An integrated and rapid evaluation of Curcumae Radix from different botanical origins based on chemical components, antiplatelet aggregation effect and Fourier transform near-infrared spectroscopy.

Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.

Revealing the Mechanisms of Qilongtian Capsules in the Treatment of Chronic Obstructive Pulmonary Disease Based on Integrated Network Pharmacology, Molecular Docking, and In Vivo Experiments.

The Qilongtian capsule (QLT) is a Chinese patent medicine that has been approved for the treatment of chronic obstructive pulmonary disease (COPD). However, the precise pharmacodynamic material basis and molecular mechanism have not been well illustrated. In this study, we identified the effect of QLT on COPD through a cigarette smoke extract (CSE)/lipopolysaccharide (LPS) induced COPD mice model. The absorption of blood components in QLT were identified using ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Network pharmacology was used to predict the potential targets and therapeutic mechanisms of QLT, which were further validated using in vivo experiments and molecular docking. Pharmacodynamic studies revealed that QLT could ameliorate pulmonary function and pulmonary pathology, reduce collagen fiber accumulation, and attenuate inflammatory responses in mice with CSE/LPS induced COPD. A total of 21 components of QLT absorbed in the blood were detected. Network pharmacology analysis indicated that TNF, IL-6, EGFR, and AKT1 may be the core targets, mainly involving the MAPK signaling pathway. Besides, Sachaloside II, Ginsenoside Rh1, Ginsenoside F1, Rosiridin, and Ginsenoside Rf were the key compounds. Molecular docking results showed that the key components could spontaneously bind to EGFR and MAPK to form a relatively stable conformation. In vivo experiments revealed that QLT could suppress the activation of the EGFR/MAPK signaling pathway, thereby improving lung injury in mice with COPD. Overall, these findings provide evidence for the treatment of COPD with QLT.

Study on the mechanism of hepatotoxicity of Aucklandiae radix through liver metabolomics and network pharmacology.

Background: Aucklandiae Radix (CAR) and its roasted processed products (PAR) are extensively used in various Chinese patent medicines due to their diverse pharmacological activities. However, numerous side effects of CAR have been reported and the hepatotoxicity and the corresponding mechanisms have not been thoroughly investigated. Our study aims to explore the underlying mechanism of the hepatotoxic impacts of CAR. Methods: In this study, metabolomic analysis was performed using liver tissue from the mice administered with different dosages of CAR/PAR extracts to examine the hepatotoxic impacts of CAR and elucidate the underlying mechanism. Network pharmacology was employed to predict the potential molecular targets and associated signaling pathways based on the distinctive compounds between CAR and PAR. A composition-target-GO-Bio process-metabolic pathway network was constructed by integrating the hepatotoxicity-related metabolic pathways. Finally, the target proteins related with the hepatotoxic effect of CAR were identified and validated in vivo. Results: The metabolomics analysis revealed that 33 related metabolic pathways were significantly altered in the high-dose CAR group, four of which were associated with the hepatotoxicity and could be alleviated by PAR. The network identified NQO1 as the primary target of the hepatotoxic effect induced by CAR exposure, which was subsequently verified by Western Blotting. Further evidence in vivo demonstrated that Nrf2 and HO-1, closely related to NQO1, were also the main targets through which CAR induced the liver injury, and that oxidative stress should be the primary mechanism for the CAR-induced hepatotoxicity. Conclusions: This preliminary study on the hepatic toxic injury of CAR provides a theoretical basis for the rational and safe use of CAR rationally and safely in clinical settings.

Establishment of an antiplatelet aggregation efficacy-oriented effect-constituent index for quality evaluation of Curcumae Rhizoma from different species (Curcuma phaeocaulis Val, Curcuma kwangsiensis S. G. Lee et C. F. Liang and Curcuma wenyujin Y. H. Chen et C. Ling).

