Chromatographic separation techniques and data handling methods for herbal fingerprints: A review

Transferability of global retention models in reversed-phase liquid chromatography for natural products

Considerable progress has been made in enhancing resolution in reversed-phase liquid chromatography for the analysis of complex samples, particularly within the field of natural products, through the application of global retention models using multi-linear gradients. Global models effectively differentiate solute retention effects from those originating from the column and solvent, offering predictive capabilities comparable to conventional individual retention models, without the requirement for standards for all compounds. While conventional individual models result in higher accuracy, they frequently demand standards that are unavailable for natural product samples. Moreover, the creation of individual models can be time-consuming due to the need for repetitive work for additional compounds. Experimental validation of global models has demonstrated that the accuracy is enough for the prediction of complex chromatograms. Through a carefully designed experimental work, this study reports the correct determination of global parameters for column and solvent, with excellent consistency across various medicinal plant samples. The successful transfer of predictions and optimisation of resolution across diverse plant species (lemon balm, peppermint, and pennyroyal) is confirmed. This highlights the applicability of predictions using global models across botanical varieties.

Comprehensive evaluation and screening of phytochemical compounds and their hypolipidemic activities of lotus leaf based on HPLC-Q-TOF-MS and spectral-effect analysis

This study aimed to identify and quantify the primary components in lotus leaf and to explore the hypolipidemic components through spectral-effect relationships and chemometric methods. Utilizing a data-dependent acquisition-diagnostic fragment ion/characteristic neutral loss screening strategy (DFI-NLS), a reliable HPLC-Q-TOF-MS analysis was conducted, identifying 77 compounds, including 36 flavonoids, 21 alkaloids, 3 terpenoids, 11 organic acids, 4 phenols, 1 lignin and 1 unsaturated hydrocarbon. A straightforward HPLC-DAD method was developed for the simultaneous determination of seven major components in lotus leaf, and quercetin-3-O-glucuronide (Q3GA) was identified as the most abundant component. The HPLC fingerprints of 36 lotus leaf sample batches were assessed using chemometric approaches such as principal component analysis and hierarchical cluster analysis. The hypolipidemic effect of these samples was analyzed by measuring total cholesterol (TC) and total triglycerides (TG) levels in palmitic acid (PA) and oleic acid (OA)-induced lipid modeling in HepG-2 cells, employing partial least squares regression and grey relation analysis to investigate the spectral-effect relationship of the lotus leaf. The in vivo hypolipidemic effect of these compounds was assessed using an egg yolk powder-induced high-fat zebrafish model. The findings indicated that peak No.11 (Q3GA) in the chemical fingerprint was significantly associated with hypolipidemic activity, suggesting it as a potential hypolipidemic compound in lotus leaf. In summary, this study facilitates the exploration of the phytochemical compounds and their bioactive properties in the lotus leaf.

Performance of global retention models in the optimisation of the liquid chromatographic separation (II): Complex multi-analyte samples

BACKGROUND

Enhancing the quality control of medicinal plants is a complex challenge due to their rich variety of chemical compounds present at varying and extreme concentrations. Chromatographic fingerprints, which have become essential for characterising these complex natural materials, require achieving optimal separation conditions to effectively maximise the number of detected peaks. The challenges in optimising fingerprints and other complex multi-analyte samples include the unavailability of standards, the presence of unknown constituents and the substantial workload that would require conventional optimisation methods based on models.

RESULTS

This work introduces an interpretive optimisation approach which operates on the premise of predicting chromatograms using global models. Initially, a multi-linear gradient experimental design is sequentially executed to accommodate all peaks in the chromatogram in an adequate time window. Following this, a small set of sample peaks (reference peaks) is selected based on their consistent traceability across all chromatograms in the design. Using this reference dataset, a global model is constructed, initially focused solely on the reference peaks and later extended to encompass all detected peaks in the sample. The aim is to find gradients that maximise resolution while minimising analysis time. These optimised gradients are applied successfully to enhance the separation of medicinal plant extracts, with particular emphasis on peppermint and pennyroyal extracts.

SIGNIFICANCE

The proposed optimisation relying on global models can be applied to highly complex samples even in the absence of standards, or in cases where standards are available but their use is impractical due to workload constraints. Moreover, in discerning the most promising gradients for highly complex samples, peak purity has demonstrated superior reliability and competitiveness compared to peak capacity as chromatographic objective function.

Analysis and classification of tea varieties using high-performance liquid chromatography and global retention models

As a result of their metabolic processes, medicinal plants produce bioactive molecules with significant implications for human health, used directly for treatment or for pharmaceutical development. Chromatographic fingerprints with solvent gradients authenticate and categorise medicinal plants by capturing chemical diversity. This work focuses on optimising tea sample analysis in HPLC, using a model-based approach without requiring standards. Predicting the gradient profile effects on full signals was the basis to identify optimal separation conditions. Global models characterised retention and bandwidth for 14 peaks in the chromatograms across varied elution conditions, facilitating resolution optimisation of 63 peaks, covering 99.95 % of total peak area. The identified optimal gradient was applied to classify 40 samples representing six tea varieties. Matrices of baseline-corrected signals, elution bands, and band ratios, were evaluated to select the best dataset. Principal Component Analysis (PCA), k-means clustering, and Partial Least Squares-Discriminant Analysis (PLS-DA) assessed classification feasibility. Classification limitations were found reasonable due to tea processing complexities, involving drying and fermentation influenced by environmental conditions.

Post-collection purity correction for internal standard correction-high performance liquid chromatography-quantitative nuclear magnetic resonance

Quantitative nuclear magnetic resonance (qNMR) has a potential risk of inaccurate quantification of complex organic compounds with low purity due to incomplete separation of the impurity signals and the target component signals. The high performance liquid chromatography-qNMR (HPLC-qNMR) method removes impurities from the sample by HPLC and accurately determines the purity of the sample by qNMR, avoiding the laborious, time-consuming, and costly step of qualitative and quantitative determination of impurities in conventional mass balance methods. An improved method, named post-collection purity correction for internal standard correction-HPLC-qNMR (ISC-HPLC-qNMR), was developed and demonstrated on a complex compound oxytetracycline with low purity. In this method, a correction factor was introduced to compensate for the inability to achieve 100% purity through the HPLC purification procedure. The purity value with standard deviation of the oxytetracycline study material using this method was 82.00% ± 0.82%, while that obtained from the conventional qNMR with deconvolution was 81.70% ± 0.35%. The consistency of these results demonstrated that the improved method extends the applicability to the samples where HPLC is not capable of purifying complex compounds with low purity to near 100%, especially containing highly similar structural-related impurities. Furthermore, this method allows purification and quantification without the need to identify impurities in the sample, resulting in significant savings of time and cost. Additionally, it effectively compensates for the limitations of qNMR deconvolution in handling peak overlap in the sample.

