Quality assessment of herbal medicines based on chemical fingerprints combined with chemometrics approach: A review

A quality control system of Chinese medicine preparation based on fingerprint identification technology, chemometrics and network pharmacology, using the Yixinshu capsule as an example

Establishing a trustworthy quality control system for traditional Chinese medicine (TCM) is crucial to ensure the stability and reliability of the therapeutic efficacy of Chinese medicinal preparations (CMPs). This study takes Yixinshu Capsules (YXSC) as the research subject and develops a quality control system for TCM by integrating fingerprint technology, chemometrics, and network pharmacology. Initially, a dual-wavelength absorption coefficient ratio fingerprint (DWAR) was employed to verify the peak purity of each fingerprint peak in YXSC, while a three-dimensional chromatographic fingerprint (3DCFP) was utilized to generate full-wavelength chromatographic fingerprints of sample components. Subsequently, electrochemical (EC) and differential scanning calorimetry (DSC) methods were adopted as supplementary analytical approaches to evaluate YXSC comprehensively. A five-dimensional quantitative fingerprint method (5DQFM) was then applied to assess the above three detection methods from both qualitative and quantitative perspectives, enabling a holistic evaluation of YXSC's quality consistency. Furthermore, chemometric analysis demonstrated that 5DQFM and 3DCFP could accurately characterize YXSC's quality. Finally, network pharmacology was employed as a research methodology to explore the potential mechanisms through which different active chemical components in YXSC exert therapeutic effects on heart failure (HF). This study evaluates YXSC's quality from both chemical and biological perspectives and develops a comprehensive and reliable quality control approach, providing novel insights for quality control and therapeutic efficacy research of CMP.

Screening and Application of DNA Markers for Novel Quality Consistency Evaluation in Panax ginseng

Quality control remains a challenge in traditional Chinese medicine (TCM). This study introduced a novel genetic-based quality control method for TCM. Genetic variations in ginseng were evaluated across whole-genome, chloroplast genome, and ITS2 DNA barcode dimensions. Significant genetic variations were found in whole-genome comparison, leading to the use of inter-simple sequence repeat markers to assess the genetic diversity of ginseng decoction pieces (PG), garden ginseng (GG), and ginseng under forest (FG). Fingerprints of ginseng samples revealed instability within some batches. These evaluations were transformed into information entropy to calculate the size of Hardy-Weinberg equilibrium population (HWEP). FG had significantly higher genetic and chemical minimum HWEP than GG (p < 0.05). Notably, a significant positive correlation was observed between the minimum HWEP for genetics and for chemistry (r = 0.857, p = 0.014). Genetic polymorphism analysis of ginseng has the potential to evaluate chemical quality consistency, offering a new method to ensure quality consistency in TCM.

A Comprehensive Quality Evaluation for Gentiana Rigescens Franch. by Fingerprinting Combined with Chemometrics and Network Pharmacology

Gentiana rigescens Franch. (G. rigescens) is a unique traditional medicinal herb from southwestern China, and its clinical mechanism for the treatment of hepatitis and the quality differences between different origins are not clear. The research aims to analyze the mechanisms for the treatment of hepatitis and differences in inter-origin differences using analytical techniques, chemometrics, and network pharmacology. Through infrared spectroscopy, spectral images, and high-performance liquid chromatography (HPLC) analysis, it was found that there were differences in absorbance intensity and significant differences in compound content among the samples' origin. G. rigescens iridoids and flavonoids exert therapeutic effects on hepatitis through multiple targets (GAPDH, EGFR, and MMP9, etc.) and multiple pathways (non-small cell lung cancer, hepatitis C, etc.). The above HPLC, chemometrics, and network pharmacology results revealed that gentiopicroside, and swertiamarine was the best quality marker among origins. The accuracy of the ResNet model train, test, and external validation sets for synchronous spectral images were 100 %, which could be utilized as an effective tool for tracing G. rigescens's origins. The R2 of the calibration and validation sets of the PLSR model was higher than 0.70. This model had excellent predictive performance in determining the content of gentiopicroside and swertiamarine, and could quickly, accurately, and effectively predict these two compounds. The research investigates the differences in G. rigescens origins from multiple perspectives, establishes image recognition models and prediction models, and provides new methods and theoretical basis for quality control of G. rigescens.

Combination ATR-FTIR with Multiple Classification Algorithms for Authentication of the Four Medicinal Plants from Curcuma L. in Rhizomes and Tuberous Roots

Curcumae Longae Rhizoma (CLRh), Curcumae Radix (CRa), and Curcumae Rhizoma (CRh), derived from the different medicinal parts of the Curcuma species, are blood-activating analgesics commonly used for promoting blood circulation and relieving pain. Due to their certain similarities in chemical composition and pharmacological effects, these three herbs exhibit a high risk associated with mixing and indiscriminate use. The diverse methods used for distinguishing the medicinal origins are complex, time-consuming, and limited to intraspecific differentiation, which are not suitable for rapid and systematic identification. We developed a rapid analysis method for identification of affinis and different medicinal materials using attenuated total reflection-Fourier-transform infrared spectroscopy (ATR-FTIR) combined with machine learning algorithms. The original spectroscopic data were pretreated using derivatives, standard normal variate (SNV), multiplicative scatter correction (MSC), and smoothing (S) methods. Among them, 1D + MSC + 13S emerged as the best pretreatment method. Then, t-distributed stochastic neighbor embedding (t-SNE) was applied to visualize the results, and seven kinds of classification models were constructed. The results showed that support vector machine (SVM) modeling was superior to other models and the accuracy of validation and prediction was preferable, with a modeling time of 127.76 s. The established method could be employed to rapidly and effectively distinguish the different origins and parts of Curcuma species and thus provides a technique for rapid quality evaluation of affinis species.

Holistic quality assessment and monitoring of YiXinShu capsule based on three-dimensional fingerprints combined with quantitative analysis, antioxidant activity and chemometrics

ETHNOPHARMACOLOGICAL RELEVANCE

YiXinShu capsule (YXSC), originally from the classical TCM formula named "Sheng-Mai-San", has been extensively utilized in clinic for the treatment of cardiovascular diseases. However, there were few reports about the quality assessment of YXSCs both internationally and domestically.

AIM OF THE STUDY

The objective was to develop a multi-strategy platform incorporating systematic quantitative fingerprint analysis and antioxidant activity determination, with chemometric analysis and bivariate correlation analysis as the auxiliary approaches, to assess and monitor the quality of YXSCs.