Curcumae rhizoma (CR) is the dried rhizoma of Curcuma phaeocaulis Val (CP), Curcuma kwangsiensis S. G. Lee et C. F. Liang (CK) and Curcuma wenyujin Y. H. Chen et C. Ling (CW), used widely to treat blood stagnation in China. Currently, quality control indicators for CR are limited to chemical composition analysis. It is unclear whether the current quality standard of the multicomponent content of CR can reflect clinical effects, due to the lack of the evaluation of biological effects. A method of evaluating quality was developed called the effect-constituent index (ECI). By meticulously measuring and calibrating the key active components, the ECI offers a comprehensive assessment of the CR's biological effects, establishing a crucial link to clinical efficacy and safety. An analytical protocol employing high-performance liquid chromatography (HPLC) was devised to ascertain the presence and measure ten principal constituents within CR sourced from various species and the content of total volatile oil was also measured. An In vitro antiplatelet aggregation assay was developed to measure the antiplatelet aggregation biopotencies of thirty batches of CR and ten main components. Then, the calibration weights for each constituent in the ECI were determined based on the antiplatelet aggregation biopotency values of eight components with notable efficacy. The ECI calculation involved summing the products obtained by multiplying the content (Ci) of each component by its corresponding biopotency weight (Wi). Correlation analysis unveiled a the most robust correlation (R = 0.8579, p < 0.001) between ECI and antiplatelet aggregation biopotency of CR, when compared to individual components or volatile oil content. The devised ECI, synthesizing chemical and biological data pertinent to clinical effectiveness, facilitates a nuanced assessment of CR quality across various species in its efficacy in treating blood stagnation. This method addresses the challenge of guaranteeing effectiveness through chemical analysis alone. This study offers substantiation for the applicability of the ECI as a tool for assessing the quality of traditional Chinese medicine (TCM).

Study on the quality difference between raw and ginger juice processed Magnoliae officinalis cortex by UPLC-Q-TOF-MS/MS and GC-MS coupled with color measurement.

INTRODUCTION: Magnoliae officinalis cortex (MOC) has been used for thousands of years as a traditional Chinese herb. In Chinese Pharmacopoeia (2020 edition), it has two types of decoction pieces, raw Magnoliae officinalis cortex (RMOC) and ginger juice processed Magnoliae officinalis cortex (GMOC). The quality difference between RMOC and GMOC has not been explored systemically. OBJECTIVE: This study aimed to discover the quality difference between RMOC and GMOC, and clarify the effect of ginger juice during processing comprehensively. METHODS: Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) and gas chromatography-mass spectrometry (GC-MS) were applied to study the non-volatile and volatile components of RMOC and GMOC; electronic eye was applied for color measurement. Meanwhile, water processed Magnoliae officinalis cortex (WMOC) was studied as the blank sample. RESULTS: There were 155 non-volatile and 72 volatile substances identified. Between RMOC and GMOC, 29 distinctive non-volatile and 34 distinctive volatile compounds were detected, among which 23 new compounds appeared and five compounds disappeared due to the addition of ginger juice during processing. The intensities of 12 common non-volatile compounds and the relative percentage contents of four common volatile compounds showed significant differences between RMOC and GMOC. In color measurement of RMOC, GMOC, and WMOC, 14 common compounds with significant differences were discovered related to their color values, and their mathematical prediction functions were built. CONCLUSION: There were significant differences between RMOC and GMOC; the processing mechanism of GMOC would be carried out based on the differential compounds in further investigation.

Structural analysis and blood-enriching effects comparison based on biological potency of Angelica sinensis polysaccharides.

