Detection of Mildewed Nutmeg Internal Quality during Storage Using an Electronic Nose Combined with Chemical Profile Analysis.

Internal mildewed nutmeg is difficult to perceive without cutting the nutmeg open and examining it carefully, which poses a significant risk to public health. At present, macroscopic identification and chromatographic analysis are applied to determine whether nutmeg is moldy or not. However, the former relies on a human panel, with the disadvantages of subjectivity and empirical dependence, whilst the latter is generally time-consuming and requires organic solvents. Therefore, it is urgent to develop a rapid and feasible approach for evaluating the quality and predicting mildew in nutmeg. In this study, the quality and odor characteristics of five groups of nutmeg samples with different degrees of mildew were analyzed by using the responses of an electronic nose combined with chemical profiling. The main physicochemical indicators, such as the levels of α-pinene, ß-pinene, elemicin, and dehydro-di-isoeugenol, were determined. The results revealed that the contents of α-pinene, ß-pinene, and elemicin changed significantly with the extension of storage time. Through the use of an electronic nose and HS-GC-MS technology to assess the overall odor characteristics of nutmeg samples, it was found that the production of volatile organic compounds (VOCs) such as ammonia/organic amines, carbon monoxide, ethanol, and hydrogen sulfide, as well as changes in the terpene and phenylpropene components of the nutmeg itself, may be the material basis for the changes in odor. The accuracy of the qualitative classification model for the degree of mildew in nutmeg was higher than 90% according to the electronic nose data combined with different machine learning algorithms. Quantitative models were established for predicting the contents of the chemical components, and models based on a BP neural network (BPNN), the support vector machine (SVM), and the random forest algorithm (RF) all showed good performance in predicting the concentrations of these chemical components, except for dehydro-di-isoeugenol. The BPNN performed effectively in predicting the storage time of nutmeg on the basis of the E-nose's responses, with an RMSE and R2 of 0.268 and 0.996 for the training set, and 0.317 and 0.993 for the testing set, respectively. The results demonstrated that the responses of the electronic nose (E-nose) had a high correlation with the internal quality of nutmeg. This work proposes a quick and non-destructive evaluation method for the quality of nutmeg, which has high accuracy in discriminating between different degrees of mold in nutmeg and is conducive to early detection and warning of moldy phenomena.

[CiteSpace knowledge map of research hotspots and frontiers of traditional Chinese medicine intervention in psoriasis in recent ten years].

This study aimed to investigate the development status of traditional Chinese medicine(TCM) intervention in psoriasis in recent ten years, analyze the research hotspots, and summarize the development trends to provide reference materials for scholars in this field. Taking the available literature related to the field of TCM intervention in psoriasis as the research object, the trends, contents, and source publications were statistically analyzed based on bibliometrics. The research cooperation and co-occurrence of keywords in this field were studied by the knowledge map analysis method based on CiteSpace. The total number of Chinese papers was 2 993 and English papers 285. In terms of publication trend, the annual publication of English papers was low but showed an obvious upward trend, while the increase in Chinese papers fluctuated and tended to be flat. In terms of the content of Chinese papers published, TCM ranked first according to the discipline(2 415). In English papers, the number of publications in pharmacology and pharmaceutical science was the highest(87). Literature source analysis showed that the Chinese and English journals with the most publications were China Journal of Traditional Chinese Medicine and Pharmacy and Evidence Based Complementary and Alternative Medicine, respectively. Beijing University of Chinese Medicine published the most dissertations in China(99). The authors with the most publications in Chinese and English were LI Bin(Yueyang Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Shanghai University of Traditional Chinese Medicine) and LU Chuan-jian(Guangdong Hospital of Traditional Chinese Medicine). As revealed by the CiteSpace analysis of the research cooperation network, there were four mature and stable core teams in this field, but the cooperation intensity between different teams was weak. According to the keywords co-occurrence knowledge graph constructed by CiteSpace, the current hot keywords in this field are as follows: psoriasis, blood-heat syndrome, blood-stasis syndrome, fire needle, blood-dryness type, imiquimod, TCM bath, etiology and pathogenesis, cytokines, cupping therapy, etc. In summary, Chinese scholars have conducted active exploration and research in the field of TCM intervention in psoriasis in recent ten years. The overall development trend is good, and the breadth and depth of the research are constantly extending. It is suggested that relevant research should be free from discipline restrictions and strive for interdisciplinary integration.

