Bone protective effects of the polysaccharides from Grifola frondosa on ovariectomy-induced osteoporosis in mice via inhibiting PINK1/Parkin signaling, oxidative stress and inflammation.

BACKGROUND: Polysaccharides from Grifola frondosa(GFP) have gained worldwide attention owing to their promising biological activities and potential health benefits. PURPOSE: This study aimed to investigate the effects of GFP on alleviation of osteoporosis in ovariectomized (OVX) mice and examine the underlying mechanism. METHOD: A mouse model of postmenopausal osteoporosis was established by OVX method, Forty eight C57BL/6 female mice were randomly divided into Normal group, OVX alone (Model group, n = 8), OVX + 10 mg/kg GFP (GFP-L group, n = 8), OVX + 20 mg/kg GFP (GFP-M group, n = 8), OVX + 40 mg/kg GFP (GFP-H group, n = 8), OVX + 10 mg/kg Estradiol valerate (Positive group, n = 8). RESULTS: The results showed that compared with Model group, the concentrations of interleukin (IL)-1ß, interleukin (IL)-6 and Tumor necrosis factor-α (TNF-α) were significantly reduced, the activity of superoxide dismutase (SOD) and glutathione (GSH) were significantly increased, the content of myeloperoxidase (MPO) and malondialdehyde (MDA) were significantly reduced, and the proteins levels of PINK1, Parkin, Beclin-1 and LC3-II were significantly decreased in the GFP groups. CONCLUSION: This study demonstrates that GFP alleviates ovariectomy-induced osteoporosis via reduced secretion of inflammatory cytokines, improvement in the oxidative stress status in the body, and inhibition of the PINK1/Parkin signaling pathway.

Prediction of the activity of early ankylosing spondylitis using radiomics texture analysis on STIR.

OBJECTIVES: The study aimed to explore the value of texture analysis of radiomics based on the short tau inversion recovery (STIR) sequence to evaluate the activity of bone marrow oedema of sacroiliac joints in early AS. METHODS: 43 patients with early AS whose data were randomly divided into the training cohort (n=116) and verification cohort (n=56) according to the ratio of 7:3. The optimal feature subsets were obtained by Mann-Whitney U-test, the minimum-Redundancy Maximum-Relevancy (mRMR), and then least absolute shrinkage and selection operator (LASSO) using these texture feature parameters, which were used to construct the final prediction model and obtained the Radscore. The ROC curve was performed to evaluate the performance of the model. The Spearman correlation test was used to analyse the correlation of various indicators. RESULTS: In the training cohort, to differentiate early AS sacroiliac joint bone marrow oedema between the active and stable groups, the AUCs of the Radscore, SPARCC and ADC were 0.81, 0.91, 0.78, respectively. In the validation cohort, the AUCs were 0.87, 0.89, 0.85. In the two cohorts, there were no significant differences in AUCs between values of the Radscore and SPARCC, ADC (p>0.05). There was a significant difference in AUC between SPARCC and ADC in the training cohort (p<0.05), with no statistical significance in the validation cohort (p>0.05). The correlations were all low between the Radscore values and the values of ESR, CRP, tI, ASDAS-ESR and ASDAS-CRP (p<0.05). CONCLUSIONS: Radiomics analysis based on STIR texture analysis has a good prediction for the evaluation of bone marrow oedema activity of sacroiliac joints in AS. It can be a new non-invasive and objective evaluation method for AS activity.

Applying Machine Learning Analysis Based on Proximal Femur of Abdominal Computed Tomography to Screen for Abnormal Bone Mass in Femur.