Angelica sinensis is a long-standing medicine used by Chinese medical practitioners and well-known for its blood-tonic and blood-activating effects. Ferulic acid, ligustilide, and eugenol in Angelica sinensis activate the blood circulation; however, the material basis of their blood-tonic effects needs to be further investigated. In this study, five homogeneous Angelica sinensis polysaccharides were isolated, and their sugar content, molecular weight, monosaccharide composition, and infrared characteristics determined. Acetylphenylhydrazine (APH) and cyclophosphamide (CTX) were used as inducers to establish a blood deficiency model in mice, and organ indices, haematological and biochemical parameters were measured in mice. Results of in vivo hematopoietic activity showed that Angelica sinensis polysaccharide (APS) could elevate erythropoietin (EPO), granulocyte colony-stimulating factor (G-CSF), and interleukin-3 (IL-3) serum levels, reduce tumor necrosis factor-α (TNF-α) level in mice, and promote hematopoiesis in the body by regulating cytokine levels. Biological potency test results of the in vitro blood supplementation indicated strongest tonic activity for APS-H2O, and APS-0.4 has the weakest haemopoietic activity. The structures of APS-H2O and APS-0.4 were characterized, and the results showed that APS-H2O is an arabinogalactan glycan with a main chain consisting of α-1,3,5-Ara(f), α-1,5- Ara(f), ß-1,4-Gal(p), and ß-1,4-Gal(p)A, and two branched chains of ß-t-Gal(p) and α-t-Glc(p) connected to each other in a (1→3) linkage to α-1,3,5-Ara(f) on the main chain. APS-0.4 is an acidic polysaccharide with galacturonic acid as the main chain, consisting of α-1,4-GalA, α-1,2-GalA, α-1,4-Gal, and ß-1,4-Rha. In conclusion, APS-H2O can be used as a potential drug for blood replenishment in patients with blood deficiency, providing a basis for APS application in clinical treatment and health foods, as well as research and development of new polysaccharide-based drugs.

Polygonati Rhizoma varieties and origins traceability based on multivariate data fusion combined with an artificial intelligence classification algorithm.

This study collected multidimensional feature data such as spectra, texture, and component contents of Polygonati Rhizoma from different origins and varieties (Polygonatum kingianum Coll. et Hemsl from Yunnan and Guizhou; Polygonatum cyrtonema Hua from Anhui and Jiangxi; Polygonatum sibiricum Red from Hunan). Multivariate statistical analysis was used to select 39 characteristic factors for distinguishing PR origins and 14 characteristic factors for discriminating PR varieties (VIP > 1 and P < 0.05). In addition, by combining multivariate statistical analysis with a deep belief network (DBN) classification algorithm, a novel artificial intelligence algorithm was developed and optimized. Compared to traditional discriminant analysis methods, the accuracy of this new approach was significantly improved, achieving a 100% discrimination rate for PR varieties and a 100% accuracy rate for tracing the origin of PR. This research provides a reference and data support for constructing intelligent algorithms based on multidimensional data fusion, to achieve food variety discrimination and origin tracing.

Discrimination between raw and ginger juice processed Fructus Gardeniae based on UHPLC-Q-TOF-MS and Heracles NEO ultra-fast gas phase electronic nose.

INTRODUCTION: Fructus Gardeniae (ZZ), a traditional Chinese herb, has been used in treating patients with jaundice, inflammation, etc. When mixed with ginger juice and stir-baked, ginger juice-processed Fructus Gardeniae (JZZ) is produced, and the chemical compositions in ZZ would be changed by adding the ginger juice. OBJECTIVE: To illuminate the differential components between ZZ and JZZ. METHODS: HPLC, UHPLC-Q-TOF-MS, and Heracles NEO ultra-fast gas phase electronic nose were applied to identify the differential components between ZZ and JZZ. RESULTS: HPLC fingerprints of ZZ and JZZ were established, and 24 common peaks were found. The content determination results showed that the contents of shanzhiside, geniposidic acid, genipin-1-ß-D-gentiobioside and geniposide increased, while the contents of crocin I and crocin II decreased in JZZ. By UHPLC-Q-TOF-MS, twenty-six possible common components were inferred, among which 11 components were different. In further investigation, eight components were identified as the possible distinctive non-volatile compounds between ZZ and JZZ. By Heracles NEO ultra-fast gas phase electronic nose, four substances were inferred as the possible distinctive volatile compounds in JZZ. CONCLUSION: Shanzhiside, caffeic acid, genipin-1-ß-D-gentiobioside, geniposide, rutin, crocin I, crocin II, and 4-Sinapoyl-5-caffeoylquinic acid were identified as the possible differential non-volatile components between ZZ and JZZ. Aniline, 3-methyl-3-sulfanylbutanol-1-ol, E-3-octen-2-one, and decyl propaonate were inferred as the possible distinctive volatile compounds in JZZ. This experiment explored a simple approach with objective and stable results, which would provide new ideas for studying decoction pieces with similar morphological appearance, especially those with different odors.