[Establishment of a fast discriminant model with electronic nose for Polygonati Rhizoma mildew based on odor variation].

The odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees was analyzed and the relationship between the odor variation and the mildewing degree was explored. A fast discriminant model was established according to the response intensity of electronic nose. The α-FOX3000 electronic nose was applied to analyze the odor fingerprint of Pollygonati Rhizoma samples with different mildewing degrees and the radar map was used to analyze the main contributors among the volatile organic compounds. The feature data were processed and analyzed by partial least squares discriminant analysis(PLS-DA), K-nearest neighbor(KNN), sequential minimal optimization(SMO), random forest(RF) and naive Bayes(NB), respectively. According to the radar map of the electronic nose, the response values of three sensors, namely T70/2, T30/1, and P10/2, increased with the mildewing, indicating that the Pollygonati Rhizoma produced alkanes and aromatic compounds after the mildewing. According to PLS-DA model, Pollygonati Rhizoma samples of three mildewing degrees could be well distinguished in three areas. Afterwards, the variable importance analysis of the sensors was carried out and then five sensors that contributed a lot to the classification were screened out: T70/2, T30/1, PA/2, P10/1 and P40/1. The classification accuracy of all the four models(KNN, SMO, RF, and NB) was above 90%, and KNN was most accurate(accuracy: 97.2%). Different volatile organic compounds were produced after the mildewing of Pollygonati Rhizoma, and they could be detected by electronic nose, which laid a foundation for the establishment of a rapid discrimination model for mildewed Pollygonati Rhizoma. This paper shed lights on further research on change pattern and quick detection of volatile organic compounds in moldy Chinese herbal medicines.

[Comparison between macroscopic identification and DNA barcoding identification of Amomi Fructus].

This study aims to explore the consistency between macroscopic identification and DNA barcoding identification of Amomi Fructus. With the DNA barcoding identification results, we evaluated the reliability of identifying Amomi Fructus quality by combining macroscopic traits with main volatile chemical components. Thirteen batches of Amomi Fructus samples were collected for identification. Firstly, the morphological and sensory characteristics of each sample were observed and recorded according to the standard in Chinese Pharmacopoeia(2020 edition). The 100-fruit weight, longitudinal diameter, transverse diameter, and longitudinal diameter-to-transverse diameter ratio were measured, which correspond to large, solid, and full kernel representing good quality in the sensory evaluation. The odor value detected by electronic nose and major volatile components(borneol, camphor, limonene, and borneol acetate) correspond to the sensory evaluation of strong odor representing good quality. Secondly, DNA barcoding was employed to identify the 13 batches of samples. Finally, clustering analysis was performed for the main volatile components and macroscopic traits, and the identification results were compared with those of DNA barcoding. Except two batches of samples(No.6 and No.10), the macroscopic identification showed the results consistent with those of DNA barcoding, with an identification rate of 84.62%. The clustering results of the content of four volatile chemical components and macroscopic traits were also consistent with the DNA barcoding identification results. DNA barcoding can verify the results of macroscopic identification and provide a scientific basis for the inheritance and development of macroscopic identification. Moreover, the combination of macroscopic traits and chemical components demonstrates higher accuracy in the quality evaluation of Chinese medicinal materials.

Identification of Nutmeg With Different Mildew Degree Based on HPLC Fingerprint, GC-MS, and E-Nose.

Nutmeg (Myristicae Semen), the so-called Rou-Dou-Kou in Chinese, is one kind of Chinese herbal medicines (CHMs) as well as a globally popular spice. Hence, its stable quality and safe application attract more attention. However, it is highly prone to mildew during storage due to its rich volatile components and fatty oil. Therefore, in this study, an electronic nose (E-nose) was introduced to attempt to reliably and rapidly identify nutmeg samples with different degrees of mildew. Meanwhile, the chemical composition and volatile oil were analyzed using HPLC fingerprint and GC-MS, respectively, which could support and validate the result of E-nose. The results showed that the cluster results of HPLC fingerprint and GC-MS were generally consistent with E-nose, and they all clustered into two categories. Additionally, a discriminant model was established, which divided the samples into three categories: mildew-free, mildew-slight, and mildew, and a high DPR was obtained, which indicates that the E-nose could be a novel and promising approach for the establishment of a quality evaluation system to identify CHMs with different degrees of mildew rapidly, especially to identify early mildew.

