Determination of bioactive diterpenoids from Andrographis paniculata by micellar electrokinetic chromatography

The present paper describes the development of a micellar electrokinetic chromatographic (MEKC) method for simultaneous determination of andrographolide, deoxyandrographolide and neoandrographolide in ethanol extracts of Andrographis paniculata. Separations were carried out in a fused-silica capillary tube with UV detection at 214 nm. Good separation was achieved using a 20 mM borate buffer, containing 20 mM sodium dodecyl sulphate and 10 mM sodium cholate, adjusted to pH 8.3 at an operating voltage of 25 kV, temperature of 35°C and a hydrodynamic injection of 5 s. The method was validated with good correlation coefficients obtained (0.9986–0.9989) while relative standard deviation (RSD) of migration time was between 1.14 and 2.42. It is concluded that this method could be used for speedy and accurate qualitative and quantitative analysis of bioactive diterpenoids in andrographis herb and its derived products.     

应用遗传算法和PLS的近红外光谱预测玉米中淀粉含量的研究

以普通玉米籽粒为试验材料,在应用遗传算法结合偏最小二乘回归法对近红外光谱数据进行特征波长选择的基础上,应用偏最小二乘回归法建立了特征波长测定玉米籽粒中淀粉含量的校正模型．试验结果表明,基于11个特征波长所建立的校正模型,其校正误差（RMSEC）、交叉检验误差（RMSECV）和预测误差（RMSEP）分别为0.30％、0.35％和0.27％,校正数据集和独立的检验数据集的预测值与实际测定值之间的相关系数分别达到0.9279和0.9390,与全光谱数据所建立的预测模型相比,在预测精度上均有所改善,表明应用遗传算法和PLS进行光谱特征选择,能获得更简单和更好的模型,为玉米籽粒中淀粉含量的近红外测定和红外光谱数据的处理提供了新的方法与途径．     

Rapid Determination of Diterpenoids in Andrographis paniculata by Microemulsion Electrokinetic Capillary Chromatography with Short-End Injection

A rapid, simple, and reliable method has been developed for routine capillary electrophoretic analysis of two diterpenoids, andrographolide and dehydroandrographolide, in Andrographis paniculata. For this system, using ethyl acetate oil-based microemulsion electrokinetic chromatography (MEEKC) and the short-end injection technique, analysis was complete in less than 2.5 min. In method validation the relative standard deviations of migration time and peak area of the two constituents were, respectively, 0.54% and 1.70% for andrographolide and 0.45% and 2.11% for dehydroandrographolide. Regression equations revealed linear relationships (correlation coefficients 0.9994 for andrographolide and 0.9993 for dehydroandrographolide) between peak area and concentration. The effects of buffer pH, borate concentration, SDS concentration, co-surfactant type and concentration, injection time, and running potential were systematically investigated. The method can be successfully implemented in routine quality-control testing.     

Second‐order calibration serves as a remedial measure for the simultaneous determination of andrographolide and dehydroandrographolide in Andrographis paniculata and its preparations by HPLC without complete baseline separation

In this work, high‐performance liquid chromatography with diode array detection was applied for the simultaneous determination of andrographolide and dehydroandrographolide in Andrographis paniculata and its preparations. As a result of the incomplete baseline separation caused by complex backgrounds, the classical univariate calibration method failed to determine accurate contents of the analytes. On this occasion, chemometric second‐order calibration based on the well‐known alternating trilinear decomposition algorithm was then explored to serve as a post‐experimental remedial tool to solve this problem. By using the intelligent “mathematical separation” of alternating trilinear decomposition, the peak areas of the analytes do not need to be directly measured and the predictive results become accurate. The contents of andrographolide and dehydroandrographolide were determined to be (7.95 ± 0.15) and (1.85 ± 0.02) μg/mL for Andrographis paniculata, (1.34 ± 0.01) and (5.53 ± 0.04) μg/mL for its preparations, which was in agreement with those obtained by a reference liquid chromatography with mass spectrometry method. This study showed the superiority of second‐order calibration method over classical univariate calibration method for simultaneous determination of multi‐analytes in complex samples. It also proved that second‐order calibration may be a good choice for remedying incomplete baseline separation problem, with the accompanied reduction of experimental burden and toxic organic solvents as well as analysis time and cost.     

