Composition Analysis and Pharmacological Activity of Avocado/Soybean Unsaponifiable Products Used in the Treatment of Osteoarthritis

Objective: Avocado/soybean unsaponifiables (ASUs) are commonly used to treat OA symptoms. However, there are many ASU mixtures on the market with differing compositions and pharmacological activities. This study aimed to compare the composition and pharmacological activity of seven commercially available ASU products on human osteoarthritis chondrocytes.Methods: The contents of the lipidic part of ASUs were characterized by gas chromatography analysis using a VARIAN 3400 chromatograph. The pharmacological activity of the ASU products was tested on human osteoarthritis chondrocytes cultured in alginate beads. Their effects were evaluated on aggrecan, interleukin (IL)-6 and -8, and matrix metalloproteases (MMP)-3 using immunoassays and on nitric oxide through measurement of nitrite via spectrometry.Results: PIASCLEDINE-ExpASU® showed a specific profile with the presence of chromatographic peaks corresponding to an alkyl furan fraction and alkyl triols. PIASCLEDINE-ExpASU®, Persemax, Insaponifiable 300, Arthrocen, and Arthocare contained quantifiable amounts of tocopherol, while tocopherol was undetectable in Avovida and Saponic. Squalene was found only in PIASCLEDINE-ExpASU®. The abundance of sterols varied depending on the product. PIASCLEDINE-ExpASU® was the most active of the tested ASU products in inhibiting nitric oxide, IL-6, and IL-8 production by chondrocytes. With the exception of Saponic and Persemax, all the ASU mixtures either slightly or significantly increased aggrecan production. MMP-3 levels were significantly decreased by Insaponifiable 300 and PIASCLEDINE-ExpASU® and significantly increased by Saponic.Conclusion: The composition of PIASCLEDINE-ExpASU® is different to that of the other evaluated ASU mixtures. This specific composition explains its better pharmacological activity, including the higher inhibitory effect on pro-inflammatory and pro-catabolic factors. Our findings are helpful in providing a basis for understanding the symptomatic effect of PIASCLEDINE-ExpASU® in patients with osteoarthritis.

Correlation Between Quality and Geographical Origins of Leonuri Herba Revealed By the Qualitative Fingerprint Profiling and Quantitative Determination of Chemical Components

BackgroundLeonuri Herba (Yimucao) is a very commonly Chinese herbs for treating menstrual and maternal diseases for thousands of years in China. However, the herb collected in different origins was easily found in the markets which induce the unstable quality for clinic use. In this study, a comprehensive strategy of using multiple chromatographic analysis and chemometric analysis was firstly investigated for chemical discrimination of Leonuri Herba from different geographical origins.MethodsUHPLC-QTOF-MS/MS was applied to identify the peaks of Leonuri Herba and chemical fingerprints were established in 30 batches from different geographical origins. Meanwhile, dissimilarities of chemical compositions among different origins were further investigated by principal component analysis and cluster analysis.ResultsA total of 49 chromatographic peaks of Leonuri Herba were unequivocally or tentatively identified by UHPLC-QTOF-MS/MS. Leonuri Herba were classified into four categories, and eight major compounds detected could be used as chemical markers for discrimination. Also, the eight components, including leonurine, 4',5-dihydroxy-7-methoxyflavone, rutin, hyperoside, apigenin, quercetin, kaempferol and salicylic acid, were simultaneously quantified using the extracting ion mode of UHPLC-QTOF-MS/MS.ConclusionThis systematic information could ensure Leonuri Herba with well-controlled quality and safe use in clinic. This study could also provide a research model for further study of other Chinese Materia Medica.

Degradation of vancomycin in external quality assessment samples is a factor to underestimate its concentration

Aim: To compare the difference between the measured and target values in vancomycin external quality assessment (EQA) samples and to investigate the factors for underestimating its concentration. Materials & methods: A retrospective analysis of 195 international vancomycin EQA results was performed. Deviations of the concentrations determined by TDx fluorescence polarization immunoassay (FPIA), Axsym FPIA and Architect chemiluminescence microparticle immunoassay (CMIA) method were -2.43, -16.28 and -10.53%, respectively. Chromatographic peaks of the crystalling degradation products appeared in samples with large deviations. Vancomycin were degraded after long-term transporting and high temperature. Conclusion: Vancomycin concentrations measured by Axsym FPIA and Architect CMIA methods were likely to be underestimated. Long-term transporting resulted in low EQA results, suggesting that establishing a local EQA system for vancomycin is essential.

