Quality evaluation of Lonicerae Japonicae Flos from different origins based on high-performance liquid chromatography (HPLC) fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition.

INTRODUCTION: Lonicerae Japonicae Flos (LJF) is widely used in food and traditional Chinese medicine. To meet demand, Lonicera japonica Thunb. is widely cultivated in many provinces of China. However, reported studies on the quality evaluation of LJF only used a single or a few active components as indicators, which could not fully reflect the quality of LJF. OBJECTIVES: In the present study, we aimed to develop a methodology for comprehensively evaluating the quality of LJF from different origins based on high-performance liquid chromatography (HPLC) fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition. MATERIALS AND METHODS: The HPLC method was developed for fingerprint analysis and was used to determine the contents of 19 components of LJF. To distinguish between samples and identify differential components, similarity analysis, hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis were performed. RESULTS: The HPLC fingerprint was established. Using the developed method, the contents of 19 components recognized in the fingerprint analysis were determined. Samples from different origins could be effectively distinguished. CONCLUSIONS: HPLC fingerprinting and multicomponent quantitative analysis combined with chemical pattern recognition is an efficient method for evaluating LJF.

Characterization of Flavor Profile of Sauced Pork from Different Regions of China Based on E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectroscopy.

This study aimed to investigate the volatile flavor compounds and tastes of six kinds of sauced pork from the southwest and eastern coastal areas of China using gas chromatography-ion mobility spectroscopy (GC-IMS) combined with an electronic nose (E-nose) and electronic tongue (E-tongue). The results showed that the combined use of the E-nose and E-tongue could effectively identify different kinds of sauced pork. A total of 52 volatile flavor compounds were identified, with aldehydes being the main flavor compounds in sauced pork. The relative odor activity value (ROAV) showed that seven key volatile compounds, including 2-methylbutanal, 2-ethyl-3, 5-dimethylpyrazine, 3-octanone, ethyl 3-methylbutanoate, dimethyl disulfide, 2,3-butanedione, and heptane, contributed the most to the flavor of sauced pork (ROAV ≥1). Multivariate data analysis showed that 13 volatile compounds with the variable importance in projection (VIP) values > 1 could be used as flavor markers to distinguish six kinds of sauced pork. Pearson correlation analysis revealed a significant link between the E-nose sensor and alcohols, aldehydes, terpenes, esters, and hetero-cycle compounds. The results of the current study provide insights into the volatile flavor compounds and tastes of sauced pork. Additionally, intelligent sensory technologies can be a promising tool for discriminating different types of sauced pork.

LC/MS-based discrimination between plasma and urine metabolomic changes following exposure to ultraviolet radiation by using data modelling.

INTRODUCTION: This study sought to compare between metabolomic changes of human urine and plasma to investigate which one can be used as best tool to identify metabolomic profiling and novel biomarkers associated to the potential effects of ultraviolet (UV) radiation. METHOD: A pilot study of metabolomic patterns of human plasma and urine samples from four adult healthy individuals at before (S1) and after (S2) exposure (UV) and non-exposure (UC) were carried out by using liquid chromatography-mass spectrometry (LC-MS). RESULTS: The best results which were obtained by normalizing the metabolites to their mean output underwent to principal components analysis (PCA) and Orthogonal Partial least squares-discriminant analysis (OPLS-DA) to separate pre-from post-of exposure and non-exposure of UV. This separation by data modeling was clear in urine samples unlike plasma samples. In addition to overview of the scores plots, the variance predicted-Q2 (Cum), variance explained-R2X (Cum) and p-value of the cross-validated ANOVA score of PCA and OPLS-DA models indicated to this clear separation. Q2 (Cum) and R2X (Cum) values of PCA model for urine samples were 0.908 and 0.982, respectively, and OPLS-DA model values were 1.0 and 0.914, respectively. While these values in plasma samples were Q2 = 0.429 and R2X = 0.660 for PCA model and Q2 = 0.983 and R2X = 0.944 for OPLS-DA model. LC-MS metabolomic analysis showed the changes in numerous metabolic pathways including: amino acid, lipids, peptides, xenobiotics biodegradation, carbohydrates, nucleotides, Co-factors and vitamins which may contribute to the evaluation of the effects associated with UV sunlight exposure. CONCLUSIONS: The results of pilot study indicate that pre and post-exposure UV metabolomics screening of urine samples may be the best tool than plasma samples and a potential approach to predict the metabolomic changes due to UV exposure. Additional future work may shed light on the application of available metabolomic approaches to explore potential predictive markers to determine the impacts of UV sunlight.

