Molecular differentiation of Panax notoginseng grown under different conditions by internal extractive electrospray ionization mass spectrometry and multivariate analysis

Geographical discrimination of dried chili peppers using femtosecond laser ablation-inductively coupled plasma-mass spectrometry (fsLA-ICP-MS)

This study presents a method for discriminating the geographical origin of dried chili peppers using femtosecond laser ablation-inductively coupled plasma-mass spectrometry (fsLA-ICP-MS) and multivariate analysis, such as orthogonal partial least squares discriminant analysis (OPLS-DA), heatmap analysis, and canonical discriminant analysis (CDA). Herein, 102 samples were analyzed for the content of 33 elements using optimized conditions of 200 Hz (repetition rate), 50 μm (spot size), and 90% (energy). Significant differences in count per second (cps) values of the elements were observed between domestic and imported peppers, with variations of up to 5.66 times (¹³³Cs). The OPLS-DA model accuracy achieved an R² of 0.811 and a Q² of 0.733 for distinguishing dried chili peppers of different geographical origins. The variable importance in projection (VIP) and s-plot identified elements 10 and 3 as key to the OPLS-DA model, and in the heatmap, six elements were estimated to be significant in discriminating between domestic and imported samples. Furthermore, CDA showed a high accuracy of 99.02%. This method can ensure food safety for consumers, and accurately determine the geographic origin of agricultural products.

Metabolite Fingerprinting for Identification of Panax ginseng Metabolites Using Internal Extractive Electrospray Ionization Mass Spectrometry

Ginseng, a kind of functional food and medicine with high nutritional value, contains various pharmacological metabolites that influence human metabolic functions. Therefore, it is very important to analyze the composition and metabolites of ginseng. However, the analysis of active metabolites in ginseng samples usually involves various experimental steps, such as extraction, chromatographic separation, and characterization, which may be time-consuming and laborious. In this study, an internal extractive electrospray ionization mass spectrometry (iEESI-MS) method was developed to analyze active metabolites in ginseng samples with sequential sampling and no pretreatment. A total of 44 metabolites, with 32 ginsenosides, 6 sugars, and 6 organic acids, were identified in the ginseng samples. The orthogonal partial least-squares discriminant analysis (OPLS-DA) score plot showed a clear separation of ginseng samples from different origins, indicating that metabolic changes occurred under different growing conditions. This study demonstrated that different cultivation conditions of ginseng can be successfully discriminated when using iEESI-MS-based metabolite fingerprints, which provide an alternative solution for the quality identification of plant drugs.

Rapid authentication of different herbal medicines by heating online extraction electrospray ionization mass spectrometry

The rapid and accurate authentication of traditional Chinese medicines (TCMs) has always been a key scientific and technical problem in the field of pharmaceutical analysis. Herein, a novel heating online extraction electrospray ionization mass spectrometry (H-oEESI-MS) was developed for the rapid and direct analysis of extremely complex substances without the requirement for any sample pretreatment or pre-separation steps. The overall molecular profile and fragment structure features of various herbal medicines could be completely captured within 10-15 s, with minimal sample (<0.5 mg) and solvent consumption (<20 μL for one sample). Furthermore, a rapid differentiation and authentication strategy for TCMs based on H-oEESI-MS was proposed, including metabolic profile characterization, characteristic marker screening and identification, and multivariate statistical analysis model validation. In an analysis of 52 batches of seven types of Aconitum medicinal materials, 20 and 21 key compounds were screened out as the characteristic markers of raw and processed Aconitum herbal medicines, respectively, and the possible structures of all the characteristic markers were comprehensively identified based on Compound Discoverer databases. Finally, multivariate statistical analysis showed that all the different types of herbal medicines were well differentiated and identified (R²X > 0.87, R²Y > 0.91, and Q² > 0.72), which further verified the feasibility and reliability of this comprehensive strategy for the rapid authentication of different TCMs based on H-oEESI-MS. In summary, this rapid authentication strategy realized the ultra-high-throughput, low-cost, and standardized detection of various complex TCMs for the first time, thereby demonstrating wide applicability and value for the development of quality standards for TCMs.

Advances in Fingerprint Analysis for Standardization and Quality Control of Herbal Medicines

Herbal drugs or herbal medicines (HMs) have a long-standing history as natural remedies for preventing and curing diseases. HMs have garnered greater interest during the past decades due to their broad, synergistic actions on the physiological systems and relatively lower incidence of adverse events, compared to synthetic drugs. However, assuring reproducible quality, efficacy, and safety from herbal drugs remains a challenging task. HMs typically consist of many constituents whose presence and quantity may vary among different sources of materials. Fingerprint analysis has emerged as a very useful technique to assess the quality of herbal drug materials and formulations for establishing standardized herbal products. Rather than using a single or two marker(s), fingerprinting techniques take great consideration of the complexity of herbal drugs by evaluating the whole chemical profile and extracting a common pattern to be set as a criterion for assessing the individual material or formulation. In this review, we described and assessed various fingerprinting techniques reported to date, which are applicable to the standardization and quality control of HMs. We also evaluated the application of multivariate data analysis or chemometrics in assisting the analysis of the complex datasets from the determination of HMs. To ensure that these methods yield reliable results, we reviewed the validation status of the methods and provided perspectives on those. Finally, we concluded by highlighting major accomplishments and presenting a gap analysis between the existing techniques and what is needed to continue moving forward.