Exploration on Varying Patterns of Morphological Features and Quality of Armeniacae Semen Amarum in Rancid Process Based on Colorimeter, Electronic Nose, and GC/MS Coupled With Human Panel.

In recent years, the domestic and international trade volumes of Chinese medicinal materials (CMMs) keep increasing. By the end of 2019, the total amount of exported CMMs reached as high as US $1.137 billion, while imported was US $2.155 billion. A stable and controllable quality system of CMMs apparently becomes the most important issue, which needs multifaceted collaboration from harvesting CMMs at a proper season to storing CMMs at a proper temperature. However, due to imperfect storage conditions, different kinds of deteriorations are prone to occur, for instance, get moldy or rancid, which not only causes a huge waste of CMM resources but also poses a great threat to clinical medication safety and public health. The key issue is to quickly and accurately distinguish deteriorated CMM samples so as to avoid consuming low-quality or even harmful CMMs. However, some attention has been paid to study the changing quality of deteriorated CMMs and a suitable method for identifying them. In this study, as a medicine and food material which easily becomes rancid, armeniacae semen amarum (ASA) was chosen as a research objective, and experimental ASA samples of different rancidness degrees were collected. Then, various kinds of analytical methods and technologies were applied to explore the changing rules of ASA quality and figure out the key indicators for the quality evaluation of ASA in the rancid process, including the human panel, colorimeter, electronic nose, and GC/MS. This study aims to analyze the correlation between the external morphological features and the inner chemical compounds, to find out the specific components from "quantitative change" to "qualitative change" in the process of "getting rancid," and to discover the dynamic changes in the aforementioned key indicators at different stages of rancidness. The results showed since ASA samples began to get rancid with the extension of storage time, morphological features, namely, surface color and smell, changed significantly, and the degree of rancidness further deepened at the same time. Based on macroscopic identification accomplished via the human panel, ASA samples with varying degrees of rancidness were divided into four groups. The result of colorimeter analysis was in agreement with that of the human panel, as well as the determination of the amygdalin content and peroxide value. Moreover, there were obvious differences in the amygdalin content and peroxide value among ASA samples with different rancidness degrees. With a higher degree of rancidness, the content of amygdalin decreased, while the peroxide value increased significantly. The rancidness degree of ASA has a negative correlation with the amygdalin content and a positive correlation with the peroxide value. The newly discovered nonanal and 2-bromopropiophenone in rancid ASA samples may be the key components of "rancidity smell," and these two components would be the exclusive components that trigger "quantitative change" to "qualitative change" in the process of rancidness of ASA. This study sheds light on studying the internal mechanism of "rancidness" of CMMs and provides an important basis for the effective storage and safe medication of easy-to-get rancid herbs, and it also plays an important foundation for the establishment of a stable and controllable quality system for CMMs.

[High-speed identification of odor changes and substance basis of Myristicae Semen mildew by electronic nose and HS-GC-MS].

This study adopted headspace-gas chromatography-mass spectrometry(HS-GC-MS) and electronic nose to detect volatile components from Myristicae Semen samples with varying degrees of mildew, aiming at rapidly identifying odor changes and substance basis of Myristicae Semen mildew. The experimental data were analyzed by electronic nose and principal component analysis(PCA). The results showed that Myristicae Semen samples were divided into the following three categories by electronic nose and PCA: mildew-free samples, slightly mildewy samples, and mildewy samples. Myristicae Semen samples with different degrees of mildew greatly varied in volatile components. The volatile components in the samples were qualitatively and quantitatively detected by HS-GC-MS, and 59 compounds were obtained. There were significant differences in the composition and content in Myristicae Semen samples with different degrees of mildew. The PCA results were the same as those by electronic nose. Among them, 3-crene, D-limonene, and other terpenes were important indicators for the identification of mildew. Bicyclo[3.1.0]hexane, 4-methylene-1-(1-methylethyl)-, terpinen-4-ol, and other alcohols were key substances to distinguish the degree of mildew. In the later stage of mildew, Myristicae Semen produced a small amount of hydroxyl and aldehyde compounds such as acetaldehyde, 2-methyl-propionaldehyde, 2-methyl-butyraldehyde, and formic acid, which were deduced as the material basis of the mildew. The results are expected to provide a basis for the rapid identification of Myristicae Semen with different degrees of mildew, odor changes, and the substance basis of mildew.