A comparative metabolomics analysis of Açaí (Euterpe oleracea Mart.) fruit, food powder, and botanical dietary supplement extracts

INTRODUCTION

Euterpe oleracea Mart. (açaí) is a botanical of interest to many who seek functional foods that provide antioxidant and anti-inflammatory properties. Cancer patients are increasingly taking botanical dietary supplements containing açaí to complement their conventional therapeutics, which may lead to serious adverse events. Before testing our açaí extracts in vitro for botanical-drug interactions, the goal is to chemically characterize our extracts for compounds whose biological activity in açaí is unknown.

OBJECTIVE

The objective of this work was to develop a chemical fingerprinting method for untargeted characterization of açaí samples from a variety of sources, including food products and botanical dietary supplement capsules, made with multiple extraction solvents.

METHODS

An optimized LC-MS method was generated for in-depth untargeted fingerprinting of chemical constituents in açaí extracts. Statistical analysis models were used to describe relationships between the açaí extracts based on molecular features found in both positive and negative mode ESI.

RESULTS

In an attempt to elucidate the differences in metabolites among açaí extracts from different cultivars, we identified or tentatively identified 173 metabolites from the 16 extracts made from 6 different sources. Of these compounds, there are 138 reported in açaí for the first time. Statistical models showed similar yet distinct differences between the extracts tested based on the polarity of compounds present and the origin of the source material.

CONCLUSION

A high-resolution mass spectrometry method was generated that allowed us to greatly characterize 16 complex extracts made from different sources of açaí with different extraction solvent polarities.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques

INTRODUCTION

Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools.

OBJECTIVES

The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources.

METHODS

The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar."

RESULTS

An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds.

CONCLUSION

Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Magnetic materials as adsorbents for the pre-concentration and separation of active ingredients from herbal medicine

Herbal medicine (HM) is crucial in disease management and contains complex compounds with few active pharmacological ingredients, presenting challenges in quality control of raw materials and formulations. Effective separation, identification, and analysis of active components are vital for HM efficacy. Traditional methods like liquid-liquid extraction and solid-phase extraction are time-consuming and environmentally concerning, with limitations such as sorbent issues, pressure, and clogging. Magnetic solid-phase extraction uses magnetic sorbents for targeted analyte separation and enrichment, offering rapid, pressure-free separation. However, inorganic magnetic particles' aggregation and oxidation, as well as lack of selectivity, have led to the use of various coatings and modifications to enhance specificity and selectivity for complex herbal samples. This review delves into magnetic composites in HM pretreatment, specifically focusing on encapsulated or modified magnetic nanoparticles and materials like silica, ionic liquids, graphene family derivatives, carbon nanotubes, metal-organic frameworks, covalent organic frameworks, and molecularly imprinted polymers.

Systematic review on fingerprinting development to determine adulteration of Chinese herbal medicines

BACKGROUND

It has been a current research hospots using fingerprinting technology for quality control of Chinese herbal medicines (CHMs), which provides a scientific basis for establishment of overall quality control in accordance with the characteristics of CHMs. The fingerprinting technology for CHMs is diverse, and the research field covers many disciplines, such as analytical chemistry, pharmacology, pharmaceutics, biochemistry, and molecular biology.

PURPOSE

To effectively understand the key areas and future directions of research regarding the fingerprint and adulteration of CHMs.

METHODS/RESULTS

this paper analyzed 879 articles in this field in the Web of Science Core Collection from 2000 to 2023 with CiteSpace and VOSviewer, and systematically assessed the research process, hotspots, topic distribution among disciplines, etc. The most prominent contributors of fingerprint and adulteration of CHMs research are mainly from China, India, the United States, England, and Brazil. The knowledge domains of fingerprint and adulteration of CHMs research focus mainly on the topics of molecular authentication, DNA barcoding, HPLC, near-infrared spectroscopy, manage data, chemometrics, and electrochemical fingerprinting. Most countries have recognized the pharmaceutical potential of natural products, and have paid more attention to the fingerprint and adulteration of CHMs in the past decade. Future the research tends to focus more on molecular identification and authentication, and electrochemical and chromatographic fingerprinting in controlling the adulteration of CHMs.

CONCLUSION

This research provides a valuable reference for scholars in related fields to analyze existing research results, understand the development trend, and explore new research directions.

Strategies for the quality control of Chrysanthemi Flos: Rapid quantification and end-to-end fingerprint conversion based on FT-NIR spectroscopy

INTRODUCTION

Chrysanthemi Flos (CF) is widely used as a natural medicine or tea. Due to its diverse cultivation regions, CF exhibits varying quality. Therefore, the quality and swiftness in evaluation holds paramount significance for CF.

OBJECTIVE

The aim of the study was to construct a comprehensive evaluation strategy for assessing CF quality using HPLC, near-infrared (NIR) spectroscopy, and chemometrics, which included the rapid quantification analyses of chemical components and the Fourier transform (FT)-NIR to HPLC conversion of fingerprints.

MATERIALS AND METHODS

A total of 145 CF samples were utilised for data collection via NIR spectroscopy and HPLC. The partial least squares regression (PLSR) models were optimised using various spectral preprocessing and variable selection methods to predict the chemical composition content in CF. Both direct standardisation (DS) and PLSR algorithms were employed to establish the fingerprint conversion model from the FT-NIR spectrum to HPLC, and the model's performance was assessed through similarity and cluster analysis.

RESULTS

The optimised PLSR quantitative models can effectively predict the content of eight chemical components in CF. Both DS and PLSR algorithms achieve the calibration conversion of CF fingerprints from FT-NIR to HPLC, and the predicted and measured HPLC fingerprints are highly similar. Notably, the best model relies on CF powder FT-NIR spectra and DS algorithm [root mean square error of prediction (RMSEP) = 2.7590, R2 = 0.8558]. A high average similarity (0.9184) prevails between predicted and measured fingerprints of test set samples, and the results of the clustering analysis exhibit a high level of consistency.

CONCLUSION

This comprehensive strategy provides a novel and dependable approach for the rapid quality evaluation of CF.

Application of PLS-NN model based on mid-infrared spectroscopy in the origin identification of Cornus officinalis

Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of Cornus officinalis samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, F1-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of Cornus officinalis with an accuracy of 91.9%.