MATERIALS AND METHODS

Firstly, according to the Chinese Pharmacopoeia (2020 edition), 12 key indicator components from seven herb medicines were quantified by HPLC method. Then, three-dimensional fingerprints comprising five-wavelength fusion fingerprint (FWF-FP), electrochemical fingerprint (EC-FP) and Differential Scanning Calorimetry fingerprint (DSC-FP) were established to assess and monitor YXSCs using systematically quantified fingerprint method (SQFM) and principal component analysis (PCA). Moreover, by integrating the analysis of the three-dimensional fingerprints, the quality of YXSCs from different batches was effectively screened. Finally, the antioxidant activity of this TCM was assessed through DPPH and ABTS methods, and the L-ascorbic acid equivalent antioxidant capacity (AEAC) values were compared to evaluate the antioxidant activities of the two methods. A Partial Least Squares (PLS) model was used to develop the spectrum-activity relationship between FWF-FP and AEAC, and a bivariate correlation analysis (BCA) was used to assess the correlation between FWF-FP and EC-FP.

RESULTS

The key indexes including tanshinone I, tol, toe, Atp, first exothermic peak, and second exothermic peak can differentiate between various batches of YXSCs based on their three-dimensional fingerprint profiles. The integration evaluation results from 42 batches of YXSCs were categorized into 2-5 grades, indicating good quality consistency across different batches. In vitro studies have indicated a significant antioxidant activity capacity of YXSCs. The PLS model revealed that 37 out of the 41 fingerprint peaks exhibited antioxidant activity. The overall trend of BCA was consistent with PLS model results.

CONCLUSION

This research presents a scientific and holistic strategy for the quality consistency evaluation of YXSCs, thereby offering an effective approach for the thorough evaluation of TCMs.

Exploring the therapeutic mechanisms of heart failure with Chinese herbal medicine: a focus on miRNA-mediated regulation

Heart failure (HF) is a clinical condition caused by abnormalities in the heart's structure or function, primarily manifested as diminished ability of the heart to pump blood, which leads to compensatory activation of neurohormones and increased left ventricular filling pressure. HF is one of the fastest-growing cardiovascular diseases globally in terms of incidence and mortality, negatively impacting patients' quality of life and imposing significant medical and economic burdens. Despite advancements in the treatment of HF, hospitalization and mortality remain rates high. In China, Chinese herbal medicine (CHM) has historically played a prominent role in addressing HF, with significant proven efficacy. MicroRNA (miRNA) exerts a pivotal regulatory influence on the maintenance of regular cardiac activity and the progression of HF. MiRNAs, a category of single-stranded RNA molecules, are characterized by their inability to code for proteins. They regulate gene expression by binding to the 3'-untranslated region (3'-UTR) of target mRNAs, thereby influencing the onset and progression of various diseases. Abnormal expression of specific miRNAs is closely associated with HF pathological processes, such as cardiomyocyte apoptosis, myocardial fibrosis, and cardiac hypertrophy. This abnormal expression can influence the pathological progression of HF through the regulation of miRNA expression. This article reviews the regulatory role of miRNAs in HF pathology discusses how CHM compounds and their active ingredients can ameliorate HF pathology through the regulation of miRNA expression. In conclusion, miRNAs represent promising therapeutic targets for HF, and CHM provides a novel strategy for treatment through the regulation of miRNA expression. Future studies must delve deeper into the precise mechanisms by which CHM modulates miRNAs and fully explore its potential for clinical application in HF treatment.

Exploring the impact of Agaricus bisporus on mitigating lead reproductive toxicity using the Caenorhabditis elegans model

Given that Agaricus bisporus, an edible mushroom, has demonstrated antioxidant properties, our investigation aimed to assess whether Agaricus bisporus could mitigate the toxic effects of lead (Pb) on Caenorhabditis elegans (C. elegans) model. A dose-response study was conducted involving Pb and Agaricus bisporus to determine appropriate doses. Subsequently, a co-exposure study utilizing C. elegans strains N2 and CL2166 was implemented, with groups designated as Control, Pb, Agaricus bisporus, and Pb + Agaricus bisporus. Our findings revealed that co-exposure to Pb + 100 mg/mL Agaricus bisporus resulted in reduced embryonic and larval lethality, increased brood size, and enhanced motility compared to nematodes exposed solely to Pb. Notably, our observations indicated a transfer of reproductive toxicity from nematode parents to their offspring. Thus, Agaricus bisporus may play a significant role in Pb detoxification, suggesting its potential as a natural antioxidant for neutralizing the detrimental effects of Pb on reproductive health.

A comprehensive strategy based on ultra-high performance liquid chromatography with diode array detector fingerprinting and multi-component ultra-performance liquid chromatography with tandem mass spectrometry technology for quality control of Jiawei Huoxiang Zhengqi Pill

Jiawei Huoxiang Zhengqi Pill (JHZP) is a commonly used Chinese patent medicine for the clinical treatment of headache, dizziness, chest tightness as well as abdominal distension, and pain caused by wind-cold flu. In this study, a comprehensive strategy combining ultra-high performance liquid chromatography with diode array detector (UHPLC-DAD) fingerprinting and multi-component quantitative analysis was established and validated for quality evaluation of JHZP. A total of 49 characteristic common peaks were selected in a chromatographic fingerprinting study to assess the similarity of 15 batches of JHZP. Furthermore, 109 compounds were identified or preliminarily identified from JHZP by coupling with an advanced hybrid linear ion trap-Orbitrap mass spectrometer. For quantification, the optimized ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS) method was employed for the simultaneous determination of 13 target compounds within 12 min. The sensitivity, precision, reproducibility, and accuracy of the method were satisfactory. This validated UPLC-MS/MS method was successfully applied to analyzing 15 batches of JHZP. The proposed comprehensive strategy combining UHPLC-DAD fingerprinting and multi-component UPLC-MS/MS analysis proved to be highly efficient, accurate, and reliable for the quality evaluation of JHZP, which can be considered as a reference for the overall quality evaluation of other Chinese herbal formulations.

Quantitative analysis of the quality constituents of Lonicera japonica Thunberg based on Raman spectroscopy

Quantitative analysis of the quality constituents of Lonicera japonica (Jinyinhua [JYH]) using a feasible method provides important information on its evaluation and applications. Limitations of sample pretreatment, experimental site, and analysis time should be considered when identifying new methods. In response to these considerations, Raman spectroscopy combined with deep learning was used to establish a quantitative analysis model to determine the quality of JYH. Chlorogenic acid and total flavonoids were identified as analysis targets via network pharmacology. High performance liquid chromatograph and ultraviolet spectroscopy were used to construct standard curves for quantitative analysis. Raman spectra of JYH extracts (1200) were collected. Subsequently, models were built using partial least squares regression, Support Vector Machine, Back Propagation Neural Network, and One-dimensional Convolutional Neural Network (1D-CNN). Among these, the 1D-CNN model showed superior prediction capability and had higher accuracy (R2 = 0.971), and lower root mean square error, indicating its suitability for rapid quantitative analysis.