RATIONALE AND OBJECTIVES: To evaluate the performance of machine learning analysis based on proximal femur of abdominal computed tomography (CT) scans in screening for abnormal bone mass in femur. MATERIALS AND METHODS: 222 patients aged 50 years or older who underwent abdominal CT and dual-energy X-ray absorptiometry scans within 14 days were retrospectively enrolled. The patients were randomly assigned to a training cohort (n = 155) and a testing cohort (n = 67) in a ratio of 7:3. A total of 2288 candidate radiomic features were extracted from the volume region of interest - the left proximal femur of the abdominal CT scans. The most valuable radiomic features were selected using minimum-Redundancy Maximum-Relevancy and the least absolute shrinkage and selection operator to construct the radiomics model. The predictive performance was assessed with receiver operating characteristic curve. RESULTS: 13 features were chosen to establish the radiomics model. The radiomics model using logistic regression displayed excellent prediction performance in distinguishing normal bone mass and abnormal bone mass, with the area under the curve (AUC), accuracy, sensitivity and specificity of 0.917 (95% CI, 0.867-0.967), 0.826, 0.935 and 0.780 in the training cohort. The testing cohort indicated a better performance with AUC, accuracy, sensitivity and specificity of 0.963 (95% CI, 0.919-0.999), 0.851, 0.923 and 0.889. CONCLUSION: The radiomics model based on proximal femur of abdominal CT scans had a high predictive performance to identify abnormal bone mass in femur, which can be used as a tool for opportunistic osteoporosis screening.

Rapid identification of α-glucosidase inhibitors from Poria using spectrum-effect, component knock-out, and molecular docking technique.

Instruction: Poria (Poria cocos) is known for its health-promoting effects and is consumed as a food due to its potential hypoglycemic activity. However, the composition of Poria is complex, and the bioactive compounds that inhibit α-glucosidase are not clear. Methods: In this study, the fingerprint of the Poria methanol extract characterized by high-performance liquid chromatography (HPLC) and the model of the corresponding spectrum-effect relationship for α-glucosidase was first established to screen the active compounds from Poria. Then, the predicted bioactive compounds were knocked out and identified using mass spectrometry. Finally, the potential binding sites and main bonds of each compound with α-glucosidase were studied using molecular docking. Results: The results have shown that at least 11 compounds from Poria could inhibit α-glucosidase effectively. Moreover, eight individual compounds, i.e., poricoic acid B (P8), dehydrotumulosic acid (P9), poricoic acid A (P10), polyporenic acid C (P12), 3- epidehydrotumulosic acid (P13), dehydropachymic acid (P14), 3-O-acetyl-16α-hydroxytrametenolic acid (P21), and pachymic acid (P22), were identified, and they exhibited effective inhibitory activity against α-glucosidase. Discussion: The possible inhibitory mechanism of them based on molecular docking showed that the binding sites are mainly found in the rings A, B, and C of these compounds, and C-3 C-16 and side chains of C-17, with the phenylalanine, arginine, tyrosine, histidine, and valine of α-glucosidase. The main interactions among them might be alkyl and hydrogen bonds, which theoretically verified the inhibitory activity of these compounds on α-glucosidase. The achievements of this study provided useful references for discovering bioactive compounds with hypoglycemic effects from Poria.

Paravertebral Block Under Direct Vision Versus Local Anesthetic Infiltration for Pediatric Thoracoscopic Surgery.

Background: For children with congenital lung malformations (CLMs), there is insufficient evidence of the efficacy of direct visual paravertebral block (PVB). We aimed to evaluate its effectiveness and safety by comparing it with local anesthetic infiltration (LAI). Materials and Methods: This was a nonrandomized control study of CLMs in children younger than 3 years of age who underwent thoracoscopic surgery in our hospital from January to December 2020. The children were divided into group A (PVB analgesia group) and group B (LAI group). The primary outcome was the incidence of rebound pain within 72 hours. Secondary outcomes included the Face, Legs, Activity, Crying, Consolability (FLACC) pain scores at 0, 6, 12, 24, 36, 48, and 72 hours, side effects, adverse events, the number of rebound pains, and the postoperative family observation scores. Results: The incidence of rebound pain was 10% in group A and 60.5% in group B within 72 hours (P < .001). The PVB was associated with decreased FLACC pain scores at 12, 24, 36, 48, and 72 hours, family observation scores, and the number of rebound pains (P < .001, P = .01, P = .028, P = .005, P = .006, P = .026, and P < .001, respectively). Group B was also associated with a higher rate of side effects and adverse events. There was no difference in the length of hospital stay. Conclusion: The PVB under direct vision analgesia technique is effective and safe for postoperative pain control in pediatric patients with CLMs. It may be an attractive alternative to LAI for pediatric thoracoscopic surgical procedures.

