Dabing Ren

Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

This review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets.

Correlation and prediction of partition coefficient using nonrandom two-liquid segment activity coefficient model for solvent system selection in counter-current chromatography separation

Selection of a suitable solvent system is the first and foremost step for a successful counter-current chromatography (CCC) separation. In this paper, a thermodynamic model, nonrandom two-liquid segment activity coefficient model (NRTL-SAC) which uses four types of conceptual segments to describe the effective surface interactions for each solvent and solute molecule, was employed to correlate and predict the partition coefficients (K) of a given compound in a specific solvent system. Then a suitable solvent system was selected according to the predicted partition coefficients. Three solvent system families, heptane/methanol/water, heptane/ethyl acetate/methanol/water (Arizona) and hexane/ethyl acetate/methanol/water, and several solutes were selected to investigate the effectiveness of the NRTL-SAC model for predicting the partition coefficients. Comparison between experimental results and predicted results showed that the NRTL-SAC model is of potential for estimating the K value of a given compound. Also a practical separation case on magnolol and honokiol suggests the NRTL-SAC model is effective, reliable and practical for the purpose of predicting partition coefficients and selecting a suitable solvent system for CCC separation.

Phytochemistry and bioactivity of Citrus flavonoids: a focus on antioxidant, anti-inflammatory, anticancer and cardiovascular protection activities

Epidemiological studies have suggested an inverse relationship between increased consumption of fruits and reduced risk of chronic diseases, such as cardiovascular diseases, cancer, and diabetes. Citrus fruit is one of the mostly consumed fruits worldwide, and numerous studies have revealed its remarkable health-promoting activities, such as antioxidant, anticancer, anti-inflammatory, and cardiovascular protection activities. These activities largely depend upon the diverse chemical constituents of Citrus fruits, including vitamins, minerals, terpenoids, and flavonoids. Notably, dietary flavonoids occurring in Citrus fruits have attracted growing interest due to their distinct beneficial effects on human health. In this review, we outlined the main health-related properties of Citrus flavonoids, with a focus on antioxidant, anticancer, anti-inflammation, and cardiovascular protection activities. Also the bioavailability, a critical factor that influences the biological efficacy, of Citrus flavonoids was discussed. It was believed that insights about these advances may encourage researchers to discover new phytochemical components and further study specific bioactivities from Citrus fruits.

Using nonrandom two-liquid model for solvent system selection in counter-current chromatography

Selection of an appropriate solvent system is of great importance for a successful counter-current chromatography separation. In this work, the nonrandom two-liquid (NRTL) model, a thermodynamic method, was used for predicting the partition coefficient based on a few measured partition coefficients. The NRTL method provides quite satisfactory results for model solutes in first correlating measured partition coefficient in a few representative biphasic liquid systems and then successfully predicting partition coefficient in other two-phase liquid systems. According to the predicted partition coefficient, a suitable solvent system can be screened. Assisted with the NRTL method, the solvent system composed of hexane/ethyl acetate/methanol/water (1:4:1:4, v/v) was rapidly screened for the successful separation of two major compounds with high purity from Malus hupehensis leaves. The results demonstrated that the NRTL model can offer a simple and practical strategy to estimate partition coefficients in support of CCC solvent system selection, which will significantly minimize the experimental efforts and cost involved in solvent system selection.

Comprehensive characterization and identification of antioxidants in Folium Artemisiae Argyi using high-resolution tandem mass spectrometry

Antioxidants from natural sources, such as vegetables and fruits, are attracting more and more interest. In this work, we evaluated the antioxidant potential of Folium Artemisia Argyi, a traditional Chinese herb medicine and food supplement. The total phenolic content, total flavonoid content, and antioxidant ability of the crude extracts and fractions obtained from consecutively partition of n-hexane, ethyl acetate, and n-butanol were measured and compared. Ethyl acetate fraction shows the highest total phenolic and flavonoid contents and highest antioxidant capability with regard to DPPH, ABTS, superoxide anion free radical scavenging ability, and ferric-reducing antioxidant power. In addition, the potential antioxidant components were screened by DPPH-UHPLC-MS experiments and subsequently characterized by using high-resolution tandem mass spectrometry. This work finally identified 45 antioxidants, including organic acids, phenolic compounds, flavonoids, and methoxylated flavonoids. The results suggested that Folium Artemisiae Argyi is a potential inexpensive resource of natural antioxidants.