Effect of Environmental Factors on Plectranthus Neochilus Volatile Composition: A GC-MS-Based Metabolomics Approach

Plectranthus neochilus Schltr. is an aromatic species, commonly used for digestive, antispasmodic, and analgesic purposes. Although many studies have reported the chemical composition of its essential oil, variations in the volatile profile were observed, which may be due to multiple factors linked to growth and field conditions. In order to detect metabolic variations in this species, we employed a GC-MS-based untargeted metabolomics approach analyzing samples of four P. neochilus individuals collected over a year. From all analyses, 24 mass features were detected and 21 were identified according to their respective chromatographic peaks. All features varied among samples, particularly (2E)-hexenal, 3-octanone and δ-3-carene, which showed the highest coefficient of variation percentage in our study. Although the four individuals presented the same peaks in the chromatograms, significant differences in the intensity of specific mass features were detected between individuals throughout the year. Time of sampling did not affect P. neochilus volatile composition; the chemical profile remained constant throughout the day. Seasonal trends were observed for the species. Winter months coincided with a drop in the intensity of most components. Air temperature showed a positive correlation with some feature intensities, while myrcene and α-thujene resulted in a positive and a negative correlation with rainfall, respectively. This study was the first attempt to correlate metabolic variation and environmental factors in P. neochilus. Our approach was successful in identifying the composition and variation of the headspace volatiles of P. neochilus leaves.

Application of carbon monolith based on exfoliated graphite for sorption and subsequent chromatographic determination of volatile organic compounds in soil air

The possibility of using a new graphene-based carbon monolith for searching new oil deposits or branches adjacent to the already registered oilfields by areal geochemical survey is demonstrated. The material has been developed at the Faculty of Chemistry of M. V. Lomonosov Moscow State University. Sorption of volatile organic compounds (VOCs) from soil air at the oilfield was carried out using two sorbents (carbon adsorbent and Tenax-TA traditionally used for such analyses) with subsequent determination by gas chromatography with mass spectrometric detection and thermal desorption as a way of sample injection (TD/GC/MS). The new material absorbs more hydrocarbons (n-alkanes and monoaromatics) in the range from C8 to C16 than Tenax-TA, the intensities of the chromatographic peaks of the compounds also being higher. The phenomenon of irreversible sorption from carbon materials is observed for VOCs from C17 and more. However, the concentration of such substances in the soil air is rather low due to the low pressure of saturated vapors of these compounds under normal conditions. Hence, the chromatogram of carbon monolith reflects the macro-characteristics of this oil deposit better than Tenax-TA. To increase the sensitivity of the determination, a preliminary optimization of thermal desorption conditions was carried out. The values of the helium flow rate through the sorbent sample and the desorption time of the compounds are chosen to get the largest peak area. The regeneration of sorbent samples is carried out to provide the possibility of their reusage. Tenax-TA decomposes at lower temperatures compared to carbon sorbent and thus cannot be purified completely unlike the new monolith. The graphene-based sorbent is reusable and much cheaper in the manufacture than imported polymer Tenax-TA since it is made of domestic materials.

Resolving of Overlapping Asymmetrical Chromatographic Peaks by Using Wavelet-Transform and Gram-Charlier Peak Model

The paper describes a method for resolving overlapping asymmetric peaks that make up a chromatogram. The presented method uses the Gram-Charlier model in the form of the first three terms of the Gram-Charlier series as a basis. Using the wavelet transform, the parameters of this model are determined, which is used to describe a single or overlapping chromatographic peak. Hermitian wavelets of the first four orders are used in the computation of the wavelet transform. To speed up the computation of multiple wavelet transforms, the possibility of coding a signal using the Chebyshev-Hermite functions is considered in order to further restore the set of wavelet transforms simultaneously. According to the presented method, the parameters of the peaks are determined by analytical expressions without using the numerical approximation of the chromatogram by the peak model, which avoids the disadvantages of the numerical approach. The resulting method is used to resolve overlapping asymmetric peaks. The advantage of the method over others is shown by calculating the area of each of the resolved peaks.

Hepatoprotective Constituents of Total Dibenzocyclooctadiene Lignans from Schisandra chinensis Based on the Spectrum-Effect Relationship

To scientifically clarify the hepatoprotective constituents of Fructus Schizandrae chinensis, eleven batches samples of total dibenzocyclooctadiene lignans (TDL) from Schisandra chinensis were prepared by using the optimum extraction technique. Characteristic high-performance liquid chromatography (HPLC) chromatograms were obtained through HPLC analysis technology, and the hepatoprotective effects of the eleven batches of TDL were evaluated by MTT assay. Based on the chemical and biological activity results, the spectrum-effect relationship between the characteristic HPLC fingerprints and the hepatoprotective effect of TDL was established using Minitab 16.0 data analysis software. On the basis of the spectrum-effect relationship, thirteen compounds (1–13) were obtained from the TDL by chemical natural product chemical separation and purification technology, and their structures were identified on the basis of the spectral data and the literature. Based on these compounds, thirteen common peaks among the thirty-three chromatographic peaks in the above HPLC fingerprints were identified. Our findings showed that some components, including, schisandrin B (2), schisandrin A (3), and schisandrol B (7) had significant roles in promoting hepatoprotective activity. Preliminary verification of the spectrum-effect relationship of TDL from S. chinensis was carried out, and the results confirmed that the activity of a composite of these three key components in optimal ratios was better than that of any individual compound, which potentially confirmed the reliability of the spectrum-effect relationship and the synergistic effects of traditional Chinese medicine.