Automated segmentation of vertebral cortex with 3D U-Net-based deep convolutional neural network.

Objectives: We developed a 3D U-Net-based deep convolutional neural network for the automatic segmentation of the vertebral cortex. The purpose of this study was to evaluate the accuracy of the 3D U-Net deep learning model. Methods: In this study, a fully automated vertebral cortical segmentation method with 3D U-Net was developed, and ten-fold cross-validation was employed. Through data augmentation, we obtained 1,672 3D images of chest CT scans. Segmentation was performed using a conventional image processing method and manually corrected by a senior radiologist to create the gold standard. To compare the segmentation performance, 3D U-Net, Res U-Net, Ki U-Net, and Seg Net were used to segment the vertebral cortex in CT images. The segmentation performance of 3D U-Net and the other three deep learning algorithms was evaluated using DSC, mIoU, MPA, and FPS. Results: The DSC, mIoU, and MPA of 3D U-Net are better than the other three strategies, reaching 0.71 ± 0.03, 0.74 ± 0.08, and 0.83 ± 0.02, respectively, indicating promising automated segmentation results. The FPS is slightly lower than that of Seg Net (23.09 ± 1.26 vs. 30.42 ± 3.57). Conclusion: Cortical bone can be effectively segmented based on 3D U-net.

Radiomics nomogram based on dual-energy spectral CT imaging to diagnose low bone mineral density.

BACKGROUND: Osteoporosis is associated with a decrease of bone mineralized component as well as a increase of bone marrow fat. At present, there are few studies using radiomics nomogram based fat-water material decomposition (MD) images of dual-energy spectral CT as an evaluation method of abnormally low Bone Mineral Density (BMD). This study aims to establish and validate a radiomics nomogram based the fat-water imaging of dual-energy spectral CT in diagnosing low BMD. METHODS: Ninety-five patients who underwent dual-energy spectral CT included T11-L2 and dual x-ray absorptiometry (DXA) were collected. The patients were divided into two groups according to T-score, normal BMD(T ≥ -1) and abnormally low BMD (T < -1). Radiomic features were selected from fat-water imaging of the dual-energy spectral CT. Radscore was calculated by summing the selected features weighted by their coefficients. A nomogram combining the radiomics signature and significant clinical variables was built. The ROC curve was performed to evaluate the performance of the model. Finally, we used decision curve analysis (DCA) to evaluate the clinical usefulness of the model. RESULTS: Five radiomic features based on fat-water imaging of dual-energy spectral CT were constructed to distinguish abnormally low BMD from normal BMD, and its differential performance was high with an area under the curve (AUC) of 0.95 (95% CI, 0.89-1.00) in the training cohort and 0.97 (95% CI, 0.91-1.00) in the test cohort. The radiomics nomogram showed excellent differential ability with AUC of 0.96 (95%CI, 0.91-1.00) in the training cohort and 0.98 (95%CI, 0.93-1.00) in the test cohort, which performed better than the radiomics model and clinics model only. The DCA showed that the radiomics nomogram had a higher benefit in differentiating abnormally low BMD from normal BMD than the clinical model alone. CONCLUSION: The radiomics nomogram incorporated radiomics features and clinical factor based the fat-water imaging of dual-energy spectral CT may serve as an efficient tool to identify abnormally low BMD from normal BMD well.

Comparison of L1 CT-attenuation and cortical thickness in predicting osteoporosis by opportunistic CT.