Metabolite profiling analysis of hepatitis B virus-induced liver cirrhosis patients with minimal hepatic encephalopathy using gas chromatography-time-of-flight mass spectrometry and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry.

This study used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) and ultra-performance liquid chromatography-quadrupole TOFMS (UPLC-QTOFMS) metabonomic analytical techniques in combination with bioinformatics and pattern recognition analysis methods to analyze the serum metabolite profiling of hepatitis B virus (HBV)-induced liver cirrhosis patients with minimal hepatic encephalopathy (MHE), to find the specific biomarkers of MHE, to reveal the pathogenesis of MHE, and to determine a promising approach for early diagnosis of MHE. Serum samples of 100 normal controls (NC group), 29 HBV-induced liver cirrhosis patients with MHE (MHE group), and 24 HBV-induced liver cirrhosis patients without MHE [comprising 12 cases of compensated cirrhosis (CS group) and 12 cases of decompensated cirrhosis (DS group)] were collected and employed into GC-TOFMS and UPLC-QTOFMS platforms for serum metabolite detection; the outcome data were then analyzed using principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA). There were no significant differential metabolites between the NC group and the CS group. A series of key differential metabolites were detected. According to the variable influence in projection values and P-values, 60 small-molecule metabolites were considered to be dysregulated in the MHE group (compared to the NC group); 27 of these 60 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 4, marked in bold); 66 small-molecule metabolites were considered to be dysregulated in the DS group (compared to the NC group); 34 of these 66 dysregulated differential metabolites were considered to be the potential biomarkers (see Table 5, marked in bold). According to the fold-change values, 9 of these 27 metabolites, namely valine, oxalic acid, erythro-sphingosine, 4,7,10,13,16,19-docosahexaenoic acid, isoleucine, allo-isoleucine, thyroxine, rac-octanoyl carnitine, and tocopherol (vitamin E), were downregulated in the MHE group (compared to the NC group); the other 18, namely adenine, glycochenodeoxycholic acid, fucose, allothreonine, glycohyocholic acid, glycoursodeoxycholic acid, tyrosine, taurocheno-deoxycholate, phenylalanine, 2-hydroxy-3-methyl-butanoic acid, hydroxyacetic acid, taurocholate, sorbitol, rhamnose, tauroursodeoxycholate, tolbutamide, pyroglutamic acid, and malic acid, were upregulated; 6 of these 34 metabolites were downregulated in the DS group (compared to the NC group), and the other 28 were upregulated, as shown in Table 5. (a) GC-TOFMS and UPLC-QTOFMS metabonomic analytical platforms can detect a range of metabolites in the serum; this might be of great help to study the pathogenesis of MHE and may provide a new approach for the early diagnosis of MHE. (b) Metabonomics analysis in combination with pattern recognition analysis might have great potential to distinguish the HBV-induced liver cirrhosis patients who have MHE from the normal healthy population and HBV-induced liver cirrhosis patients without MHE.

Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling.

