A comparative study of the predictive performance of different descriptor calculation tools: Molecular-based elution order modeling and interpretation of retention mechanism for isomeric compounds from METLIN database.

In the pharmaceutical industry, the need for analytical standards is a bottleneck for comprehensive evaluation and quality control of intermediate and end products. These are complex mixtures containing structurally related molecules. In this regard, chromatographic peak annotation, especially for critical pairs of isomers and closest structural analogs, can be supported by using a Quantitative Structure Retention Relationship (QSRR) approach. In our study, we investigated the fundamental basis of the reversed-phase (RP) retention mechanism for 1141 isomeric compounds from the METLIN SMRT dataset. Nine different descriptor calculation tools combined with different feature selection methods (genetic algorithm (GA), stepwise, Boruta) and machine learning (ML) approaches (support vector machine (SVM), multiple linear regression (MLR), random forest (RF), XGBoost) were applied to provide a reliable molecular structure-based interpretation of RP retention behaviour of the isomeric compounds. Strict internal and external validation metrics were used to select models with the best predictive capabilities (rtest > 0.73, order of elution > 60 %). For the developed models, mean absolute errors were in the range of 60 to 110 s. Stepwise and GA showed the most suitable performance as descriptor selection methods, while SVM and XGBoost modeling gave satisfactory predictive characteristics in most cases. Validation performed on the published experimental data for structurally related pharmaceutical compounds confirmed the best accuracy of MLR modeling in combination with GA feature selection of general physico-chemical properties. The resulting models will be useful for the prediction of separation and identification of structurally related compounds in pharmaceutical analysis, providing a simultaneous understanding of the interaction mechanisms leading to their retention under RP conditions.

Analysis of Primary Liquid Chromatography Mass Spectrometry Data by Neural Networks for Plant Samples Classification.

Plant samples are potential sources of physiologically active secondary metabolites and their classification is an extremely important task in traditional medicine and other fields of research. In the production of herbal drugs, different plant parts of the same or related species can serve as adulterants for primary plant material. The use of highly informative and relatively easily accessible tools, such as liquid chromatography and low-resolution mass spectrometry, helps to solve these tasks by means of fingerprint analysis. In this study, to reveal specific plant part features for 20 species from one family (Apiaceae), and to preserve the maximum information content, two approaches are suggested. In both cases, minimal raw data pretreatment, including rescaling of time and m/z axes and cutting off some uninformative regions, was applied. For the support vector machine (SVM) method, tensor unfolding was required, while neural networks (NNs) were able to work directly with squared heatmaps as input data. Moreover, five data augmentation variants are proposed, to overcome the typical problem of a lack of data. As a result, a comparable F1-score close to 0.75 was achieved by SVM and two employed NN architectures. Eight marker compounds belonging to chlorophylls, lipids, and coumarin apio-glucosides were tentatively identified as characteristic of their corresponding sample groups: roots, stems, leaves, and fruits. The proposed approaches are simple, information-saving and can be applied to a broad type of tasks in metabolomics.

An application of the standardised reference extract quantification strategy in the quality control of ginseng infusions by liquid chromatography with mass spectrometric detection.

INTRODUCTION: Limited availability of individual standards is a bottleneck for quality control of functional foods and natural medicines. The use of standard mixtures or secondary standards is a possible alternative in this case. Earlier, an approach known as standardised reference extract (RE) strategy was introduced for HPLC-UV analysis of different plant materials; however, its application in HPLC-MS analysis has not been investigated. OBJECTIVE: To establish an HPLC-MS-based RE method for determination of ginsenoside content in ginseng infusions using commercially available extract reference material of Panax quinquefolius L. RESULTS: The developed HPLC-MS method was validated as precise (1.1%-9.4% intra-day variation; 1.6%-12.8% inter-day variation) and highly sensitive [limit of detection (LOD): 1-40 ng/mL; limit of quantification (LOQ): 4-120 ng/mL]. The stability of samples was satisfactory (5.7%-16.3%). The RE quantification method was compared with the external standard method, and the obtained difference was not significant, mostly in the range of 5%-10%. Matrix effects for the diluted samples of RE and ginseng infusions, determined via the standard addition method, were in the range of 85%-115% and 80%-126%, respectively, and were also positively correlated with the ginsenoside concentration. Eleven batches of ginseng infusions from different manufacturers were analysed using the established method. CONCLUSION: The method for HPLC-MS-based ginsenoside quantification using RE as a secondary standard was established for the first time. The results of this study demonstrate that the application of the standardised RE strategy in HPLC-MS can minimise the matrix effect-related error in addition to the cost-effective quality control of herbal products, foods, and traditional medicines.

