Characterization of Pleural Mesothelioma by Hierarchical Clustering Analyses Using Immune Cells within Tumor Microenvironment

INTRODUCTION

Over the past decade, classifications using immune cell infiltration have been applied to many types of tumors; however, mesotheliomas have been less frequently evaluated.

METHODS

In this study, 60 well-characterized pleural mesotheliomas (PMs) were evaluated immunohistochemically for the characteristics of immune cells within tumor microenvironment (TME) using 10 immunohistochemical markers: CD3, CD4, CD8, CD56, CD68, CD163, FOXP3, CD27, PD-1, and TIM-3. For further characterization of PMs, hierarchical clustering analyses using these 10 markers were performed.

RESULTS

Among the immune cell markers, CD3 (p < 0.0001), CD4 (p = 0.0016), CD8 (p = 0.00094), CD163+ (p = 0.042), and FOXP3+ (p = 0.025) were significantly associated with an unfavorable clinical outcome. Immune checkpoint receptor expressions on tumor-infiltrating lymphocytes such as PD-1 (p = 0.050), CD27 (p = 0.014), and TIM-3 (p = 0.0098) were also associated with unfavorable survival. Hierarchical clustering analyses identified three groups showing specific characteristics and significant associations with patient survival (p = 0.016): the highest number of immune cells (ICHigh); the lowest number of immune cells, especially CD8+ and CD163+ cells (ICLow); and intermediate number of immune cells (ICInt). ICHigh tumors showed significantly higher expression of PD-L1 (p = 0.00038). Cox proportional hazard model identified ICHigh [hazard ratio (HR) = 2.90] and ICInt (HR = 2.97) as potential risk factors compared with ICLow. Tumor CD47 (HR = 2.36), tumor CD70 (HR = 3.04), and tumor PD-L1 (HR = 3.21) expressions were also identified as potential risk factors for PM patients.

CONCLUSION

Our findings indicate immune checkpoint and/or immune cell-targeting therapies against CD70-CD27 and/or CD47-SIRPA axes may be applied for PM patients in combination with PD-L1-PD-1 targeting therapies in accordance with their tumor immune microenvironment characteristics.

Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning

Urban rainfall events can lead to the runoff of pollutants, including industrial, pesticide, and pharmaceutical chemicals. Transporting micropollutants (MPs) into water systems can harm both human health and aquatic species. Therefore, it is necessary to investigate the dynamics of MPs during rainfall events. However, few studies have examined MPs during rainfall events due to the high analytical expenses and extensive spatiotemporal variability. Few studies have investigated the occurrence patterns of MPs and factors that influence their transport, such as rainfall duration, antecedent dry periods, and variations in streamflow. Moreover, while there have been many analyses of nutrients, suspended solids, and heavy metals during the first flush effect (FFE), studies on the transport of MPs during FFE are insufficient. This study aimed to identify the dynamics of MPs and FFE in an urban catchment, using high-resolution monitoring and machine learning methods. Hierarchical clustering analysis and partial least squares regression (PLSR) were implemented to estimate the similarity between each MP and identify the factors influencing their transport during rainfall events. Eleven dominant MPs comprised 75% of the total MP concentration and had a 100% detection frequency. During rainfall events, pesticides and pharmaceutical MPs showed a higher FFE than industrial MPs. Moreover, the initial 30% of the runoff volume contained 78.0% of pesticide and 50.1% of pharmaceutical substances for events W1 (July 5 to July 6, 2021) and W6 (August 31 to September 1, 2021), respectively. The PLSR model suggested that stormflow (m³/s) and the duration of antecedent dry hours (h) significantly influenced MP dynamics, yielding the variable importance on projection scores greater than 1.0. Hence, our findings indicate that MPs in urban waters should be managed by considering FFE.

