simultaneous quality analysis of the three active components in Lonicerae Japonicae Flos by near-infrared spectroscopy.

Lonicerae Japonicae Flos (LJF) has historically been widely utilized as a tea and health food. To better understand and evaluate its quality evaluate its quality, a near-infrared spectroscopy (NIRS) method was developed for the rapid and simultaneous analysis of the 3 main active components (chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C). The NIRS model was built using 2 different strategies: partial least squares (PLS) as a linear regression method and artificial neural networks (ANN) as a nonlinear regression method. Furthermore, the NIRS method was applied to analyze the 4 main quality factors, which included 5 processing methods (shade drying, sun drying, vacuum drying, freeze drying and hot-air drying), 2 kinds of harvest time (flower bud stage and florescence stage), 2 species and 8 geographical origins. Collectively, NIRS is a promising method for the quality analysis of LJF.

Network Pharmacological Screening of the Active Ingredients and Hypoglycemic Effect of Isodon rubescens in the Treatment of Diabetes.

This study was firstly to study the relationship of "ingredient-target-pathway" and the pharmacological effects of Isodon rubescens for the treatment of diabetes. Based on a network pharmacology method, 138 active ingredients of Isodon rubescens were screened from the relative literatures, and their targets were confirmed by comparing these with the hypoglycemic targets in the DrugBank database. Results showed that Isodon rubescens contained 25 hypoglycemic ingredients, such as rabdoternin A, rabdoternin B, and epinodosinol. These ingredients could activate 6 hypoglycemic targets, including 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), integrin α-L (ITGAL), integrin ß-2 (ITGB2), progesterone receptor (PGR), glucocorticoid receptor (NR3C1), and nuclear receptor subfamily 1 group I member 2 (NR1I2). These targets were involved in 94 signaling pathways, such as the Rap1, PI3K-Akt, and HIF-1 signaling pathways. The cell viability showed that the human umbilical vein endothelial cells (HUVECs) treated with alcohol extract (1.00 g/L) and the water extract (0.13 - 0.50 g/L) exhibited high viability compared to the model group (p < 0.05), respectively. 0In animal experiments, the rats treated with water extract of Isodon rubescens showed significant hypoglycemic effects compared to rats in the model group (p < 0.05). Overall, this approach provides an efficient strategy to explore hypoglycemic ingredients of Isodon rubescens and other traditional Chinese medicine.

Puerarin-loaded ultrasound microbubble contrast agent used as sonodynamic therapy for diabetic cardiomyopathy rats.

In this study, a puerarin-loaded ultrasound sulfur hexafluoride microbubble contrast agent as a sonodynamic therapy (SDT) was developed to improve targeted drug delivery and pharmacodynamic effects in diabetic cardiomyopathy (DCM) treatment. Fluorescence microscope morphology was applied to confirm the fabrication of the puerarin - microbubbles (PMBs). The average size distribution and zeta potential of PMBs were 760.0 ± 101.2 nm and -20.4 ± 6.59 mV, respectively. In vitro and in vivo experiments were carried out to study the pharmacodynamic effects and targeted drug delivery of PMBs. The cytotoxicity, assessed by the cell viability of human umbilical vein endothelial cells (HUVECs), showed that the microbubbles were nontoxic even in high concentration of 2.500 mg/mL, and the wound healing scratch assay proved that PMBs cloud obviously improve the migration ability of HUVECs. Furthermore, streptozotocin (STZ) accompanied with high-energy diets was employed to build the DCM rat model. The blood glucose, histological changes of the pancreas and heart, and cardiac function were used to confirm the obtainment of the DCM rat model. Histological and physiological changes of the PMBs treatment group indicated that PMBs had a significant therapeutic efficacy when compared to the DCM model group. Therefore, PMBs are a promising strategy for a targeted drug delivery system and a novel noninvasive treatment for DCM.

Rapid and Simultaneous Determination of Three Active Components in Raw and Processed Root Samples of Scutellaria baicalensis by Near-infrared Spectroscopy.