Quality grade classification of China commercial moxa floss using electronic nose: A supervised learning approach.

Moxa floss is the primary material used in moxibustion, an important traditional Chinese medicine therapy that uses ignited moxa floss to apply heat to the body for disease treatment. Till date, there is no available data regarding quality control of different grades of moxa floss. The objectives of this study were to explore the probative value of the electronic nose (e-nose) in differentiating different quality grades of commercial moxa floss sold in China, and to investigate if data mining techniques could be used to optimize the sensor array while retaining classification accuracy of the samples. The e-nose with 12 metal oxide semiconductor type sensors was used to analyze the odor profiles of 15 commercial moxa floss samples of different quality grades. Feature selection algorithms using principal component analysis (PCA) and BestFirst (BC) coupled with correlation-based feature subset selection (CfsSubsetEval) method were used to obtain the most efficient feature subsets. Results for the BC feature selection method identified 3 optimized sensors (S2, S6, and S11), suggesting that aromatic compounds relate more to the identification of the samples. Radial basis function (RBF), multilayer perceptron (MLP), and random forests (RF) performed well in discriminating the samples, retaining prediction accuracies above 85%, which achieved cost-effectiveness and operational simplicity, while retaining prediction accuracy. The e-nose could be a rapid and nondestructive method for objective preliminary classification of quality grades of moxa floss and may be used for future studies related to moxa products safety and quality.

[Change pattern and correlation analysis of macroscopic characteristics, active components and rancidness degrees of Armeniacae Semen Amarum in deterioration process].

To discuss the effect of deterioration on the quality of Armeniacae Semen Amarum by observing the changes of macroscopic characteristics, active components and rancidness degrees of Armeniacae Semen Amarum in deterioration process. The traditional macroscopic identification was used to observe, identify and classify the morphologic and organleptic characteristics of Armeniacae Semen Amarum. The contents of amygdalin and fatty oil(two representatives of active components) were detected by HPLC and general rule 0713 in Chinese Pharmacopoeia, respectively. Acid value and peroxide value of the samples were selected as the representative indices of different rancidness degrees, and the general rule 2303 was adopted as the method for quantitative analysis. Then principal component analysis(PCA), partial least square analysis discrimination analysis(PLS-DA) were further utilized to establish the discriminative models of samples with different rancidness degrees, and also to screen out the largest contribution factors. In sensory evaluation, Armeniacae Semen Amarum samples were divided into three groups: non-rancid, slightly-rancid, and noticeably-rancid. The color of seed coat, cotyledon and surface of noticeably-rancid samples was deepened, and the odor differed much from non-rancid samples. Average content of amygdalin and fatty oil in non-rancid samples was 4.12% and 67.77%, respectively, both meeting the requirements of Chinese Pharmacopoeia; and decreased to some extent in slightly-rancid samples. However, the content of amygdalin sharply dropped to 0.074% in noticeably-rancid samples. The acid value and peroxide value were increased significantly with the intensifying of the rancidness degree, from only 1.363 and 0.016 74 in non-rancid samples to 1.865 and 0.023 70 in slightly-rancid samples, even doubled in noticeably-rancid samples(2.167 and 0.033 82). The discriminative models established by PCA and PLS-DA could complete the task of distinguishing the non-rancid samples from noticeably-rancid ones. The contribution degree of amygdalin content as one of the input attributes of discriminative model was higher than 1. Rancidness affected the quality of Armeniacae Semen Amarum, resulting in appearance changes, decrease in content of active components, and increase in acid value and peroxide value. Obviously, noticeably-rancid samples were non-conforming to Chinese Pharmacopoeia and no longer suitable for medicinal use. Rancidness can significantly reduce the quality of Armeniacae Semen Amarum, and even could possibly produce toxicity, which should attach more attention.

The Absorption Characteristics of Nonvolatile Components in a Water Extraction From Amomi fructus as Determined by In Situ Single-Pass Intestinal Perfusion and High-Performance Liquid Chromatography.