近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量

应用近红外光谱(NIRS)技术定量分析连作滁菊土壤样品中阿魏酸的含量.通过标准杠杆值、学生残差和马氏距离判断异常光谱,经二阶导数和Norris平滑滤噪预处理后,在6000~4000 cm-1范围,最佳因子数为7,采用偏最小二乘法(PLS)构建数学模型.结果表明,模型校正集和验证集与高效液相色谱仪(HPLC)测定的参考值之间均呈现良好相关关系,校正相关系数Rc为0.9914,交叉验证相关系数Rcv为0.9935,校正集误差均方根(RMSEC)为0.484,预测误差均方根(RMSEP)为0.539,交叉验证误差均方根(RMSECV)为0.615.研究结果表明,NIRS分析技术能够实现连作土壤中阿魏酸的快速检测,结果准确可靠.     

Determination of polyphenols in oats by near-infrared spectroscopy (NIRS) and two-dimensional correlation spectroscopy

Two-dimensional correlation spectroscopy (2DCOS) and near-infrared spectroscopy (NIRS) were used to determine the polyphenol content in oat grain. A partial least squares (PLS) algorithm was used to perform the calibration. A total of 116 representative oat samples from four locations in China were prepared and the corresponding near-infrared spectra were measured. Two-dimensional correlation spectroscopy was employed to select wavelength bands for the PLS regression model for the polyphenol determination. The number of PLS components and intervals was optimized according to the coefficients of determination (R²) and root mean square error of cross validation (RMSECV) in the calibration set. The performance of the final model was evaluated using the correlation coefficient (R) and the root mean square error of validation (RMSEV) in the prediction set. The results showed the band corresponding to the optimal calibration model was between 1350 and 1848?nm and the optimal spectral preprocessing combination was second derivative with second smoothing. The optimal regression model was obtained with an R² of 0.8954 and an RMSECV of 0.06651 in the calibration set and R of 0.9614 and RMSEV of 0.04573 in the prediction set. These measurements reveal the calibration model had qualified predictive accuracy. The results demonstrated that the 2DCOS with PLS was a simple and rapid method for the quantitative determination of polyphenols in oats.     

偏最小二乘近红外光谱法测定瘦肉脂肪酸组成的研究

利用偏最小二乘将瘦肉的近红外光谱数据分别与其棕榈酸、棕榈油酸、硬脂酸、油酸、亚油酸含量建立校正模型,并用交互校验和外部检验来考查模型的可靠性.各脂肪酸模型的校正相关系数分别为0.9998、0.9844、0.9963、0.9754、0.9969,均方估计残差(RMSEC)分别为0.0231、0.0485、0.111、0.373、0.311,交互校验均方残差(RMSECV)分别为0.509、0.115、0.225、0.848、0.649.应用所建立的各脂肪酸近红外模型对瘦肉脂肪酸组成进行预测,并对各脂肪酸的预测值与气相色谱法测定值进行配对t-检验,结果表明两者差异均不显著(p>0.05).     

烟草灰分、总挥发酸和总挥发碱的近红外光谱分析

应用偏最小二乘法(PLS)结合近红外光谱(NIR)对烟草灰分(ash)、总挥发酸(TVA)和总挥发碱(TVB)建立校正模型。烟草灰分、总挥发酸和总挥发碱模型相关系数分别为0.97312、0.96220和0.98050;均方预测残差(RMSECV)分别为0.41227、0.00688和0.09790;预测范围分别为1.74~31.31、0.0570~0.2336和0.042~1.136;通过对模型进行t-检验,在显著性水平大于0.05的条件下,其预测结果与行业标准方法的测定结果对比,结果令人满意。     

Simultaneous Determination of Andrographolide and Dehydroandrographolide in Chicken Plasma for Application to Pharmacokinetic Studies

A simple, suitable reverse phase liquid chromatographic method was developed for simultaneous determination of andrographolide (1) and dehydroandrographolide (2) in chicken plasma after orally administrating the ultra-fine powder of Andrographis paniculata. Plasma samples were extracted with ethyl acetate. Analysis of the extract was performed on a reversed-phase C18 column with gradient eluent composed of acetonitrile and 0.5% acetic acid. The flow rate was kept at 1 mL min⁻¹ and the detection wavelength was set at 225 and 255 nm for 1 and 2, respectively. All calibration curves showed good linear regression (R ≥ 0.9991). The good precision and recoveries with intra-day and inter-day were 3.2–8.7% and 91.1–98.4%, respectively. The limit of detection was 0.016 µg mL⁻¹ and the limit of quantitation was 0.040 µg mL⁻¹ for the target analytes. This validated method has been successfully applied in the pharmacokinetics study of 1 and 2 after orally administrating the Andrographis paniculata ultra-fine powder to chicken.