Chemometric-Based Analysis of Metabolomics Studies of Bioactive Fractions of Pleurotus osteratus and Their Correlation with In Vitro Anti-Cancer Activity

Richness in nutrients with an ample of the myco-bioactive molecules makes Pleurotus osteratus preferential mushroom. In this paper, we conducted a preliminary study on bio-assay-guided fractionation of dichloromethane:ethanol crude extract (1:1, v/v) of P. osteratus (CD) against human breast cancer cell line (MDA-MB-231). Later, CD and its potent hexane (H) and ethyl acetate (EA) fraction were screened against a panel of a human cancer cell lines. H fraction possesses higher cytotoxicity followed by EA and CD. Literature review revealed that polyphenol and ergosterol are the biomarkers found in P. osteratus and could responsible for its cytotoxic potential. Accordingly, hyphenated liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based polyphenol and ergosterol-targeted myco-metabolite profiling of CD, H, and EA fractions were carried out. Despite being significantly rich in polyphenol and ergosterol content, EA fraction showed moderate cytotoxicity. Considering this, liquid chromatography-hybrid quadrupole time-of-flight mass spectrometry (LC-QTOF/MS)-based untargeted myco-metabolite profiling of CD, H and EA fractions was further conducted to identify a new biomarker. Tentatively, 20 myco-metabolites were identified, belonging to the class of steroids, alkaloid, terpenoid, fatty alcohol, and polyketide. The myco-metabolite variabilities among potent samples in correlation to their in vitro anti-cancer activity was explored using the different chemometric tools: principal component analysis (PCA), hierarchical clustering analysis (HCA), and partial least square (PLS). A probable synergistic action among identified myco-metabolites (betulin, solanocapsine, ophiobolin F, linoleoyl ethanolamide, (13R,14R)-7-labdene-13,14,15-triol, asterosterol, cholest-5-ene, (3b,6b,8a,12a)-8,12-epoxy-7(11)-eremophilene-6,8,12-trimethoxy-3-ol, beta-obscurine, myxalamid B, momordol, and avocadyne 4-acetate) may be responsible for the observed cytotoxicity potential of H fraction of P. osteratus.

Leveraging single-cell Raman spectroscopy and single-cell sorting for the detection and identification of yeast infections

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics.

Clustering of Chromatin Remodeling Enzymes Predicts Prognosis and Clinical Benefit of Therapeutic Strategy in Pancreatic Cancer

In recent years, translational research and pharmacological targeting of epigenetic modifications have become the focus of personalized therapy for patients with pancreatic cancer. Preclinical and clinical trials targeting post-translational modifications have been evaluated as monotherapy or in combination with standard chemotherapy. In this study, we selected 43 genes from seven families of chromatin-modifying enzymes and investigated the influences of epigenetic modifications and their interactions on pancreatic ductal adenocarcinoma (PDAC) using hierarchical clustering analysis. Our analysis also evaluated their effects on treatment modalities and regimens of chemotherapy for PDAC. RNA-seq data for a total of 177 patients with pancreatic cancer, obtained from The Cancer Genome Atlas database, were analyzed. Our results suggested that high-risk patients of survival significant chromatin remodeling-associated gene cluster (gene cluster 2), composed of histone methyltransferases, histone acetyltransferases, histone deacetylases, histone demethylases, and 10-11 translocation family, demonstrated inferior progression-free survival and overall survival in patients with PDAC, especially in men. Our novel biomarker, survival significant chromatin remodeling-associated gene cluster, showed superior prediction performance compared with the conventional TNM system. Overall, these findings suggest that epigenetic modifications and interactions play an important role in the prognosis and therapeutic response of patients with PDAC.

Heavy metal accumulation and health risk assessment of crayfish in the middle and lower reaches of Yangtze River during 2015-2017

This study performed statistical analysis and risk assessment of five heavy metals (As, Cd, Cr, Hg, Pb) in crayfish samples collected from six provinces in the middle and lower reaches of Yangtze River during 2015-2017. The Spearman correlation test and the results of hierarchical cluster analysis (HCA) indicated that As, Pb, and Cd in crayfish were significantly correlated, and the results of HCA showed that Jiangxi, Jiangsu, and Zhejiang were clustered into one group; Hubei, Hunan, and Anhui were clustered into another group; and provinces in the same group had spatial similarities in heavy metals. The pollution index (PI) values of five heavy metals in all provinces were below 1, implying that crayfish samples in this area were not highly contaminated. The target hazard quotient (THQ) values of five heavy metals were mainly below 1 except Hg in Anhui (2.9709), which was far beyond 1, indicating that the health risk posed by Hg exposure should not be ignored in Anhui.

