Detection of trace components in Xiangdan injection of Dalbergia odorifera based on microextraction and back-extraction along with bar-form-diagram strategy.

Xiangdan Injection are commonly used traditional Chinese medicine formulations for the clinical treatment of cardiovascular diseases. However, the trace components of Dalbergia odorifera in Xiangdan Injection pose a challenge for evaluating its quality due to the difficulty of detection. This study proposes a technology combining dispersive liquid-liquid microextraction and back-extraction (DLLME-BE) along with Bar-Form-Diagram (BFD) to address this issue. The proposed combination method involves vortex-mixing tetradecane, which has a lower density than water, with the sample solution to facilitate the transfer of the target components. Subsequently, a new vortex-assisted liquid-liquid extraction step is performed to enrich the components of Dalbergia odorifera in acetonitrile. The sample analysis was performed on HPLC-DAD, and a clear overview of the chemical composition was obtained by integrating spectral and chromatographic information using BFD. The combination of BFD and CRITIC-TOPSIS strategies was used to optimize the process parameters of DLLME-BE. The determined optimal sample pre-treatment process parameters were as follows: 200 µL extraction solvent, 60 s extraction time, 50 µL back-extraction solvent, and 90 s back-extraction time. Based on the above strategy, a total of 29 trace components, including trans-nerolidol, were detected in the Xiangdan Injection. This combination technology provides valuable guidance for the enrichment analysis of trace components in traditional Chinese medicines.

Improving the geographical origin classification of Radix glycyrrhizae (licorice) through hyperspectral imaging assisted by U-Net fine structure recognition.

Radix glycyrrhizae (licorice) is extensively employed in traditional Chinese medicine, and serves as a crucial raw material in industries such as food and cosmetics. The quality of licorice from different origins varies greatly, so classification of its geographical origin is particularly important. This study proposes a technique for fine structure recognition and segmentation of hyperspectral images of licorice using deep learning U-Net neural networks to segment the tissue structure patterns (phloem, xylem, and pith). Firstly, the three partitions were separately labeled using the Labelme tool, which was utilized to train the U-Net model. Secondly, the obtained optimal U-Net model was applied to predict three partitions of all samples. Lastly, various machine learning models (LDA, SVM, and PLS-DA) were trained based on segmented hyperspectral data. In addition, a threshold method and a circumcircle method were applied to segment licorice hyperspectral images for comparison. The results revealed that compared with the threshold segmentation method (which yielded SVM classifier accuracies of 99.17%, 91.15%, and 92.50% on the training set, validation set, and test set, respectively), the U-Net segmentation method significantly enhanced the accuracy of origin classification (99.06%, 94.72% and 96.07%). Conversely, the circumcircle segmentation method did not effectively improve the accuracy of origin classification (99.65%, 91.16% and 92.13%). By integrating Raman imaging of licorice, it can be inferred that the U-Net model, designed for region segmentation based on the inherent tissue structure of licorice, can effectively improve the accuracy origin classification, which has positive significance in the development of intelligence and information technology of Chinese medicine quality control.

An intelligent extraction approach of feature information from three-dimensional DAD chromatogram for integrated quality control of traditional Chinese medicines: Gardenia jasminoides root as an example.

Traditional Chinese medicine (TCM) fingerprinting, which has the characteristics of holism and ambiguity, is a conventional strategy for the holistic quality control of TCMs. However, the fingerprinting of TCMs at the current stage generally adopts a single wavelength or few wavelengths, lacking the effective utilization of diode-array detector (DAD) chromatogram data. This study proposes an intelligent extraction approach of feature information from a three-dimensional DAD chromatogram to establish a novel bar-form-diagram (BFD) for integrated quality control of TCMs. The BFD was automatically established by the chromatographic and spectral information of a complex hybrid system in a DAD chromatogram. This covered the peak areas of target compositions at the optimal absorption wavelength. Taking 27 batches of Gardenia jasminoides root as samples, the BFD combined with chemometrics was applied for assessing the quality of samples completely, which improved the accuracy of origin classification using hierarchical cluster analysis, principal component analysis, soft independent modeling of class analogy and orthogonal partial least squares discriminant analysis. Single-wavelength fingerprinting and BFD used 23 and 38 common peaks as variables respectively, and the adjusted rand index results of the single wavelength and BFD were 0.559 and 0.819, respectively. Compared with the ergodic methods of each single wavelength, the peak recognition method in this study improved the operation speed from 180 s to 4 s and the computational complexity. The established BFD approach performed more abundant characteristic information of chemical components of TCMs and more accurate origin classification ability, and it had great advantages in the overall quality control of TCMs.