     

傅里叶变换近红外光谱法快速检测人血清生化成分

应用傅里叶变换近红外光谱透射技术结合偏最小二乘法(PLS)建立了人血清中7种生化成分的定标模型,利用内部交叉验证和自动优化功能对定标模型进行了优化,确定了最优建模参数。模型对人血清中总胆固醇、甘油三酯、总蛋白、白蛋白、载脂蛋白B、低密度脂蛋白胆固醇、葡萄糖定标样品集的预测值与化学值的相关系数r分别为0.9011、0.9593、0.9249、0.761、0.8831、0.5191、0 9148,预测校正标准误差RMSECV分别为15mg/dL,21.6mg/dL,2 66g/L,3 96g/L,0.091g/L,16.2mg/dL,0.49mmol/L。     

Determination of andrographolide and dehydroandrographolide in rabbit plasma by on-line solid phase extraction of high-performance liquid chromatography

The high-performance liquid chromatography (HPLC) coupled with on-line solid phase extraction (SPE) and ultraviolet (UV) detection was developed for determining andrographolide and dehydroandrographolide in rabbit plasma. Plasma samples (100 μL) were injected directly into a C18 SPE column and the biological matrix was washed out for 6 min using 15% aqueous methanol. By rotation of the switching valve, andrographolide and dehydroandrographolide were eluted in the back-flush mode and transferred to the analytical column by the chromatographic mobile phase consisted of methanol:acetonitrile (ACN):water (50:10:40; v/v). The UV detection was performed at 225 nm. The calibration curves showed excellent linear relationship (R ≥ 0.9993) over the concentration range of 0.05-5.0 μg mL⁻¹. The within- and between-day precisions (R.S.D.) of two analytes were in the range of 1.2-6.5% and the accuracies were between 92.0% and 102.1%. Their recoveries were all greater than 94%. The limits of detection were 0.019 μg mL⁻¹ for andrographolide and 0.022 μg mL⁻¹ for dehydroandrographolide. This method was successfully applied to the plasma concentration-time curve study after oral administration of Andrographis paniculata Nees extract in rabbit.     

Noncontact analysis of the fiber weight per unit area in prepreg by near-infrared spectroscopy

The fiber weight per unit area in prepreg is an important factor to ensure the quality of the composite products. Near-infrared spectroscopy (NIRS) technology together with a noncontact reflectance sources has been applied for quality analysis of the fiber weight per unit area. The range of the unit area fiber weight was 13.39–14.14 mg cm⁻². The regression method was employed by partial least squares (PLS) and principal components regression (PCR). The calibration model was developed by 55 samples to determine the fiber weight per unit area in prepreg. The determination coefficient (R²), root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.82, 0.092, 0.099, respectively. The predicted values of the fiber weight per unit area in prepreg measured by NIRS technology were comparable to the values obtained by the reference method. For this technology, the noncontact reflectance sources focused directly on the sample with neither previous treatment nor manipulation. The results of the paired t-test revealed that there was no significant difference between the NIR method and the reference method. Besides, the prepreg could be analyzed one time within 20 s without sample destruction.     

Determination of bioactive diterpenoids from Andrographis paniculata by micellar electrokinetic chromatography.

The present paper describes the development of a micellar electrokinetic chromatographic (MEKC) method for simultaneous determination of andrographolide, deoxyandrographolide and neoandrographolide in ethanol extracts of Andrographis paniculata. Separations were carried out in a fused-silica capillary tube with UV detection at 214 nm. Good separation was achieved using a 20 mM borate buffer, containing 20 mM sodium dodecyl sulphate and 10 mM sodium cholate, adjusted to pH 8.3 at an operating voltage of 25 kV, temperature of 35°C and a hydrodynamic injection of 5 s. The method was validated with good correlation coefficients obtained (0.9986–0.9989) while relative standard deviation (RSD) of migration time was between 1.14 and 2.42. It is concluded that this method could be used for speedy and accurate qualitative and quantitative analysis of bioactive diterpenoids in andrographis herb and its derived products.     