[Charcoal-frying process and quality markers of Sanguisorbae Radix based on hemostatic effect].

Studies have reported that the hemostatic effect of Sanguisorbae Radix(SR) is significantly enhanced after processing with charcoal. However, the standard components(tannins and gallic acid) specified in the Chinese Pharmacopeia decrease in charcoal-fried Sanguisorbae Radix(CSR), which is contrast to the enhancement of the hemostatic effect. Therefore, this study aimed to optimize the charcoal-frying process of SR based on its hemostatic efficacy and comprehensively analyze the components of SR and its processed products, thus exploring the material basis for the hemostatic effect. The results indicated that SR processed at 250 ℃ for 14 min(14-min CSR) not only complied with the description in the Chinese Pharmacopeia but also demonstrated improved blood-coagulating and blood-adsorbing effects compared with raw SR(P<0.05). Moroever, 14-min CSR reduced the bleeding time in the rat models of tail snipping, liver bleeding, and muscle injury, surpassing both raw and excessively fried SR(16 min processed) as well as tranexamic acid(P<0.05). Ellagitannin, ellagic acid, methyl gallate, pyrogallic acid, protocatechuic acid, Mg, Ca, Mn, Cu, and Zn contributed to the hemostatic effect of CSR over SR. Among these substances, ellagitannin, ellagic acid, Mg, and Ca had high content in the 14 min CSR, reaching(106.73±14.87),(34.86±4.43),(2.81±0.23), and(1.21±0.23) mg·g~(-1), respectively. Additionally, the color difference value(ΔE~*ab) of SR processed to different extents was correlated with the content of the aforementioned hemostatic substances. In summary, this study optimized the charcoal-frying process as 250 ℃ for 14 min for SR based on its hemostatic effect. Furthermore, ellagic acid and/or the powder chromaticity are proposed as indicators for the processing and quality control of CSR.

Research on quality marker based on the processing from Aconiti lateralis radix praeparata to Heishunpian.

INTRODUCTION: Aconiti lateralis radix praeparata (ALRP), the sub root of Aconitum carmichaelii Debx., is a traditional Chinese medicine with good pharmacological effects. Heishunpian (HSP), prepared through the process of brine immersing, boiling, rinsing, dyeing, and steaming ALRP is one of the most widely used forms of decoction pieces in clinical practice. OBJECTIVES: This study aims to investigate the mechanisms of component changes and transformations during the processing from ALRP to HSP, and to screen for their quality markers through UHPLC-QTOF-MS analysis. METHODS: Samples from ALRP to HSP during processing were prepared and analyzed by UHPLC-QTOF-MS. By comparing the differences between before and after each processing step, the purpose of processing and the transformation of components during processing were studied. In addition, multiple batches of ALRP and HSP were determined, and potential quality markers were screened. RESULTS: Through the analysis of ALRP and five key processing samples, 55 components were identified. Immersing in brine, rinsing, and dyeing were the main factors of component loss, and boiling caused a slight loss of components. Some components were enhanced during the steaming process. Combining the screened differences components between multiple ALRP and HSP, 10 components were considered as potential quality biomarkers. CONCLUSION: This study found that the adjacent hydroxyl groups of the ester group may have a positive impact on the hydrolysis of the ester group, and 10 quality markers were preliminarily screened. It provides a reference for quality control and clinical application of ALRP and HSP.

Exploring the effective components of honey-processed licorice (Glycyrrhiza uralensis Fisch.) in attenuating Doxorubicin-induced myocardial cytotoxicity by combining network pharmacology and in vitro experiments.