Applying a risk assessment guided evaluation for verifying comprehensive two-dimensional gas chromatography to analyse complex pharmaceuticals

The reliability of analytical results is critical and indispensable when applied in regulated environments such as the pharmaceutical industry. Therefore, analytical workflows must be validated. However, validation guidelines are often designed for quantitative targeted analysis and rarely apply to qualitative untargeted approaches. In this study, we employ a risk assessment approach to identify critical parameters which might influence the qualitative results derived by online derivatisation - comprehensive two-dimensional gas chromatography coupled to a high-resolution time-of-flight mass spectrometer (GC × GC-HR-ToF-MS) for the analysis of the active pharmaceutical ingredient (API) sodium bituminosulfonate (SBS). To show the complexity and feasibility of such an approach, we focus on investigating three potential risk factors: sample preparation, vapourability, and the thermal stability of sulfonates. Through the individual evaluation of these potential risk factors due to the application of sample preparation approaches and thermal gravimetric analysis (TGA), we demonstrate the high derivatisation efficiency and repeatability of the online derivatisation method and confirm the absence of derivatisation-induced side reactions. In addition, we also show the potential thermal instability of an incompletely derivatised API. To address the limitation of these individual assessments, we applied a holistic evaluation step with negative electrospray ionisation Fourier transform ion cyclotron resonance mass spectrometry (ESI( -) FT-ICR MS) as an orthogonal technique. This confirms that most of the API is detected via the presented GC-based method. Thereby, we demonstrated the practical feasibility of the risk assessment-based approach to ensure the validity of the qualitative data for a complex untargeted method.

Spectrum-Effect Relationship in Chinese Herbal Medicine: Current Status and Future Perspectives

The quality of Chinese herbal medicine (CHM) directly impacts clinical efficacy and safety. Fingerprint technology is an internationally recognized method for evaluating the quality of CHM. However, the existing quality evaluation models based on fingerprint technology have blocked the ability to assess the internal quality of CHM and cannot comprehensively reflect the correlation between pharmacodynamic information and active constituents. Through mathematical methods, a connection between the "Spectrum" (fingerprint) and the "Effect" (pharmacodynamic data) was established to conduct a spectrum-effect relationship (SER) of CHM to unravel the active component information associated with the pharmacodynamic activity. Consequently, SER can efficiently address the limitations of the segmentation of chemical components and pharmacodynamic effect in CHM and further improve the quality evaluation of CHM. This review focuses on the recent research progress of SER in the field of CHM, including the establishment of fingerprint, the selection of data analysis methods, and their recent applications in the field of CHM. Various advanced fingerprint techniques are introduced, followed by the data analysis methods used in recent years are summarized. Finally, the applications of SER based on different research subjects are described in detail. In addition, the advantages of combining SER with other data are discussed through practical applications, and the research on SER is summarized and prospected. This review proves the validity and development potential of the SER and provides a reference for the development and application of quality evaluation methods for CHM.

A global meta-analysis of phthalate esters in drinking water sources and associated health risks

Phthalate esters (PAEs) are known as esters of phthalic acid, which are commonly used as plasticizers in the plastic industry. Due to the lack of chemical bonding with the polymer matrix, these compounds are easily separated from plastic products and enter the environment. To investigate the growth of concentration of PAEs like DBP (Dibutyl phthalate), DEP (Diethyl phthalate), DMP (Dimethyl phthalate), DIBP (Diisobutyl phthalate), and TPMBP (tris(2-methylbutyl) phosphate) in different water sources, a study from January 01, 1976, to April 30, 2021, was implemented via a global systematic review plus meta-analysis in which, 109 articles comprising 4061 samples, 4 water types, and 27 countries were included. Between various types of water sources, river water and lake water were the most contaminated resources with PAEs. Among all studies of PAEs, DBP and DEP with the values >15,573 mg L-1 have the highest average concentration and TPMBP with the value 0.002885 mg L-1 has the lowest average concentration in water sources. The most contaminated water sources with PAEs were in Nigeria and the least contaminated was in China. Besides, Monte-Carlo simulation indicated that for DMP and DEP minimum values that are lower than the acceptable limit are generated. However, most of the population (>75 %) is at risk for both adults and child cases. For DIBP and DBP the situation is much worse, the simulations not providing at least one case where the R index is lower than the acceptable limit of 1E-06.

Qualitative identification and quantitative comparison of Physochlainae Radix from different regions based on chemometric methods

Physochlainae Radix (PR) is an essential herbal medicine that has been generally applied for treating cough and asthma. In this study, a comprehensive strategy for quality evaluation of PR from different origins was established by integrating qualitative identification, quantitative analysis, and chemometric methods. A total of 58 chemical components were identified by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS/MS), and a sensitive and rapid UHPLC-QqQ-MS/MS method was established for the simultaneous determination of 12 compounds. In addition, multivariate statistical analysis was applied for discriminant analysis to compare the differences among 30 batches of PR samples. The results showed that the 30 batches of PR collected from four provinces could be clustered into three categories, in which scoparone, protocatechuic acid, tropic acid, and scopolin were important components to distinguish the primary and non-primary producing areas, as well as superior and inferior products of PR. Chemometric results were consistent and validated each other, and systematically explained the intrinsic quality characteristics of PR. This study first demonstrated that LC-MS combined with multivariate statistical analysis, provided a comprehensive and effective means for quality evaluation of PR.

Quality control for a traditional Chinese medicine, Millettia speciosa Champ, using ultra-high-performance liquid chromatography fingerprint, serum pharmacochemistry and network pharmacology

Millettia speciosa (M. speciosa) Champ (MSC) is a healthy food type with medicinal and edible homology, which is now considered a clinically significant anti-rheumatoid arthritis medicine. However, there is currently no standardized or generally accepted research strategy by which we can assess M. speciosa. Thus, it is essential to develop novel theories, strategies and evaluation methods for the scientific quality control of M. speciosa. Herein, our use ultra-high-performance liquid chromatography (UPLC)-MS/MS analysis identified 12 common bioactive components absorbed into MSC serum. Next, network pharmacology analysis exhibited that 5 MSC components may be those active components in treating rheumatoid arthritis and may be considered potential quality markers. These 5 components were then quantified using a fast UPLC approach, based on the quality marker of measurability, showing that lenticin can be regarded as the MSC quality marker. The cumulative study findings, based on systematic assessment of chemical composition both in vivo and in vitro, and the potential efficacy of M. speciosa, provide a novel approach for M. speciosa quality control.

Spectrum-Effect Relationships as an Effective Approach for Quality Control of Natural Products: A Review

As natural products with biological activity, the quality of traditional Chinese medicines (TCM) is the key to their clinical application. Fingerprints based on the types and contents of chemical components in TCM are an internationally recognized quality evaluation method but ignore the correlation between chemical components and efficacy. Through chemometric methods, the fingerprints represented by the chemical components of TCM were correlated with its pharmacodynamic activity results to obtain the spectrum-effect relationships of TCM, which can reveal the pharmacodynamic components information related to the pharmacodynamic activity and solve the limitations of segmentation of chemical components and pharmacodynamic research in TCM. In the 20th anniversary of the proposed spectrum-effect relationships, this paper reviews its research progress in the field of TCM, including the establishment of fingerprints, pharmacodynamic evaluation methods, chemometric methods and their practical applications in the field of TCM. Furthermore, the new strategy of spectrum-effect relationships research in recent years was also discussed, and the application prospects of this technology were discussed.