Motivated by the wide use of Scutellariae Radix (SR) in the food and pharmaceutical industries, a rapid and non-destructive near-infrared spectroscopy (NIRS) method was developed for the simultaneous analysis of three main active components in raw SR and SR processed by stir-frying with wine. From seven geographical areas, 58 samples were collected. The reference contents for the SR components baicalin, baicalein, and wogonin were determined by high-performance liquid chromatography. Two multivariate analysis methods, partial least-squares (PLS) regression as a linear regression method and artificial neural networks (ANN) as a nonlinear regression method, were applied to the NIR data, and their results were compared. In the PLS model, different model parameters (i.e., 11 spectral pre-treatment methods), spectral region, and latent variables were investigated to optimize the calibration model; additionally, the ANN model was applied with five different spectral pre-treatment methods and six algorithms. For the optimal model parameters, the correlation coefficients of the calibration set for baicalin, baicalein, and wogonin were 0.9979, 0.9786, and 0.9773, respectively; the correlation coefficients of the prediction set were 0.9756, 0.9843, and 0.9592, respectively; the root mean square error of validation values were 0.215, 0.321, and 0.174, respectively. The optimal NIR models were then employed to analyze the effects of processing and geographical regions on analyte contents. The established NIR methods were robust, accurate, and reproducible. NIRS may be a promising approach for the routine screening and quality control of traditional Chinese medicines.

Near-infrared spectroscopy for rapid and simultaneous determination of five main active components in rhubarb of different geographical origins and processing.

Rhubarb (Rhei Radix et Rhizoma) is a classic herbal laxative medicine in Europe and a very famous natural medicine in Asia, especially in China. In this study, near-infrared spectroscopy (NIRS) was first used for rapid and simultaneous analysis of five main active components (chrysophanol, aloe-emodin, rhein, emodin and physcion) in rhubarb of 6 geographical origins, processing and spurious samples. A total of 124 samples (73 raw, 40 processed and 11 spurious samples) were collected. With the reference values determined by HPLC, two calibration strategies, partial least squares (PLS) as a linear regression method and artificial neural networks (ANN) as a non-linear regression method, were studied. For the PLS strategy, 11 spectral pre-processing methods, 5 spectral regions and different latent variables (LVs) were systematically compared, while 3 spectral pre-processing methods and 5 ANN algorithms were studied for the ANN strategy. The results indicated that PLS was more suitable for the analysis of chrysophanol, aloe-emodin, emodin and physcion, whereas ANN was better for rhein. For the optimal NIR models of chrysophanol, aloe-emodin, rhein, emodin and physcion, the correlation coefficients of the calibration set (Rcal) were 0.9916, 0.9762, 0.9839, 0.9794 and 0.9800, respectively; the correlation coefficients of the prediction set (Rpre) were 0.9888, 0.9359, 0.9410, 0.9805 and 0.9785, respectively; the root mean square error of validation (RMSEP) were 0.0402, 0.0197, 0.0593, 0.0133 and 0.0192, respectively. Subsequently, the optimal NIR models were used to study the effects of geographical regions and processing, and identify the spurious rhubarb. Collectively, NIRS may be a well-acceptable method for quality evaluation of rhubarb and other traditional Chinese medicine (TCM).

Rapid and simultaneous analysis of five alkaloids in four parts of Coptidis Rhizoma by near-infrared spectroscopy.

Near-Infrared Spectroscopy (NIRS) was first used to develop a method for rapid and simultaneous determination of 5 active alkaloids (berberine, coptisine, palmatine, epiberberine and jatrorrhizine) in 4 parts (rhizome, fibrous root, stem and leaf) of Coptidis Rhizoma. A total of 100 samples from 4 main places of origin were collected and studied. With HPLC analysis values as calibration reference, the quantitative analysis of 5 marker components was performed by two different modeling methods, partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regression. The results indicated that the 2 types of models established were robust, accurate and repeatable for five active alkaloids, and the ANN models was more suitable for the determination of berberine, coptisine and palmatine while the PLS model was more suitable for the analysis of epiberberine and jatrorrhizine. The performance of the optimal models was achieved as follows: the correlation coefficient (R) for berberine, coptisine, palmatine, epiberberine and jatrorrhizine was 0.9958, 0.9956, 0.9959, 0.9963 and 0.9923, respectively; the root mean square error of validation (RMSEP) was 0.5093, 0.0578, 0.0443, 0.0563 and 0.0090, respectively. Furthermore, for the comprehensive exploitation and utilization of plant resource of Coptidis Rhizoma, the established NIR models were used to analysis the content of 5 active alkaloids in 4 parts of Coptidis Rhizoma and 4 main origin of places. This work demonstrated that NIRS may be a promising method as routine screening for off-line fast analysis or on-line quality assessment of traditional Chinese medicine (TCM).

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy.