Unsupervised methods in LC-MS data treatment: Application for potential chemotaxonomic markers search.

The combination of Liquid Chromatography and Mass Spectrometry (LC-MS) is commonly used to determine and characterize biologically active compounds because of its high resolution and sensitivity. In this work we explore the interpretation of LC-MS data using multivariate statistical analysis algorithms to extract useful chemical information and identify clusters of similar samples. Samples of leaves from 19 plants belonging to the Apiaceae family were analyzed in unified LC conditions by high- and low-resolution mass spectrometry in a wide range scan mode. LC-MS data preprocessing was performed followed by statistical analysis using tensor decomposition in the form of Parallel Factor Analysis (PARAFAC); matrix factorization following tensor unfolding with principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF); or unsupervised feature selection (UFS). The optimal number of components for each of these methods were found and results were compared using four different metrics: silhouette score, Davies-Bouldin index, computational time, number of noisy components. It was found that PCA, ICA and UFS give the best results across the majority of the criteria for both low- and high-resolution data. An algorithm for biomarker signal selection is suggested and 23 potential chemotaxonomic markers were tentatively identified using MS2 data. Dendrograms constructed by the methods were compared to the molecular phylogenic tree by calculating pixel-wise mean square error (MSE). Therefore, the suggested approach can support chemotaxonomic studies and yield valuable chemical information for biomarker discovery.

Estimating population-level of alcohol, tobacco and morphine use in a small Russian region using wastewater-based epidemiology.

INTRODUCTION: Alcohol, tobacco and illicit drug use combined are the largest modifiable health risk factors. Wastewater-based epidemiology (WBE) is a complementary approach for monitoring substance use in the population. In this study we applied WBE technique to a community in the Moscow region to estimate population-level consumption of alcohol, tobacco and morphine. METHODS: Wastewater sampling was carried out over 47 days, in 2018 and 2019, including the New Year period. Analysis of the samples for consumption biomarkers (ethyl sulphate, cotinine and morphine) were undertaken using liquid chromatography tandem mass spectrometry (LC-MS/MS). Daily consumption estimates were then compared with sales/production/prescription data and between different days of the week using Mann-Whitney U test. RESULTS: Alcohol consumption was significantly higher on Sundays and during the New Year and Russian Christmas period compared to weekdays and Saturdays. Tobacco consumption estimates were largely consistent throughout the week. Morphine was detected by WBE during the monitoring period but was inconsistent with prescription record data. DISCUSSION AND CONCLUSIONS: This study provides evidence for the feasibility of conducting WBE in Russia. Estimates of alcohol consumption derived from WBE were higher than average alcohol sales data for the country. The estimated consumption of nicotine is generally consistent with the production data, with estimates higher than in most other countries. Our results also suggest potential illegal use of opioids (morphine-based) in the population. Given the considerable health and economic costs of substance use in Russia, more extensive WBE testing is recommended to inform and evaluate public health policies.

A novel simple and sensitive approach for determination of 1,1-dimethylhydrazine in aqueous samples by high performance liquid chromatography with ultraviolet and tandem mass spectrometric detection after derivatization with unsubstituted aromatic aldehydes.