Use of Secondary Metabolites Profiling and Antioxidant Activity to Unravel the Differences between Two Species of Nettle

In recent years, the interest in natural remedies has increased, so it is important to analyze the plants widely distributed in nature but whose composition is little known. The main objective of the present work is to obtain information based on the profiles of secondary metabolites and antioxidant activity in Lamium album, a very widespread but little studied plant, with the aim of revealing the differences compared to Urtica dioica. First, the optimization of enzymatic extraction assisted by ultrasound was carried out by the Box-Behnken method. The optimized parameters were: concentration of the enzyme-3.3% cellulase, temperature-55 °C, and the extraction time-40.00 min. The efficiency was estimated based on the content of iridoids, the main class of secondary metabolites from Lamium album. Second, the secondary metabolites profiles of the nettle extracts were obtained by thin-layer chromatography using both normal and reverse phases and by RP-UHPLC. The antioxidant activity was evaluated using DPPH and ABTS+ radicals. The obtained results revealed significant differences between the two nettle species, both in terms of the phytochemical compounds, as well as the antioxidant activity, confirming the fact that Lamium album has a high potential to be used in phytomedicine.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

Isolation, development and validation of HPTLC method for the estimation of β-carotene from Gymnosporia senegalensis (Lam.) Loes

The present study is aimed to isolate terpenoids from Gymnosporia senegalensis through analytical and preparative thin-layer chromatography (TLC) and to determine their antioxidant activity using the 2, 2-diphenyl-1- picrylhydrazyl (DPPH) assay and to find out the presence of β-carotene through high-performance thin-layer chromatography (HPTLC). The validation included linearity, limit of detection (LOD), limit of quantification (LOQ), specificity, precision, recovery, and robustness. All the isolated compounds from TLC exhibited significant antioxidant activity. Among all, isolated compounds from leaf showed highest IC50 values. The highest total terpenoid content (TTC) was found 51.6 ± 0.06 in stem, then 49.02 ± 0.01 in bark, and 46.27 ± 0.01 in leaf. DPPH results indicated that leaf-isolated compound 1 (LIC1) showed the highest IC50 at 7.55 ± 0.02 and stem-isolated compound 2 (SIC2) showed the lowest IC50 at 0.616 ± 0.01 among all the isolated compounds of G. senegalensis. HPTLC separation was carried out on aluminium plates pre-coated with silica gel 60 F254 as the stationary phase and n-hexane: ethyl acetate (6:4, v/v) as the mobile phase. Quantification was achieved based on a densitometric analysis of β-carotene in the concentration range of 100-500 ng/band at 254 nm. For the calibration plots, linear regression produced r2 = 0.96450 and Rf = 0.27. The LOD and LOQ were 10.15 and 30.76 ng/mL for HPTLC and relative standard deviation were 137.26 ± 2.03 and 160.43 ± 2.95 (intra-day) and 127.88 ± 2.14 and 157.27 ± 1.90 (inter-day) for 200 and 400 ng/band, respectively. The present study shows the presence of various types of terpenoids through TLC whereas the HPTLC results indicated that the developed methods were accurate and precise. It also shows that the approach is appropriate for its intended use in routine quality control testing of commercially available tablet formulations and drug assay to assist both industries and researchers in making important decisions at a reasonable cost. Moreover, due to the use of a safer and more environmentally friendly mobile phase in comparison to the toxic mobile phases used in recent analytical techniques to estimate β-carotene, this methodology is also secure and sustainable.

Chemical fingerprint analysis and quality assessment of Tibetan medicine Triphala from different origins by high-performance liquid chromatography

INTRODUCTION

Although the Tibetan medicine Triphala (THL) is widely used in many countries, insufficient progress has been made in quality control.

OBJECTIVES

The present study aimed to propose a methodology for quality control of THL based on HPLC fingerprinting combined with an orthogonal array design.

METHODS

Seven identified peaks were used as indicators to examine the effects of temperature, extraction time, and solid-liquid ratio on the dissolution of active ingredients in THL. Fingerprint analysis was performed on 20 batches of THL from four geographical areas (China, Laos, Thailand, and Vietnam). For further chemometric assessment, analysis techniques including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to classify the 20 batches of samples.

RESULTS

Fingerprints were established and 19 common peaks were identified. The similarity of 20 batches of THL was more than 0.9 and the batches were divided into two clusters. Four differential components of THL were identified based on OPLS-DA, including chebulinic acid, chebulagic acid, and corilagin. The optimal extraction conditions were an extraction time of 30 min, a temperature of 90°C, and a solid-liquid ratio of 30 mL/g.

CONCLUSION

HPLC fingerprinting combined with an orthogonal array design could be used for comprehensive evaluation and quality assessment of THL, providing a theoretical basis for further development and utilization of THL.

Multidimensional Chromatographic Fingerprinting Combined with Chemometrics for the Identification of Regulated Plants in Suspicious Plant Food Supplements

The popularity of plant food supplements has seen explosive growth all over the world, making them susceptible to adulteration and fraud. This necessitates a screening approach for the detection of regulated plants in plant food supplements, which are usually composed of complex plant mixtures, thus making the approach not so straightforward. This paper aims to tackle this problem by developing a multidimensional chromatographic fingerprinting method aided by chemometrics. To render more specificity to the chromatogram, a multidimensional fingerprint (absorbance × wavelength × retention time) was considered. This was achieved by selecting several wavelengths through a correlation analysis. The data were recorded using ultra-high-performance liquid chromatography (UHPLC) coupled with diode array detection (DAD). Chemometric modelling was performed by partial least squares-discriminant analysis (PLS-DA) through (a) binary modelling and (b) multiclass modelling. The correct classification rates (ccr%) by cross-validation, modelling, and external test set validation were satisfactory for both approaches, but upon further comparison, binary models were preferred. As a proof of concept, the models were applied to twelve samples for the detection of four regulated plants. Overall, it was revealed that the combination of multidimensional fingerprinting data with chemometrics was feasible for the identification of regulated plants in complex botanical matrices.

Identification of the Authenticity and Geographical Origin of Bear Bile Powder by Using High Performance Liquid Chromatography - Charged Aerosol Detector Fingerprints Combined with Chemometrics

Bear bile powder (BBP) is a rare animal-derived traditional Chinese medicine, and it has been widely used to treat visual disorders and hepatobiliary diseases in East Asia. However, there is still a lack of reliable quality control methods for BBP. This study was designed to establish a comprehensive quality map of BBP based on bile acids. High-performance liquid chromatography coupled with charged aerosol detector (HPLC-CAD) was used for fingerprint establishment and quantitative analysis of BBP. The similarities of HPLC-CAD chromatograms for 50 batches of BBP were more than 0.95, while the similarities of reference chromatograms between 6 other animal bile and BBP were low than 0.7. Additionally, five bile acids in BBP, including tauroursodeoxycholic acid, taurocholic acid, taurochenodeoxycholic acid, ursodesoxycholic acid, and chenodeoxycholic acid, were simultaneously quantified. This method has been validated with good regression as well as satisfactory precision, sensitivity, stability, repeatability, and accuracy. Using this method, the contents of five bile acids in BBP samples from five producing areas were determined and compared. Furthermore, Fisher linear discriminant analysis was performed to discriminate the geographic origins of BBP. The result demonstrated that HPLC-CAD fingerprint combined with multi-components quantification is an effective and reliable method for quality control of BBP, it could be a meaningful reference for the quality evaluation of medicinal bile.