Applications of Hyperspectral Imaging Technology Combined with Machine Learning in Quality Control of Traditional Chinese Medicine from the Perspective of Artificial Intelligence: A Review.

Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of crucial importance. In recent years, with the quick rise of artificial intelligence (AI) and the rapid development of hyperspectral imaging (HSI) technology, the combination of the two has been widely used in the quality evaluation of TCM. Machine learning (ML) is the core wisdom of AI, and its progress in rapid analysis and higher accuracy improves the potential of applying HSI to the field of TCM. This article reviewed five aspects of ML applied to hyperspectral data analysis of TCM: partition of data set, data preprocessing, data dimension reduction, qualitative or quantitative models, and model performance measurement. The different algorithms proposed by researchers for quality assessment of TCM were also compared. Finally, the challenges in the analysis of hyperspectral images for TCM were summarized, and the future works were prospected.

Recognition of the rhizome of red ginseng based on spectral-image dual-scale digital information combined with intelligent algorithms.

Red ginseng is a widely used and extensively researched food and medicinal product with high nutritional value, derived from steamed fresh ginseng. The components in various parts of red ginseng differ significantly, resulting in distinct pharmacological activities and efficacies. This study proposed to establish a hyperspectral imaging technology combined with intelligent algorithms for the recognition of different parts of red ginseng based on the dual-scale of spectrum and image information. Firstly, the spectral information was processed by the best combination of first derivative as pre-processing method and partial least squares discriminant analysis (PLS-DA) as classification model. The recognition accuracy of the rhizome and the main root of red ginseng is 96.79% and 95.94% respectively. Then, the image information was processed by the You Only Look Once version 5 small (YOLO v5s) model. The best parameter combination is epoch = 30, learning rate = 0.01, and activation function is leaky ReLU. In the red ginseng dataset, the highest accuracy, recall and mean Average Precision at IoU (Intersection over Union) threshold 0.5 (mAP@0.5) were 99.01%, 98.51% and 99.07% respectively. The application of spectrum-image dual-scale digital information combined with intelligent algorithms in the recognition of red ginseng is successful, which provides a positive significance for the online and on-site quality control and authenticity identification of crude drugs or fruits.

Multi-wavelength fusion column fingerprint technology combined with chemometric analysis to evaluate the overall quality of the Gardenia jasminoides root.

Chromatographic fingerprinting provides effective technical means for quality evaluation of traditional Chinese medicine. In this work, a novel multi-wavelength fusion column fingerprint was obtained by intelligent selection of chromatographic peaks from different wavelengths, which displayed the maximum peak area information under the optimal wavelength at the same retention time. Here, the Gardenia jasminoides root was selected as a sample. The multi-wavelength fusion column fingerprint graph of the Gardenia jasminoides root was constructed from five wavelengths (203 nm, 210 nm, 238 nm, 250 nm and 330 nm). The peak capacity, peak resolution, the number of common peaks and similarity were used to evaluate the performance. The 19 batches of Gardenia jasminoides root were classified into three categories with clear distinction between origin categories based on the multi-wavelength fusion column fingerprint combined with chemometrics, including hierarchical cluster analysis and principal component analysis. Nine markers of variation that led to differences between batches were screened by orthogonal partial least squares discriminant analysis. This study demonstrated that the classification model based on the multi-wavelength fusion column fingerprint was better than that on a single-wavelength, and the fusion fingerprint was suitable for the identification and quality control of traditional Chinese medicine with more comprehensive chemical composition information and more accurate prediction ability.

[Discrimination of quality markers of Shujin Huoxue Capsules based on five principles coupled with cobweb model].

