Background American ginseng (AG) is a valuable medicine widely consumed as a herbal remedy throughout the world. Huge price difference among AG with different growth years leads to intentional adulteration for higher profits. Thus, developing reliable approaches to authenticate the cultivation ages of AG products is of great use in preventing age falsification. Methods A total of 106 batches of AG samples along with their 9 physicochemical features were collected and measured from experiments, which was then split into a training set and two test sets (test set 1 and 2) according to the cultivation regions. Principle component analysis (PCA) was carried out to examine the distribution of the three data sets. Four machine learning (ML) algorithms, namely elastic net, k-nearest neighbors, support vector machine and multi-layer perception (MLP) were employed to construct predictive models using the features as inputs and their growth years as outputs. In addition, a similarity-based applicability domain (AD) was defined for these models to ensure the reliability of the predictive results for AG samples produced in different regions. Results A positive correlation was observed between the several features and the growth years. PCA revealed diverse distributions among different cultivation regions. The most accurate model derived from MLP shows good prediction power for the fivefold cross validation and the test set 1 with mean square error (MSE) of 0.017 and 0.016 respectively, but a higher MSE value of 1.260 for the test set 2. After applying the AD, all models showed much lower prediction errors for the test samples within AD (IDs) than those outside the AD (ODs). MLP remains the best predictive model with an MSE value of 0.030 for the IDs. Conclusion Cultivation years have a close relationship with bioactive components of AG. The constructed models and AD are also able to predict the cultivation years and discriminate samples that have inaccurate prediction results. The AD-equipped models used in this study provide useful tools for determining the age of AG in the market and are freely available at https://github.com/dreadlesss/Panax_age_predictor.

Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67–3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex.

Background The raw and processed roots of Polygonum multiflorum Thunb (PM) are commonly used in clinical practice to treat diverse diseases; however, reports of hepatotoxicity induced by Polygoni Multiflori Radix (PMR) and Polygoni Multiflori Radix Praeparata (PMRP) have emerged worldwide. Thus, it is necessary for researchers to explore methods to improve quality standards to ensure their quality and treatment effects. Methods In the present study, an ultra-high performance liquid chromatography triple quadrupole mass spectrometry (UHPLC-QQQ-MS/MS) method was optimized and validated for the determination of dianthrones in PMR and PMRP using bianthronyl as the internal standard. Chromatographic separation with a gradient mobile phase [A: acetonitrile and B: water containing 0.1% formic acid (v/v)] at a flow rate of 0.25 mL/min was achieved on an Agilent ZORBAX SB-C18 column (2.1 mm × 50 mm, 1.8 μm). The triple quadrupole mass spectrometer (TQMS) was operated in negative ionization mode with multiple reaction monitoring for the quantitative analysis of six dianthrones. Moreover, compounds 5 and 6 were further evaluated for their cytotoxicity in HepaRG cells by CCK-8 assay. Results The UHPLC-QQQ-MS/MS method was first developed to simultaneously determine six dianthrones in PMR and PMRP, namely, polygonumnolides C1–C4 (1–4), trans-emodin dianthrones (5), and cis-emodin dianthrones (6). The contents of 1–6 in 90 batches of PMR were in the ranges of 0.027–19.04, 0.022–13.86, 0.073–15.53, 0.034–23.35, 0.38–83.67 and 0.29–67.00 µg/g, respectively. The contents of 1–6 in 86 batches of commercial PMRP were in the ranges of 0.020–13.03, 0.051–8.94, 0.022–7.23, 0.030–12.75, 0.098–28.54 and 0.14–27.79 µg/g, respectively. Compounds 1–4 were almost completely eliminated after reasonable processing for 24 h and the contents of compounds 5 and 6 significantly decreased. Additionally, compounds 5 and 6 showed inhibitory activity in HepaRG cells with IC50 values of 10.98 and 15.45 μM, respectively. Furthermore, a systematic five-step strategy to standardize TCMs with endogenous toxicity was proposed for the first time, which involved the establishment of determination methods, the identification of potentially toxic markers, the standardization of processing methods, the development of limit standards and a risk–benefit assessment. Conclusion The results of the cytotoxicity evaluation of the dianthrones indicated that trans-emodin dianthrones (5) and cis-emodin dianthrones (6) could be selected as toxic markers of PMRP. Taking PMR and PMRP as examples, we hope this study provides insight into the standardization and internationalization of endogenous toxic TCMs, with the main purpose of improving public health by scientifically using TCMs to treat diverse complex diseases in the future.

Pyrrolizidine alkaloids are toxins having hepatotoxic and carcinogenic effects on human health. A ultra high performance liquid chromatography tandem mass spectrometry technique was developed for the first time for the simultaneous determination of eight pyrrolizidine alkaloids, including four diastereoisomers (intermedine, lycopsamine, rinderine, and echinatine) and their respective N‐oxide forms, in different parts of Eupatorium lindleyanum. The risk assessment method for pyrrolizidine alkaloids in Eupatorium lindleyanum was explored using the margin of exposure strategy for the first time based on a real‐life exposure scenario. Differences were found in all eight pyrrolizidine alkaloids in various parts of Eupatorium lindleyanum. Besides, the total levels of pyrrolizidine alkaloids in Eupatorium lindleyanum followed the order of root > flower > stem > leaf. Moreover, the risk assessment data revealed that the deleterious effects on human health were unlikely at exposure times of less than 200, 37, and 12 days during the lifetimes of Eupatorium lindleyanum leaves, stems, and flowers, respectively. This study reported both the contents of and risk associated with Eupatorium lindleyanum pyrrolizidine alkaloids. The comprehensive application of the novel ultra high performance liquid chromatography tandem mass spectrometry technique alongside the risk assessment approach provided a scientific basis for quality evaluation and rational utilization of toxic pyrrolizidine alkaloids in Eupatorium lindleyanum to improve public health safety.

Polygonummultiflorum (PM) Thunb., a typical Chinese herbal medicine with different therapeutic effect in raw and processed forms, has been used worldwide for thousands of years. However, hepatotoxicity caused by PM has raised considerable concern in recent decades. The exploration of toxic components in PM has been a great challenge for a long time. In this study, we developed a stepwise strategy integrating metabolomics and pseudotargeted spectrum–effect relationship to illuminate the potential hepatotoxic components in PM. First, 112 components were tentatively identified using ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS). Second, based on the theory of toxicity attenuation after processing, we combined the UPLC-Q-TOF-MS method and plant metabolomics to screen out the reduced differential components in PM between raw and processed PM. Third, the proposed pseudotargeted MS of 16 differential components was established and applied to 50 batches of PM for quantitative analysis. Fourth, the hepatocytotoxicity of 50 batches of PM was investigated on two hepatocytes, LO2 and HepG2. Last, three mathematical models, gray relational analysis, orthogonal partial least squares analysis, and back propagation artificial neural network, were established to further identify the key variables affecting hepatotoxicity in PM by combining quantitative spectral information with toxicity to hepatocytes of 50 batches of PM. The results suggested that 16 components may have different degrees of hepatotoxicity, which may lead to hepatotoxicity through synergistic effects. Three components (emodin dianthrones, emodin-8-O-β-D-glucopyranoside, PM 14-17) were screened to have significant hepatotoxicity and could be used as toxicity markers in PM as well as for further studies on the mechanism of toxicity. Above all, the study established an effective strategy to explore the hepatotoxic material basis in PM but also provides reference information for in-depth investigations on the hepatotoxicity of PM.