Proteome analysis of response to different spectral light irradiation in Synechocystis sp. PCC 6803

In cyanobacteria, it is known that the excitation ratios of photosystem (PS) I and PSII changes with the wavelength of irradiated light due to mobile phycobilisome (PBS) and spillover, affecting the photosynthetic ATP/NADPH synthesis ratio and metabolic flux state. However, the mechanisms by which these changes are controlled have not been well studied. In this study, we performed a targeted proteomic analysis of Synechocystis sp. PCC 6803 under different spectral light conditions to clarify the regulation mechanisms of mobile PBS, spillover and metabolisms under different light qualities at the protein level. The results showed an increase in the amount of proteins mainly involved in CO₂ fixation under Red1 light conditions with a high specific growth rate, suggesting that the rate of intracellular metabolism is controlled by the rate of carbon uptake, not by changes in the amount of each enzyme. Correlation analysis between protein levels and PSI/PSII excitation ratios revealed that PsbQUY showed high correlations and significantly increased under Blue and Red2 light conditions, where the PSI/PSII excitation ratio was higher due to spillover. In the strains lacking the genes encoding these proteins, a decrease in the PSI/PSII excitation ratio was observed, suggesting that PsbQUY contribute to spillover occurrence. SIGNIFICANCE: In cyanobacteria, the photosynthetic apparatus's responses, such as state transition [mobile PBS and spillover], occur due to the intensity and wavelength of irradiated light, resulting in changes in photosynthetic electron transport and metabolic flux states. Previous studies have analyzed the response of Synechocystis sp. PCC 6803 to light intensity from various directions, but only spectroscopic analysis of the photosynthetic apparatus has been done on the response to changes in the wavelength of irradiated light. This study analyzed the response mechanisms of mobile PBS, spillover, photosynthetic, and metabolic systems in Synechocystis sp. PCC 6803 under six different spectral light conditions by a targeted proteomic analysis. As a result, many proteins were successfully quantified, and the metabolic enzymes and photosynthetic apparatus were analyzed using an integrated approach. Principal component and correlation analyses and volcano plots revealed that the PSII subunits PsbQ, PsbU, and PsbY have a strong correlation with the PSI/PSII excitation ratio and contribute to spillover occurrence. Thus, statistical analysis based on proteome data revealed that PsbQ, PsbU, and PsbY are involved in spillover, as revealed by spectroscopic analysis.

Aquatic toxicity (Pre)screening strategy for structurally diverse chemicals: global or local classification tree models?

With an ever-increasing number of synthetic chemicals being manufactured, it is unrealistic to expect that they will all be subjected to comprehensive and effective risk assessment. A shift from conventional animal testing to computer-aided methods is therefore an important step towards advancing the environmental risk assessments of chemicals. The aims of this study are two-fold: firstly, it examines the relationships between structural and physicochemical features of a diverse set of organic chemicals, and their acute aquatic toxicity towards Daphnia magna and Oryzias latipes using a classification tree approach. Secondly, it compares the efficiency and accuracy of the predictions of two modeling schemes: local models that are inherently restricted to a smaller subset of structurally-related substances, and a global model that covers a wider chemical space and a number of modes of toxic action. The classification tree-based models differentiate the organic chemicals into either 'highly toxic' or 'low to non-toxic' classes, based on internal and external validation criteria. These mechanistically-driven models, which demonstrate good performance, reveal that the key factors driving acute aquatic toxicity are lipophilicity, electrophilic reactivity, molecular polarizability and size. A comparative analysis of the performance of the two modeling schemes indicates that the local models, trained on homogeneous data sets, are less error prone, and therefore superior to the global model. Although the global models showed worse performance metrics compared to the local ones, their applicability domain is much wider, thereby significantly increasing their usefulness in practical applications for regulatory purposes. This demonstrates their advantage over local models and shows they are an invaluable tool for modeling heterogeneous chemical data sets.