ETHNOPHARMACOLOGICAL RELEVANCE: Licorice is widely used clinically as one of the most famous traditional Chinese herbs. Its herb roasted with honey is called honey-processed licorice (HPL). Modern studies have shown that HPL has a stronger cardioprotective ability compared to raw licorice (RL), however the material basis and mechanism of action of the potential cardioprotection have not been fully elucidated. AIM OF THE STUDY: To screen and validate the material basis of cardioprotection exerted by HPL and to preliminarily predict the potential mechanism of action. MATERIALS AND METHODS: UPLC-QTOF-MS/MS was used to analyze HPL samples with different processing levels, and differential compounds were screened out through principal component analysis. Network pharmacology and molecular docking were applied to explore the association between differential compounds and doxorubicin cardiomyopathy and their mechanisms of action were predicted. An in vitro model was established to verify the cardioprotective effects of differential compounds. RESULTS: Six differential compounds were screened as key components of HPL for potential cardioprotection. Based on network pharmacology, 113 potential important targets for the treatment of Dox-induced cardiotoxicity were screened. KEGG enrichment analysis predicted that the PI3K-Akt pathway was closely related to the mechanism of action of active ingredients. Molecular docking results showed that the six differential compounds all had good binding activity with Nrf2 protein. In addition, in vitro experiments had shown that five of the active ingredients (liquiritin, isoliquiritin, liquiritigenin, isoliquiritigenin, and licochalcone A) can significantly increase Dox-induced H9c2 cell viability, SOD activity, and mitochondrial membrane potential, significantly reduces MDA levels and inhibits ROS generation. CONCLUSION: Liquiritin, isoliquiritin, liquiritigenin, isoliquiritigenin and licochalcone A are key components of HPL with potential cardioprotective capabilities. Five active ingredients can alleviate Dox-induced cardiotoxicity by inhibiting oxidative stress and mitochondrial damage.

A study of volatiles of young citrus fruits from four areas based on GC-MS and flash GC e-nose combined with multivariate algorithms.

The present study has successfully established a scientific and precise approach for distinguishing the geographical origins of young citrus fruits (Qingpi) from four primary production regions in China, using gas chromatography-mass spectrometry (GC-MS) and flash gas chromatography electronic nose (flash GC e-nose) to analyze the volatile composition and odor characteristics. Through the application of chemometric analysis, a clear differentiation among Qingpi samples was established using GC-MS. Additionally, the application of flash GC e-nose facilitated the extraction of flavor information, which enabled the discrimination of geographical origins. Several flavor components were identified as significant factors for origin certification. Furthermore, two pattern recognition algorithms were employed to achieve high accuracy in regional identification. The results of this investigation demonstrate that the amalgamation of multivariate chemometrics and algorithms can proficiently discern the sources of those young citrus fruits. The findings of this research can provide a reference for the assessment of quality control in food and other agricultural commodities in the times ahead.

Optimizing BP neural network algorithm for Pericarpium Citri Reticulatae (Chenpi) origin traceability based on computer vision and ultra-fast gas-phase electronic nose data fusion.

This study utilized computer vision to extract color and texture features of Pericarpium Citri Reticulatae (PCR). The ultra-fast gas-phase electronic nose (UF-GC-E-nose) technique successfully identified 98 volatile components, including olefins, alcohols, and esters, which significantly contribute to the flavor profile of PCR. Multivariate statistical Analysis was applied to the appearance traits of PCR, identifying 57 potential marker-trait factors (VIP > 1 and P < 0.05) from the 118 trait factors that can distinguish PCR from different origins. These factors include color, texture, and odor traits. By integrating multivariate statistical Analysis with the BP neural network algorithm, a novel artificial intelligence algorithm was developed and optimized for traceability of PCR origin. This algorithm achieved a 100% discrimination rate in differentiating PCR samples from various origins. This study offers a valuable reference and data support for developing intelligent algorithms that utilize data fusion from multiple intelligent sensory technologies to achieve rapid traceability of food origins.