In this work, simple, rapid and highly sensitive method of hazardous chemical 1,1-dimethylhydrazine (unsymmetrical dimethylhydrazine, UDMH) determination based on pre-column derivatization with unsubstituted aromatic aldehydes and reversed-phase high performance liquid chromatography-ultraviolet-tandem mass spectrometry (RP HPLC-UV-MS/MS) has been developed. Along with benzaldehyde, commercially available aromatic aldehydes, namely: 2-naphthaldehyde, 2-pyridinecarboxaldehyde, and 2-quinolinecarboxaldehyde, were used as derivatizing reagents in the analysis of hydrazines for the first time. The reactions were studied in a wide pH range by varying reaction time and other conditions. A slightly alkaline pH 9 was shown to be optimal for the derivatization of UDMH by aromatic aldehydes. The quantitative yield of derivatization products under the established conditions was confirmed by HPLC analysis with amperometric detection. For all studied reagents, wide linear ranges of concentrations (0.01-1000 µg/L) in natural water samples were observed. The limits of detection for UDMH in natural water were in the 3.7-130 ng/L range. 2-Quinolinecarboxaldehyde was selected as the most appropriate reagent for HPLC-UV-MS/MS determination of UDMH. In case of using this reagent, the accuracy was in the range of 97-102%, and precision, expressed as RSD was less than 8%. The developed approach does not require laborious stages of pre-concentration and isolation of UDMH from natural water components.

Author Correction: Employing fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A new PARAFAC-based algorithm for HPLC-MS data treatment: herbal extracts identification.

INTRODUCTION: Role of highly informative high-performance liquid chromatography mass spectrometry (HPLC-MS) methods in quality control is increasing. Complex herbal products and formulations can simultaneously contain extracts from different plants. Therefore, due to the leads to lack of commercial standards it is important to develop novel approaches for comprehensive treatment of big datasets. OBJECTIVE: The aim of this study is to create a straightforward and information-saving algorithm for the identification of plants extracts in commercial products. MATERIAL AND METHODS: In total, 34 samples, including Glycyrrhiza glabra and Panax ginseng dried roots; and Abrus precatorius dried leaves, their double and triple mixtures and flavoured oolong tea samples were analysed by HPLC-MS and combined in a three-dimensional dataset (retention time-mass-to-charge ratio (m/z)-samples). This dataset was subjected to smoothing and denoising techniques and further decomposed using parallel factor analysis (PARAFAC). RESULTS: Samples were divided into eight clusters; loading matrices were interpreted and the presence of the most characteristic triterpene glycoside groups was demonstrated and supported by the characteristic chromatogram approach. The occurrence of Abrus precatorius and G. glabra additives in flavoured tea was confirmed. CONCLUSION: Developed HPLC-MS-PARAFAC method is potentially reliable and an efficient tool for handling untreated experimental data and its future development may lead to more comprehensive evaluation of chemical composition and quality control of food additives and other complex mixtures.

Manipulating selectivity of covalently-bonded hyperbranched anion exchangers toward organic acids. Part III: Effect of diamine structure in the external part of the functional layer.

The chromatographic properties of three hyperbranched anion exchangers having various diamines in the external part of the functional layer are studied in order to reveal diamine influence on selectivity toward mono- and divalent organic acids. The obtained stationary phases have the same structure of the internal part of the functional layer formed by repeating 4 modification cycles including alkylation with 1,4-butanediol diglycidyl ether (1,4-BDDGE) and amination with methylamine (MA) and differ by the structure of diamine used in the 5th modification cycle. For the first time several diamines (ethylenediamine, (2-aminoethyl)aminoethanol, and N,N'-bis(2-hydroxyethyl)ethylenediamine) are used for completing the last modification cycle in hyperbranching. The performance of three prepared anion exchangers is investigated using KOH and NaHCO3 as eluents and discussed with respect to the differences in hydrophilicity of the external part of the functional layer showing its effect on the separation of organic acids.

The comparison of retention behaviour of imidazoline and serotonin receptor ligands in non-aqueous hydrophilic interaction chromatography and supercritical fluid chromatography.