Effects of climatic and social factors on dispersal strategies of alien species across China

Determination of dispersal strategies of alien species and its relationship with social and climatic factors are essential to understand the mechanisms of species invasion and adaption. Based on morphological trait, dispersal mode, and dispersal agent of diaspore of 562 alien species across China, we determined: (i) the proportions of five dispersal strategies (i.e., autochory, anemochory, hydrochory, zoochory, and anthropochory), (ii) the relationships between the dispersal strategies and socio-climatic factors in 34 administrative regions across China, and (iii) the correlations between different dispersal strategies. Anthropochory, zoochory, and anemochory account for nearly 90.0% of all the dispersal strategies of alien species. Mean frost days (MFD), mean annual humidity (MAH), and gross domestic product (GDP) were the main climatic and social factors that were correlated to different dispersal strategies. Zoochory was positively related to MFD, but negatively related to the autochory and anthropochory. MAH negatively influenced the anemochory, while GDP positively influenced the hydrochory. We classified the six dispersal strategies into two groups based on the correlations among dispersal strategies, group I included autochory and anthropochory, and group II included anemochory, hydrochory, and zoochory. Within a group, dispersal strategies were positively correlated, while between groups, dispersal strategies were negatively correlated. Positive correlation between different strategies might be co-owned while negative correlation between different strategies might not be co-owned by one alien species. Understanding the characteristics of the dispersal strategies of alien species is important for policy makers when controlling the dispersal of malignant invasive alien species, predicting the distribution, and decreasing or cutting off the dispersal pathways of invasive alien species.

Comparative analysis of the main active constituents from different parts of Leonurus japonicus Houtt. and from different regions in China by ultra-high performance liquid chromatography with triple quadrupole tandem mass spectrometry

A rapid, sensitive and convenient analytical method of ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC-QTRAP®/MS²) was proposed for the simultaneous determination of characteristic alkaline and acidic components covering many structure types including alkaloids, phenolic acids, phenylpropanoids and flavonoids in Leonurus japonicus Houtt. (LJ). The proposed method was first reported and validated by assessing the matrix effects, linearity, limit of detections, limit of quantifications, precision, repeatability, stability and recovery of target components. The developed UPLC-QTRAP®/MS² was successfully applied to simultaneously determine all target compounds in 38 batches of LJ from 11 different producing regions in China and five organs (including root, caulis, branch, flower and leaf) of LJ from the same stand planting base in Jiangsu Province (China). The result showed that LJ in different regions with different geographical position would affect the accumulation of different compounds, and the significant discrepancies of some target compounds were also observed in different organs of LJ due to different biosynthetic pathway and enzymes in different organs. Furthermore, both hierarchical clustering analysis and principal components analysis were performed to classify the 38 batches of LJ samples from different producing regions on the basis of target compounds. As a result, the samples could be mainly clustered into different groups, which were similar with areas classification. Overall, the presented method would be helpful for the comprehensive utilization and development of LJ resources.

Quality consistency evaluation of Kudiezi Injection based on multivariate statistical analysis of the multidimensional chromatographic fingerprint