PeakBot: Machine learning based chromatographic peak picking

MotivationChromatographic peak picking is among the first steps in software pipelines for processing LC-HRMS datasets in untargeted metabolomics applications. Its performance is crucial for the holistic detection of all metabolic features as well as their relative quantification for statistical analysis and metabolite identification. Unfortunately, random noise, non-baseline separated compounds and unspecific background signals complicate this task.ResultsA machine-learning framework entitled PeakBot was developed for detecting chromatographic peaks in LC-HRMS profile-mode data. It first detects all local signal maxima in a chromatogram, which are then extracted as super-sampled standardized areas (retention time vs. m/z). These are subsequently inspected by a custom-trained convolutional neural network that forms the basis of PeakBot’s architecture. The model reports if the respective local maximum is the apex of a chromatographic peak or not as well as its peak center and bounding box.In independent training and validation datasets used for development, PeakBot achieved a high performance with respect to discriminating between chromatographic peaks and background signals (F1 score of 0.99). A comparison of different sets of reference features showed that at least 100 reference features (including isotopologs) should be provided to achieve high-quality results for detecting new chromatographic peaks.PeakBot is implemented in Python (3.8) and uses the TensorFlow (2.4.1) package for machine-learning related tasks. It has been tested on Linux and Windows OSs.AvailabilityThe framework is available free of charge for non-commercial use (CC BY-NC-SA). It is available at https://github.com/christophuv/[email protected] informationSupplementary data are available at Bioinformatics online.

Iterative Multivariate Peaks Fitting—A Robust Approach for The Analysis of Non-baseline Resolved Chromatographic Peaks

Selectivity in separation science is defined as the extent to which a method can determine the target analyte free of interference. It is the backbone of any method and can be enhanced at various steps, including sample preparation, separation optimization and detection. Significant improvement in selectivity can also be achieved in the data analysis step with the mathematical treatment of the signals. In this manuscript, we present a new approach that uses mathematical functions to model chromatographic peaks. However, unlike classical peak fitting approaches where the fitting parameters are optimized with a single profile (one-way data), the parameters are optimized over multiple profiles (two-way data). Thus, it allows high confidence and robustness. Furthermore, an iterative approach where the number of peaks is increased at each step until convergence is developed in this manuscript. It is demonstrated with simulated and real data that this algorithm is: (1) capable of mathematically separating each component with minimal user input and (2) that the peak areas can be accurately measured even with resolution as low as 0.5 if the peak’s intensities does not differ by more than a factor 10. This was conclusively demonstrated with the quantification of diterpene esters in standard mixtures.

Multiple Chromatographic Analysis of Urine in the Detection of Bladder Cancer

Bladder cancer (BC) is the most common type of carcinoma of the urological system. Recently, there has been an increasing interest in non-invasive diagnostic tumor markers due to the invasive attribute of cystoscopy, which is still considered the gold standard diagnostic method. However, markers published in the literature so far do not meet expectations for replacing cystoscopy due to their low specificity and excessively high false-positive results, which can be mainly caused by frequently occurring hematuria also in benign cases. No reliable non-invasive method has yet been identified that can distinguish patients with bladder cancer and non-malignant hematuria patients. Our work examined the possibilities of non-targeted biomarkers of urine to distinguish patients with malignant and non-malignant diseases of the bladder using 3D HPLC in combination with computer processing of multiple datasets. Urine samples from 47 patients, 23 patients with bladder cancer (BC) and 24 patients with non-malignant hematuria (NMHU), were enrolled in clinical trials. For the separation and subsequent analysis of a large number of urine components, 3D HPLC (high-performance liquid chromatography) with an absorption and fluorescence detector was used. The obtained dataset was further subjected to various uni- and multi-dimensional statistical analyses and mathematical modeling. We found 334 chromatographic peaks, of which 18 peaks were identified as significantly different for BC and NMHU patients. Using receiver operating characteristic (ROC) analysis, we assessed the informative ability of significant chromatographic peaks (90% sensitivity and 74% specificity). By logistic regression, we identified the optimal and simplified set of seven chromatographic peaks (5 absorptions plus 2 fluorescence) with strong classification power (100% sensitivity and 100% specificity) for distinguishing patients with bladder cancer and those with non-malignant hematuria. Partial least square discriminant analysis (PLS-DA) model and orthogonal projection to latent structure discriminant analysis (OPLS-DA) with 100% sensitivity and 96% specificity were used to distinguish BC and NMHU patients. Multivariate statistical analysis of urinary metabolomic profiles of patients revealed that BC patients can be discriminated from NMHU patients and the results can likely contribute to an early and non-invasive diagnosis of BC.