Flower Species Ingredient Verification Using Orthogonal Molecular Methods

Flowers are gaining considerable interest among consumers as ingredients in food, beverages, cosmetics, and natural health products. The supply chain trades in multiple forms of botanicals, including fresh whole flowers, which are easier to identify than dried flowers or flowers processed as powdered or liquid extracts. There is a gap in the scientific methods available for the verification of flower species ingredients traded in the supply chains of multiple markets. The objective of this paper is to develop methods for flower species ingredient verification using two orthogonal methods. More specifically, the objectives of this study employed both (1) DNA-based molecular diagnostic methods and (2) NMR metabolite fingerprint methods in the identification of 23 common flower species ingredients. NMR data analysis reveals considerable information on the variation in metabolites present in different flower species, including color variants within species. This study provides a comprehensive comparison of two orthogonal methods for verifying flower species ingredient supply chains to ensure the highest quality products. By thoroughly analyzing the benefits and limitations of each approach, this research offers valuable insights to support quality assurance and improve consumer confidence.

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.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Holistic quality evaluation method of Epimedii Folium based on NIR spectroscopy and chemometrics

INTRODUCTION

There are some problems in the quality control of Epimedii Folium (leaves of Epimedium brevicornum Maxim.), such as the mixed use of Epimedii Folium from different harvesting periods and regions, incomplete quality evaluation, and time-consuming analysis methods.

OBJECTIVE

Near-infrared (NIR) spectroscopy was conducted to establish a rapid overall quality evaluation method for Epimedii Folium.

MATERIALS AND METHODS

Quantitative models of the total solid, moisture, total flavonoid, and flavonol glycoside (Epimedin A, Epimedin B, Epimedin C, Icariin) contents of Epimedii Folium were established by partial least squares regression (PLSR). The root mean square error (RMSE) and correlation coefficient (R) were used to evaluate the performance of models. The qualitative models of Epimedii Folium from different geographic origins and harvest periods were established based on K-nearest neighbor (KNN), back-propagation neural network (BPNN), and random forest (RF). Accuracy and Kappa values were used to evaluate the performance of models. A new multivariable signal conversion strategy was proposed, which combines NIR spectroscopy with the PLSR model to predict the absorbance values of retention time points in the high-performance liquid chromatography (HPLC) fingerprint to obtain the predicted HPLC fingerprint. The Pearson correlation coefficient and cosine coefficient were used to evaluate the similarity between real and predicted HPLC fingerprints.

RESULTS

Qualitative models, quantitative models, and the similarity between real and predicted HPLC fingerprints are satisfactory.

CONCLUSION

The method serves as a fast and green analytical quality evaluation method of Epimedii Folium and can replace traditional methods to achieve the overall quality evaluation of Epimedii Folium.

Application, challenges and future prospects of recent nondestructive techniques based on the electromagnetic spectrum in food quality and safety

Safety and quality aspects of food products have always been critical issues for the food production and processing industries. Since conventional quality measurements are laborious, time-consuming, and expensive, it is vital to develop new, fast, non-invasive, cost-effective, and direct techniques to eliminate those challenges. Recently, non-destructive techniques have been applied in the food sector to improve the quality and safety of foodstuffs. The aim of this review is an effort to list non-destructive techniques (X-ray, computer tomography, ultraviolet-visible spectroscopy, hyperspectral imaging, infrared, Raman, terahertz, nuclear magnetic resonance, magnetic resonance imaging, and ultrasound imaging) based on the electromagnetic spectrum and discuss their principle and application in the food sector. This review provides an in-depth assessment of the different non-destructive techniques used for the quality and safety analysis of foodstuffs. We also discussed comprehensively about advantages, disadvantages, challenges, and opportunities for the application of each technique and recommended some solutions and developments for future trends.

A Rapid and Accurate UHPLC Method for Determination of Monosaccharides in Polysaccharides of Different Sources of Radix Astragali and Its Immune Activity Analysis

With the escalating demand for Astragalus polysaccharides products developed from Radix Astragali (RA), the necessity for quality control of polysaccharides in RA has become increasingly urgent. In this study, a specific method for the simultaneous determination of seven monosaccharides in polysaccharides extracted from Radix Astragali (RA) has been developed and validated using ultra-performance liquid chromatography equipped with an ultraviolet detector (UHPLC-UV) for the first time. The 1-phenyl-3-methyl-5-pyrazolone (PMP) derivatizations were separated on a C18 column (Waters ACQUITYTM, Milfor, MA, USA, 1.8 µm, 2.1 × 100 mm) using gradient elution with a binary system of 5 mm ammonium formate (0.1% formic acid)-acetonitrile for 24 min. Additionally, seven monosaccharides showed good linear relationships (R2, 0.9971-0.9995), adequate precision (RSD < 4.21%), and high recoveries (RSD < 4.70%). The established method was used to analyze 109 batches of RA. Results showed that the Astragalus polysaccharides (APSs) mainly consist of mannose (Man), rhamnose (Rha), glucose (Glu), galactose (Gal), arabinose (Ara), xylose (Xyl); and fucose (Fuc); however, their composition was different among RA samples from different growth patterns, species, growth years, and origins, and the growth mode of RA and the age of wild-simulated RA can be accurately distinguished by principal component analysis (PCA). In addition, the immunological activity of APSs were also evaluated jointly by measurement of the NO release with RAW264.7, with the results showing that APSs have a promoting effect on the release of NO and exhibit a significant correlation with Man, Glu, Xyl, and Fuc contents. Accordingly, the new established monosaccharides analytical method and APS-immune activity determination in this study can provide a reference for quality evaluation and the establishment of quality standards for RA.

Distinguishment of different varieties of rhubarb based on UPLC fingerprints and chemometrics

Rhubarb, a widely used traditional Chinese medicine (TCM), is primarily used for purging in practice. It is derived from the dried roots and rhizomes of R. tanguticum Maxim. ex Balf. (RT), Rheum officinale Baill. (RO) and R. palmatum L. (RP). To date, although the three varieties of rhubarb have been used as the same medicine in clinical, studies have found that they have different chemical compositions and pharmacological effects. To ensure the stability of rhubarb for clinical use, a simple and effective method should be built to compare and discriminate three varieties of rhubarb. Here, ultra-performance liquid chromatography-diode array detection (UPLC-DAD) fingerprints combined with chemometric methods were developed to evaluate and discriminate 29 batches of rhubarb. Similarity evaluation, hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed that the chemical constituents of the three varieties of rhubarb were significantly different, and the three varieties could be effectively distinguished. Finally, all the 14 common peaks were identified by ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS). In this research, the developed UPLC fingerprints offer a simple, reliable and specific approach for distinguishing different varieties of rhubarb. This research aims to promote the scientific and appropriate clinical application of rhubarb from three varieties.