BACKGROUND: In vertebrae, the amount of cortical bone has been estimated at 30-60%, but 45-75% of axial load on a vertebral body is borne by cortical bone. OBJECTIVE: To compare the role of L1 CT-attenuation and cortical thickness in predicting osteoporosis by opportunistic CT and explore cortical thickness value in osteoporosis. METHODS: We collected data of 94 patients who underwent DXA and thoracic and/or abdominal CT to demonstrate an entire L1 for other indications in routine practice. Patients were divided into three groups according to T-score: osteoporosis, osteopenia, or normal. CT-attenuation value and cortical thickness of L1 were measured. ANOVA analysis was utilized to analyze CT-attenuation and cortical thickness among the three groups. Sensitivity, specificity, and area under the curve (AUC) predicting low BMD were determined using ROC. Pearson correlations were employed to describe relationship between L1 BMD and CT-attenuation value, BMD, as well as cortical thickness. RESULTS: The mean cortical thickness was 0.83±0.11, 0.72±0.10, and 0.64±0.09 mm for normal, osteopenia, and osteoporotic subgroups, respectively. A statistically significant difference was observed in cortical thickness and CT-attenuation value among these three subgroups. A mean CT-attenuation value threshold of > 148.7 yielded 73.0% sensitivity and 86.0% specificity for distinguishing low BMD from normal with an AUC = 0.83. Pearson correlation analysis indicated that BMD was positively correlated with CT-attenuation (r = 0.666, P < 0.001) and cortical thickness (r = 0.604, P < 0.001). CONCLUSIONS: L1 CT-attenuation and cortical thickness measured on opportunistic CT can help predict osteoporosis. Compared with cortical thickness, CT-attenuation is a more sensitive and accurate index for distinguishing low BMD from normal.

Prediction of acute versus chronic osteoporotic vertebral fracture using radiomics-clinical model on CT.

PURPOSE: This paper aims to use radiomics-clinical analysis based on CT imaging to distinguish between acute and chronic osteoporotic vertebral fractures. METHOD: A total of 147 patients who underwent both dual-energy X-ray absorptiometry (DEXA), CT and MRI of the spine were analyzed retrospectively. The patients were assigned to either a training cohort (n = 103) or a validation cohort (n = 44). The radiomics model and combined nomogram model were established by multivariate logistic regression analysis. The predictive performance was assessed with receiver operating characteristic (ROC) curve. RESULTS: Fourteen radiomic features based on spine CT images were constructed to distinguish acute versus chronic osteoporotic vertebral fractures, and its differentialperformance was good with an area under the curve (AUC) of 0.90 (95% CI, 0.84-0.95) in the training cohort and 0.82 (95% CI, 0.69-0.94) in the validation cohort. Based on the radiomic signature and clinical fracture line feature, a combined nomogram was developed and showed excellent differential ability with highest AUC of 0.93 (95 %CI,0.88-0.98) in the training cohort and 0.86 (95 %CI,0.73-0.98) in the validation cohort, which performed better than the clinical model significantly only. CONCLUSIONS: A quantitative nomogram based on clinical fracture line feature and radiomic features of CT images can be used to distinguish acute and chronic osteoporotic vertebral fractures with excellent predictive ability, which can be served as a potential decision support tool to assist clinicians in evaluating the phase of vertebral fractures timely, especially in situation where spine MRI was not available for patient.

Quantitative DCE-MRI: an efficient diagnostic technique for evaluating early micro-environment permeability changes in ankylosing spondylitis.

BACKGROUND: In the management of early inflammatory joint of ankylosing spondylitis (AS), there is a need for reliable noninvasive quantitative monitoring biomarker to closely assess status of synovitis progression. Cognizant to this,studies geared on improving techniques for quantitative evaluation of micro-environment permeability of the joint space are necessary. Such improved techniques may provide tissue perfusion as important biological parameters and can further help in understanding the origin of early changes associated with AS. The purpose of this study was to prospectively evaluate the diagnostic performance and determine longitudinal relationships of early micro-environment active in the joint space of the sacroiliac joint (SIJ) with a rat model by using quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: Thirty wistar male rats were randomly assigned to the model (n = 15) or control (n = 15) group. All rats underwent DCE-MRI of SIJ region at fixed time points (12, 17 and 22 weeks),between September 2018 and October 2019. Differences in permeability parameters between the two groups at the same time point were compared by using an independent samples t test. Spearman correlations of DCE-MRI parameters with different time points in model group were analyzed. All statistical analyses were performed with software. RESULTS: At 12 weeks,the Ktrans,Kep and Ve values in the model group were slightly lower than those in control group,but all the differences were not statistically significant (p > 0.05). Compared with control group,the transfer constant (Ktrans) values increased significantly at 17 weeks and 22 weeks in model group,while the rate constant (Kep) and volume of extravascular extracellular space (Ve) significantly increased only at 22 weeks(p < 0.05). The Ktrans,Kep and Ve were positively correlated with increasing time points (r = 0.946, P<0.01 for Ktrans; r = 0.945, P<0.01 for Kep; and r = 0.832, P<0.01 for Ve). CONCLUSION: Quantitative DCE-MRI parameters are valuable for evaluating the early longitudinal relationship of micro-environment permeability changes in the joint space of SIJ.