BACKGROUND: Amomi fructus is a famous traditional Chinese medicine (TCM) that can exert beneficial effects during the treatment of gastrointestinal diseases and is used widely in China and other countries in Southeast Asia. However, the nonvolatile active ingredients that are present in the water extractions from A. fructus used to treat gastrointestinal diseases have yet to be elucidated. The goal of this study was to identify the nonvolatile active ingredients of A. fructus. METHODS: We used an in situ single-pass intestinal perfusion (SPIP) model to identify the active ingredients of A. fructus that play significant roles in gastrointestinal absorption. In addition, we developed a high-performance liquid chromatography (HPLC) method to identify key fractions in intestinal outflow perfusate. RESULTS: Nineteen components were identified in a water extraction from A. fructus; these exhibited different absorption capabilities in different intestinal segments. Of these, six components were determined by the newly developed HPLC method: catechin, vanillic acid, epicatechin, polydatin, isoquercitrin, and quercitrin. CONCLUSIONS: The current study aimed to identify the active ingredients present in water extractions prepared from A. fructus in a single-intestinal perfusate from rats. Our findings provide an experimental basis to explain the pharmacodynamic actions of A. fructus.

[Discrimination of Armeniacae Semen Amarum from different processed products and various rancidness degrees by electronic nose and support vector machine].

This study was aimed to develop a simple, rapid and reliable method for identifying Armeniacae Semen Amarum from different processed products and various rancidness degrees. The objective odor information of Armeniacae Semen Amarum was obtained by electronic nose. 105 batches of Armeniacae Semen Amarum samples were studied, including three processed products of Armeniacae Semen Amarum, fried Armeniacae Semen Amarum and peeled Armeniacae Semen Amarum, as well as the samples with various rancidness degrees: without rancidness, slight rancidness, and rancidness. The discriminant models of different processed products and rancidness degrees of Armeniacae Semen Amarum were established by Support Vector Machine(SVM), respectively, and the models were verified based on back estimation of blind samples. The results showed that there were differences in the characteristic response radar patterns of the sensor array of different processed products and the samples with different rancidness degrees. The initial identification rate was 95.90% and 92.45%, whilst validation recognition rate was 95.38% and 91.08% in SVM identification models. In conclusion, differentiation in odor of different processed and rancidness degree Armeniacae Semen Amarum was performed by the electronic nose technology, and different processed and rancidness degrees Armeniacae Semen Amarum were successfully discriminated by combining with SVM. This research provides ideas and methods for objective identification of odor of traditional Chinese medicine, conducive to the inheritance and development of traditional experience in odor identification.

Comprehensive Investigation of the Differences of the Roots of Wild and Cultivated Mirabilis himalaica (Edgew) Heim Based on Macroscopic and Microscopic Identification Using HPLC Fingerprint.

Mirabilishimalaica (Edgew) Heim (MH) is an important Tibetan medicine with demonstrated medicinal efficacy and promising developmental value. A previous study of MH was limited to vague morphological and microscopic descriptions, restricting its clinical application and further development as a medicine. The goal of this study was to comprehensively characterize wild and cultivated products of MH using macroscopic and microscopic identification using HPLC fingerprint. The results revealed that the cultivated and wild MH exhibited differences in macroscopic and microscopic characteristics and chemical components. This analysis can facilitate the establishment of a more comprehensive quality evaluation method for MH. These results provide the basis for clinical applications and the improvement of quality standards of MH as a step towards modernization of Tibetan medicine.

[Identification of Curcuma herbs using XGBoost algorithm in electronic nose odor fingerprint].

This article aims to identify four commonly applied herbs from Curcuma genus of Zingiberaceae family,namely Curcumae Radix( Yujin),Curcumae Rhizoma( Ezhu),Curcumae Longae Rhizoma( Jianghuang) and Wenyujin Rhizoma Concisum( Pianjianghuang). The odor fingerprints of those four herbal medicines were collected by electronic nose,respectively. Meanwhile,XGBoost algorithm was introduced to data analysis and discriminant model establishment,with four indexes for performance evaluation,including accuracy,precision,recall,and F-measure. The discriminant model was established by XGBoost with positive rate of returning to 166 samples in the training set and 69 samples in the test set were 99. 39% and 95. 65%,respectively. The top four of the contribution to the discriminant model were LY2/g CT,P40/1,LY2/Gh and LY2/LG,the least contributing sensor was T70/2. Compared with support vector machine,random forest and artificial neural network,XGBoost algorithms shows better identification capacity with higher recognition efficiency. The accuracy,precision,recall and F-measure of the XGBoost discriminant model forecast set were 95. 65%,95. 25%,93. 07%,93. 75%,respectively. The superiority of XGBoost in the identification of Curcuma herbs was verified. Obviously,this new method could not only be suitable for digitization and objectification of traditional Chinese medicine( TCM) odor indicators,but also achieve the identification of different TCM based on their odor fingerprint in electronic nose system. The introduction of XGBoost algorithm and more excellent algorithms provide more ideas for the application of electronic nose in data mining for TCM studies.