This work presents an investigation of retention characteristics of imidazoline and serotonin receptor ligands in non-aqueous hydrophilic interaction liquid chromatography (NA-HILIC) and supercritical fluid chromatography (SFC). The separation has been carried out by using methanol as a mobile phase modifier with addition of two types of additives (NH4HCOO; NH4HCOO/HCOOH) and two different stationary phases (diol; mixed-mode diol). The selectivity characteristics were observed based on S-factors, logk-logk plots and radar plots. NA-HILIC vs. SFC retention of tested compounds was also described by considering the molecular properties of the analytes within the LSER analysis. The differences between SFC vs. NA-HILIC retention of imidazoline and serotonin receptor ligands grow with the acid addition to a mobile phase, noticeably on mixed-mode diol stationary phase (S ≥ 87). In addition, the good selectivity performances of the certain NA-HILIC and SFC conditions were confirmed by good separation of structurally related compounds (α ≥ 2). The molecular basis of NA-HILIC and SFC retention were explained by using Abraham's equation. The dominant analyte descriptors influencing retention were hydrogen bonding and dipolar interactions. The current study will present the theory, and discuss the applicability within the SFC vs. NA-HILIC regimes. In this way, it was provided the placing of two relatively new methods (SFC, NA-HILIC) in the map of modern analytical chromatography in terms of the pharmaceutical analysis.

Nerve agent markers screening after accumulation in garden cress (Lepidium sativum) used as a model plant object.

In this research an accumulation of nerve agent markers in garden cress (Lepidium sativum) as a model plant object was studied using LC-QTOF hybrid system. For the determination of methylphosphonic acid and alkyl methylphosphonates, which are specific markers of sarin, soman, VR and VX, simple and sensitive approach was developed. Direct analysis of aqueous extracts on the reversed phase column with polar endcapping allowed to achieve satisfactory retention factor for methylphosphonic acid, which has high polarity and is usually very weakly retained on the ordinary reversed phase columns. Application of the QTOF mass spectrometer with high mass resolution led to the increase in the accuracy of the conducted measurements. The HPLC-HRMS technique developed exclusively for this study has been validated for linearity, limit of detection, limit of quantification, precision, accuracy and matrix effect prior to the analysis of plant extract samples. Hydroponic growth model was employed to examine accumulation of nerve agent markers in garden cress. It was found that after elimination of nerve agent markers from the plant growth medium, garden cress was able to store these substances for at least 5 weeks providing high retrospectivity of the analysis. Moreover, during the cress growth, no metabolization of alkyl methylphosphonates was observed. This allows not only to reveal the fact of nerve agents release into environment, but also to define its type after a long period of time.

Manipulating selectivity of covalently-bonded hyperbranched anion exchangers toward organic acids. Part II: Effect of mono- and dicarboxylic amino acids in the internal part of the functional layer.

Four covalently-bonded hyperbranched anion exchangers based on poly(styrene-divinylbenzene) (PS-DVB) substrate with different structure of the functional layer were prepared using mono- and dianionic amino acids such as glycine, ß-alanine, aspartic acid, and glutamic acid in the internal part of the functional layer. Selectivity of all anion exchangers toward weakly retained organic acids was investigated at different temperatures in order to evaluate the effect of the number of carboxylic groups in the functional layer and its hydrophilicity on the separation. It was found that dianionic amino acids used in the first modification cycle of hyperbranching provide the best resolution for mono- and divalent organic acids, which makes the number of carboxylic groups in the structure of amino acid a key factor in the separation of such analytes with covalently-bonded hyperbranched anion exchangers, while the role of amino acid hydrophilicity is not that significant. Stationary phases prepared using aspartic and glutamic acids provided baseline resolution for quinic, glycolic, acetic, lactic, formic, and galacturonic acids, which are not resolved to baseline with modern commercially available anion exchangers; the increase of temperature was found to be favorable for improving the resolution even further.

Manipulating selectivity of covalently-bonded hyperbranched anion exchangers toward organic acids. Part I: Influence of primary amine substituents in the internal part of the functional layer.

Three covalently-bonded poly(styrene-divinylbenzene)-based (PS-DVB) hyperbranched anion exchangers prepared using primary amines with carboxylic, sulfonic or 2-hydroxyethyl substituents in the internal part of the functional layer were studied and compared for evaluating the effect of amines substituents on the chromatographic performance of the stationary phases. The hyperbranched coating was created on the surface of aminated PS-DVB substrate by repeating the modification cycles including alkylation with 1,4-butanediol diglycidyl ether (1,4-BDDGE) and amination with primary amine; glycine, taurine (2-aminoethanesulfonic acid) or ethanolamine were used in the first cycle, and 4 more cycles were conducted with methylamine (MA). The influence of the structure and type of primary amine used in the first cycle on the retention and selectivity toward inorganic anions, short-chain carboxylic acids, and polyphosphates was investigated using hydroxide eluent. The effect of temperature on the separation of organic acids was also studied for all stationary phases, which revealed the possibility to control and improve resolution for some pairs of analytes.