Traditional Chinese Medicine Injection (TCMI) was restricted due to the batch-to-batch variability caused by the variable compositions of botanical raw materials and complexities of the current manufacturing process. To evaluate and control the quality of Kudiezi Injection (KDZI), a comprehensive and practical method based on multidimensional chromatographic fingerprint associated with multivariate statistical analysis was proposed. The multidimensional chromatographic fingerprint was established by integrating three kinds of chromatographic fingerprints, including High Performance Liquid Chromatography-Ultraviolet spectrum (HPLC-UV), Gas Chromatography-Mass Spectrometer (GC-MS) and High performance ion-exchange chromatography (HPIEC), which were used to detect flavones, nucleosides, organic acids, amino acids and saccharides in KDZI. In addition, four main multivariate statistical analyses were compared to assess the batch-to-batch consistency of samples. Results showed that the cosine method, which has been widely used in the quality evaluation of TCM, failed to distinguish the differences among batches based on neither chromatographic peaks' area nor contents information. t-test and Bayes' theorem could reveal the content difference among batches, while hierarchical clustering analysis could differentiate KDZI batches, and Luteolin-7-O-β-D-glucuronopyranoside, Tau, Ser, guanine and allose were the main indicators. In conclusion, multidimensional chromatographic fingerprints could reflect the quality information of KDZI comprehensively and hierarchical clustering analysis was suitable to identify the differences among batches. This could provide an integrated method for consistency evaluation of TCMI, process improvement of TCMI and solving similar problems in TCMI.

Flavonoids rather than alkaloids as the diagnostic constituents to distinguish Sophorae Flavescentis Radix from Sophorae Tonkinensis Radix et Rhizoma: an HPLC fingerprint study

Sophorae Flavescentis Radix (Sophora flavescens Ait., SFR) and Sophorae Tonkinensis Radix et Rhizoma (S. tonkinensis Gapnep., STR) are two commonly used traditional Chinese medicines from Sophora (Leguminosae) plants, which are believed to possess similar bioactive components with entirely different clinical applications. In order to find out the characteristic chemical constituents potentially leading to the unique medicinal properties claimed for each of the two closely related TCMs, an HPLC fingerprint method was developed for analyses of the alkaloid and flavonoid constituents of SFR and STR, respectively, which were further evaluated and compared through similarity calculation and hierarchical clustering analysis (HCA). The results from the present study showed that the alkaloid fingerprints of the two herbs were similar, with many components co-existing in both drugs and various batches of samples from different species being mixed together in the HCA dendrogram. However, their flavonoid constituents were totally different with specific fingerprints being yielded for each herb, and further HCA analysis showed that the tested samples could almost be clearly divided into two groups based on their origins of species. The results from the present study indicated that the flavonoid constituents could serve as the differentially diagnostic constituents of SFR and STR and might potentially attributed to their distinct therapeutic effects.

Screening optimal substrates from Erhai lakeside for Ottelia acuminata (Gagnep.) Dandy, an endangered submerged macrophyte in China

Because of the unstable hydrodynamic conditions in the wild, the endangered aquatic plant should be cultivated first in constructed wetlands for the protection and expansion of germplasm resources. Ottelia acuminata (Gagnep.) Dandy has become extinct in Erhai Lake, Yunnan province, China. In order to optimize substrates for this species to artificial cultivation, the native substrate (sandy soils) and the other three representative ones (red paddy soils, alluvial paddy soils, and purple paddy soils) collected from Erhai lakeside were applied to cultivate O. acuminata for 50 days. Multi indicators, such as antioxidant enzymes activity, malondialdehyde and chlorophyll-α concentration, and relative growth rate of O. acuminata, were discussed and statistically analyzed to classify the substrates. The results suggested that even disregarding the physiology significance of these indicators, hierarchical clustering analysis had high efficiency on optimizing substrates. Although various single indexes suggested different optimal substrates for macrophyte growth, red paddy soil was never excluded out the optimal substrate classes. Further study is needed to assess the substrates optimization functionalities of these indicators. This study offers amounts of physiology data and an effective method to optimize substrates of O. acuminata. It is helpful for environmental scientists and ecological engineers to conduct the similar study on endangered species.

Targeted and untargeted-metabolite profiling to track the compositional integrity of ginger during processing using digitally-enhanced HPTLC pattern recognition analysis

Tracking the impact of commonly applied post-harvesting and industrial processing practices on the compositional integrity of ginger rhizome was implemented in this work. Untargeted metabolite profiling was performed using digitally-enhanced HPTLC method where the chromatographic fingerprints were extracted using ImageJ software then analysed with multivariate Principal Component Analysis (PCA) for pattern recognition. A targeted approach was applied using a new, validated, simple and fast HPTLC image analysis method for simultaneous quantification of the officially recognized markers 6-, 8-, 10-gingerol and 6-shogaol in conjunction with chemometric Hierarchical Clustering Analysis (HCA). The results of both targeted and untargeted metabolite profiling revealed that peeling, drying in addition to storage employed during processing have a great influence on ginger chemo-profile, the different forms of processed ginger shouldn't be used interchangeably. Moreover, it deemed necessary to consider the holistic metabolic profile for comprehensive evaluation of ginger during processing.