Comparative study of imaging and histology of sacroiliac joint in normal rats based on IVIM-DWI and DCE-MRI.

BACKGROUND: Currently, few studies have described the relationship between functional MRI findings and histology of normal sacroiliac joint (SIJ). Besides, due to the difficulties in access to SIJ, authentic animal models are important in providing opportunities for quantitative parameter extraction on imaging. AIMS: This study aimed at exploring the parameters of Intravoxel Incoherent Motion Diffusion-Weighted Imaging (IVIM-DWI) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) and comparing them with the histology of the SIJ in normal rats with different ages. METHODS: A total of thirty 7-week-old male Wistar rats were included in the study. The parameters of IVIM-DWI and DCE-MRI in the bone marrow and the joint space of SIJ were measured at 8, 13, 18, 23, 28, and 33 weeks. The histological analysis of the SIJ was examined using light microscopy. One-way ANOVA was used for statistical analysis. RESULTS: The D values in the sacral and iliac bone marrow of normal rats decreased with an increase in age. One-way ANOVA analysis indicated a significant difference in D values in different age groups (P<0.005). The normal values of D*, f, Fenh (%), Senh (%/s) in the sacral bone marrow, the iliac bone marrow, and the joint space in SIJ of normal rats were obtained. The results showed that in the six groups of rats of different ages, the histology of the SIJ surface was smooth and clear, the cartilage cells were intact, and no thickening or pannus formation was observed. CONCLUSIONS: This study obtained the IVIM-DWI and DCE-MRI parameters of the sacral and iliac bone marrow and the synovial area of the joint space in normal rats. The parameters in normal rats can be used in future research to compare to similar parameters in animal models or patients with SIJ diseases. This study serves as a guide for future research in SIJ diseases.

Ionic Liquid-Based Ultrasonic-Assisted Extraction Coupled with HPLC and Artificial Neural Network Analysis for Ganoderma lucidum.

Ganoderma lucidum is widely used in traditional Chinese medicine (TCM). Ganoderic acid A and D are the main bioactive components with anticancer effects in G. lucidum. To obtain the maximum content of two compounds from G. lucidum, a novel extraction method, an ionic liquid-based ultrasonic-assisted method (ILUAE) was established. Ionic liquids (ILs) of different types and parameters, including the concentration of ILs, ultrasonic power, ultrasonic time, rotational speed, solid-liquid ratio, were optimized by the orthogonal experiment and variance analysis. Under these optimal conditions, the total extraction yield of the two compounds in G. lucidum was 3.31 mg/g, which is 36.21% higher than that of the traditional solvent extraction method. Subsequently, an artificial neural network (ANN) was developed to model the performance of the total extraction yield. The Levenberg-Marquardt back propagation algorithm with the sigmoid transfer function (logsig) at the hidden layer and a linear transfer function (purelin) at the output layer were used. Results showed that single hidden layer with 9 neurons presented the best values for the mean squared error (MSE) and the correlation coefficient (R), with respectively corresponding values of 0.09622 and 0.93332.

Values of intravoxel incoherent motion diffusion weighted imaging and dynamic contrast-enhanced MRI in evaluating the activity of sacroiliitis in ankylosing spondylitis of rat model.