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

A Dual-signal Amplification Method for DNA Detection Based on Exonuclease Ⅲ and Fluorescence Quenching Ability of MoS2 Nanosheet / 分析化学

A highly sensitive and selective DNA biosensor is described based on the fluorescence quenching ability of MoS2 nanosheet and exonucleaseⅢ( ExoⅢ) assisted dual-signal amplification. In this sensor, the fluorescence probes ( HP1 and HP2 ) cannot be degraded by Exo Ⅲdue to the 3 '-termini protrusion and thus are adsorbed on the surface of MoS2 nanosheets, which will result in the quenching of MoS2 nanosheets toward the probes and induce a low fluorescent signal. The presence of the target DNA leads to the desorption of probes on the surface of MoS2 nanosheets due to the hybridization toward probes, generating many fluorescent fragments by Exo Ⅲdigestion and inducing dual-signal amplification. This method can improve the sensitivity and detection limit compared with single amplification method, and shows excellent selectivity in the discrimination of single base mismatched targets. On the basis of the significantly high sensitivity, the developed biosensor can be potentially extended to detect various DNA targets with excellent sequence selectivity.

The practice and discussion of innovative teaching in the field practice of pharmaceutical botany / 中华医学教育探索杂志

Field practice teaching is an important part in pharmaceutical botany. According to the problems in the traditional field practice, an innovative system of field practice teaching was built. A series of reform and innovation was integrating and rationally allocating the existing resources. Combining the tra-ditional cognitive practice teaching and self-study, image-text card of medicinal plant was edited to enrich the teaching content, and the diversification of evaluation methods was proposed. This method could mobi-lize the enthusiasm of the students, improve the comprehensive quality of students and obtain good teaching effect.

Rapid Determination of Puerarin by Near-infrared Spectroscopy During Percolation and Concentration Process of Puerariae Lobatae Radix.

BACKGROUND: Gegen (Puerariae Labatae Radix) is one of the important medicines in Traditional Chinese Medicine. The studies showed that Gegen and its preparation had effective actions for atherosclerosis. OBJECTIVE: Near-infrared (NIR) was used to develop a method for rapid determination of puerarin during percolation and concentration process of Gegen. MATERIALS AND METHODS: About ten batches of samples were collected with high-performance liquid chromatography analysis values as reference, calibration models are generated by partial least-squares (PLS) regression as linear regression, and artificial neural networks (ANN) as nonlinear regression. RESULTS: The root mean square error of prediction for the PLS and ANN model was 0.0396 and 0.0365 and correlation coefficients (r (2)) was 97.79% and 98.47%, respectively. CONCLUSIONS: The NIR model for the rapid analysis of puerarin can be used for on-line quality control in the percolation and concentration process. SUMMARY: Near-infrared was used to develop a method for on-line quality control in the percolation and concentration process of GegenCalibration models are generated by partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regressionThe root mean square error of prediction for the PLS and ANN model was 0.0396 and 0.0365 and correlation coefficients (r (2)) was 97.79% and 98.47%, respectively. Abbreviations used: NIR: Near-Infrared Spectroscopy; Gegen: Puerariae Loabatae Radix; TCM: Traditional Chinese Medicine; PLS: Partial least-squares; ANN: Artificial neural networks; RMSEP: Root mean square error of validation; R2: Correlation coefficients; PAT: Process analytical technology; FDA: The Food and Drug Administration; Rcal: Calibration set; RMSECV: Root mean square errors of cross-validation; RPD: Residual predictive deviation; SLS: Straight Line Subtraction; MLP: Multi-Layer Perceptron; MSE: Mean square error.

Profiling the dynamics of abscisic acid and ABA-glucose ester after using the glucosyltransferase UGT71C5 to mediate abscisic acid homeostasis in Arabidopsis thaliana by HPLC-ESI-MS/MS / 药物分析学报

The HPLC-MS/MS method was developed to profile the dynamics of abscisic acid (ABA) and ABA-glucose ester (ABA-GE) after cloning glycosyltransferase enzyme family gene AtUGT71C5 into Arabidopsis thaliana. By constructing over-expression lines (OE) and down-expression lines (DN), we acquired mutant strains to analyze the function of AtUGT71C5. The multiple-reaction monitoring (MRM) was used for quantitative determination in negative mode. The transition was m/z 263.1-153.0 for ABA ([M-H]t), m/z 425.1-263.0 for ABA-GE ([M-H]t), and m/z 321.0-152.0 for chloramphe-nicol. The linear range was 0.8684-217.1 ng/mL for ABA and 0.3920-196.0 ng/mL for ABA-GE. The accuracy was 88.0-109.0% for ABA and 86.6-113.0% for ABA-GE; the inter-day and intra-day precisions were less than 5.4%for ABA and 8.9%for ABA-GE, respectively. This method is simple and sensitive enough for determination of ABA and ABA-GE in A. thaliana leaves. All the evidence confirmed the speculation that AtUGT71C5 can mediate abscisic acid homeostasis.