Employing fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task.

A dataset of liquid chromatography-mass spectrometry measurements of medicinal plant extracts from 74 species was generated and used for training and validating plant species identification algorithms. Various strategies for data handling and feature space extraction were tested. Constrained Tucker decomposition, large-scale (more than 1500 variables) discrete Bayesian Networks and autoencoder based dimensionality reduction coupled with continuous Bayes classifier and logistic regression were optimized to achieve the best accuracy. Even with elimination of all retention time values accuracies of up to 96% and 92% were achieved on validation set for plant species and plant organ identification respectively. Benefits and drawbacks of used algortihms were discussed. Preliminary test showed that developed approaches exhibit tolerance to changes in data created by using different extraction methods and/or equipment. Dataset with more than 2200 chromatograms was published in an open repository.

Application of quantitative analysis of multi-component system approach for determination of ginsenosides in different mass-spectrometric conditions.

The lack of standard substances is a bottleneck for quality control in traditional and alternative medicine. Development of the HPLC-UV approaches combined with single standard for quantitative analysis of multi-component system (QAMS) allowed determination of several plant biomarkers by implementation of the relative response factors (RRFs). Robustness and ruggedness of such methods are commonly demonstrated by performing the analysis in changing analytical conditions on the different HPLC equipment and columns. The nature of MS detection is much more complicated and dependent on the instrumentation. Therefore, this study was conducted to justify the use of RRFs for HPLC-MS determination of bioactive compounds from plants. Protopanaxatriol (PPT), protopanaxadiol (PPD) and ocotillol (OT) ginseng saponins (ginsenosides) were successfully separated on a reversed-phase PFP-column with high group selectivity. Fragmentation patterns for these groups of compounds were established on different HPLC-ESI-MS systems and at varied declustering potentials (DPs). The use of sapogenin fragmentation ions in positive detection mode along with group reference standards was shown to be an optimal way to perform quantification. The performance of the developed group targeted HPLC-MS-QAMS approach was tested in the course of measurements conducted on the different instrumentation. The differences between QAMS and external standard method (ESM) quantification results were below 15% for all determined saponins.

Unified strategy for HPLC-MS evaluation of bioactive compounds for quality control of herbal products.

Evaluation of safety, quality and composition of herbal products and food supplements based on botanical ingredients is a matter of serious concern. For screening of botanicals in herbal products multitargeted and group-targeted approaches may be applied. In the group-targeted approach botanicals are characterized by means of an appropriate group of structurally related biomarkers compared with the multitargeted approach where a number of selected analytes are monitored based on a multiple reaction monitoring survey. In this study a unified strategy for quality control of herbal products was developed on the basis of fast ultrasound-assisted extraction, chromatographic separation and mass spectrometric quantification of bioactive compounds. A large list of unique biomarkers were monitored under almost identical chromatographic conditions, while an efficient strategy for HPLC-MS group-targeted analysis was also developed for comprehensive evaluation of chemical composition of botanicals intensively used for herbal product manufacturing. In the latter case, structurally close compounds were determined in a single ion monitoring mode for the characteristic group of fragment ions, allowing fast profiling and quality assessment of the plant material or complex food supplement. The sensitivity of the developed approaches was on the level of 1-50 ng/mL, which is higher than that of existing HPLC-UV quality control methods.

LC-MS determination of steroidal glycosides from Dioscorea deltoidea Wall cell suspension culture: Optimization of pre-LC-MS procedure parameters by Latin Square design.