Origin identification of Cornus officinalis based on PCA-SVM combined model

Infrared spectroscopy can quickly and non-destructively extract analytical information from samples. It can be applied to the authenticity identification of various Chinese herbal medicines, the prediction of the mixing amount of defective products, and the analysis of the origin. In this paper, the spectral information of Cornus officinalis from 11 origins was used as the research object, and the origin identification model of Cornus officinalis based on mid-infrared spectroscopy was established. First, principal component analysis was used to extract the absorbance data of Cornus officinalis in the wavenumber range of 551~3998 cm-1. The extracted principal components contain more than 99.8% of the information of the original data. Second, the extracted principal component information was used as input, and the origin category was used as output, and the origin identification model was trained with the help of support vector machine. In this paper, this combined model is called PCA-SVM combined model. Finally, the generalization ability of the PCA-SVM model is evaluated through an external test set. The three indicators of Accuracy, F1-Score, and Kappa coefficient are used to compare this model with other commonly used classification models such as naive Bayes model, decision trees, linear discriminant analysis, radial basis function neural network and partial least square discriminant analysis. The results show that PCA-SVM model is superior to other commonly used models in accuracy, F1 score and Kappa coefficient. In addition, compared with the SVM model with full spectrum data, the PCA-SVM model not only reduces the redundant variables in the model, but also has higher accuracy. Using this model to identify the origin of Cornus officinalis, the accuracy rate is 84.8%.

LC-TOF-MS/MS and GC-MS based phytochemical profiling and evaluation of wound healing activity of Oroxylum Indicum (L.) Kurz (Beka)

Background: Beka (Oroxylum indicum (L.) Kurz) has been used as a culinary herb and natural remedy by the local communities in Malaysia. The leaf of O. indicum is traditionally used for the treatment of diarrhea, high blood pressure, and improving digestive health. Objectives: The present study was conducted to evaluate the phytochemical constituents and wound healing properties (in vitro and in vivo models) of aqueous and ethanol extracts of O. indicum leaves. Methods: The total phenolic (TPC) and total flavonoid (TFC) contents in the plant extracts were determined by the spectrophotometric methods. Further, the extract was characterized by Liquid Chromatography Time-of-Flight Mass Spectrometry (LC-TOF-MS/MS) and Gas Chromatography-Mass Spectrometry (GC-MS). The wound healing activity was assessed using the in vitro scratch wound-healing assay and in vivo excisional wound model. Results: The results show the ethanol leaves extract had the higher TPC (164 mg GAE/g) when compared with the aqueous leaves extract (30 mg gallic acid equivalents/g). The ethanol leaves extract was also found to have higher TFC (101 mg Catechin equivalents/g) than the aqueous leaves extract (76 mg Catechin equivalents/g). The ethanol leaves extract was then used for further chemical analysis. The LC-TOF-MS/MS analysis showed that the leaves extracts of O. indicum contains many important compounds such as Orientin, Chrysin, Pinoquercetin, Cupressuflavone, Puerarin xyloside, Forsythiaside and Paederoside. In GC-MS analysis, 19 compounds were identified in ethanolic leaves extract. The wound healing studies shows that O. indicum has promising wound healing activity by increasing the rate of wound contraction significantly (p < 0.05). Conclusion: In conclusion, the present study showed that O. indicum leaf contains important phytochemicals and the wound healing potential of the O. indicum extract may probably be as a result of the presence of various phytoconstituents.

Quality evaluation of commercial herbal products using chemical methods

Herbal products comprise a wide spectrum of locally, nationally or internationally commercialized commodities. As these products have an increasingly important position in healthcare systems worldwide, a detailed product quality assessment is of crucial importance. For the quality evaluation of commercial herbal products, a wide range of methods were used, from simpler, quicker, and cost-effective HPTLC, to hyphenated methods with MS or NMR, where more precise quantification or specific structural information is required. Additionally, most of the methods have been coupled with chemometric tools, such as PCA, or PDA, for the multivariate analysis of the high amount of data generated by chromatograms, electropherograms or spectra. The chemical methods have revealed the widespread presence of low or variable quality herbal products in the marketplace. The majority of analytical investigations present major, qualitative and quantitative, inter-product variations of their chemical composition, ranging from missing ingredients, to strikingly and unnaturally high concentrations of some compounds. Moreover, the inter-batch quality variations were frequently reported, as well as the presence of some undesirable substances. The chemical analysis of herbal products is a vital component to raise the overall awareness of quality in the herbal market and generate a quality driven approach.

Plant-derived natural products for drug discovery: current approaches and prospects

Nature has abundant source of drugs that need to be identified/purified for use as essential biologics, either individually or in combination in the modern medical field. These drugs are divided into small bio-molecules, plant-made biologics, and a recently introduced third category known as phytopharmaceutical drugs. The development of phytopharmaceutical medicines is based on the ethnopharmacological approach, which relies on the traditional medicine system. The concept of ‘one-disease one-target drug’ is becoming less popular, and the use of plant extracts, fractions, and molecules is the new paradigm that holds promising scope to formulate appropriate drugs. This led to discovering a new concept known as polypharmacology, where natural products from varying sources can engage with multiple human physiology targets. This article summarizes different approaches for phytopharmaceutical drug development and discusses the progress in systems biology and computational tools for identifying drug targets. We review the existing drug delivery methods to facilitate the efficient delivery of drugs to the targets. In addition, we describe different analytical techniques for the authentication and fingerprinting of plant materials. Finally, we highlight the role of biopharming in developing plant-based biologics.

Quality assessment of African herbal medicine: A systematic review and the way forward

BACKGROUND

In Africa, herbalism supplements allopathic medicine's efforts to ensure Universal Health Coverage attainment. This review was conducted to identify and to summarise current literature on methodological approaches used for quality control of herbal medicines in Africa, to evaluate the gaps associated with existing strategies within context of best practices, and make recommendations for future improvements.

METHODS

A systematic search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Articles were screened and assessed for eligibility.

RESULTS

118 articles were included into the study. There was a high preference for impurity profiling tests (77%) indicating the prioritization for tests that guarantee safety despite the limited analytical resources available. Other classes of tests reported included identification tests (29%), physicochemical tests (18%), and content assays (12%). Although standard methods exist in preparing samples for impurity tests, different techniques were observed in different studies, and this could lead to differences in analytical outcomes. Content assays focused on single marker assessments, which may be inadequate to comprehensively assess the quality of products.