Improved quantitative analysis of tenuifolin using hydrolytic continuous-flow system to build prediction models for its content based on near-infrared spectroscopy

This study used two types of analyses and statistical calculations on powdered samples of Polygala root (PR) and Senega root (SR): (1) determination of saponin content by an independently developed quantitative analysis of tenuifolin content using a flow reactor, and (2) near-infrared spectroscopy (NIR) using crude drug powders as direct samples for metabolic profiling. Furthermore, a prediction model for tenuifolin content was developed and validated using multivariate analysis based on the results of (1) and (2). The goal of this study was to develop a rapid analytical method utilizing the saponin content and explore the possibility of quality control through a wide-area survey of crude drugs using NIR spectroscopy. Consequently, various parameters and appropriate wavelengths were examined in the regression analysis, and a model with a reasonable contribution rate and prediction accuracy was successfully developed. In this case, the wavenumber contributing to the model was consistent with that of tenuifolin, confirming that this model was based on saponin content. In this series of analyses, we have succeeded in developing a model that can quickly estimate saponin content without post-processing and have demonstrated a brief way to perform quality control of crude drugs in the clinical field and on the market.

Establishing an integrated, four-dimensional quality assessment system for traditional Chinese medicine: A case study of Shuanghuanglian oral liquid

The quality of traditional Chinese medicine (TCM) is the premise to ensure its safety and effectiveness in clinical application. In this study, a complete quality control system for four-dimensional fingerprinting of TCM was innovatively constructed based on multiple detection techniques, and the quality of Shuanghuanglian oral liquid (SHL) was evaluated. Electrochemical fingerprinting (ECFP) as an emerging method without pretreatment provides rich and quantifiable information for SHL samples. The first quantitative ECFP of SHL was developed by the B-Z oscillation system. Eight characteristic parameters were analyzed and a good linear relationship was found between the oscillation lifetime and sample volume, by which the calculated values of the added sample volume (VL) showed different fluctuations between samples. What is more, high-performance liquid chromatography five-wavelength fusion fingerprint (HPLC-FWFP), GC fingerprint (GC-FP), and UV quantum fingerprint (UV-QFP) was established. Meanwhile, the purity of the peaks of the HPLC-FWFP was verified by the dual-wavelength absorption coefficient ratio spectrum (DWAR). Equal weighted ratio quantitative fingerprinting method (EWRQFM) was successfully proposed to extract all potential features for the overall quality assessment of the samples. Finally, a comprehensive evaluation strategy was proposed, namely the variation coefficient weighting algorithm (VCWA). The results of qualitative and quantitative evaluation of HPLC-FWFP, GC-FP, electrochemical quantum fingerprints (EC-QFP), and UV-QFP were integrated by this method. The established evaluation system is also a suitable strategy to control the quality of other TCM preparations.

The contemporary nexus of medicines security and bioprospecting: a future perspective for prioritizing the patient

Reacting to the challenges presented by the evolving nexus of environmental change, defossilization, and diversified natural product bioprospecting is vitally important for advancing global healthcare and placing patient benefit as the most important consideration. This overview emphasizes the importance of natural and synthetic medicines security and proposes areas for global research action to enhance the quality, safety, and effectiveness of sustainable natural medicines. Following a discussion of some contemporary factors influencing natural products, a rethinking of the paradigms in natural products research is presented in the interwoven contexts of the Fourth and Fifth Industrial Revolutions and based on the optimization of the valuable assets of Earth. Following COP28, bioprospecting is necessary to seek new classes of bioactive metabolites and enzymes for chemoenzymatic synthesis. Focus is placed on those performance and practice modifications which, in a sustainable manner, establish the patient, and the maintenance of their prophylactic and treatment needs, as the priority. Forty initiatives for natural products in healthcare are offered for the patient and the practitioner promoting global action to address issues of sustainability, environmental change, defossilization, quality control, product consistency, and neglected diseases to assure that quality natural medicinal agents will be accessible for future generations.

Quality Consistency Evaluation of Traditional Chinese Medicines: Current Status and Future Perspectives

Quality consistency evaluation of traditional Chinese medicines (TCMs) is a crucial factor that determines the safe and effective application in clinical settings. However, TCMs exhibit diverse, heterogeneous, complex, and flexible chemical compositions, as well as variability in preparation processes. These characteristics pose greater challenges in researching the consistency of TCMs compared to chemically synthesized and biological drugs. Therefore, it is paramount to develop effective strategies for evaluating the quality consistency of TCMs. From the starting point of quality properties, this review explores the strategy used to evaluate quality consistency in terms of chemistry-based strategy (chemical consistency) and the biology-based strategy (bioequivalence). Among them, the chemistry-based strategy is the mainstream, and biology-based strategy complements the chemistry-based strategy each other. Furthermore, the emerging chemistry-biology strategies (overall evaluation) is discussed, including individually combining strategy and integration strategy. Finally, this review provides insights into the challenges and future perspectives in this field. By highlighting current status and trends in TCMs quality consistency, this review aims to contribute to establishment of generally applicable chemistry-biology integrated evaluation strategy for TCMs. This will facilitate the advancement toward a higher stage of overall quality evaluation.

Application of Data Fusion in Traditional Chinese Medicine: A Review

Traditional Chinese medicine is characterized by numerous chemical constituents, complex components, and unpredictable interactions among constituents. Therefore, a single analytical technique is usually unable to obtain comprehensive chemical information. Data fusion is an information processing technology that can improve the accuracy of test results by fusing data from multiple devices, which has a broad application prospect by utilizing chemometrics methods, adopting low-level, mid-level, and high-level data fusion techniques, and establishing final classification or prediction models. This paper summarizes the current status of the application of data fusion strategies based on spectroscopy, mass spectrometry, chromatography, and sensor technologies in traditional Chinese medicine (TCM) in light of the latest research progress of data fusion technology at home and abroad. It also gives an outlook on the development of data fusion technology in TCM analysis to provide references for the research and development of TCM.

Applications of some advanced sequencing, analytical, and computational approaches in medicinal plant research: a review

The potential active chemicals found in medicinal plants, which have long been employed as natural medicines, are abundant. Exploring the genes responsible for producing these compounds has given new insights into medicinal plant research. Previously, the authentication of medicinal plants was done via DNA marker sequencing. With the advancement of sequencing technology, several new techniques like next-generation sequencing, single molecule sequencing, and fourth-generation sequencing have emerged. These techniques enshrined the role of molecular approaches for medicinal plants because all the genes involved in the biosynthesis of medicinal compound(s) could be identified through RNA-seq analysis. In several research insights, transcriptome data have also been used for the identification of biosynthesis pathways. miRNAs in several medicinal plants and their role in the biosynthesis pathway as well as regulation of the disease-causing genes were also identified. In several research articles, an in silico study was also found to be effective in identifying the inhibitory effect of medicinal plant-based compounds against virus' gene(s). The use of advanced analytical methods like spectroscopy and chromatography in metabolite proofing of secondary metabolites has also been reported in several recent research findings. Furthermore, advancement in molecular and analytic methods will give new insight into studying the traditionally important medicinal plants that are still unexplored.