Organoleptic Evaluation of Amomi Fructus and Its Further Background Verified via Morphological Measurement and GC Coupled with E-Nose.

The present study investigated the maneuverability and reasonability of sensory analysis, which has been applied in TCM identification for a long time. Ten assessors were trained and generated the human panel to carry out the organoleptic evaluation of twenty-five batches of Sha-Ren samples. Accordingly, samples were scored from 0 (lowest) to 10 (highest) for sensory attributes. Based on this, samples were divided into three classes: high class (Yang-Chun-Sha from Guang-Dong), moderate class (Yang-Chun-Sha samples from Yun-Nan and Guang-Xi), and low class (Lv-Qiao-Sha from marketplaces). For further background, three instrumental approaches were employed: morphological measurement with three indices (longitudinal diameter, transverse diameter, and 100-fruit weight), GC for determination of bornyl acetate contents, and E-nose for aromatic fingerprint. It is demonstrated in the results that GC and E-nose analyses were in great agreement with organoleptic evaluation. It gives insights into further studies on searching better morphological indicators and improving discriminant model of E-nose.

Metabolic profiling of the traditional Chinese medicine formulation Yu Ping Feng San for the identification of constituents relevant for effects on expression of TNF-α, IFN-γ, IL-1ß and IL-4 in U937 cells.

Yu Ping Feng San (YPFS) is a classical TCM formulation which has been traditionally used for treatment of immune system related diseases such as chronic bronchitis, allergic rhinitis and asthma. The formula is a mixture of Radix Saposhnikoviae (Fangfeng), Radix Astragali (Huangqi), and Rhizoma Atractylodis macrocephalae (Baizhu). TLC- and LC-DAD-ESI-MS/MS methods have been developed for the analysis of the metabolic profiles of the single herbs and of the formula. Decoctions and ASE extracts were analyzed in order to trace components of the individual herbs in YPFS. Nine constituents of Radix Saposhnikoviae, ten constituents of Radix Astragali and five constituents of Rhizoma Atractylodis macrocephalae have been assigned in the chemical profiles of the formula, which now allow the standardisation of YPFS. The pharmacological testing showed that all extracts significantly inhibited expression of TNF-α, IFN-γ, and IL-1ß in U937 cells, while the inhibition of IL-4 was consistently low. Compared to conventional analyses which are focused on a limited set of compounds, metabolomics approaches, together with novel data processing tools, enable a more holistic comparison of the herbal extracts. In order to identify the constituents which are relevant for the immunomodulatory effects of the formula, metabolomics studies (PCA, OPLS-DA) have been performed using UPLC/QTOF MS data.

Increased Intestinal Absorption of Genistein by Coadministering Verapamil in Rats.

Combination of genistein (GT) and verapamil, a P-glycoprotein (P-gp) inhibitor, can increase GT absorption in situ perfusion technology in rat. To date, little information is yet available about the effect of verapamil on oral absorption of GT in vivo. In this study, a simple and reproducible HPLC-UV method was developed and validated for determination of total GT in rat plasma. Based on this, a pharmacokinetic experiment was designed to characterize biopharmaceutical properties of GT with or without coadministration of verapamil (10.0, 20.0, 30.0 mg/kg) in rats. The coadministration of verapamil (30.0 mg/kg) with GT caused a significant increase of the maximum GT plasma concentration (1.31-fold vs. GT, P < 0.05) and area under the curve (1.39-fold vs. GT, P < 0.05). Our data show that verapamil would increase intestinal absorption of GT in rat, suggesting there is some drug-nutrition interaction between verapamil and GT.