CONCLUSION

This review provides knowledge of existing strengths and challenges for herbal medicine quality assessments in Africa. For future it is recommended to implement more studies on contaminants (e.g. mycotoxins) and pharmaceutical adulterants. The use of chemometrics to develop analytical methods should be promoted. Also, stakeholders in the medicine quality industry in Africa need to effectively collaborate to establish a well co-ordinated and harmonized system to provide a sustainable framework for the GACP and GMP guided production and quality assurance of herbal medicines.

Application of Laser-Induced Breakdown Spectroscopy and Chemometrics for the Quality Evaluation of Foods with Medicinal Properties: A Review

Laser-induced Breakdown Spectroscopy (LIBS) is becoming an increasingly popular analytical technique for characterizing and identifying various products; its multi-element analysis, fast response, remote sensing, and sample preparation is minimal or nonexistent, and low running costs can significantly accelerate the analysis of foods with medicinal properties (FMPs). A comprehensive overview of recent advances in LIBS is presented, along with its future trends, viewpoints, and challenges. Besides reviewing its applications in both FMPs, it is intended to provide a concise description of the use of LIBS and chemometrics for the detection of FMPs, rather than a detailed description of the fundamentals of the technique, which others have already discussed. Finally, LIBS, like conventional approaches, has some limitations. However, it is a promising technique that may be employed as a routine analysis technique for FMPs when utilized effectively.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

The growing market of herbal medicines, the increase in international trade in Latvia, and the lack of adequate analytical methods have raised the question of the potential use of herbal fingerprinting methods. In this study, high-performance liquid chromatography (HPLC) and thin layer chromatography (TLC) methods were developed for obtaining chromatographic fingerprints of four taxonomically and evolutionary different medicinal plants (Hibiscus sabdariffa L., Calendula officinalis L., Matricaria recutita L., Achillea millefolium L.). Retention time shifting, principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal projections to latent structures (OPLS) analysis were used to improve and analyze the obtained fingerprints. HPLC data detection at 270 nm was determined superior to 360 nm for the distinction of medicinal plants and used data alignment method significantly increased similarity between samples. Analyzed medicinal plant extracts formed separate, compact clusters in PCA, and the results of HCA correlated with the evolutionary relationships of the analyzed medicinal plants. Herbal fingerprinting using chromatographic analysis coupled with multivariate analysis has a great potential for the identification of medicinal plants as well as for the distinction of Latvian native medicinal plants.

Evaluating the quality consistency of Keteling capsules by three-dimensional quantum fingerprints and HPLC fingerprint

Keteling capsules (KCs), as a kind of Traditional Chinese Medicine (TCM), have been widely used in curing cough and relieving asthma. However, the complicated compositions make it challenging to evaluate their quality consistency by common methods. Herein, we explored comprehensive and efficient strategies by combining the multiple techniques to monitor and assess the characteristics of KCs. We employed the fingerprints and corresponding quantum fingerprints by fourier transform infrared spectroscopy (FT-IR), ultraviolet (UV), and differential scanning calorimetry (DSC). The antioxidant activity profiles were also studied combined with the result of three-dimensional quantum fingerprints and showed a good correlation with the internal structure and physical-chemical state. Furthermore, the 17 samples were separated and identified simultaneously by HPLC quantitative fingerprint, of which four active ingredients (chlorogenic acid, p-coumaric acid, vitexin and isovitexin) were quantitatively determined. The 17 samples were successfully classified into different grades by the systematically quantified fingerprint method (SQFM) and the quality of the samples was integrated according to the mean algorithm. The mean algorithm fusion of different evaluation techniques was compared to reveal the relationship between them, which indicated the effective improvement in accuracy and integrality. The combination of multiple analytical techniques developed in this study would effectively improve the existing single analytical methods and provide new strategy for drug quality consistency control.

Chiral Metal-Organic Frameworks

In the past two decades, metal-organic frameworks (MOFs) or porous coordination polymers (PCPs) assembled from metal ions or clusters and organic linkers via metal-ligand coordination bonds have captivated significant scientific interest on account of their high crystallinity, exceptional porosity, and tunable pore size, high modularity, and diverse functionality. The opportunity to achieve functional porous materials by design with promising properties, unattainable for solid-state materials in general, distinguishes MOFs from other classes of materials, in particular, traditional porous materials such as activated carbon, silica, and zeolites, thereby leading to complementary properties. Scientists have conducted intense research in the production of chiral MOF (CMOF) materials for specific applications including but not limited to chiral recognition, separation, and catalysis since the discovery of the first functional CMOF (i.e., d- or l-POST-1). At present, CMOFs have become interdisciplinary between chirality chemistry, coordination chemistry, and material chemistry, which involve in many subjects including chemistry, physics, optics, medicine, pharmacology, biology, crystal engineering, environmental science, etc. In this review, we will systematically summarize the recent progress of CMOFs regarding design strategies, synthetic approaches, and cutting-edge applications. In particular, we will highlight the successful implementation of CMOFs in asymmetric catalysis, enantioselective separation, enantioselective recognition, and sensing. We envision that this review will provide readers a good understanding of CMOF chemistry and, more importantly, facilitate research endeavors for the rational design of multifunctional CMOFs and their industrial implementation.

Geographical origin traceability of traditional Chinese medicine Atractylodes macrocephala Koidz. by using multi-way fluorescence fingerprint and chemometric methods

Atractylodes macrocephala Koidz. (AM) is an important plant of traditional Chinese medicine (TCM), and its status can be comparable with ginseng in China. The efficacy and quality of AM are closely related to the place of origin. Hence, we proposed a simple and fast strategy to classify AM from different geographical origins by using multi-way fluorescence fingerprint combined with chemometric methods. AM samples with different dilution levels have different fluorescence characteristics, resulting from different content of fluorescence components and chemical microenvironment. Therefore, AM samples were diluted 5-fold, 10-fold, and 20-fold with 40% ethanol aqueous solution to obtain excitation-emission matrix data, and multi-way (three-way and four-way) data arrays were constructed. And then, the fluorescence fingerprints of AM samples were characterized by three-way and four-way parallel factor analysis (PARAFAC). In addition, four pattern recognition methods were used to classify AM from different provinces. The results show that the four-way data array can provide more abundant information than three-way data arrays, so it is more conducive to sample classification. According to the results obtained from the analysis of four-way data array, the correct classification rate (CCR) of the cross-validation and prediction set obtained by partial least squares-discrimination analysis (PLS-DA) were 90.5% and 100%, respectively. To sum up, the proposed method can be regarded as a powerful, feasible, convenient, reliable, and universal classification tool for the classification of AM samples from different provinces and can be used as a promising method to realize the geographical origin traceability of other TCMs.