The quality markers(Q-markers) of Shujin Huoxue Capsules were comprehensively discriminated based on the five principles of transfer and traceability, specificity, compatibility, effectiveness and measurability. The compounds that could be transferred from the original medicinal materials to the preparation were selected with the principle of transfer and traceability. The specific components in the prescription were screened by reviewing literature with the principle of specificity. According to the principle of compatibility, the attributes of compounds were evaluated by the sovereign, minister, assistant and guide combination rules of the original medicinal materials in the prescription. According to the principle of measurability, the measurable components were summarized by reference to the pharmacopoeia and literature combined with the content. The mechanism of Shujin Huoxue Capsules in the treatment of osteoporosis was studied through network pharmacology based on the principle of effectiveness, which was the evaluation index of effectiveness. The chemical components screened out above were regarded as candidate Q-markers, and the cobweb model was plotted to obtain the comprehensive score of Q-markers. Hydroxysafflor yellow A, trachelosid, eleutheroside B, α-cyperone, protocatechuic acid, protocatechualdehyde and 4-methoxy salicylaldehyde were discriminated as the Q-markers of Shujin Huoxue Capsules based on the five principles combined with cobweb model.

[Integrated smart hyperspectral imaging and CARS-based characteristic band selection for rapid determination of SO_2 content in sulphur-fumigated Achyranthis Bidentatae Radix].

In order to realize the rapid and non-destructive detection of SO_2 content in sulphur-fumigated Achyranthis Bidentatae Radix, this paper first prepared the sulphur-fumigated Achyranthis Bidentatae Radix samples with the usage amount of sulphur being 0, 2.5%, and 5% of the mass of Achyranthis Bidentatae Radix pieces. The SO_2 content in different batches of sulphur-fumigated Achyranthis Bidentatae Radix was determined using the method in Chinese Pharmacopoeia, followed by the acquisition of their hyperspectral data within both visible-near infrared(435-1 042 nm) and short-wave infrared(898-1 751 nm) regions by hyperspectral imaging. Meanwhile, the first derivative, AUTO, multiplicative scatter correction, Savitzky-Golay(SG) smoothing, and standard normal variable transformation algorithms were used to pre-process the original hyperspectral data, which were then subjected to characteristic band extraction based on competitive adaptive reweighted sampling(CARS) and the partial least square regression analysis for building a quantitative model of SO_2 content in sulphur-fumigated Achyranthis Bidentatae Radix. It was found that the accuracy of the quantitative model built depending on the visible-near infrared spectra was high, with the determination coefficient of prediction set(R■) reaching 0.900 1. The established quantitative model has enabled the rapid and non-destructive detection of SO_2 content in sulphur-fumigated Achyranthis Bidentatae Radix, which can serve as an effective supplement to the method described in Chinese Pharmacopeia.

A novel high-resolution monophenolase/diphenolase/radical scavenging profiling for the rapid screening of natural whitening candidates from Peaonia lactiflora root and their mechanism study with molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: The root of Paeonia lactiflora is a traditionally-used whitening medicine in China for thousands of years. Although some tyrosinase inhibitors and/or antioxidants such as 1,2,3,4,6-pentagalloylglucose, gallic acid, have been isolated and identified, their tyrosinase inhibition pathway (monophenolase or diphenolase inhibition, or both two) have not been systematically studied and the underlying tyrosinase inhibition mechanism has not been revealed yet. Moreover, the exploring of new natural tyrosinase inhibitors and antioxidants is urgently needed. AIM OF THE STUDY: This review aimed to develop a new microplate-based high-resolution tyrosinase inhibition profiling assay and establish a furthermore triple high-resolution monophenolase/diphenolase/radical scavenging profiling for accelerating identification bioactive compounds from complicated plant extract. MATERIALS AND METHODS: The targeted isolation and structure elucidation were performed with high-performance liquid chromatography-high-resolution mass spectrometry and preparative high-performance liquid chromatography. It allows to be a proof of concept with the root of Paeonia lactiflora crude extract as a natural whitening herbal drug. RESULTS: The result showed that galloylpaeoniflorin specifically inhibited monophenolase activity. While 1,2,3,4,6-pentagalloylglucose, gallic acid and catechin demonstrated the inhibition towards both monophenolase and diphenolase. Among them, 1,2,3,4,6-pentagalloylglucose can inhibit monophenolase activity was reported for the first time. In addition, antioxidant properties were attributed to catechin, 1,2,3,4,6-pentagalloylglucose and gallic acid. Due to its low content and complicated configuration in the root of Paeonia lactiflora, a new potential tyrosinase inhibitor and radical scavenger which tentatively identified as hexagalloylglucose by high-resolution MS was still need further verification. What's more, the molecular docking unveiled that bioactive enzymatic inhibitors mainly interacted with amino acid catalytic residues of tyrosinase via H-bonds and van der wals, which may be helpful to understand their inhibition mechanisms with tyrosinase in the skin whitening. CONCLUSIONS: The platform provided a promising and efficient strategy for the rapid screening of whitening active components from natural sources.