In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks were detected in these rice varieties, and 91 volatile flavour substances were identified. Amongst them, 28 aldehydes (28.89~31.17%), 24 alcohols (34.85~40.52%), 14 ketones (12.26~14.74%), 12 esters (2.30~4.15%), 5 acids (7.80~10.85%), 3 furans (0.30~0.68%), 3 terpenes (0.34~0.64%), and 2 species of ethers (0.80~1.78%) were detected. SIMCA14.1 was used to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis, and some potential character markers (VIP > 1) were further screened out of the 91 flavour substances identified based on the variable important projections, including ethanol, 1-hexanol, hexanal, heptanal, nonanal, (E)-2-heptenal, octanal, trans-2-octenal, pentanal, acetone, 6-methyl-5-hepten-2-one, ethyl acetate, propyl acetate, acetic acid, and dimethyl sulphide. Based on the established fingerprint information, combined with principal component analysis and orthogonal partial least squares discriminant analysis, different rice varieties were also effectively classified, and the results of this study provide data references for the improvement in aromatic rice varieties.

[Simultaneous determination of eleven volatile components in Cinnamomi Oleum by GC-MS].

A gas chromatography-triple quadrupole mass spectrometry(GC-MS) method was established for the simultaneous determination of eleven volatile components in Cinnamomi Oleum and the chemical pattern recognition was utilized to evaluate the quality of essential oil obtained from Cinnamomi Fructus medicinal materials in various habitats. The Cinnamomi Fructus medicinal materials were treated by water distillation, analyzed using GC-MS, and detected by selective ion monitoring(SIM), and the internal standards were used for quantification. The content results of Cinnamomi Oleum from various batches were analyzed by hierarchical clustering analysis(HCA), principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) for the statistic analysis. Eleven components showed good linear relationships within their respective concentration ranges(R~2>0.999 7), with average recoveries of 92.41%-102.1% and RSD of 1.2%-3.2%(n=6). The samples were classified into three categories by HCA and PCA, and 2-nonanone was screened as a marker of variability between batches in combination with OPLS-DA. This method is specific, sensitive, simple, and accurate, and the screened components can be utilized as a basis for the quality control of Cinnamomi Oleum.

[Comparison on volatile components between Artemisiae Verlotori Folium and Artemisiae Argyi Folium based on GC-MS and chemometrics].

Artemisiae Argyi Folium is commonly used in clinical practice. Artemisiae Verlotori Folium, the dried leaves of Artemisia verlotorum, is often used as a folk substitute for Artemisiae Argyi Folium in Lingnan area. In this study, gas chromatography-triple quadrupole mass spectrometry(GC-MS) was used to detect the volatile oil components of 27 samples of Artemisiae Verlotori Folium and 13 samples of Artemisiae Argyi Folium, and the volatile components were compared between the two species. The internal standard method was combined with multi-reaction monitoring mode(MRM) to determine the content of six major volatile components. Hierarchical clustering analysis(HCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were carried out for the content data. The results showed that the Artemisiae Argyi Folium samples had higher content and more abundant volatile oils than the Artemisiae Verlotori Folium samples. Artemisiae Argyi Folium mainly had the components with lower boiling points, while Artemisiae Verlotori Folium mainly had the components with higher boiling points. Terpenoids were the main volatile components in Artemisiae Verlotori Folium(mainly sesquiterpenoids) and Artemisiae Argyi Folium(monoterpenoids). In addition, Artemisiae Argyi Folium had higher content of oxygen-containing derivatives than Artemisiae Verlotori Folium. Furthermore, the stoichiometric analysis showed that the two species could be distinguished by both HCA and OPLS-DA, indicating that the volatile components of the two were significantly different. This study can provide a scientific basis for the quality evaluation and data support for the local rational application of Artemisiae Verlotori Folium in Lingnan.

Untargeted 2D NMR Metabolomics of [13C-methyl]Methionine-Labeled Tumor Models Reveals the Non-DNA Methylome and Provides Clues to Methyl Metabolism Shift during Tumor Progression.

For more than a decade, DNA and histone methylations have been the focus of extensive work, although their relationship with methyl group metabolism was overlooked. Recently, it has emerged that epigenetic methylations are influenced by methyl donor nutrient availability, cellular levels of S-adenosyl-methionine (SAM), and cytoplasmic methyltransferase activities. SAM-dependent methyltransferases methylate a wide range of targets, from small molecules to proteins and nucleic acids. However, few investigations of the global methylome of tumors have been performed. Here, untargeted NMR metabolomics of two mouse tumor models labeled with [13C-methyl]methionine were used to search for the NMR-visible set of cellular methyl acceptors denoted the global methylome. Tumor models were B16 melanoma cell cultures and B16 melanoma tumors, which may be considered as two stages of B16 tumor development. Based on 2D 1H-13C NMR spectra and orthogonal partial least squares discriminant analysis of spectra, our study revealed markedly different global methylomes for melanoma models. The methylome of B16 melanoma cell cultures was dominated by histone methylations, whereas that of B16 melanoma tumors was dominated by cytoplasmic small-molecule methylations. Overall, the technique gave access to the non-DNA methylome. Comparison of tumor models also exhibiting differential expression of aerobic glycolysis provided clues to a methyl metabolism shift during tumor progression.

Perinatal risk factors for mortality in very preterm infants-A nationwide, population-based discriminant analysis.

AIM: To assess the strength of associations between interrelated perinatal risk factors and mortality in very preterm infants. METHODS: Information on all live-born infants delivered in Sweden at 22-31 weeks of gestational age (GA) from 2011 to 2019 was gathered from the Swedish Neonatal Quality Register, excluding infants with major malformations or not resuscitated because of anticipated poor prognosis. Twenty-seven perinatal risk factors available at birth were exposures and in-hospital mortality outcome. Orthogonal partial least squares discriminant analysis was applied to assess proximity between individual risk factors and mortality, and receiver operating characteristic (ROC) curves were used to estimate discriminant ability. RESULTS: In total, 638 of 8,396 (7.6%) infants died. Thirteen risk factors discriminated reduced mortality; the most important were higher Apgar scores at 5 and 10 min, GA and birthweight. Restricting the analysis to preterm infants <28 weeks' GA (n = 2939, 16.9% mortality) added antenatal corticosteroid therapy as significantly associated with lower mortality. The area under the ROC curve (the C-statistic) using all risk factors was 0.86, as determined after both internal and external validation. CONCLUSION: Apgar scores, gestational age and birthweight show stronger associations with mortality in very preterm infants than several other perinatal risk factors available at birth.

Advanced Glycation End-Products (AGEs) of Lysine and Effects of Anti-TCR/Anti-TNF-α Antibody-Based Therapy in the LEW.1AR1-iddm Rat, an Animal Model of Human Type 1 Diabetes.

The LEW.1AR1-iddm rat is an animal model of human type 1 diabetes (T1D). Previously, we have shown that combination with anti-TCR/anti-TNF-α antibody-based therapy re-established normoglycemia and increased proteinic arginine-dimethylation in the spleen, yet not in the pancreas. High blood glucose is often associated with elevated formation of advanced glycation end-products (AGEs) which act via their receptor (RAGE). Both anti-TCR and anti-TNF-α are inhibitors of RAGE. The aim of the present work was to investigate potential biochemical changes of anti-TCR/anti-TNF-α therapy in the LEW.1AR1-iddm rat. We determined by stable-isotope dilution gas chromatography-mass spectrometry (GC-MS) the content of free and proteinic AGEs and the Nε-monomethylation of lysine (Lys) residues in proteins of pancreas, kidney, liver, spleen and lymph nodes of normoglycemic control (ngCo, n = 6), acute diabetic (acT1D, n = 6), chronic diabetic (chT1D, n = 4), and cured (cuT1D, n = 4) rats after anti-TCR/anti-TNF-α therapy. Analyzed biomarkers included Lys and its metabolites Nε-carboxymethyl lysine (CML), furosine and Nε-monomethyl lysine (MML). Other amino acids were also determined. Statistical methods including ANOVA, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to evaluate the effects. Most statistical differences between the study groups were observed for spleen, pancreas and kidney, with liver and lymph nodes showing no such differences. In the pancreas, the groups differed with respect to proteinic furosine (p = 0.0289) and free CML (p = 0.0023). In the kidneys, the groups differed with respect to proteinic furosine (p = 0.0076) and CML (p = 0.0270). In the spleen, group differences were found for proteinic furosine (p = 0.0114) and free furosine (p = 0.0368), as well as for proteinic CML (p = 0.0502) and proteinic MML (p = 0.0191). The acT1D rats had lower furosine, CML and MML levels in the spleen than the rats in all other groups. This observation corresponds to the lower citrullination levels previously measured in these rats. PCA revealed diametric associations between PC1 and PC2 for spleen (r = -0.8271, p < 0.0001) compared to pancreas (r = 0.5805, p = 0.0073) and kidney (r = 0.8692, p < 0.0001). These findings underscore the importance of the spleen in this animal model of human T1D. OPLS-DA showed that in total sixteen amino acids differed in the experimental groups.

Analysis and Comparison of Aroma Compounds of Brown Sugar in Guangdong, Guangxi and Yunnan Using GC-O-MS.

Guangdong, Guangxi and Yunnan are the three provinces in China that yield the most brown sugar, a brown-red colored solid or powdered sugar product made from sugar cane. In the present study, the differences between odor compounds of brown sugar from Guangdong, Guangxi, and Yunnan provinces in China were compared and analyzed by gas chromatography-olfactometry-mass spectrometry (GC-O-MS). A total of 80 odor compounds, including 5 alcohols, 9 aldehydes, 8 phenols, 21 acids, 14 ketones, 5 esters, 12 pyrazines, and 6 other compounds, were detected. The fingerprint analysis of the brown sugar odor compounds showed 90% similarity, indicating a close relationship among the odor properties of brown sugar in each province. Moreover, the orthogonal partial least squares discriminant analysis (OPLS-DA) was performed to identify the compounds contributing to the volatile classification of the brown sugar from three provinces, which confirmed that OPLS-DA could be a potential tool to distinguish the brown sugar of three origins.

[Quality assessment of different forms of Cervi Cornu Pantotrichum based on content of free amino acids].

In this study, we analyzed the composition and content of 25 free amino acids in 32 batches of different forms of Cervi Cornu Pantotrichum(CCP; one-branched, two-branched, and three-branched) from 15 producing areas. The clustering analysis and orthogonal partial least squares discriminant analysis(OPLS-DA) were performed based on the content of 25 free amino acids. Potential differential metabolites were identified based on VIP value. The results showed that there were 25 free amino acids in CCP, and the average content of essential, non-essential, and total amino acids was 6.13, 32.99, and 39.12 mg·g~(-1), respectively. The clustering analysis and OPLS-DA demonstrated that 25 free amino acids had different content among the three forms of CCP, of which two-branched CCP samples were separately gathered into a group. Five differential components, including glutamic acid, tryptophan, ornithine, γ-aminobutyric acid, and hydroxylysine, were screened out as potential quality markers for the identification of different forms of CCP. This study provides a theoretical basis for the quality evaluation, processing, and utilization of different forms of CCP.

1H NMR Combined with Multivariate Statistics for Discrimination of Female and Male Flower Buds of Populus tomentosa.

1H Nuclear Magnetic Resonance (1H NMR) combined with multivariate statistics was adopted to discriminate female and male flower buds of Populus tomentosa in the study. Samples of 11 female and 16 male flower buds of P. tomentosa were collected in Beijing, China. 1H NMR spectra were acquired on a 400 MHz spectrometer. In total, 30 chemical compounds were identified with standards and literature according to chemical shifts, peak areas, and multiplicity. Principal component analysis (PCA), hierarchical clustering analysis (HCA), and supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to discriminate female and male flower buds. An apparent grouping trend (R2X, 0.809; Q2, 0.903) between female and male groups was exhibited with PCA and HCA. The two groups were also well discriminated with OPLS-DA (R2X, 0.808; R2Y, 0.976; Q2, 0.960). Combined with variable importance in projection (VIP) > 1.0 and p < 0.05 of OPLS-DA, it was found that the content of daucosterol, ß-sitosterol, ursolic acid, and betulonic acid in male group was higher than that in female, which should be the key differences of chemical constituents in female and male flower buds of P. tomentosa. The study demonstrated that 1H NMR combined with multivariate statistics could be used to discriminate female and male plants and clarify differences, which provided a novel method to identify the gender of dioecious plants.

[Research on quality difference of standard decoction of raw and fried Paeoniae Radix Alba based on fingerprint and multicomponent determination].

The extract rates, multicomponent content and fingerprint were determined in this study to investigate the quality diffe-rence between standard decoction of raw Paeoniae Radix Alba and fried Paeoniae Radix Alba. UPLC fingerprint was established for 17 batches of standard decoction of raw and fried Paeoniae Radix Alba, and the contents of gallic acid, catechin, albiflorin, paeoniflorin and benzoyl paeoniflorin were determined. The peak areas of standard decoction were analyzed by the independent t-test and orthogonal partial least squares discriminant analysis. There was no significant difference in extract rates between the standard decoction of raw and fried Paeoniae Radix Alba. After fried processing, the content of albiflorin increased by 0.26%, while the contents of gallic acid, catechin, paeoniflorin and benzoyl paeoniflorin decreased by 13.04%, 27.97%, 10.30% and 18.79% respectively. There were 14 common peaks in the fingerprint of standard decoction of raw Paeoniae Radix Alba, and 16 common peaks in the fried Paeoniae Radix Alba. Peak 1 and peak 3 were new ones after processing, among which the peak 3 was 5-hydroxymethylfurfural. The results showed that peak 1, peak 3, peak 11 and peak 15 were the key compounds to distinguish standard decoction of raw and fried Paeoniae Radix Alba. In conclusion, this method is stable and can be used for the study of quantity transfer and quality control in the preparation process of standard decoction, granules and other dosage forms for raw and fried Paeoniae Radix Alba, providing reference for the identification of raw and fried Paeoniae Radix Alba and related preparations.

Rapid and label-free screening of echinococcosis serum profiles through surface-enhanced Raman spectroscopy.

Echinococcosis is a serious zoonotic parasitic disease that could be fatal without diagnosis and treatment in a timely manner. Herein, we present a rapid and label-free method for screening of echinococcosis using surface-enhanced Raman spectroscopy (SERS). Three groups of serum SERS spectra based on porous silicon/silver composites are obtained: one group from healthy volunteers (normal, n = 163) and two other groups from patients with pathologically confirmed echinococcosis (cystic echinococcosis (CE), n = 69 and alveolar echinococcosis (AE), n = 38). The derived characteristic spectrum was analyzed to explain differences between echinococcosis and healthy volunteers and a principal component analysis (PCA) was applied for classification. Raman spectra revealed that high sensitivity and specificity for echinococcosis diagnosis were associated with the contents of phenylalanine and tyrosine. In addition, Raman spectroscopy analysis identified two metabolites including phenylalanine and carotenoids that could distinguish three types of serum. Orthogonal partial least squares discriminant analysis (OPLS-DA) was successfully used as a discriminative model to classify echinococcosis with the highest sensitivity and specificity of 100% and 98.6%, respectively. Combination of serum metabolomics with SERS enabled accurate screening of echinococcosis patients. The results indicate that SERS-based serum profile analysis has the potential to be a valuable tool for the early diagnosis and screening of echinococcosis.