Camphor sulphonic acid mediated quantitative 1,3–diol protection of major Labdane diterpenes isolated from Andrographis paniculata

Phytochemical survey of the methanol extract of the dried aerial parts of Andrographis paniculata led to the isolation of major labdane diterpenes, namely 14-deoxy-11,12-didehydroandrographolide, andrographolide and neoandrographolide. Andrographolide was found to be the major phytoconstituent of the plant which was biologically active. For better physiochemical characteristics and bioefficacy, andrographolide is subjected to semi-synthetic modifications. However, presence of several free hydroxyl groups associated with this molecule make it quite polar and poorly soluble in many organic solvents and hence unsuitable for synthetic modifications. One way of resolving its solubility issue is to protect 1,3-diol quantitatively under mild reaction condition without effecting other functional groups. Reaction conditions were optimised using different solvent systems and catalysts towards this direction. X-ray structure of 3,19-isopropylidene-14-deoxy-11,12-didehydroandrographolide is being reported here for the first time. Isolated compounds and derivatives were confirmed by spectral analysis or X-ray data analysis.     

On-line coupling of dynamic microwave-assisted extraction with high-performance liquid chromatography for determination of andrographolide and dehydroandrographolide in Andrographis paniculata Nees

A novel technique based on dynamic microwave-assisted extraction (DMAE) coupled on-line with high-performance liquid chromatography (HPLC) through a flow injection interface has been developed for determination of andrographolide and dehydroandrographolide in Andrographis paniculata Nees. A TM(010) microwave resonance cavity built in the laboratory was applied to concentrating the microwave energy. An extraction vessel was placed in microwave irradiation zone. The extraction was performed in a recirculating system. When a number of extraction cycles were completed, the fractional extract (20muL) was driven to the analytical column by 65% aqueous methanol and was measured by diode array detector (DAD) at 225nm. The optimized extraction conditions are follows: extraction solvent 60% aqueous methanol; microwave forward power 80W; extraction time 6min; extraction solvent flow-rate 1.0mLmin(-1). The detection and quantification limits obtained are 0.5 and 1.7microgmL(-1) for andrographolide and 0.6 and 1.9microgmL(-1) for dehydroandrographolide, respectively. The within-day and between-day precision (RSD) are 2.1% and 3.7% for andrographolide and 1.7% and 4.1% for dehydroandrographolide, respectively. Mean recoveries for andrographolide and dehydroandrographolide are 97.7% and 98.7%, respectively. Compared with ultrasonic extraction used in the Chinese pharmacopoeia, the proposed method was demonstrated to obtain higher extraction yield in a shorter time. In addition, only small quantities of solvent (5mL) and sample (10mg) were required.     

Determination of Fipronil in Acetamiprid Formulation by Attenuated Total Reflectance-Mid-Infrared Spectroscopy Combined with Partial Least Squares Regression

There is a high demand for rapid determination of fipronil in pesticide preparations because it has been restricted and even prohibited in many countries. An infrared-based methodology was developed for this analyte in acetamiprid formulations by attenuated total reflectance mid-infrared spectroscopy. The quantitative calibration models of fipronil were established by partial least squares regression. The determination coefficients (R²) of the model were above 0.99 while both the root mean square error of prediction and root mean square error of calibration were below 0.0011, which showed the partial least squares model accurately predicted fipronil concentrations in acetamiprid. The accuracy was further demonstrated by comparison with another two models' results of low (<1.0%, w/w) and high concentration sample sets (1.0%–4.5%, w/w). These results demonstrate the potential of infrared spectroscopy to quickly detect fipronil in acetamiprid.     

Application of genetic algorithm‐support vector regression (GA‐SVR) for quantitative analysis of herbal medicines

In this paper, a genetic algorithm‐support vector regression (GA‐SVR) coupled approach was proposed for investigating the relationship between fingerprints and properties of herbal medicines. GA was used to select variables so as to improve the predictive ability of the models. Two other widely used approaches, Random Forests (RF) and partial least squares regression (PLSR) combined with GA (namely GA‐RF and GA‐PLSR, respectively), were also employed and compared with the GA‐SVR method. The models were evaluated in terms of the correlation coefficient between the measured and predicted values (Rp), root mean square error of prediction, and root mean square error of leave‐one‐out cross‐validation. The performance has been tested on a simulated system, a chromatographic data set, and a near‐infrared spectroscopic data set. The obtained results indicate that the GA‐SVR model provides a more accurate answer, with higher Rp and lower root mean square error. The proposed method is suitable for the quantitative analysis and quality control of herbal medicines. Copyright © 2012 John Wiley & Sons, Ltd.     