Tracing anti-osteoporosis components from raw and salt-processed semen of Cuscuta chinensis by employing a biochemometrics strategy that integrates ultrasonic-assisted extraction, quantitation, efficacy assessment in zebrafish, and grey relationship analysis.

Semen of Cuscuta chinensis has been reported to have an anti-osteoporosis effect, however, the components which account for the anti-osteoporosis effect have not been clarified. In this work we propose a biochemometrics strategy that integrates quantitation, anti-osteoporosis evaluation in zebrafish, and grey relationship analysis for the identification of anti-osteoporosis components from the semen of Cuscuta chinensis. In the beginning, a precise and accurate liquid chromatography-tandem mass spectrometry method was established for simultaneous quantitation of seven major components in crude and salt-processed Cuscuta chinensis. The mode of multiple reaction monitoring was used. Chloramphenicol was selected as the internal standard. The method showed good linearity and repeatability. The recovery rates of each component ranged from 95.4 to 103.9%. The precisions of intra-day and inter-day were all within 5.0%. The method was then applied for quantitation of the seven major components in 11 batches of crude and salt-processed Cuscuta chinensis. Subsequently, the anti-osteoporosis effects of crude and salt-processed Cuscuta chinensis were evaluated in zebrafish. Principle component analysis, grey relationship analysis, and partial least squares regression were applied for deciphering the relationship between the contents of seven major components and the anti-osteoporosis effects. Hyperin, p-hydroxycinnamic acid, and astragalin were found to be the major anti-osteoporosis components.

An integrated approach to discriminate the quality markers of Traditional Chinese medicine preparation based on multi-dimensional characteristic network: Shenqi Jiangtang Granule as a case.

BACKGROUND: Due to the complexity of traditional Chinese medicine (TCM), the current quality evaluation of TCM are difficult to associate with clinical efficacy. Shenqi Jiangtang Granule (SJG), a classical TCM formula, is proven as a therapy for treatment of type II diabetes mellitus (DM) and complications while the substantial basis of the therapeutic effects is not clear. PURPOSE: The present study proposed an integrated approach to discriminate the quality markers (Q-markers) based on multi-dimensional characteristic network for quality control of TCM. METHODS: The multi-dimensional characteristic network was established by "Spider-web" mode, which was comprehensively integrating "compatibility-content-activity- efficiency-stability" of the candidate ingredients. The activity dimension was evaluated by the inhibitory activity of SJG on α-glucosidase and aldose reductase. The efficacy dimension was assessed through the association between the compounds and the target pathway of diabetic nephropathy (DN) based on integrated pharmacology platform. Each dimension for the feature network was quantified by multivariate statistical analysis, and regression area of the candidate compounds was constructed in the network. Finally, the candidate compounds were sorted comprehensively by the regression area. RESULTS: A total of 30 chemical compounds with effective hypoglycemic activity were identified as the potential Q-markers. From the data analysis, three dimensions of activity, efficacy and content performed a greater impact on the regression area of the characteristic network. Among these compounds, ginsenoside Re, ginsenoside Rd, ginsenoside Rg1, calycosin, ginsenoside Rb1, formononetin, astragaloside IV, ginsenoside Rf, ginsenoside Rc, notoginsenoside Fe, schisandrol A, gomisin D were screened out as the candidate Q-markers of SJG. CONCLUSION: The multi-dimensional characteristic network integrating compatibility, content, activity, efficiency and stability is efficient to discriminate the potential Q-markers of TCM prescription. Our results demonstrated that 12 candidate compounds from Panax Ginseng, Radix Astragali and Schisandrae Chinensis might select as Q-markers for qualitative evaluation of SJG.

[Identification of Armeniacae Semen Amarum and Persicae Semen from different origins based on near infrared hyperspectral imaging technology].