Recent trends of machine learning applied to multi-source data of medicinal plants

In traditional medicine and ethnomedicine, medicinal plants have long been recognized as the basis for materials in therapeutic applications worldwide. In particular, the remarkable curative effect of traditional Chinese medicine during corona virus disease 2019 (COVID-19) pandemic has attracted extensive attention globally. Medicinal plants have, therefore, become increasingly popular among the public. However, with increasing demand for and profit with medicinal plants, commercial fraudulent events such as adulteration or counterfeits sometimes occur, which poses a serious threat to the clinical outcomes and interests of consumers. With rapid advances in artificial intelligence, machine learning can be used to mine information on various medicinal plants to establish an ideal resource database. We herein present a review that mainly introduces common machine learning algorithms and discusses their application in multi-source data analysis of medicinal plants. The combination of machine learning algorithms and multi-source data analysis facilitates a comprehensive analysis and aids in the effective evaluation of the quality of medicinal plants. The findings of this review provide new possibilities for promoting the development and utilization of medicinal plants.

Comparison of Metabolites and Species Classification of Thirteen Zingiberaceae Spices Based on GC-MS and Multi-Spectral Fusion Technology

Due to a similar plant morphology in the majority of Zingiberaceae spices, substitution and adulteration frequently take place during the sales process. Therefore, it is important to analyze the metabolites and species classification of different Zingiberaceae spices. This study preliminarily explored the differences in the metabolites in thirteen Zingiberaceae spices through untargeted gas chromatography-mass spectrometry (GC-MS) and combined spectroscopy, establishing models for classifying different Zingiberaceae spices. On one hand, a total of 81 metabolites were successfully identified by GC-MS. Thirty-seven differential metabolites were screened using variable important in projection (VIP ≥ 1). However, the orthogonal partial least squares discriminant analysis (OPLS-DA) model established using GC-MS data only explained about 30% of the variation. On the other hand, the partial least squares discriminant analysis (PLS-DA) models with three spectral data fusion strategies were compared, and their classification accuracy reached 100%. Among them, the mid-level data fusion model based on latent variables had the best performance. This study provides a powerful tool for distinguishing different Zingiberaceae spices and assists in reducing the occurrence of substitution and adulteration phenomena.

Comprehensive Quality Evaluation of Qizhi Xiangfu Pills Based on Quantitative Analysis of Multi-Components by a Single Marker Combined with GC Fingerprints and Chemometrics

BACKGROUND

Qizhi Xiangfu Pills (QXPs) are a traditional Chinese medicine (TCM) used clinically for qi stagnation and blood stasis. The current quality control of QXPs in the ministry standards and the reported literature is minimal, and requires improvement.

OBJECTIVE

This study aimed to analyze and determine the active ingredients in QXPs for its overall evaluation.

METHODS

In this study, a quantitative analysis of multi-components by a single marker (QAMS) method was established to simultaneously determine caryophyllene oxide, cyperotundone, ligustilide, and α-cyperone in QXPs by GC. Moreover, the GC fingerprints of 22 batches of samples were also established, and the common peaks were initially identified by GC-MS, then classified in various dimensions using chemometric methods, and the main markers causing the discrepancies between groups were analyzed by orthogonal partial least-squares discrimination analysis (OPLS-DA).

RESULTS

Compared with an internal standard method (ISM), the determination results obtained by QAMS had no significant difference. Twenty-two common peaks were distinguished in the fingerprint of 22 batches of QXPs, 17 of which were identified, and the similarity of the fingerprints was greater than 0.898. The 22 batches of QXPs were roughly divided into 3 categories, and 12 main markers causing the discrepancies were discovered.

CONCLUSION

The established QAMS method combined with the GC fingerprint and chemometrics is convenient and feasible, which helps to improve the quality evaluation of QXPs and provides a demonstration for the related study of compound preparations and single herbs.

HIGHLIGHTS

QAMS combined with a GC fingerprint and chemometrics method was established to evaluate the quality of QXPs for the first time.

Thorough evaluation of the Chinese medicine preparations and intermediates using high performance liquid chromatography fingerprints and ultraviolet quantum fingerprints along with antioxidant activity: Shuanghuanglian oral solution as an example

The growing global popularity of traditional Chinese medicine (TCM) has generated a growing interest in the quality control of TCM products. Shuanghuanglian Oral Liquid (SHL) is a commonly used TCM formula for treating respiratory tract infections. In this study, we present a thorough evaluation method for the quality of SHL and its intermediates. We assessed the quality through multi-wavelength fusion high-performance liquid chromatogram (HPLC) fingerprints of 40 batches of SHL samples and 15 batches of intermediates. Meanwhile, we introduced a new method called multi-markers assay by monolinear method (MAML) to quantify ten components in SHL, and revealed quality transmitting of ten components from intermediates to formulations. This information allowed us to establish a quality control system for intermediates, ensuring their quality consistency. Furthermore, we proposed UV quantum fingerprinting as an orthogonal complement to the quality evaluation by HPLC fingerprint. The relationship between fingerprinting and antioxidant capacity was also established. Overall, this study presented a novel and integrated approach for the quality evaluation of TCM products, providing valuable information for ensuring the safety and efficacy of TCM products for consumers.

Discrimination of Radix Astragali from Different Growth Patterns, Origins, Species, and Growth Years by an H1-NMR Spectrogram of Polysaccharide Analysis Combined with Chemical Pattern Recognition and Determination of Its Polysaccharide Content and Immunological Activity

The fraud phenomenon is currently widespread in the traditional Chinese medicine Radix Astragali (RA) market, especially where high-quality RA is substituted with low-quality RA. In this case, focused on polysaccharides from RA, the classification models were established for discrimination of RA from different growth patterns, origins, species, and growth years. 1H Nuclear Magnetic Resonance (H1-NMR) was used to establish the spectroscopy of polysaccharides from RA, which were used to distinguish RA via chemical pattern recognition methods. Specifically, orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were used to successfully establish the classification models for RA from different growth patterns, origins, species, and growth years. The satisfactory parameters and high accuracy of internal and external verification of each model exhibited the reliable and good prediction ability of the developed models. In addition, the polysaccharide content and immunological activity were also tested, which was evaluated by the phagocytic activity of RAW 264.7. And the result showed that growth patterns and origins significantly affected the quality of RA. However, there was no significant difference in the aspects of origins and growth years. Accordingly, the developed strategy combined with chemical information, biological activity, and multivariate statistical method can provide new insight for the quality evaluation of traditional Chinese medicine.