A colorimetric sensor array based on sulfuric acid assisted KMnO4 fading for the detection and identification of pesticides

Pesticides play a critical role in improving crop yield in modern agriculture, but their residues significantly harm the environment and human health. Herein, a novel and simple colorimetric sensor array built on sulfuric acid assisted KMnO₄ fading strategy has been developed for pesticides detection and discrimination. This sensor array is facilely fabricated by KMnO₄ and sulfuric acid through simply adjusting their concentrations and ratios. Hierarchical clustering analysis (HCA) demonstrates that the as-fabricated colorimetric sensor array has a high dimensionality, and shows excellent capability to recognize common kinds of pesticides from potential interferants. Semi-quantitative detection was achieved through combining HCA and corresponding fitting curves. Moreover, the proposed sensor array was successfully applied to detect pesticide residues (e.g. carbaryl) in real samples. The strategy described herein will not only "maximally" simplify the design and fabrication approach, but expand the application fields of colorimetric sensor array methodology towards weak-reactive analytes.

Utilizing Direct Analysis in Real Time-High Resolution Mass Spectrometry-Derived Dark Matter Spectra to Classify and Identify Unknown Synthetic Cathinones

Herein we describe a new method of statistical analysis processing of direct analysis in real time-high resolution mass spectrometry-derived neutral loss spectra of synthetic cathinones. The dark matter observed under collision-induced dissociation conditions is rendered as "neutral loss spectra," and these are subsequently subjected to statistical analysis processing, specifically hierarchical clustering analysis. The resulting hierarchical clustering dendrogram provides a means by which to classify an unknown as a member of a subgroup of cathinones, based on structural similarity of its backbone to that of the scaffolds of the drugs represented in the training set. The described method can be utilized for the classification and identification of a number of classes of psychoactive compounds.

Metabolite profiles of essential oils and molecular markers analysis to explore the biodiversity of Ferula communis: Towards conservation of the endemic giant fennel

Giant fennel (Ferula communis L.) is well known in folk medicine for the treatment of various organ disorders. The biological importance of members of genus Ferula prompted us to investigate the leaves of the endangered Tunisian medicinal plant F. communis L. not previously investigated. An estimate of genetic diversity and differentiation between genotypes of breeding germplasm is of key importance for its improvement. Thus, four F. communis populations were RAPD fingerprinted (63 RAPD markers generated by 7 primers) and the composition of their leaf essential oils (EO) (134 EO compounds) was characterized by GC-MS. Cluster analysis based on the leaf volatiles chemical composition of F. communis accessions defined three chemotypes according to main compounds have been distinguished: α-eudesmol/β-eudesmol/γ-terpinene; α-eudesmol/α-pinene/caryophyllene oxide and chamazulene/α-humulene chemotypes. A high genetic diversity within population and high genetic differentiation among them, based on RAPDs, were revealed (H(pop)=0.320 and GST=0.288) caused both by the habitat fragmentation, the low size of most populations and the low level of gene flow among them. The RAPD dendrogram showed separation of three groups. Populations dominated by individuals from the β-eudesmol/γ-terpinene; chemotype showed the lowest gene diversity (H=0.104), while populations with exclusively α-pinene/caryophyllene oxide chemotype showed the highest value (H=0.285). The UPGMA dendrogram and PCA analysis based on volatiles yielded higher separation among populations, indicated specific adaptation of populations to the local environments. Correlation analysis showed a non-significant association between the distance matrices based on the genetic markers (RAPD) and chemical compounds of essential oil (P>0.05) indicating no influence of genetic background on the observed chemical profiles. These results reinforce the use of both volatile compounds and RAPD markers as a starting point for in situ conservation. The analysis of chemical constitution of oil of the populations from a specific region revealed predominance of specific constituents indicating possibility of their collection/selection for specific end uses like phytomedicines. Sufficient molecular and biochemical diversity detected among natural populations of this species will form the basis for the future improvement. The correlation between matrices of RAPD and essential oils was not significant. The conservation strategies of populations should be made according to their level of genetic and chemical diversity in relation to geographic location of populations. Our results give some insights into the characterization of this as yet little investigated plant.