In this paper, the ultrasound assisted extraction method for isolation of steroidal glycosides from D. deltoidea plant cell suspension culture with a subsequent HPLC-MS determination was developed. After the organic solvent was selected via a two-factor experiment the optimization via Latin Square 4 × 4 experimental design was carried out for the following parameters: extraction time, organic solvent concentration in extraction solution and the ratio of solvent to sample. It was also shown that the ultrasound assisted extraction method is not suitable for isolation of steroidal glycosides from the D. deltoidea plant material. The results were double-checked using the multiple successive extraction method and refluxing extraction. Optimal conditions for the extraction of steroidal glycosides by the ultrasound assisted extraction method were: extraction time, 60 min; acetonitrile (water) concentration in extraction solution, 50%; the ratio of solvent to sample, 400 mL/g. Also, the developed method was tested on D. deltoidea cell suspension cultures of different terms and conditions of cultivation. The completeness of the extraction was confirmed using the multiple successive extraction method.

Structure elucidation of sweet-tasting cycloartane-type saponins from ginseng oolong tea and Abrus precatorius L. leaves.

The composition of ginseng oolong a widely used tea product was investigated. A new sweet-tasting cycloartane-type saponin 3ß-O-[ß-D-glucuronopyranosyl(1→2)]-ß-D-6-acetylglucopyranosyl)-(20S,22S)-3ß,22-dihydroxy-9,19-cyclolanost-24-en-26,29-oic acid (9), along with five new compounds, was identified in the methanolic extract of the ginseng oolong tea. Structural elucidation was conducted by spectroscopic methods, including 1D- and 2D-NMR, HR-MS, HPLC-LITMS/MS. It was shown that these compounds have different sugar chains connected to the abrusogenin molecule. Then saponin profiles of four commercially available ginseng oolong samples and Abrus precatorius L. leaves were compared and the presence of three known abrusosides and six new acetyl and malonyl abrusogenin derivatives was proved. The original ginsenosides were not detected in the extract, therefore, abrusosides could serve as a replacement responsible for the sweet taste of the tea.

Rapid IC-MS/MS determination of methylphosphonic acid in urine of rats exposed to organophosphorus nerve agents.

A direct approach for the determination of a specific hydrolysis product of organophosphorus nerve agents such as methylphosphonic acid (MPA) in urine by ion chromatography and tandem mass spectrometry (IC-MS/MS) has been developed. The first advantage of the proposed approach is a rapid and simple sample preparation, which does not require a large sample volume, complicated and laborious preconcentration and derivatization steps, and takes less than 7min per sample. The second advantage is the fast and selective IC determination of MPA carried out on a noncommercial anion exchanger based on a poly(styrene-co-divinylbenzene) (PS-DVB) substrate with a high degree of crosslinking and a covalently-bonded branched functional layer, which enables complete resolution of MPA from major urine matrix components and allows one to overcome matrix effects. Hyphenation of IC with tandem mass spectrometry results in highly sensitive and reliable MPA determination with the lowest detection limit (4ngmL-1) reported so far for HPLC determination of MPA in urine. The proposed approach is successfully applied for the analysis of urine from rats exposed to nonlethal doses of organophosphorus nerve agents such as sarin, soman, and VR in up to 13days after initial exposure, which shows the possibility to verify the nerve agent exposure after a long period of time.

Anion exchangers with negatively charged functionalities in hyperbranched ion-exchange layers for ion chromatography.

Novel pellicular poly(styrene-divinylbenzene)-based (PS-DVB) anion exchangers with covalently-bonded hyperbranched functional ion-exchange layers containing negatively charged functionalities are obtained and examined. The hyperbranched coating is created on the surface of aminated PS-DVB substrate by repeating the modification cycles including alkylation with 1,4-butanediol diglycidyl ether (1,4-BDDGE), and amination of the terminal epoxide rings with methylamine (MA) or glycine (Gly). The influence of the position and the number of the layers with glycine, as well as of the total number of the layers of amine in the coating on the chromatographic properties of the obtained stationary phases is investigated. Chromatographic performance of the obtained stationary phases is evaluated using the model mixtures of inorganic and organic anions with hydroxide eluent. It is shown that the best selectivity toward weakly retained organic acids and oxyhalides is possessed by the anion exchanger obtained after 5 modification cycles, with glycine being used in the first one. Such anion exchanger packed in 25-cm long column is capable of separating 22 anions in 58min including 7 standard anions, mono-, di- and trivalent organic acids, oxyhalides, and some other double- and triple-charged anions.