[Analysis of quality difference based on Astragalus membranaceus var. mongholicus in genuine region].

This work is to establish the fingerprint of Astragalus membranaceus var. mongholicus by HPLC-ELSD method, and to analyze the simulated wildness degree of A. membranaceus var. mongholicus in the genuine region of Inner Mongolia, Ningxia and Gansu. Compared with wild A. membranaceus var. mongholicus, the quality differences of A. membranaceus var. mongholicus in the genuine region were analyzed by identification of chromatographic peaks and similarity evaluation, cluster analysis(CA), principal components analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA). HPLC fingerprints of A. membranaceus var. mongholicus in different genuine regions are established. The qualitative analysis of mass spectrometry identified 18 components. The similarity evaluation shows that the similarity of 32 batches of A. membranaceus var. mongholicus samples was 0.688-0.993. Among them, the similarity of samples in Shanxi, Inner Mongolia, Ningxia is 0.688-0.993, 0.835-0.989, 0.934-0.988, respectively and the similarity of samples in Gansu is 0.729-0.876 except No. 25 sample. The results of CA show that the samples of A. membranaceus var. mongholicus can be grouped into four categories according to the production area except the No. 11 and No. 25 samples. The results of PCA indicate that 32 batches of A. membranaceus var. mongholicus samples can be clustered according to quality and origin, and the quality of A. membranaceus var. mongholicus in Inner Mongolia is the closest to the wild breed. The results of OPLS-DA indicate that there are six components that can distinguish the wild and domestic A. membranaceus var. mongholicus, which are malonylastragaloside Ⅰ, astragaloside Ⅰ, calycosin-7-O-ß-D-glycoside-6″-O-malonate, calycosin-7-O-ß-D-glycoside, formononetin-7-O-ß-D-glycoside-6″-O-malonate, and astrapterocarpan-3-O-ß-D-glycoside-6″-O-malonate. The established method can be used to analyze differences between A. membranaceus var. mongholicus origin and planting environment, and can provide references for the protection and replacement of wild A. membranaceus var. mongholicus resources, and the cultivation, processing and production of A. membranaceus var. mongholicus.

Rapid identification and antibiotic susceptibility test of pathogens in blood based on magnetic separation and surface-enhanced Raman scattering.

An effective surface-enhanced Raman scattering (SERS) method is presented for the rapid identification and drug sensitivity analysis of pathogens in blood. In a first step, polyethyleneimine-modified magnetic microspheres (Fe3O4@PEI) were used to enrich bacteria from blood samples. Next, the Fe3O4@PEI@bacteria complex was cultured on both ordinary and drug-sensitive plates. Lastly, the SERS spectra of single colonies were acquired in order to identify different pathogens and their resistant strains by comparison with established standardized bacterial SERS spectras and orthogonal partial least squares discriminant analysis (OPLS-DA) method. Staphylococcus aureus, Acinetobacter baumannii, Pseudomonas aeruginosa and their resistant strains were used to evaluate the performance of the SERS method. The results demonstrate that the method can accurately detect and identify all the tested sensitive and drug-resistant strains of bacteria, including 77 clinical blood infection samples. The method provides a way for rapid identification and susceptibility test of pathogens, and has great potential to replace currently used time-consuming methods. Graphical abstract Schematic presentation of a method for the rapid identification and drug sensitivity analysis of pathogens in blood. It is based on a combination of magnetic separation, SERS fingerprint analysis and orthogonal partial least squares discriminant analysis (OPLS-DA).

A GC-MS Protocol for Separating Endangered and Non-endangered Pterocarpus Wood Species.