Determination of Ruscogenin in Ophiopogonis Radix by High-performance Liquid Chromatography-evaporative Light Scattering Detector Coupled with Hierarchical Clustering Analysis

Background:

Ophiopogonis Radix is a famous traditional Chinese medicine. It is necessary to establish a suitable quality control methods of Ophiopogonis Radix.

Objective:

To investigate the quality control methods of Ophiopogonis Radix by high-performance liquid chromatography (HPLC) coupled with evaporative light scattering detector (ELSD).

Materials and Methods:

A rapid and simple method, HPLC coupled with ELSD, was applied to determinate ruscogenin in 35 batches of Ophiopogenis Radix samples. Orthogonal tests and single factor explorations were used to optimize the extraction condition of ruscogenin. The content of ruscogenin in different origin was further analyzed by hierarchical clustering analysis (HCA).

Results:

The ruscogenin was successfully determined by HPLC-ELSD with a two-phase solvent system composed of methanol-water (88:12) at a flow rate 1.0 ml/min, column temperature maintained at 25°C, detector draft tube temperature at 42.2°C, nebulizer gas flow rate at 1.4 L/min, and the gain at 8. The result showed the good linearity of ruscogenin in the range of 40.20–804.00 μg/ml (R² = 0.9996). Average of recovery was 101.3% (relative standard deviation = 1.59%). A significant difference of ruscogenin content was shown among 35 batches of Ophiopogenis Radix from different origin, varied from 0.0035% to 0.0240%. HCA based on the content of ruscogenin indicated that Ophiopogonis Radix in different origin was mainly divided into two clusters.

Conclusion:

This simple, rapid, low-cost, and reliable HPLC-ELSD method could be suitable for measurement of ruscogenin content rations and quality control of Ophiopogonis Radix.

SUMMARY

Ophiopogonis Radix is an important Traditional Chinese Medicine (TCM) to treat and prevent cardiovascular diseases and acute or chronic inflammation for thousands of years. Steroidal saponins were known as the dominant active components for their significant cardiovascular activity, and the most steroid sapogenin of them is ruscogenin. Therefore, ruscogenin was chosen as the marker component for evaluating the quality of Ophiopongonis Radix. This study focused on establishing a stable, low-cost, simple and practical method of HPLC-ELSD to determine the ruscogenin content, and 35 batches of samples of Ophiopogonis Radix were determined. Meanwhile, these results were analyzed by hierarchical clustering analysis and the methodology validation was based on USP34-NF-29 <1225>. Results showed that this analysis method was simple and stable, which would provide an important reference to establish the quality control methodology for other herb preparations and formulas containing Ophiopogonis Radix.

In situ detection of histone variants and modifications in mouse brain using imaging mass spectrometry

Histone posttranslational modifications and histone variants control the epigenetic regulation of gene expression and affect a wide variety of biological processes. A complex pattern of such modifications and variants defines the identity of cells within complex organ systems and can therefore be used to characterize cells at a molecular level. However, their detection and identification in situ has been limited so far due to lack of specificity, selectivity, and availability of antihistone antibodies. Here, we describe a novel MALDI imaging MS based workflow, which enables us to detect and characterize histones by their intact mass and their correlation with cytological properties of the tissue using novel statistical and image analysis tools. The workflow allows us to characterize the in situ distribution of the major histone variants and their modification in the mouse brain. This new analysis tool is particularly useful for the investigation of expression patterns of the linker histone H1 variants for which suitable antibodies are so far not available.

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting.