A novel comprehensive strategy for high-thoroughly studying released compounds during the combustion process of herbs. A case study for Artemisia argyi Levl. et Vant.

The comprehensive study of compound variations in released smoke during the combustion process is a great challenge in many scientific fields related to analytical chemistry like traditional Chinese medicine, environment analysis, food analysis, etc. In this work, we propose a new comprehensive strategy for efficiently and high-thoroughly characterizing compounds in the online released complex smokes: (i) A smoke capture device was designed for efficiently collecting chemical constituents to perform gas chromatography-mass spectrometry (GC-MS) based untargeted analysis. (ii) An advanced data analysis tool, AntDAS-GCMS, was used for automatically extracting compounds in the original acquired GC-MS data files. Additionally, a GC-MS data analysis guided instrumental parameter optimizing strategy was proposed for the optimization of parameters in the smoke capture device. The developed strategy was demonstrated by the study of compound variations in the smoke of traditional Chinese medicine, Artemisia argyi Levl. et Vant. The results indicated that more than 590 components showed significant differences among released smokes of various moxa velvet ratios. Finally, about 88 compounds were identified, of which phenolic compounds were the most abundant, followed by aromatics, alkenes, alcohols and furans. In conclusion, we may provide a novel approach to the studies of compounds in online released smoke.

Geographical discrimination of Flos Trollii by GC-MS and UHPLC-HRMS-based untargeted metabolomics combined with chemometrics.

For centuries, Flos Trollii has been consumed as functional tea and a folk medicine in China's north and northwest zones. The quality of Flos Trollii highly depends on the producing zones. Unfortunately, few studies have been reported on the geographical discrimination of Flos Trollii. This work comprehensively investigated Flos Trollii compounds with an integration strategy combining gas chromatography-mass spectrometry (GC-MS) and ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) with chemometrics to explore the differences between Flos Trollii obtained from various origins of China. About 71 volatile and 22 involatile markers were identified with GC-MS and UHPLC-HRMS, respectively. Geographical discrimination models were synthetically investigated based on the identified markers. The results indicated that the UHPLC-HRMS coupled with the fisher discrimination model provided the best prediction capability (>97%). This study provides a new solution for Flos Trollii discrimination.

Orientin regulates the proliferation and migration of hepatocellular carcinoma cells.

Orientin is a flavone isolated from medicinal plants used in traditional Chinese medicine (TCM) that suppresses the growth of cancer cells in vitro. The effects of orientin in hepatoma carcinoma cells remain unknown. The aim of this paper is to investigate the effects of orientin on the viability, proliferation, and migration of hepatocellular carcinoma cells in vitro. In this study, we found that orientin could inhibit the proliferation, migration, and the activation of NF-κB signaling pathway in hepatocellular carcinoma cells. An activator of NF-κB signaling pathway, PMA, could abolish the inhibitory effect of orientin on NF-κB signaling pathway and proliferation and migration of Huh7 cells. These findings raise the possibility that orientin can be used in the treatment of hepatocellular carcinoma.

Chemometric discrimination of the geographical origin of licorice in China by untargeted metabolomics.

Licorice is famous as a herbal medicine and food sweetener. This study provided a comprehensive strategy for investigating the quality of licorice based on untargeted metabolomics. A new strategy for identifying metabolite was developed, including fragment ion identification algorithm and ion fusion algorithm. The results showed that it can accurately integrate mass spectra from positive and negative ion modes to benefit metabolite identification. Based on the strategy, a number of significant difference metabolites were identified among licorice samples and 9 metabolites were confirmed by standards. Additionally, the geographical discrimination models of licorice samples were comprehensively investigated by chemometric methods. The results indicated that the supporting vector machine provided the best performance, with a prediction accuracy above 80%. The study results supported the conclusion that the quality of licorice from different regions in China was inconsistent.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

Tanshinol alleviates impaired bone formation by inhibiting adipogenesis via KLF15/PPARγ2 signaling in GIO rats.

Glucocorticoid (GC)-induced osteoporosis (GIO) is characterized by impaired bone formation, which can be alleviated by tanshinol, an aqueous polyphenol isolated from Salvia miltiorrhiza Bunge. In this study we investigated the molecular mechanisms underlying GC-induced modulation of osteogenesis as well as the possibility of using tanshinol to interfere with GIO. Female SD rats aged 4 months were orally administered distilled water (Con), prednisone (GC, 5 mg·kg-1·d-1), GC plus tanshinol (Tan, 16 mg·kg-1·d-1) or GC plus resveratrol (Res, 5 mg·kg-1·d-1) for 14 weeks. After the rats were sacrificed, samples of bone tissues were collected. The changes in bone formation were assessed using Micro-CT, histomorphometry, and biomechanical assays. Expression of Kruppel-like factor 15 (KLF15), peroxisome proliferator-activated receptor γ 2 (PPARγ 2) and other signaling proteins in skeletal tissue was measured with Western blotting and quantitative RT-PCR. GC treatment markedly increased the expression of KLF15, PPARγ2, C/EBPα and aP2, which were related to adipogenesis, upregulated FoxO3a pathway proteins (FoxO3a and Gadd45a), and suppressed the canonical Wnt signaling (ß-catenin and Axin2), which was required for osteogenesis. Thus, GC significantly decreased bone mass and bone quality. Co-treatment with Tan or Res effectively counteracted GC-impaired bone formation, suppressed GC-induced adipogenesis, and restored abnormal expression of the signaling molecules in GIO rats. We conclude that tanshinol counteracts GC-decreased bone formation by inhibiting marrow adiposity via the KLF15/PPARγ2/FoxO3a/Wnt pathway.