Advances in the treatment of pancreatic cancer with traditional Chinese medicine

Pancreatic cancer is a common malignancy of the digestive system. With a high degree of malignancy and poor prognosis, it is called the "king of cancers." Currently, Western medicine treats pancreatic cancer mainly by surgical resection, radiotherapy, and chemotherapy. However, the curative effect is not satisfactory. The application of Traditional Chinese Medicine (TCM) in the treatment of pancreatic cancer has many advantages and is becoming an important facet of comprehensive clinical treatment. In this paper, we review current therapeutic approaches for pancreatic cancer. We also review the protective effects shown by TCM in different models and discuss the potential molecular mechanisms of these.

Geographical Classification of Saffron (Crocus Sativus L.) Using Total and Synchronous Fluorescence Combined with Chemometric Approaches

There is an increasing interest in food science for high-quality natural products with a distinct geographical origin, such as saffron. In this work, the excitation-emission matrix (EEM) and synchronous fluorescence were used for the first time to geographically discriminate between Moroccan saffron from Taroudant, Ouarzazate, and Azilal. Moreover, to differentiate between Afghan, Iranian, and Moroccan saffron, a unique fingerprint was assigned to each sample by visualizing the EEM physiognomy. Moreover, principal component analysis (LDA) and linear discriminant analysis (LDA) were successfully applied to classify the synchronous spectra of samples. High fluorescence intensities were registered for Ouarzazate and Taroudant saffron. Yet, the Azilal saffron was distinguished by its low intensities. Furthermore, Moroccan, Afghan, and Iranian saffron were correctly assigned to their origins using PCA and LDA for different offsets (Δλ) (20-250 nm) such that the difference in the fluorescence composition of the three countries' saffron was registered in the following excitation/emission ranges: 250-325 nm/300-480 nm and 360-425 nm/500-550 nm. These regions are characterized by the high polyphenolic content of Moroccan saffron and the important composition of Afghan saffron, including vitamins and terpenoids. However, weak intensities of these compounds were found in Iranian saffron. Furthermore, a substantial explained variance (97-100% for PC1 and PC2) and an important classification rate (70-90%) were achieved. Thus, the non-destructive applied methodology of discrimination was rapid, straightforward, reliable, and accurate.

Comprehensive HPLC fingerprint analysis based on a two-step extraction method for quality evaluation of Perilla frutescens (L.) Britt

Abundant chemical components are key to ensure the evaluation accuracy of fingerprint analysis of traditional Chinese medicines (TCMs). A two-step extraction method combining supercritical fluid extraction (SFE) and water ultrasonic extraction was established for the quality evaluation of Perilla frutescens (L.) Britt. Weakly polar components were extracted under optimal SFE conditions (15% co-solvent (EtOH : n-hexane = 1 : 14, (v/v)), 40 °C, 250 bar, and 30 min), and polar components were subsequently extracted by an ultrasonic step (100% water as solvent, 40 °C, and 45 min). Then, HPLC methods were established, which were validated to be accurate, stable, and reliable. In this work, 25 batches of samples were evaluated and the data were analysed by similarity analysis (SA) and hierarchical cluster analysis (HCA). The similarity values of SFE extracts and aqueous extracts were respectively 0.616-0.999, and 0.252-0.997, proving the importance of the extraction method for the accuracy of the subsequent fingerprint analysis results. For the HCA, 25 samples were divided into two categories (leaves and stems), among which four batches of leaves with less similarity were considered as stems, indicating that quality differences of P. frutescens depending on medicinal parts and origin exist. The two-step extraction method developed in this work has been proved to be suitable for the quality evaluation of TCMs with complex compositions.

Quality assessment of traditional Chinese medicine based on data fusion combined with machine learning: A review

The authenticity and quality of traditional Chinese medicine (TCM) directly impact clinical efficacy and safety. Quality assessment of traditional Chinese medicine (QATCM) is a global concern due to increased demand and shortage of resources. Recently, modern analytical technologies have been extensively investigated and utilized to analyze the chemical composition of TCM. However, a single analytical technique has some limitations, and judging the quality of TCM only from the characteristics of the components is not enough to reflect the overall view of TCM. Thus, the development of multi-source information fusion technology and machine learning (ML) has further improved QATCM. Data information from different analytical instruments can better understand the connection between herbal samples from multiple aspects. This review focuses on the use of data fusion (DF) and ML in QATCM, including chromatography, spectroscopy, and other electronic sensors. The common data structures and DF strategies are introduced, followed by ML methods, including fast-growing deep learning. Finally, DF strategies combined with ML methods are discussed and illustrated for research on applications such as source identification, species identification, and content prediction in TCM. This review demonstrates the validity and accuracy of QATCM-based DF and ML strategies and provides a reference for developing and applying QATCM methods.

Quantitative fingerprint and antioxidative properties of Artemisia argyi leaves combined with chemometrics

Quantitative fingerprint and differences of Artemisia argyi from different varieties, picking time, aging year, and origins were analyzed combing with chemometrics. The antioxidant activity was determined and antioxidant markers of Artemisia argyi were screened. Variety WA3 was significantly different from that of the other varieties. Fingerprint peak response and antioxidant activity of A. argyi picked in December were lower than samples collected in May and August. Fresh A. argyi leaves were significantly superior to withered leaves and stems. Artemisia argyi aging 1-5 years presented a classification trend. Antioxidant activity of A. argyi produced in Nanyang was generally superior to others origins. Peak 9, isochlorogenic acid A, and 6-methoxyluteolin contributed greatly for classification of A. argyi from different variety, picking time, aging year, and origin. Isochlorogenic acid A, isochlorogenic acid C, 6-methoxyluteolin, and chlorogenic acid were selected as antioxidant marker of A. argyi. The method based on quantitative fingerprint, antioxidant activity evaluation, and chemometrics was reliable to analyze the differences of A. argyi samples from different sources.

Multiple approaches to characterize and visualize the chemical composition of Sijunzi Decoction comprehensively

Sijunzi Decoction is composed of Ginseng Radix et Rhizoma, Atractylodes Macrocephalae Rhizoma, Poria, and Glycyrrhizae Radix Et Rhizoma Praeparata Cum Melle, and it is a classic formula for treating spleen deficiency syndrome in Chinese medicine. Clarifying the active substances is an effective way to develop Traditional Chinese medicine and innovative medicines. Carbohydrates, proteins, amino acids, saponins, flavonoids, phenolic acids, and inorganic elements in the decoction were analyzed by multiple approaches. A molecular network was also used for visualizing the ingredients in Sijunzi Decoction, and representative components were also quantified. The detected components accounted for 74.544% of the Sijunzi Decoction freeze-dried powder, including 41.751% crude polysaccharides, 17.826% sugars (degree of polymerization 1-2), 8.181% total saponins, 2.427% insoluble precipitates, 2.154% free amino acids, 1.177% total flavonoids, 0.546% total phenolic acids, and 0.483% inorganic elements. Molecular network and quantitative analysis used to characterize the chemical composition of Sijunzi Decoction. The present study systematically characterized the constituents of Sijunzi Decoction, revealed the composition ratio of each type of constituent, and provided a reference for study on the substance basis of other Chinese medicine.

