Pharmacokinetics and tissue distribution of monotropein and deacetyl asperulosidic acid after oral administration of extracts from Morinda officinalis root in rats.

BACKGROUND: Iridoid glycosides (IGs), including monotropein (MON) and deacetyl asperulosidic acid (DA) as the main ingredients, are the major chemical components in Morinda officinalis How. (MO) root, possessing various pharmacological properties including anti-osteoporosis, anti-inflammation and anti-rheumatism activities.The aim of the present study was to further elucidate the pharmacological actions of MO by investigating the pharmacokinetics and tissue distribution of IGs in MO. METHODS: An ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS) method was developed and validated for simultaneous determination of MON and DA levels in plasma and various tissues of Wistar rats. MON, DA and acetaminophen (ACE) as the internal standard (IS) were extracted from rat plasma and tissue samples by direct deproteinization with methanol. The rats were administered orally at 1650 mg/kg MO and 25, 50 and 100 mg/kg MO iridoid glycosides (MOIGs) or intravenously at MOIG 25 mg/kg for pharmacokinetic study of MON and DA. In addition, 100 mg/kg MOIG was administered orally for tissue distribution study of MON and DA. Non-compartmental pharmacokinetic profiles were constructed. Tissue distributions were calculated according to the validated methods. RESULTS: Significant differences in the pharmacokinetic parameters were observed in male and female rats. The AUC0-t, Cmax and bioavailability of MON and DA in female rats were higher than those in male rats. MON and DA mainly distributed in the intestine and stomach after oral administration, and noteworthily high concentrations of MON and DA were detected in the rat hypothalamus. CONCLUSION: The results of the present study may shed new lights on the biological behavior of MOIGs in vivo, help explain their pharmacological actions, and provide experimental clues for rational clinical use of these IGs extracted from the MO root.

[Near-infrared spectroscopy technology for online monitoring of the column separation and purification process of active components of Centella asiatica L. Urban].

The present paper is to study and develop a method for online monitoring of the column separation and purification process of active components that are madecassoside and asiaticoside of Centella asiatica L. Urban using near-infrared (NIR) spectroscopy technology. After collecting 50%-ethanol eluant, we detected their NIR spectra and developed the high performance liquid chromatography (HPLC) assay method of active components. Then, partial least square (PLS) was used to develop linear correlation between their NIR spectra and contents. During modeling, correlation coefficient (R2) and root mean square errors of cross-validation (RMSECV) were regarded as the indexes to select optimal wavenumbers and preprocessing methods. The optimal wavenumbers of madecassoside and asiaticoside were in the range of 12 000.8-7 499.8 cm(-1) and 12 000.8-9 750.3 cm(-1), respectively; R2 were 96.44 and 96.07, respectively, and RMSECV were 0.084 80 and 0.000 99, respectively. The above developed model was used for online monitoring of the contents of madecassoside and asiaticoside during the column separation and purification process of Centella asiatica L. Urban. The predicted results were satisfactory. This method was proved to be fast, convenient and precise. It can be used in online monitoring and quality control of the manufacturing of madecassoside and asiaticoside.

[Establishment of the model for online monitoring of the column separation and purification process by near-infrared spectroscopy and determination of total ginsenosides in Folium Ginseng].

A method was developed for online monitoring of the constituents of ginsenoside of Folium Ginseng in the column separation and purification process using near-infrared (NIR) spectroscopy technology. Determination method of ginsenoside Rg1, Re and Rb1 was developed by high performance liquid chromatography (HPLC). After collecting 40%-ethanol eluant, their NIR spectra were detected and the contents of Rg1, Re and Rb1 were determined by the above HPLC method. The quantitative analysis models of the above three compounds and the total ginsenosides were established using partial least squares (PLS). During modeling, coefficient of determination (R2) and root mean square errors of cross-validation (RMSECV) were regarded as the indexes to select optimal wave numbers and preprocessing methods. The optimal wave numbers of ginsenoside Rg1, Re, Rb1 and total ginsenosides were all in the range of 12 000. 8 approximately 7499.8 cm-1; R2 were 0.9887, 0. 9603, 0.9905 and 0.9701, respectively; RMSECV were 0.0597, 0.0722, 0.00488 and 0.0755, respectively. A lot of samples, collected during the column separation and purification process of Folium Ginseng extract, were used to validate the predicttion effect of quantitative analysis model of total ginsenosides. As a result, the correlation coefficient of NIR predicted value and HPLC value of total ginsenosides was 0.9928 and the mean prediction recovery was 100.52%, which indicated that the prediction effect of the developed model was satisfactory. This method was proved to be fast, convenient and precise. It can be used for assaying and quality control of total ginsenosides in manufacture.

[Discriminating and quantifying potential adulteration in virgin olive oil by near infrared spectroscopy with BP-ANN and PLS].

In the present paper, the use of near infrared spectroscopy (NIR) as a rapid and cost-effective classification and quantification techniques for the authentication of virgin olive oil were preliminarily investigated. NIR spectra in the range of 12 000 - 3 700 cm(-1) were recorded for pure virgin olive oil and virgin olive oil samples adulterated with varying concentrations of sesame oil, soybean oil and sunflower oil (5%-50% adulterations in the weight of virgin olive oil). The spectral range from 12 000 to 5 390 cm(-1) was adopted to set up an analysis model. In order to handle these data efficiently, after pretreatment, firstly, principal component analysis (PCA) was used to compress thousands of spectral data into several variables and to describe the body of the spectra, and the analysis suggested that the cumulate reliabilities of the first six components was more than 99.999%. Then ANN-BP was chosen as further research method. The six components were secondly applied as ANN-BP inputs. The experiment took a total of 100 samples as original model examples and left 52 samples as unknown samples to predict. Finally, the results showed that the 52 test samples were discriminated accurately. And the calibration models of quantitative analysis were built using partial-least-square (PLS). The R values for PLS model are 98.77, 99.37 and 99.44 for sesame oil, soybean oil and sunflower oil respectively, the root mean standard errors of cross validation (RMSECV) are 1.3, 1.1 and 1.04 respectively. Overall, the near infrared spectroscopic method in the present paper played a good role in the discrimination and quantification, and offered a new approach to the rapid discrimination of pure and adulterated virgin olive oil.