Determination of D-glucaric acid and/or D-glucaro-1,4-lacton in different apple varieties through hydrophilic interaction chromatography.

d-Glucaric acid (GA) derivatives exhibit anti-cancerogenic properties in vivo in apples, but quantitative information about these derivatives is limited. Hydrophilic interaction-based HPLC with ultraviolet detection or mass spectrometry was developed to quantify GA and/or D-glucaro-1,4-lacton (1,4-GL) in apples. Although the formation of 1,4-GL from GA could be the prerequisite to exert biological effects in vivo, only a small portion of GA (<5%) was identified and converted to 1,4-GL in the rat stomach. The 1,4-GL content in apples ranged from 0.3 mg/g to 0.9 mg/g, and this amount can substantiate health claims associated with apples. The amount of 1,4-GL was 1.5 times higher in Gala and the ratio of 1,4-GL to GA was lower in Green Delicious apples than those in the other varieties. Our findings suggested that the variety and maturity of apples at harvest are factors that determine 1,4-GL content.

Influence of storage duration and processing on chromatic attributes and flavonoid content of moxa floss.

OBJECTIVE: Moxibustion is an important traditional Chinese medicine therapy using heat from ignited moxa floss for disease treatment. The purpose of the present study is to establish a reproducible method to assess the color of moxa floss, discriminate the samples based on chromatic coordinates and explore the relationship between chromatic coordinates and total flavonoid content (TFC). METHODS: Moxa floss samples of different storage years and production ratios were obtained from a moxa production factory in Henan Province, China. Chromatic coordinates (L*, a* and b*) were analyzed with an ultraviolet-visible spectrophotometer and the chroma (C*) and hue angle (h°) values were calculated. TFC was determined by a colorimetric method. Data were analyzed with correlation, principal component analysis (PCA). RESULTS: Significant differences in the chromatic values and TFC were observed among samples of different storage years and production ratios. Samples of higher production ratio displayed higher chromatic characteristics and lower TFC. Samples of longer storage years contained higher TFC. Preliminary separation of moxa floss production ratio was obtained by means of color feature maps developed using L*-a* or L*-b* as coordinates. PCA allowed the separation of the samples from their storage years and production ratios based on their chromatic characteristics and TFC. CONCLUSION: The use of a colorimetric technique and CIELAB coordinates coupled with chemometrics can be practical and objective for discriminating moxa floss of different storage years and production ratios. The development of color feature maps could be used as a model for classifying the color grading of moxa floss.

Is it possible to rapidly and noninvasively identify different plants from Asteraceae using electronic nose with multiple mathematical algorithms?

Many plants originating from the Asteraceae family are applied as herbal medicines and also beverage ingredients in Asian areas, particularly in China. However, they may be confused due to their similar odor, especially when ground into powder, losing their typical macroscopic characteristics. In this paper, 11 different multiple mathematical algorithms, which are commonly used in data processing, were utilized and compared to analyze the electronic nose (E-nose) response signals of different plants from Asteraceae family. Results demonstrate that three-dimensional plot scatter figure of principal component analysis with less extracted components could offer the identification results more visually; simultaneously, all nine kinds of artificial neural network could give classification accuracies at 100%. This paper presents a rapid, accurate, and effective method to distinguish Asteraceae plants based on their response signals in E-nose. It also gives insights to further studies, such as to find unique sensors that are more sensitive and exclusive to volatile components in Chinese herbal medicines and to improve the identification ability of E-nose. Screening sensors made by other novel materials would be also an interesting way to improve identification capability of E-nose.

Rapid Identification of Asteraceae Plants with Improved RBF-ANN Classification Models Based on MOS Sensor E-Nose.

Plants from Asteraceae family are widely used as herbal medicines and food ingredients, especially in Asian area. Therefore, authentication and quality control of these different Asteraceae plants are important for ensuring consumers' safety and efficacy. In recent decades, electronic nose (E-nose) has been studied as an alternative approach. In this paper, we aim to develop a novel discriminative model by improving radial basis function artificial neural network (RBF-ANN) classification model. Feature selection algorithms, including principal component analysis (PCA) and BestFirst + CfsSubsetEval (BC), were applied in the improvement of RBF-ANN models. Results illustrate that in the improved RBF-ANN models with lower dimension data classification accuracies (100%) remained the same as in the original model with higher-dimension data. It is the first time to introduce feature selection methods to get valuable information on how to attribute more relevant MOS sensors; namely, in this case, S1, S3, S4, S6, and S7 show better capability to distinguish these Asteraceae plants. This paper also gives insights to further research in this area, for instance, sensor array optimization and performance improvement of classification model.