In order to establish a rapid and non-destructive evaluation method for the identification of Armeniacae Semen Amarum and Persicae Semen from different origins, the spectral information of Armeniacae Semen Amarum and Persicae Semen in the range of 898-1 751 nm was collected based on hyperspectral imaging technology. Armeniacae Semen Amarum and Persicae Semen from different origins were collected as research objects, and a total of 720 Armeniacae Semen Amarum samples and 600 Persicae Semen samples were used for authenticity discrimination. The region of interest(ROI) and the average reflection spectrum in the ROI were obtained, followed by comparing five pre-processing methods. Then, partial least squares discriminant analysis(PLS-DA), support vector machine(SVM), and random forest(RF) method were established for classification models, which were evaluated by the confusion matrix of prediction results and receiver operating characteristic curve(ROC). The results showed that in the three sample sets, the se-cond derivative pre-processing method and PLS-DA were the best model combinations. The classification accuracy of the test set under the 5-fold cross-va-lidation was 93.27%, 96.19%, and 100.0%, respectively. It was consistent with the confusion matrix of the predicted results. The area under the ROC curve obtained the highest values of 0.992 3, 0.999 6, and 1.000, respectively. The study revealed that the near-infrared hyperspectral imaging technology could accurately identify the medicinal materials of Armeniacae Semen Amarum and Persicae Semen from different origins and distinguish the authentication of these two varieties.

An efficient high-speed countercurrent chromatography method for preparative isolation of highly potent anti-cancer compound antroquinonol from Antrodia camphorata after experimental design optimized extraction.

To avoid irreversible stationary phase adsorption and tedious and time-consuming separation steps, high-speed countercurrent chromatography was employed for the preparative separation of anti-tumor compound antroquinonol from solid fermentation culture of Antrodia camphorata for the first time. A Box-Behnken experimental design, based on three parameters including liquid-to-solid ratio, extraction time, and extraction temperature, was applied to optimize the ultrasonic extraction procedure. The optimal extraction condition was set as follows: liquid-to-solid ratio: 49.57:1; extraction time: 55.76 min; extraction temperature was arranged as 44.21°C. Meanwhile, an optimized solvent system containing petroleum ether, ethyl acetate, methanol, and water (4:1:4:1, v/v/v/v) was selected for the preparative separation of antroquinonol at a flow rate of 2.0 mL/min. The yield of isolated antroquinonol was determined to be 6.0 mg from 0.67 g of ethyl acetate extracts. The isolated antroquinonol was elucidated by ultra-high-performance liquid chromatography-tandem mass spectrometry, and NMR spectroscopy, and by comparison with literature data. The purity of isolated antroquinonol was determined to be 97.12%. This study confirmed that high-speed countercurrent chromatography was powerful and cost-effective for the preparative separation of the high-potently anti-tumor compound antroquinonol from solid fermentation culture of A. camphorata.

[Fusion of spectrum and image features to identify Glycyrrhizae Radix et Rhizoma from different origins based on hyperspectral imaging technology].

To identify Glycyrrhizae Radix et Rhizoma from different geographical origins, spectrum and image features were extracted from visible and near-infrared(VNIR, 435-1 042 nm) and short-wave infrared(SWIR, 898-1 751 nm) ranges based on hyperspectral imaging technology. The spectral features of Glycyrrhizae Radix et Rhizoma samples were extracted from hyperspectral data and denoised by a variety of pre-processing methods. The classification models were established by using Partial Least Squares Discriminate Analysis(PLS-DA), Support Vector Classification(SVC) and Random Forest(RF). Meanwhile, Gray-Level Co-occurrence matrix(GLCM) was employed to extract textural variables. The spectrum and image data were implemented from three dimensions, including VNIR and SWIR fusion, spectrum and image fusion, and comprehensive data fusion. The results indicated that the spectrum in SWIR range performed better classification accuracy than VNIR range. Compared with other four pre-processing methods, the second derivative method based on Savitzky-Golay(SG) smoothing exhibited the best performance, and the classification accuracy of PLS-DA and SVC models were 93.40% and 94.11%, separately. In addition, the PLS-DA model was superior to SVC and RF models in terms of classification accuracy and model generalization capability, which were evaluated by confusion matrix and receiver operating characteristic curve(ROC). Comprehensive data fusion on SPA bands achieved a classification accuracy of 94.82% with only 28 bands. As a result, this approach not only greatly improved the classification efficiency but also maintained its accuracy. The hyperspectral imaging system, a non-invasively, intuitively and quickly identify technology, could effectively distinguish Glycyrrhizae Radix et Rhizoma samples from different origins.