GC-MS Fingerprinting Combined with Chemometric Methods Reveals Key Bioactive Components in Acori Tatarinowii Rhizoma

This present study aims to identify the key bioactive components in acorus tatarinowii rhizoma (ATR), a traditional Chinese medicine (TCM) with various bioactivities. Partial least squares regression (PLSR) was employed to describe the relationship between the radical scavenging activity and the volatile components. The PLSR model was improved by outlier elimination and variable selection and was evaluated by 10-fold cross-validation and external validation in this study. Based on the PLSR model, eleven chemical components were identified as the key bioactive components by variable importance in projection. The final PLS regression model with these components has good predictive ability. The Q2 was 0.8284, and the root mean square error for prediction was 2.9641. The results indicated that the eleven components could be a pattern to predict the radical scavenging activity of ATR. In addition, we did not find any specific relationship between the radical scavenging ability and the habitat of the ATRs. This study proposed an efficient strategy to predict bioactive components using the combination of quantitative chromatography fingerprints and PLS regression, and has potential perspective for screening bioactive components in complex analytical systems, such as TCM.

Characterizing Alzheimer's disease through metabolomics and investigating anti-Alzheimer's disease effects of natural products

Alzheimers disease (AD) is the most common cause of dementia in elderly people and is among the greatest healthcare challenges of the 21st century. However, the etiology and pathogenesis of AD remain poorly understood, and no curative treatments are available to slow down or stop the degenerative effects of AD. As a high‐throughput approach, metabolomics is gaining significant attention in AD research, because it has a powerful potential to discover novel biomarkers, unravel new therapeutic targets for AD, and identify perturbed metabolic pathways involved in AD progression. Here, we systematically review metabolomics with regard to its recent advances and applications in the identification of potential biomarkers for early AD diagnosis and pathogenesis research. In addition, we illustrate the developments in metabolomics as an effective tool for understanding the anti‐AD mechanisms of natural products. We believe that the insights from these advances can narrow the gap between metabolomics research and clinical applications of laboratory findings. Moreover, we discuss some limitations and perspectives of biomarker identification in metabolomics.

Combined application of chromatographic techniques for the separation of phenolic compounds from Stenoloma chusanum Ching

High-speed countercurrent chromatography combined with preparative high-performance liquid chromatography was successfully used to separate seven phenolic compounds from Stenoloma chusanum Ching. A biphasic solvent system composed of hexane/ethyl acetate/methanol/water (1:2:1:2, v/v) was used for the first step high-speed countercurrent chromatography separation in elution-extrusion mode. A mobile phase composed of acetonitrile (18%) and pure water (82%) was used for further preparative high-performance liquid chromatography purification. In total, the combined separation yielded seven compounds, including 3,4-dihydroxy benzoic acid, 3,4-dihydroxy benzaldehyde, esculetin, caffeic acid, syringic acid, luteolin, and apigenin, at a purity of over 90%. Esculetin was separated from Stenoloma chusanum Ching for the first time. The results suggest that the proposed combination method is a useful strategy for separating compounds from complex samples.

Systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient model for real-life counter-current chromatography separation

Solvent system selection is the first step toward a successful counter-current chromatography (CCC) separation. This paper introduces a systematic and practical solvent system selection strategy based on the nonrandom two-liquid segment activity coefficient (NRTL-SAC) model, which is efficient in predicting the solute partition coefficient. Firstly, the application of the NRTL-SAC method was extended to the ethyl acetate/n-butanol/water and chloroform/methanol/water solvent system families. Moreover, the versatility and predictive capability of the NRTL-SAC method were investigated. The results indicate that the solute molecular parameters identified from hexane/ethyl acetate/methanol/water solvent system family are capable of predicting a large number of partition coefficients in several other different solvent system families. The NRTL-SAC strategy was further validated by successfully separating five components from Salvia plebeian R.Br. We therefore propose that NRTL-SAC is a promising high throughput method for rapid solvent system selection and highly adaptable to screen suitable solvent system for real-life CCC separation.

Effects of injection volume on chromatographic features and resolution in the process of counter-current chromatography.

Counter-current chromatography is a high efficiency separation and purification technique. As a preparative separation technique, the final goal that we are concerned about is acquisition of maximum yields of the separated compounds under specific conditions. In this paper, the theory of counter current extraction table (TCCET), a numerical model for counter-current chromatography, was employed firstly to investigate the effects of injection volume on chromatographic features (retention time, peak height and peak width) and resolution between the separated compounds from theoretical point of view. Moreover, a series of experiments were performed to evaluate the effectiveness of the TCCET model when used for analysis of the influences of the injection volume on a counter-current chromatography separation process. Both the theoretical analysis and experiments show that: (1) the retention time or retention volume increases with the injection volume linearly; (2) the peak height increases with increase of the injection volume, and when the injection volume is smaller than ten percent of V(m) (volume occupied by mobile phase in a CCC column), the relationship between the peak height and the injection volume is a kind of linear relationship; and (3) the peak width also increases with increase of the injection volume, and obvious linear relationship between the peak width and the injection volume can be observed when the injection volume is smaller than a certain volume. In contrast, the resolution between the separated compounds decreases with increase of the injection volume.