Quality difference analysis of raw and vinegar-processed products of Qingpi based on color and component correlation.

The dried young fruit of Citrus reticulata Blanco, known as Qingpi, is commonly used in clinic both with its raw and vinegar-processed products. However, the distinctions in quality between these two products remain unclear, and the methods for identification are considerably intricate. In this study, an electronic eye technique was applied to assess the overall color of Qingpi products before and after processing. The luminosity (L*) and yellow-blue (b*) values of Qingpi decreased after vinegar processing, while red-green (a*) values increased. The discriminant function models based on color parameters were established to effectively classify the two products. The chemical compositions of different Qingpi products were characterized using ultra-high performance liquid chromatography fingerprint technology, and 10 distinct components were considered as potential chemical markers. The correlation analysis revealed a significant relationship between chromatic values and chemical components. In conclusion, the results of this study suggested that chromaticity can be effectively considered as a valuable instrument for the prediction of component content in both raw and vinegar-processed Qingpi products. This study will provide new ideas and methods for identification and quality evaluation of Qingpi processed products, as well as provide a reference for standardizing traditional Chinese medicine processing techniques.

Sono-assembly of ellagic acid into nanostructures significantly enhances aqueous solubility and bioavailability.

INTRODUCTION: Ellagic acid (EA), commonly found in foods, offers significant health benefits in combating chronic diseases. However, its therapeutic potential is hindered by its extremely poor solubility and bioavailability. METHOD: In this study, EA nanoparticles (EA NPs) were produced using a sono-assembly method, without additional agents. RESULTS: EA NPs exhibited stick-like nanoparticle structures with an average size of 147.3 ± 0.73 nm. EA NPs likely adopt a tunnel-type solvate structure, with 4 water participating in disruption of intramolecular hydrogen bonds in EA and establishment of intermolecular hydrogen bonds between EAs. Importantly, EA NPs exhibited remarkable enhancements in water solubility, with 120.7-fold increase in water, and 97.8-fold increase in pH 6.8 buffer. Moreover, ex vivo intestinal permeability studies demonstrated significant improvements (P < 0.5). These findings were further supported by in vivo pharmacokinetic studies, where EA NPs significantly enhanced the relative bioavailability of EA by 4.69 times.

Ultra-high-performance liquid chromatography-quadrupole-time of flight-mass spectrometry combined with network pharmacology for analysis of potential quality markers of three processed products of Qingpi.

Qingpi, a well-known traditional Chinese medicine for qi-regulating and commonly processed into three types of pieces, has been widely used in the clinical application of liver disease for thousands of years. In this study, an ultra-high-performance liquid chromatography-quadrupole-time of flight-mass spectrometry approach along with multivariate statistical analysis was developed to assess and characterize the differentiations of three processed products and confirm the potential quality markers of Qingpi. In addition, a systematic analysis combined with network pharmacology and molecular docking was performed to clarify the potential mechanism of Qingpi for the treatment of liver disease. As a result, 18 components were identified and an integrated network of Qingpi-Components-Target-Pathway-Liver Disease was constructed. Eight compounds were finally screened out as the potential quality markers acting on ten main targets and pathways of liver disease. Molecular docking analysis results indicated that the quality markers had a good binding activity with the targets. Overall, this work preliminarily identified the potential quality markers of three processed products of Qingpi, and predicted its targets in the prevention and treatment of liver disease, which can provide supporting information for further study of the pharmacodynamic substances and mechanisms of Qingpi.

E-eye and FT-NIR combined with multivariate algorithms to rapidly evaluate the dynamic changes in the quality of Gastrodia elata during steaming process.