A global systematic review on the concentration of organophosphate esters in water resources: Meta-analysis, and probabilistic risk assessment

Organophosphate esters (OPEs) are used as additives in various industries. They do not chemically bond with the polymeric structure of materials, so they can stay for a long time and have a very adverse effect on the environment. To analyze the development of the prevalence and concentration of OPEs such as TCEP, TCPP, TDCP, TnBP, TPHP, TBOEP, TEHP, TMP, TCIPP, TDCIPP, TMPP, and TDBPP in water resources, a search between January 01, 2000, to April 08, 2021, was followed by a systematic review and meta-analysis. Among of the 888 articles scanned in the identity step, 58 articles containing 2676 samples, 10 countries, and 4 water types were included in the meta-analysis study. Among all studied OPEs, the concentration of TcrP, TCPP, TDCPP, and TnBP were at the top in water resources, with values >715 μg L^-1 and lowest average concentrations were obtained for TDBPP and TpeP with values <0.0004 μg L^-1. The most polluted area in terms of the concentration of OPEs in water resources was China. Besides, data analysis showed that there only was carcinogenic risk for China. A Monte-Carlo simulation indicated that although these obtained averages are in the same order of magnitude as the acceptable limit, for both adults and children, 95% of the population is at risk.

Application of HPTLC Multiwavelength Imaging and Color Scale Fingerprinting Approach Combined with Multivariate Chemometric Methods for Medicinal Plant Clustering According to Their Species

In the current study, multiwavelength detection combined with color scales HPTLC fingerprinting procedure and chemometric approach were applied for direct clustering of a set of medicinal plants with different geographical growing areas. The fingerprints profiles of the hydroalcoholic extracts obtained after single and double development and detection under 254 nm and 365 nm, before and after selective spraying with specific derivatization reagents were evaluated by chemometric approaches. Principal component analysis (PCA) with factor analysis (FA) methods were used to reveal the contribution of red (R), green (G), blue (B) and, respectively, gray (K) color scale fingerprints to HPTLC classification of the analyzed samples. Hierarchical cluster analysis (HCA) was used to classify the medicinal plants based on measure of similarity of color scale fingerprint patterns. The 1-Pearson distance measurement with Ward’s amalgamation procedure proved to be the most convenient approach for the correct clustering of samples. Data from color scale fingerprints obtained for double development procedure and multiple visualization modes combined with appropriate chemometric methods proved to detect the similar medicinal plant extracts even though they are from different geographical regions, have different storage conditions and no specific markers are individually extracted. This approach could be proposed as a promising tool for authentication and identification studies of plant materials based on HPTLC fingerprinting analysis.

Ethanol extract of Bergenia ciliata (Haw.) Sternb. (rhizome) impedes the propagation of the malaria parasite

ETHNOPHARMACOLOGICAL RELEVANCE

The increasing resistant cases even against artemisinin-based combination therapy have necessitated the need to develop new antimalarials. Phytomedicinal therapy is a benchmark for malaria in the Himalayan region. As the dialect and traditional variations have been seen along with this, usage of medicinal plant, its portion (shoot and root system) and mode of preparation also varies. There is no scientific evidence available for illustrating the antiplasmodial activity of the rhizomes of Bergenia ciliata (Saxifragaceae), which is known to be an antipyretic (fever akin to malaria), hepato-protective, and also for spleen enlargement.

AIM OF THE STUDY

The present study evaluates the antimalarial activity of ethanol extract of B. ciliata rhizomes (EREBC).

MATERIALS AND METHODS

HPTLC was performed to identify and quantify three marker compounds in EREBC. The in vitro antimalarial activity was evaluated by schizont maturation inhibition assay. MTT assay was employed to test the cytotoxicity of EREBC. Peter's 4-day test and Peters method was employed to discern the suppressive and preventive activity of the extract respectively.

RESULTS

HPTLC analysis revealed the presence of bergenin, epicatechin and gallic acid in the extract. EREBC exhibited considerable inhibition (IC₅₀ < 5 μg/mL) of schizont maturation of both RKL-9 and MRC-2 strains of P. falciparum. EREBC was non-toxic to both HeLa cells and normal dermal fibroblasts (CC₅₀ > 1000 μg/mL). The selectivity index was > 200 for both strains. Acute toxicity of EREBC was > 4 g/kg. EREBC exhibited considerable in vivo suppressive activity with 96.48% inhibition at 500 mg/kg in comparison to chloroquine (96.08%). The ED₅₀ of the extract was < 50 mg/kg. No mortality was evident in mice administered with different doses of EREBC (50-500 mg/kg) throughout the follow up period of 28 days. EREBC exhibited safety to liver and kidney function of mice as observed from biochemical analysis.

CONCLUSION

Overall, the study illustrates the marked efficacy and potential of EREBC as an antimalarial agent with bergenin, epicatechin and gallic acid its major constituents, which played a pivotal role in the generation of the immune response.

Gas Chromatographic Fingerprint Analysis for the Comparison of Seized Cannabis Samples

Cannabis sativa L. is widely used as recreational illegal drugs. Illicit Cannabis profiling, comparing seized samples, is challenging due to natural Cannabis heterogeneity. The aim of this study was to use GC-FID and GC-MS herbal fingerprints for intra (within)- and inter (between)-location variability evaluation. This study focused on finding an acceptable threshold to link seized samples. Through Pearson correlation-coefficient calculations between intra-location samples, 'linked' thresholds were derived using 95% and 99% confidence limits. False negative (FN) and false positive (FP) error rate calculations, aiming at obtaining the lowest possible FP value, were performed for different data pre-treatments. Fingerprint-alignment parameters were optimized using Automated Correlation-Optimized Warping (ACOW) or Design of Experiments (DoE), which presented similar results. Hence, ACOW data, as reference, showed 54% and 65% FP values (95 and 99% confidence, respectively). An additional fourth root normalization pre-treatment provided the best results for both the GC-FID and GC-MS datasets. For GC-FID, which showed the best improved FP error rate, 54 and 65% FP for the reference data decreased to 24 and 32%, respectively, after fourth root transformation. Cross-validation showed FP values similar as the entire calibration set, indicating the representativeness of the thresholds. A noteworthy improvement in discrimination between seized Cannabis samples could be concluded.

Screening for the Active Anti-Inflammatory and Antioxidant Polyphenols of Gaultheria procumbens and Their Application for Standardisation: From Identification through Cellular Studies to Quantitative Determination

Aerial parts, leaves, and stems of Gaultheria procumbens are polyphenol-rich herbal medicines with anti-inflammatory and antioxidant effects. The present study focused on identifying active markers of the G. procumbens extracts in an integrated approach combining phytochemical and biological capacity tests. The target compounds, representing all classes of Gaultheria polyphenols, were pre-selected by LC-ESI-PDA-MS/MS. For unambiguous identification, the key analytes, including a rare procyanidin trimer (cinnamtannin B-1), miquelianin potassium salt, and two new natural products: quercetin and kaempferol 3-O-β-d-xylopyranosyl-(1→2)-β-d-glucuronopyranosides, were isolated by preparative HPLC and investigated by spectroscopy (HR-ESI-MS, UV-vis, CD, 1D- and 2D-NMR), thiolysis, flame photometry, optical rotation experiments, and absolute configuration studies. The significant contribution of the pre-selected compounds to the biological effects of the extracts was confirmed in vitro: the analytes significantly and in a dose-dependent manner down-regulated the pro-oxidant and pro-inflammatory functions of human neutrophils ex vivo (inhibited the release of reactive oxygen species, IL-1β, TNF-α, and neutrophils elastase, ELA-2), inhibited two key pro-inflammatory enzymes (cyclooxygenase, COX-2, and hyaluronidase), and most of them, except gaultherin, exerted potent direct antioxidant activity (ferric reducing antioxidant power and superoxide anion scavenging capacity). Moreover, cellular safety was confirmed for all compounds by flow cytometry. Eventually, as these mechanisms have been connected to the health benefits of G. procumbens, 11 polyphenols were accepted as active markers, and a simple, accurate, reproducible, and fully validated RP-HPLC-PDA method for standardisation of the target extracts was proposed.