A comprehensive quality evaluation method of Corydalis yanhusuo by HPLC fingerprints, chemometrics, and correlation analysis.

A novel quality evaluation method of Corydalis yanhusuo was established by researching the high-performance liquid chromatography behavior of alkaloids under different buffer solutions and exploring the correlation between alkaloids in C. yanhusuo. The retention times of tetrahydropalmatine and corydaline were significantly influenced by pH, while the peak shape was affected by buffer types and ionic strength. The resolution of compounds in fingerprint was satisfactory under acetonitrile-0.2% phosphoric acid buffer (adjusted pH to 5.0 with triethylamine). Twelve common peaks were found by comparing 20 batches of C. yanhusuo fingerprints, and three tertiary alkaloids and four quaternary alkaloids were identified. The fingerprints were analyzed by similarity analysis, hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis. All samples were divided into three groups, and the contents of dehydrocorydaline and coptisine from Zhejiang province were relatively higher than other origins. There were six components performing more contributions to the quality of C. yanhusuo. The correlations between alkaloids were conducted by Pearson correlation analysis and mathematical model analysis. The content correlation between palmatine and berberine was y = 0.28x2  + 0.03x + 0.03, and the dehydrocorydaline and coptisine was y = -7.54/(1 + (x/0.14)0.5 ) + 2.61. The established mathematical model of alkaloids provided a guiding significance for the quality control of C. yanhusuo.

Simultaneous Determination of Saponins and Lignans in Rat Plasma by UPLC- MS/MS and its Application to a Pharmacokinetic Study of Shenqi Jiangtang Granule.

BACKGROUND: Shenqi Jiangtang Granule (SJG), a classical prescription of traditional Chinese medicine, is widely used to treat diabetes and its complications. Although, the clinical efficacy of SJG, is sufficient, the pharmacokinetic behavior of various substances in the plasma of SJG is unknown. OBJECTIVE: The aim of this study was to investigate the plasma pharmacokinetics during absorption of SJG after oral administration in rats. METHODS: A rapid and accurate ultra-high performance liquid chromatography/tandem mass spectrometry (UPLC- MS/MS) method was developed for the simultaneous determination of eight analytes in SJG, including gomisin D, schisandrin A, schisandrin B, schizandrol A, schizandrol B, ginsenoside Rd, ginsenoside Re and notoginsenoside Ft1. The analysis was carried out on a BEH C18 column (2.1 mm × 50 mm, 1.7 µm) with gradient elution at a flow rate of 0.2 mL/min in a mobile phase consisting of 0.1% formic acid water and acetonitrile. In addition, lignans and saponins were detected in positive ion mode and negative ion mode, respectively. RESULTS: Eight analytes in SJG, including gomisin D, schisandrin A, schisandrin B, schizandrol A, schizandrol B, ginsenoside Rd, ginsenoside Re and notoginsenoside Ft1, showed good linearity (R2 in the range of 0.9955 ~ 0.9999). The lower limit of quantification (LLOQ) was 5, 0.8, 0.8, 8, 0.8, 5, 0.6 and 10 ng/mL. The accuracy and precision of all analytes were at ±15%. Matrix effect and average extraction recovery were > 85%. All analytes performed well under four storage conditions. CONCLUSION: The results showed that in vivo absorption and exposure of gomisin D and ginsenoside Rd were better than other analytes, while schizandrol B and notoginsenoside Ft1 were poorly absorbed. This approach could be applied to study the pharmacokinetic characteristics of various analytes in plasma after oral administration of SJG in rats.