Automatic time-shift alignment method for chromatographic data analysis.

Time shift among samples remains a significant challenge in data analysis, such as quality control of natural plant extracts and metabolic profiling analysis, because this phenomenon may lead to invalid conclusions. In this work, we propose a new time shift alignment method, namely, automatic time-shift alignment (ATSA), for complicated chromatographic data analysis. This technique comprised the following alignment stages: (1) automatic baseline correction and peak detection stage for providing useful chromatographic information; (2) preliminary alignment stage through adaptive segment partition to correct alignment for the entire chromatogram; and (3) precise alignment stage based on test chromatographic peak information to accurately align time shift. In ATSA, the chromatographic peak information of both reference and test samples can be completely employed for time-shift alignment to determine segment boundaries and avoid loss of information. ATSA was used to analyze a complicated chromatographic dataset. The obtained correlation coefficients among samples and data analysis efficiency indicated that the influences of time shift can be considerably reduced by ATSA; thus accurate conclusion could be obtained.

Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure.

Fast analysis of synthetic antioxidants in edible vegetable oil using trilinear component modeling of liquid chromatography-diode array detection data.

A new chromatographic methodology is presented for fast quantitative analysis of ten synthetic phenolic antioxidants in five kinds of oil samples: propyl gallate (PG), 2,4,5-trihydroxybutyrophenone (THBP), tert-butylhydroquinone (TBHQ), nordihydroguaiaretic acid (NDGA), ethoxyquin (EQ), 3-tert-butyl-4- hydroxyanisole (BHA), octyl gallate (OG), 2,6-di-tert-butyl-4-hydroxymethyphenol (Ionox-100), dodecyl gallate (DG), 3,5-di-tert-butyl-4-hydroxytoluene (BHT). The second-order calibration, with second-order advantage, based on the alternating penalty trilinear decomposition (APTLD) algorithm has shown to be an excellent tool for modeling the three-way data, where overlapping peaks, uncalibrated inteferences, and baseline drift existed, making the fast determination and resolution of the phenolic antioxidants in oils possible. Such extraction procedure in which the antioxidants of interest would be seperated is unnecessary and the ten antioxidants can be eluted within 6 mins. For the validation of the method, linearity, root-mean-square error of prediction (RMSEP) and limit of detection (LOD) have been performed. The average recovery of antioxidants ranges from 94.9 to 106.1% and the ten analytes can be adequately determined with limits of detection of 0.18-5.72 µgm l(-1).

Chemometric resolution of coeluting peaks of eleven antihypertensives from multiple classes in high performance liquid chromatography: a comprehensive research in human serum, health product and Chinese patent medicine samples.

A novel chemometric-assisted high performance liquid chromatography method coupled with diode array detector (HPLC-DAD) was presented for the simultaneous determination of eleven antihypertensives from multiple classes in most concerned matrix systems. With the aid of second-order calibration which enables specific information of analytes to be well extracted, the heavily overlapping profiles between analytes and the coeluting interferences can be successfully separated and thus accurately quantified. A great advantage of the novel strategy lies in the fact that the analysis could be carried out with the same isocratic mobile phase (methanol/KH(2)PO(4): 58:42, v/v, pH 2.60) in a short time regardless of the changes of matrices, such as human serum, health product and Chinese patent medicine. Both qualitative and quantitative results indicate that the hybrid strategy that using HPLC-DAD coupled with second-order chemometric method would be a high performance approach for the purpose of simultaneously quantifying multiple classes of antihypertensives in complex systems. Additionally, the analytical strategy can potentially benefit drug monitoring in both therapeutic research and pharmaceutical quality control. Moreover, the accuracy and reliability of the proposed methodology has been evaluated using several statistical parameters such as root mean squared error of prediction (RMSEP), figures of merit (FOM) and reproducibility of inter-day analysis.

Second-order calibration applied to quantification of two active components of Schisandra chinensis in complex matrix.

The effectiveness of traditional Chinese medicine (TCM) against various diseases urges more low cost, speed and sensitive analytical methods for investigating the phamacology of TCM and providing a theoretical basis for clinical use. The potential of second-order calibration method was validated for the quantification of two effective ingredients of Schisandra chinensis in human plasma using spectrofluorimetry. The results obtained in the present study demonstrate the advantages of this strategy for multi-target determination in complex matrices. Although the spectra of the analytes are similar and a large number of interferences also exist, second-order calibration method could predict the accurate concentrations together with reasonable resolution of spectral profiles for analytes of interest owing to its 'second-order advantage'. Moreover, the method presented in this work allows one to simply experimental procedure as well as reduces the use of harmful chemical solvents.