Development and application of a chemical profiling method for the assessment of the quality and consistency of the Pelargonium sidoides extract

The evaluation of chemical similarity is very significant for the evaluation and standardization of the quality of herbal medicines as the biological activity of herbal medicines depends on the composition and proportion of many individual components. Many health organizations have recommended chemical profiling for the quality and consistency evaluation of herbal medicines. In this study, chemical profiling was performed to evaluate the similarity between batches of Pelargonium sidoides maltodextrin mixture (PMM) from EPs® 7630, a Pelargonium sidoides extract preparation. For chemical profile analysis, 7 common peaks were selected from 27 different PMM batches and specificity, linearity, accuracy, and precision tests were performed to develop the analytical method. The Pearson correlation coefficients of the similarity for all 27 batches manufactured over the years were higher than 0.90, indicating that quality consistency is well ensured over the years. This profiling method confirms the chemical profile of various commercial products using not only PMM but also Pelargonium sidoides extract and shows that it can be applied to standardization of quality.

Characteristic profiling of Aconiti Lateralis Radix for distinguishing it from compatible herbal pair using UPLC-Q-TOF-MS coupled with chemometrics

A method combining ultra-high-performance liquid chromatograph/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and chemometrics was established to evaluate the differences in chemical composition between Aconiti Lateralis Radix (Fuzi in Chinese) before and after combination with Glycyrrhizae Radix et Rhizoma (Gancao in Chinese). UPLC-Q-TOF-MS was used to characterize the chemical components before and after the combination of Fuzi with Gancao, and genetic algorithm selection variables were applied to extract important variables. Partial least square discriminant analysis was used to verify the reliability of the variables obtained by genetic algorithm selection in differentiating Fuzi and combinations with Gancao, and nine potential chemical markers were obtained. The changes in content of chemical markers in Fuzi before and after combination were visualized using a heat map and hierarchical cluster analysis. Based on the chemical markers, characteristic profiling of UPLC-Q-TOF-MS data was developed, then unsupervised principal components analysis and a supervised counter-propagation artificial neural network were used to validate the characteristic profiling approach and showed that it performed well in differentiating between Fuzi and combinations with Gancao.

Quality Control of Herbal Medicines: From Traditional Techniques to State-of-the-art Approaches

Herbal medicines are important options for the treatment of several illnesses. Although their therapeutic applicability has been demonstrated throughout history, several concerns about their safety and efficacy are raised regularly. Quality control of articles of botanical origin, including plant materials, plant extracts, and herbal medicines, remains a challenge. Traditionally, qualitative (e.g., identification and chromatographic profile) and quantitative (e.g., content analyses) markers are applied for this purpose. The compound-oriented approach may stand alone in some cases (e.g., atropine in Atropa belladonna). However, for most plant materials, plant extracts, and herbal medicines, it is not possible to assure quality based only on the content or presence/absence of one (sometimes randomly selected) compound. In this sense, pattern-oriented approaches have been extensively studied, introducing the use of multivariate data analysis on chromatographic/spectroscopic fingerprints. The use of genetic methods for plant material/plant extract authentication has also been proposed. In this study, traditional approaches are reviewed, although the focus is on the applicability of fingerprints for quality control, highlighting the most used approaches, as well as demonstrating their usefulness. The literature review shows that a pattern-oriented approach may be successfully applied to the quality assessment of articles of botanical origin, while also providing directions for a compound-oriented approach and a rational marker selection. These observations indicate that it may be worth considering to include fingerprints and their data analysis in the regulatory framework for herbal medicines concerning quality control since this is the foundation of the holistic view that these complex products demand.

A green and sustainable method for monitoring the chemical composition of soybean: an alternative for quality control

INTRODUCTION

Soybean is one of the most important crops in the world, an important source of isoflavones, and used to treat various chronic diseases. High-performance liquid chromatography (HPLC), associated with multivariate experiments and green solvents, is increasingly used to develop comprehensive elution methods for quality control of plants and derivatives.

OBJECTIVE

The work aims to establish a HPLC fingerprinting method for soybean seeds employing Green Chemistry Principles, a sustainable solvent with low toxicity, and a comprehensive experimental design that reduces the number of experiments.

MATERIALS AND METHODS

The fingerprinting method was optimised through Design of Experiments by evaluating seven chromatographic variables: initial percentage of ethanol (X1), final percentage of ethanol (X2), temperature (X3), percentage of acetic acid in water (X4), flow rate (X5), run time (X6), and stationary phase (X7). The dependent variable was the number of peaks (n).

RESULTS

An initial factorial design for screening purposes indicated that the most significant quantitative parameters to separate soybean metabolites were X1 and X3. The conditions were optimised by a Doehlert design, to obtain a HPLC-PAD (photodiode array detector) fingerprinting of the polar extract of soybean seeds with the markers identified by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). The optimum fingerprinting method was determined as 5-55% of ethanol in 30 min, at 35°C, and flow rate of 1 mL/min, by employing a phenyl-hexyl column (150 mm × 4.6 mm).

CONCLUSION

The developed green method enabled markers of soybean to be separated and identified and could be an eco-friendlier alternative for soybean quality control that covered seven Green Analytical Chemistry Principles.

Applicability of high-resolution NMR in combination with chemometrics for the compositional analysis and quality control of spices and plant-derived condiments

Over the last years, the consumption of spices and plant-derived condiments has increased considerably, owing to new culinary trends. Unfortunately, the current marketing channels make them highly vulnerable to adulteration and food fraud. High-resolution nuclear magnetic resonance (NMR) is a powerful tool for the compositional study of spices and plant-derived condiments. It allows the chemical characterization of a wide range of polar and non-polar metabolites, and provides unique structural information not available by other techniques. The chemometric-based analysis of NMR 'fingerprints' has been used to discriminate samples according to species and geographical origin and to detect adulterations, among other applications. The comprehensive identification and quantification of marker compounds can be achieved even in complex mixtures, demonstrating a great potential for high-throughtput quality control applications. © 2020 Society of Chemical Industry.

Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review

Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.