OBJECTIVE: To prospectively evaluate the ability of IVIM-DWI and DCE-MRI in detecting early activity of sacroiliitis in rat model of ankylosing spondylitis by comparing with pathological results. METHODS: 20 wistar male rats were induced by bovine proteoglycan combined with complete/incomplete Freund's adjuvant as model group, and 20 healthy male rats were used as the control group. The parameters of IVIM-DWI and DCE-MRI in synovial regions of SIJ were measured respectively at 7th, 12th, 17th, and 22th weeks after the last induction, and the pathological features of SIJ were taken also, further studying the pathological characteristics of sacroiliac region. Independent sample t-test and one-way ANOVA were used for statistical analysis. The prediction parameters and diagnostic efficiency were compared by ROC curve. RESULTS: There was no significant difference of image parameters between the model and control groups at the 7th, 12th weeks after the last induction, and there were no positive findings in histopathological examination at the same time. At the 17th week after induction, the f and Fenh%, Senh% between the model and the control groups were statistically significant. At the 22th week, there was a statistically significant increase all the values in model group than those in control group (P < 0.05). Histologic examination confirmed inflmmtorycell infiitrtion at the 17th week and pannus forming of synovium on the surface of cartilage at the 22th week in the model groups. The Fenh%, Senh%, Dslow and f had the moderate diagnostic efficiency and the areas under the curve were 0.77, 0.75, 0.77 and 0.82 respectively. The Senh% demonstrated the highest sensitivity (71.4%) and f demonstrated the highest specificity (95.0%). CONCLUSION: IVIM-DWI and DCE-MRI can be used as the sensitive imaging methods to detect and accurate diagnosis the early activity of sacroiliitis in AS.

Evaluation Procoagulant Activity and Mechanism of Astragalin.

Astragalin, isolated from flowers of Rosa chinensis Jacq., is a kind of flavonoid, with anti-inflammatory, antioxidant, antiviral, analgesic, antibacterial, antiallergic, and antihepatotoxic effects. However, no studieson the procoagulant effect of astragalin have been reported. This study aimed to investigate the procoagulant activity of astragalin and its mechanism. Its procoagulant effect was investigated by activated partial thromboplastin time (APTT), thrombin time (TT), prothrombin time (PT), and fibrinogen (FIB) in vitro, and a rat model established by heparin sodium was used to evaluate the mechanism for the procoagulant effect in vivo. The results showed that astragalin had good procoagulant effects compared with the control group in vitro. Compared with the model group in vivo, astragalin could shorten the coagulation time and significantly increase the number of platelets. Meanwhile, astragalin could significantly reduce the effectual time of PT and APTT and increase the content of FIB. The contents of 6-keto-PGF1α and eNOS significantly decreased. Astragalin could increase whole blood viscosity (WBV), plasma viscosity (PV), erythrocyte sedimentation rate (ESR) and packedcell volume (PCV). All of the above revealed that astragalin had good procoagulant effects by promoting the intrinsic and extrinsic coagulation system.

CYPs-mediated drug-drug interactions on psoralidin, isobavachalcone, neobavaisoflavone and daidzein in rats liver microsomes.

The incubation system of CYP2E1 and CYP3A4 enzymes in rat liver microsomes was established to investigate the effects of psoralidin, isobavachalcone, neobavaisoflavone and daidzein from Fructus Psoraleae in vitro. The relevant metabolites were measured by the method of high performance liquid chromatography (HPLC), after probe substrates of 4-nitrophenol, testosterone and the drugs at different concentrations were added to the incubation systems. In addition, real-time RT-PCR was performed to determine the effect of psoralidin, neobavaisoflavone and daidzein on the mRNA expression of CYP3A4 in rat liver. The results suggested that psoralidin, isobavachalcone and neobavaisoflavone were Medium-intensity inhibitors of CYP2E1 with Ki values of 2.58, 1.28 and 19.07 µM, respectively, which could inhibit the increase of CYP2E1 and reduce diseases caused by lipid peroxidation. Isobavachalcone (Ki = 37.52 µM) showed a weak competitive inhibition on CYP3A4. Psoralidin and neobavaisoflavone showed obvious induction effects on CYP3A4 in the expression level of mRNA, which could accelerate the effects of drug metabolism and lead to the risk of inducing DDIs and serious adverse reactions. The results could be used for guideline of Fructus Psoraleae in clinic, which aimed to calculate the drug toxicity by studying the drug-drug interactions caused by the induction and inhibition of CYP450.

Chemical constituents and coagulation activity of Syringa oblata Lindl flowers.