An in silico and in vitro integrated analysis method to reveal the curative mechanisms and pharmacodynamic substances of Bufei granule on chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease with high disability and mortality. Clinical studies have shown that the Traditional Chinese Medicine Bufei Granule (BFG) has conspicuous effects on relieving cough and improving lung function in patients with COPD and has a reliable effect on the treatment of COPD, whereas the therapeutic mechanism is vague. In the present study, the latent bronchodilators and mechanism of BFG in the treatment of COPD were discussed through the method of network pharmacology. Then, the molecular docking and molecular dynamics simulation were performed to calculate the binding efficacy of corresponding compounds in BFG to muscarinic receptor. Finally, the effects of BFG on bronchial smooth muscle were validated by in vitro experiments. The network pharmacology results manifested the anti-COPD effect of BFG was mainly realized via restraining airway smooth muscle contraction, activating cAMP pathways and relieving oxidative stress. The results of molecular docking and molecular dynamics simulation showed alpinetin could bind to cholinergic receptor muscarinic 3. The in vitro experiment verified both BFG and alpinetin could inhibit the levels of CHRM3 and acetylcholine and could be potential bronchodilators for treating COPD. This study provides an integrating network pharmacology method for understanding the therapeutic mechanisms of traditional Chinese medicine, as well as a new strategy for developing natural medicines for treating COPD.

Rapid quality evaluation of Chinese herbal medicines using a miniature mass spectrometer: Lygodium japonicum (Thunb.) Sw. as an example

The quality of Chinese herbal medicine (CHM) raw materials is essential, and mass spectrometry (MS)-based technologies have been playing key roles in the quality control of CHMs. However, the use of miniature mass spectrometry (mini-MS) for quality control of CHMs has rarely been reported. In this work, we developed a rapid analytical method for the quality evaluation of CHMs based on paper spray ionization (PSI)-mini-MS/MS. The quality evaluation of Lygodium japonicum (Thunb.) Sw. was used as an example. Following a "multi-component" quality evaluation strategy, nine active constituents of L. japonicum were selected to be used as analytes for quality control. We confirmed that the precursor-product ion information in the MS/MS spectra of each analyte in the herbal extracts was consistent with the standards. Also, we developed a mini-MS-based quantitative method for each analyte using its quantification ion. The quantitative methodology was rigorously validated using quality control samples. Finally, the quality evaluation of L. japonicum was carried out using the established MS/MS method combined with statistical analysis. A wide range of common quality issues with L. japonicum can be effectively determined, including whether it is adulterated with sand and distinguishing among different parts and species. This study demonstrates that mini-MS for quality evaluation of CHMs is feasible. Mini-MS for quality evaluation of herbal medicines will potentially have a good prospect due to its many advantages such as low cost, low power consumption, and portability in the future.

A Focused Review on Cognitive Improvement by the Genus Salvia L. (Sage)-From Ethnopharmacology to Clinical Evidence

Ethnopharmacology has been an important starting point in medical and pharmaceutical sciences for discovering drug candidates from natural sources. In this regard, the genus Salvia L., commonly known as sage, is one of the best-known medicinal and aromatic plants of the Lamiaceae family; it has been recorded as being used for memory enhancement in European folk medicine. Despite the various uses of sage in folk medicines, the records that have pointed out sage's memory-enhancing properties have paved the way for the aforementioned effect to be proven on scientific grounds. There are many preclinical studies and excellent reviews referring to the favorable effect of different species of sage against the cognitive dysfunction that is related to Alzheimer's disease (AD). Hence, the current review discusses clinical studies that provide evidence for the effect of Salvia species on cognitive dysfunction. Clinical studies have shown that some Salvia species, i.e., hydroalcoholic extracts and essential oils of S. officinalis L. and S. lavandulaefolia leaves in particular, have been the most prominently effective species in patients with mild to moderate AD, and these species have shown positive effects on the memory of young and healthy people. However, the numbers of subjects in the studies were small, and standardized extracts were not used for the most part. Our review points out to the need for longer-term clinical studies with higher numbers of subjects being administered standardized sage preparations.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS), part II. Recent noteworthy developments

This comprehensive survey review compiles noteworthy developments and new concepts of two-dimensional correlation spectroscopy (2D-COS) for the last two years. It covers review articles, books, proceedings, and numerous research papers published on 2D-COS, as well as patent and publication trends. 2D-COS continues to evolve and grow with new significant developments and versatile applications in diverse scientific fields. The healthy, vigorous, and diverse progress of 2D-COS studies in many fields strongly confirms that it is well accepted as a powerful analytical technique to provide an in-depth understanding of systems of interest.

Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives

Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.

ResNet Model Automatically Extracts and Identifies FT-NIR Features for Geographical Traceability of Polygonatum kingianum

Medicinal plants have incredibly high economic value, and a practical evaluation of their quality is the key to promoting industry development. The deep learning model based on residual convolutional neural network (ResNet) has the advantage of automatic extraction and the recognition of Fourier transform near-infrared spectroscopy (FT-NIR) features. Models are difficult to understand and interpret because of unknown working mechanisms and decision-making processes. Therefore, in this study, artificial feature extraction methods combine traditional partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) models to understand and compare deep learning models. The results show that the ResNet model has significant advantages over traditional models in feature extraction and recognition. Secondly, preprocessing has a great impact on the feature extraction and feature extraction, and is beneficial for improving model performance. Competitive adaptive reweighted sampling (CARS) and variable importance in projection (VIP) methods screen out more feature variables after preprocessing, but the number of potential variables (LVs) and successive projections algorithm (SPA) methods obtained is fewer. The SPA method only extracts two variables after preprocessing, causing vital information to be lost. The VIP feature of traditional modelling yields the best results among the four methods. After spectral preprocessing, the recognition rates of the PLS-DA and SVM models are up to 90.16% and 88.52%. For the ResNet model, preprocessing is beneficial for extracting and identifying spectral image features. The ResNet model based on synchronous two-dimensional correlation spectra has a recognition accuracy of 100%. This research is beneficial to the application development of the ResNet model in foods, spices, and medicinal plants.