Pterocarpus santalinus and Pterocarpus tincorius are commonly used traded timber species of the genus Pterocarpus. P. santalinus has been listed in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). As a non-CITES species, P. tincorius is also indiscriminately labeled as P. santalinus due to the similar macroscopic and microscopic features with P. santalinus. In order to understand the molecular discrimination between these easily confused species, xylarium heartwoods of these two species were extracted by three different kinds of solvents and analyzed using gas chromatography⁻mass spectrometry (GC-MS). Multivariate analyses were also applied for the selection of marker compounds that are distinctive between P. santalinus and P. tincorius. A total of twenty volatile compounds were detected and tentatively identified in three kinds of extracts, and these compounds included alcohols, stilbenoids, esters, aromatic hydrocarbons, ketones, miscellaneous, phenols, and flavonoids. GC-MS analyses also revealed that extraction solvents including ethanol and water (EW), ethyl acetate (EA), and benzene⁻ethanol (BE) gave the best chemotaxonomical discrimination in the chemical components and relative contents of the two Pterocarpus species. After chemometric analyses, EW displayed higher predictive accuracy (100%) than those of EA extract (83.33%) and BE extract (83.33%). Furthermore, spathulenol (17.58 min) and pterostilbene (23.65 min) were elucidated as the critical compounds for the separation of the EW extracts of P. santalinus and P. tinctorius. Thus, a protocol of GC-MS and multivariate analyses was developed to use for successfully distinguishing P. santalinus from P. tinctorius.

The impacts of brewing in glass tumblers and thermos vacuum mugs on the aromas of green tea (Camellia sinensis).

This study investigated the effect of brewing apparatus on the aromatic feature of tea infusion. Huangshan Maofeng tea infusion was brewed under glass tumblers (GT) or thermos vacuum mugs (TVM) for up to 180 min. Tea infusion sensory attributes were evaluated using quantitative descriptive analysis and the composition of volatiles were analyzed using headspace solid phase microextraction coupled with gas chromatography-mass spectrometry. Results showed that GT tea infusion at each brewing duration possessed stronger 'Pure', 'Fresh' and 'Grassy' attributes than TVM tea infusion, whereas TVM tea infusion showed a higher intensity on 'Steamed' aroma. A total of 74 volatiles were detected in tea infusion, and aldehydes and alcohols appeared to be the major volatiles. Total aldehydes concentration percentage decreased in tea infusion with brewing process, whereas an increase on total alcohol percentage was found. Principal component analysis indicated that brewing duration and apparatus played vital roles in altering the volatile composition in tea infusion, whereas orthogonal partial least squares discriminant analysis (OPLS-DA) revealed that GT tea infusion samples were separated from TVM tea infusion samples. OPLS-DA also screened 20 volatiles that significantly contributed to the differentiation of GT and TVM tea infusion.

[HPLC-UV fingerprints and chemical pattern recognition of Ilicis Pubescentis Radix].

The present study is to establish the fingerprints for the quality evaluation of Ilicis Pubescentis Radix by HPLC-UV. The chromatographic conditions were defined as Phenomenex Luna C18(4.6 mm × 250 mm, 5 µm). Mobile phase was acetonitrile-0.05% phosphoric acid in gradient elution, and the flow rate was 0.8 mL·min⁻¹.Column temperature was 30 °C and the injection volume was 10 µL．The detection wavelength was 210 nm. According to the similarity evaluation, the chemometric method was used to assess the quality of Ilicis Pubescentis Radix. The fingerprints of 16 batches of Ilicis Pubescentis Radix were established. There were 29 common peaks in the fingerprints and 12 common peaks were identified by reference substances. Fingerprints similarity of samples were greater than 0.92. The samples were classified into three groups by hierarchical cluster analysis combined with principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA), and seven components were the main markers that cause differences in the different batches of samples. By comparing the on-line UV spectra of chromatographic peaks, the chromatographic fingerprint was divided into three regions: region A showed seventeen main peaks (mainly lignans and phenolic acids); region B showed eight main peaks, which were proved as saponins; region C showed four main peaks, which were proved as other components. The established HPLC-UV fingerprint is highly specific, and can be used to evaluate the quality consistency of different batches of Ilicis Pubescentis Radix.