Gastrodia elata (GE) is traditionally subjected to steaming, and steaming duration plays a crucially important role in determining GE quality. This study examined the variations in bioactive components during the steaming process and proposed the utilization of electronic eye and Fourier Transform near-infrared (FT-NIR) spectroscopy for quality assessment. The findings revealed that the levels of parishin E parishin B, parishin A, and gastrodin initially rose and subsequently declined, while 4-Hydroxybenzyl alcohol exhibited a rapid decrease followed by stabilization. With prolonged steaming, the brightness of GE decreased, while the red and yellow tones became more pronounced and the color saturation increased. FT-NIR divided the steaming process into three stages: 0 min (raw GE), 0-9 min (partially steamed GE), and 9-30 min (fully steamed GE), and the partial least squares regression models effectively predicted the levels of five components. Overall, this study provided valuable insights into quality control in food processing.

Research on the effects of processing Heishunpian from Aconiti lateralis radix praeparata on components and efficacy using the "step knockout" strategy.

Heishunpian is obtained through complex processing of Aconiti lateralis radix praeparata. However, the impact of each processing step on chemical compositions and pharmacological activities is still unclear. The mechanism of the processing needs to be further studied. The samples were all prepared using the "step knockout" strategy for UPLC-QTOF-MS analysis, and analgesic and anti-inflammatory efficacy evaluation. Each sample was analyzed by UPLC-QTOF-MS to determine the component differences. The hot plate test and acetic acid writhing test were used to evaluate the analgesic effect. Anti-inflammatory efficacy was evaluated by xylene-induced ear edema test. The correlation between components and efficacies was studied to screen the effective components for further investigating the processing of Heishunpian. Mass spectrum analysis results showed that 49 components were identified, and it appeared that brine immersion and rinsing had a great influence on the components. In the hot plate test, ibuprofen and Heishunpian had the most significant effect, while ibuprofen and the sample without rinsing showed the best efficacy for the acetic acid writhing test. The sample without dyeing had the best effect on ear edema. The correlation analysis indicated that mesaconine, aconine, 3-deoxyaconine, delbruine, and asperglaucide were potentially considered effective analgesic components. It is not recommended to remove brine immersion and rinsing. Boiling and steaming are necessary processes that improve efficacy. Dyeing, which does not have a significant impact on components and efficacy, may be an unnecessary process. This research has been of great significance in identifying anti-inflammatory and analgesic components and optimizing processing for Heishunpian.

Rapid evaluation of Ziziphi Spinosae Semen and its adulterants based on the combination of FT-NIR and multivariate algorithms.

Ziziphi Spinosae Semen (ZSS) is a valued seed renowned for its sedative and sleep-enhancing properties. However, the price increase has been accompanied by adulteration. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) combined with multivariate algorithms were employed to identify the adulteration and quantitatively predict the adulteration ratio. The findings suggested that the utilization of chromaticity extractor was insufficient for identification of adulteration ratio. The raw spectrum of ZMS and HAS adulterants extracted by FT-NIR was processed by SNV + CARS and 1d + SG + ICO respectively, the average accuracy of machine learning classification model was improved from 77.06 % to 97.58 %. Furthermore, the R2 values of the calibration and prediction set of the two quantitative prediction regression models of adulteration ratio are greater than 0.99, demonstrating excellent linearity and predictive accuracy. Overall, this study demonstrated that FT-NIR combined with multivariate algorithms provided a significant approach to addressing the growing issue of ZSS adulteration.

Comparative study on Angelica sinensis after different processing with yellow rice wine in color, aromas, chemical components, and antioxidant activities.

This study aimed to explore the differences in raw Angelica Sinensis (RAS), wine washing AS (WAS), and wine stir-frying AS (WSAS). The results showed there were differences among the three AS in color and aroma, and 34 aroma compounds were identified. The content determination results revealed the ferulic acid and Z-ligustilide levels of RAS decreased after processing, and those in WAS were higher than in WSAS. Furthermore, 85 representative common components and 37 unique components were tentatively identified in three AS. Finally, the free radical scavenging assay results indicated the antioxidant capacity of RAS was reduced after processing, and the antioxidant capacity of WAS was better than WSAS. Collectively, the RAS undergoes significant changes in color, aromas, components, and antioxidant ability after processing, and the different processing methods also result in significant differences between WAS and WSAS.