Detection of Saffron’s Main Bioactive Compounds and Their Relationship with Commercial Quality

This review aims to evaluate the state of saffron’s main bioactive compounds and their relationship with its commercial quality. Saffron is the commercial name for the dried red stigmas of the Crocus sativus L. flower. It owes its sensory and functional properties mainly to the presence of its carotenoid derivatives, synthesized throughout flowering and also during the whole production process. These compounds include crocin, crocetin, picrocrocin, and safranal, which are bioactive metabolites. Saffron’s commercial value is determined according to the ISO/TS3632 standard that determines their main apocatotenoids. Other techniques such as chromatography (gas and liquid) are used to detect the apocarotenoids. This, together with the determination of spectral fingerprinting or chemo typing are essential for saffron identification. The determination of the specific chemical markers coupled with chemometric methods favors the discrimination of adulterated samples, possible plants, or adulterating compounds and even the concentrations at which these are obtained. Chemical characterization and concentration of various compounds could be affected by saffron’s geographical origin and harvest/postharvest characteristics. The large number of chemical compounds found in the by-products (flower parts) of saffron (catechin, quercetin, delphinidin, etc.) make it an interesting aromatic spice as a colorant, antioxidant, and source of phytochemicals, which can also bring additional economic value to the most expensive aromatic species in the world.

Application of Analytical Technologies in the Discrimination and Authentication of Herbs from Fritillaria: A Review

Medicinal plants of Fritillaria are widely distributed in numerous countries around the world and possess excellent antitussive and expectorant effects. In particular, Fritillariae Bulbus (FB) as a precious traditional medicine has thousands of years of medical history in China. Herbs of Fritillaria have a high market value and demand while limited by harsh growing circumstances and scarce wild resources. As a consequence, fraudulent behaviors are regularly engaged by the unscrupulous merchants in an attempt to reap greater profits. It is of an urgent need to evaluate the quality of Fritillaria herbs and their products using various analytical instruments and techniques. This review has scrutinized approximately 160 articles from 1995 to 2022 published on the investigation of Fritillaria herbs and related herbal products. The botanical classification of genus Fritillaria, types of counterfeits, technologies applied for differentiating Fritillaria species were comprehensively summarized and discussed in the current review. Molecular and chromatographic identification were the dominant technologies in the authentication of Fritillaria herbs. Additionally, we brought some potential and promising technologies and analytical strategies into attention, which are worthy attempting in the future researches. This review could conduce to excellent reference value for further investigations of the authenticity assessment of Fritillaria species.

Review of Recent Modern Analytical Technology Combined with Chemometrics Approach Researches on Mushroom Discrimination and Evaluation

Mushroom is a macrofungus with precious fruiting body, as a food, a tonic, and a medicine, human have discovered and used mushrooms for thousands of years. Nowadays, mushroom is also a "super food" recommended by the World Health Organization (WHO) and Food and Agriculture Organization (FAO), and favored by consumers. Discrimination of mushroom including species, geographic origin, storage time, etc., is an important prerequisite to ensure their edible safety and commodity quality. Moreover, the effective evaluation of its chemical composition can help us better understand the nutritional properties of mushrooms. Modern analytical technologies such as chromatography, spectroscopy and mass spectrometry, etc., are widely used in the discrimination and evaluation researches of mushrooms, and chemometrics is an effective means of scientifically processing the multidimensional information hidden in these analytical technologies. This review will outline the latest applications of modern analytical technology combined with chemometrics in qualitative and quantitative analysis and quality control of mushrooms in recent years. Briefly describe the basic principles of these technologies, and the analytical processes of common chemometrics in mushroom researches will be summarized. Finally, the limitations and application prospects of chromatography, spectroscopy and mass spectrometry technology are discussed in mushroom quality control and evaluation.

Electrochemical-based quantitative fingerprint evaluation strategy combined with multi-markers assay by monolinear method for quality control of herbal medicine

BACKGROUND

Improving the quality control (QC) criterion of herbal medicine (HM) is an ongoing challenge. A rapid and convenient electrochemical analysis technique is now emerging as a promising application for HM QC. So far, extraction and analysis of the overall electroactive components is a key issue need to be solved to improve its application in integral HM QC.

PURPOSE

In this work, using compound liquorice tablets (CLQTs) as an example, we like to put forward a more reliable and accurate quantification method of multi-components for the precise QC of HM. Furthermore, we propose an electrochemical fingerprint-based data mining, extract and synthesis strategy for in-depth and comprehensive QC of HM, qualitatively and quantitatively.

METHODS AND DESIGN

Firstly, the electrochemical quantitative fingerprint of 54 batches of CLQTs from nine manufacturers were developed using B-Z oscillatory system. Secondly, eight characteristic parameters were recorded and compared among samples using intuitive information and PCA. Then, t_und was used to establish the correlation with sample dosage for determination of the relative content of overall electroactive components (Rc). The quantitative determination of five quality markers (Q-markers) were also performed using the novel method, called multi-markers assay by monolinear method (MAML). Finally, after using area integral calculus for electrochemical fingerprint, average linear quantitative fingerprint method (ALQFM) was successfully proposed to extract all latent characteristics for integral quality evaluation of samples.

RESULTS

The t_und and dosage showed a good correlation, by which the obtained Rc displayed different fluctuation among nine manufacturers. Moreover, the contents of five Q-markers obtained by MAML displayed no significant difference with the traditional quantification method. Samples evaluated by ALQFM manifested the integral information and were divided into eight quality grades. The deduced results of correlation between P_l with P_5C, Rc and P_A were more persuasive for demonstrating the reliability and integrity of ALQFM in quality evaluation of HM electrochemical fingerprint.

CONCLUSION

The study confirmed the idea that quantification of Q-markers combined electrochemical-based quality evaluation strategy could be used as a reliable method for HM QC qualitatively and quantitatively from point (precise) to face (integral).

Anticoagulant activity analysis and origin identification of Panax notoginseng using HPLC and ATR-FTIR spectroscopy

INTRODUCTION

Panax notoginseng is one of the traditional precious and bulk-traded medicinal materials in China. Its anticoagulant activity is related to its saponin composition. However, the correlation between saponins and anticoagulant activities in P. notoginseng from different origins and identification of the origins have been rarely reported.

OBJECTIVES

We aimed to analyze the correlation of components and activities of P. notoginseng from different origins and develop a rapid P. notoginseng origin identification method.

MATERIALS AND METHODS

Pharmacological experiments, HPLC, and ATR-FTIR spectroscopy (variable selection) combined with chemometrics methods of P. notoginseng main roots from four different origins (359 individuals) in Yunnan Province were conducted.

RESULTS

The pharmacological experiments and HPLC showed that the saponin content of P. notoginseng main roots was not significantly different. It was the highest in main roots from Wenshan Prefecture (9.86%). The coagulation time was prolonged to observe the strongest effect (4.99 s), and the anticoagulant activity was positively correlated with the contents of the three saponins. The content of ginsenoside Rg₁ had the greatest influence on the anticoagulant effect. The results of spectroscopy combined with chemometrics show that the variable selection method could extract a small number of variables containing valid information and improve the performance of the model. The variable importance in projection has the best ability to identify the origins of P. notoginseng; the accuracy of the training set and the test set was 0.975 and 0.984, respectively.

CONCLUSION

This method is a powerful analytical tool for the activity analysis and identification of Chinese medicinal materials from different origins.