Simultaneous Determination of Eight Bioactive Components of Radix Dipsaci by Near-infrared Spectroscopy

A new method was developed using Fourier transform near-infrared spectroscopy and high-performance liquid chromatography with diode array detection for the identification and determination of eight major compounds in crude and sweated Radix Dipsaci. Partial least square regression was selected for the analysis. Multiplicative scatter correction, first derivative, and a Savitzky–Golay filter were used for the spectral pretreatment of the crude material, while standard normal variation, first derivative, and the Savitzky–Golay filter were used for the sweated samples. The correlation coefficients of the calibration models were above 0.99 and the root mean square error of calibration, the root mean square error of prediction, and root mean square error of cross-validation were under 0.63. The developed models were used to analyze unknown crude and sweated Radix Dipsaci with satisfactory results. The established methods were rapid, simple, nondestructive, and useful for quality control of Radix Dipsaci.     

Near-infrared spectroscopy quantitative determination of Pefloxacin mesylate concentration in pharmaceuticals by using partial least squares and principal component regression multivariate calibration

Pefloxacin mesylate, a broad-spectrum antibacterial fluoroquinolone, has been widely used in clinical practice. Therefore, it is very important to detect the concentration of Pefloxacin mesylate. In this research, the near-infrared spectroscopy (NIRS) has been applied to quantitatively analyze on 108 injection samples, which was divided into a calibration set containing 89 samples and a prediction set containing 19 samples randomly. In order to get a satisfying result, partial least square (PLS) regression and principal components regression (PCR) have been utilized to establish quantitative models. Also, the process of establishing the models, parameters of the models, and prediction results were discussed in detail. In the PLS regression, the values of the coefficient of determination (R²) and root mean square error of cross-validation (RMSECV) of PLS regression are 0.9263 and 0.00119, respectively. For comparison, though applying PCR method to get the values of R² and RMSECV we obtained are 0.9685 and 0.00108, respectively. And the values of the standard error of prediction set (SEP) of PLS and PCR models are 0.001480 and 0.001140. The result of the prediction set suggests that these two quantitative analysis models have excellent generalization ability and prediction precision. However, for this PFLX injection samples, the PCR quantitative analysis model achieved more accurate results than the PLS model. The experimental results showed that NIRS together with PCR method provide rapid and accurate quantitative analysis of PFLX injection samples. Moreover, this study supplied technical support for the further analysis of other injection samples in pharmaceuticals.     

Determination of Iridoids in Gentiana rigescens by Infrared Spectroscopy and Multivariate Analysis

Gentiana rigescens is a famous herbal medicine in China for treatment of convulsion, rheumatism, and jaundice. Here, the infrared determination of gentiopicroside, swertiamarin, sweroside, and loganic acid in G. rigescens from different areas and varieties was presented for the first time. Reference information for the iridoids were obtained by high-performance liquid chromatography. Partial least squares was used to characterize the relationship between spectra matrix and concentration vector for the determination of the analytes. For determination of gentiopicroside, the appropriate performance of partial least squares model was acquired with coefficient of determination of calibration and coefficient of determination of prediction values of 0.965 and 0.868. The root mean square error of estimation (RMSEE), root mean square error of cross validation (RMSECV), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) values were 2.612, 5.292, 5.239?mg g^?1, and 2.701, respectively, based on the first derivative and multiplicative scatter correction. For determination of the total iridoids, the best results were obtained using the coefficient of determination of calibration and coefficient of determination of prediction of 0.943 and 0.834, RMSEE, RMSECV, RMSEP and RPD of 3.896, 7.536, 6.543?mg g^?1 and 2.438, respectively, based on the first derivative. Both models were reliable and robust. The results demonstrated that infrared spectroscopy provided a rapid, low-cost tool to monitor the quality of G. rigescens by the determination of the iridoids.