Screening and characterization of aldose reductase inhibitors from Traditional Chinese medicine based on ultrafiltration-liquid chromatography mass spectrometry and in silico molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: Shenqi Jiangtang granule (SJG) is an ancient Chinese herbal formula used for treatment of Diabetes mellitus and its complications. AIM OF THE STUDY: To establish an integrated approach for discovery of effective Aldose reductase inhibitors (ARIs) from SJG. MATERIALS AND METHODS: An integrated approach combining ultrafiltration-liquid chromatography-mass spectrometry (UF-LC-MS) with in silico molecular docking was established for development of ARIs. AR enzyme was separated from the rabbit's crystalline lens. The inhibitory activities of these compounds were detected by UV spectrophotometry with DL-glyceraldehyde as a substrate. Furthermore, molecular docking was used to understand the binding mechanism of these screened compounds interacting with AR. RESULTS: After optimization of AR reaction system and ultrafiltration incubation system, 17 active ingredients were screened from SJG by UF-LC-MS technique. Among these potential AR inhibitors, ginsenoside Rd exhibited the strongest activity with IC50 value of 45.77 µM. Three of them, calycosin, gomisin J and schisandrin A were demonstrated to be potential inhibitors for the first time, with IC50 at 447.34 µM, 181.73 µM, and 429.00 µM, respectively. Most of the active compounds exhibited competitive inhibition against AR. The docking scores of saponins were higher than that of lignans, which was consistent with the verification results. CONCLUSION: The results indicated that TCM formula with clinical efficacy was indeed hopeful source for screening active ingredients, and the combination of UF-LC-MS and in silico molecular docking was a universal and promising approach for development of effective enzyme inhibitors.

LABEL-FREE BIO-AFFINITY MASS SPECTROMETRY FOR SCREENING AND LOCATING BIOACTIVE MOLECULES.

Despite the recent increase in the development of bioactive molecules in the drug industry, the enormous chemical space and lack of productivity are still important issues. Additional alternative approaches to screen and locate bioactive molecules are urgently needed. Label-free bio-affinity mass spectrometry (BA-MS) provides opportunities for the discovery and development of innovative drugs. This review provides a comprehensive portrayal of BA-MS techniques and of their applications in screening and locating bioactive molecules. After introducing the basic principles, alongside some application notes, the current state-of-the-art of BA-MS-assisted drug discovery is discussed, including native MS, size-exclusion chromatography-MS, ultrafiltration-MS, solid-phase micro-extraction-MS, and cell membrane chromatography-MS. Finally, several challenges and limitations of the current methods are summarized, with a view to potential future directions for BA-MS-assisted drug discovery. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

[Evaluation of key production processes of Schizonepetae Herba formula granules based on characteristic chromatogram and quantitative transfer relationship].

The aim of this paper was to evaluate the key production processes of Schizonepetae Herba formula granules based on the new model of combining characteristic chromatogram with quantitative transfer relationship. The rationality of production process design was evaluated by studying the intermediates in different processes of formula granules, analyzing the loss of index component pulegone in each step, and establishing the characteristic chromatogram. The content of pulegone in 10 batches of standard decoction ranged between 0.067% and 0.124%(70%-130% of the average value), and the transfer rate of pulegone was 44.58%-93.97%. After the improvement of the production process, the content of pulegone in Schizonepetae Herba formula granules was 0.093%, and the transfer rate of pulegone was 68.38%, which was consistent with the parameters range of standard decoction. This study emphasized the integrality of the research process of traditional Chinese medicine(TCM) formula granules, and provided a new idea for the quality control of TCM with content determination as the main evaluation index for a long time.

Simultaneous determination of seven compounds in Chinese patent medicines Chenxiangqu by matrix solid-phase dispersion coupled with ultra high performance liquid chromatography and quadrupole time-of-flight mass spectrometry.

A simple, efficient, and sensitive strategy by coupling matrix solid-phase dispersion with ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry was proposed to extract and determine three types of components (including seven analytes) in Chinese patent medicines Chenxiangqu. The highly ordered mesoporous material Fe-SBA-15 synthesized under weakly acidic conditions was selected as a dispersant in matrix solid phase dispersion extraction for the first time. Several parameters including the mass ratio of sample to dispersant, the type of dispersant, the grinding time, and the elution condition were investigated in this work. Under the optimized conditions, 20 compounds were identified by quadrupole time-of-flight mass spectrometry and seven analytes were quantified. The results demonstrated that the developed method has good linearity (r > 0.9995), and the limits of detection of the analytes were as low as 0.55 ng/mL. The recoveries of all seven analytes ranged from 97.6 to 104.6% (relative standard deviation < 3.4%). Finally, the improved method was successfully applied to determination of five batches of Chenxiangqu samples, which provided a robust method in quality control of Chinese patent medicines Chenxiangqu. The developed strategy also shows its great potential in analysis of complex matrix samples.