The leaves and bark of Syringa oblata Lindl are used as folk medicine which has heat-clearing, detoxifying, dampness-removing and jaundice-relieving effects. There are many studies about leaves of S. oblata because of its abundant resource, however, less reports about the components of S. oblata flowers. The previous studies on S. oblate flowers were mainly focused on the volatile components and its traditional pharmacological activity. Thus, this study aimed to investigate the nonvolatile chemical constituents and the coagulation activity of S. oblate flowers. The chemical constituents of S. oblate flowers were isolated with various column chromatographies and coagulation activity of the major constituents was investigated by assaying the activated partial thromboplastin time (APTT), prothrombin time (PT), thrombin time (TT) and fibrinogen (FIB) on plasma of rabbit in vitro. Fifteen known compounds (namely compound 1-15) were isolated from S. oblata flowers. Compound 6, 10, 11 and 14 were isolated from Syringa genus for the first time. Compound 1, 2, 4, 5, 8 and 9 were isolated from the plant for the first time. The results of coagulation activity showed that water part of S. oblate flowers, lauric acid and kaempferol-rutinose significantly shorten PT (P < 0.001), TT (P < 0.001) and APTT (P < 0.001) compared with blank group, thus revealed that water extract of S. oblate flowers, lauric acid and kaempferol-rutinose possessed the procoagulant activity, but the effects were not better than that of Yunnan Baiyao as positive control.

Ionic Liquid-Based Ultrasonic-Assisted Extraction to Analyze Seven Compounds in Psoralea Fructus Coupled with HPLC.

Psoralea Fructus is widely used in traditional Chinese medicine (TCM), and the content of psoralen, isopsoralen, neobavaisoflavone, bavachin, psoralidin, isobavachalcone, and bavachinin A is the main quality control index of Psoralea Fructus because of its clinical effects. Thus, a fast and environmentally-benign extraction method of seven compounds in Psoralea Fructus is necessary. In this work, an ionic liquid-based ultrasonic-assisted method (ILUAE) for the extraction of seven compounds from Psoralea Fructus was proposed. Several ILs of different types and parameters, including the concentration of ILs, concentration of ethanol (EtOH), solid-liquid ratio, particle size, ultrasonic time, centrifugal speed, and ultrasonic power, were optimized by the Placket-Burman (PB) design and Box-Behnken response surface analysis. Under this optimal condition, the total extraction yield of the seven compounds in Psoralea Fructus was 18.90 mg/g, and significantly greater than the conventional 75% EtOH solvent extraction.

Screening the Marker Components in Psoralea corylifolia L. with the Aids of Spectrum-Effect Relationship and Component Knock-Out by UPLC-MS².

Psoralea corylifolia L., (P. corylifolia), which is used for treating vitiligo in clinic, shows inhibitory and activating effects on tyrosinase, a rate-limiting enzyme of melanogenesis. This study aimed to determine the active ingredients in the ethenal extracts of P. corylifolia on tyrosinase activity. The spectrum-effect relationship and knock-out method were established to predict the active compounds. Their structures were then identified with the high resolution mass spectra. A high performance liquid chromatography method was established to obtain the specific chromatograms. Tyrosinase activity in vitro was assayed by the method of oxidation rate of levodopa. Partial least squares method was used to test the spectrum-effect relationships. Chromatographic peaks P2, P4, P9, P10, P11, P13, P21, P26, P28, and P30 were positively related to the activating effects on tyrosinase activity in PE, whereas chromatographic peaks P1, P3, P6, P14, P16, P19, P22, and P29 were negatively related to the activating effects on tyrosinase in the P. corylifolia (PEs). When the sample concentration was 0.5 g·mL-1, equal to the amount of raw medicinal herbs, the target components were daidzein (P2), psoralen (P5), neobavaisoflavone (P13), and psoralidin (P20), which were consistent with the results of spectrum-effect relationships.

Simultaneous determination of myricetrin, quercitrin and afzelin in leaves of Cercis chinensis by a fast and effective method of ionic liquid microextraction coupled with HPLC.

In this study, the contents of myricetrin, quercitrin and afzelin in Cercis chinensis leaves were determined simultaneously by 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM] BF4/70% ethanol microextraction combined with High Performance Liquid Chromatograph (HPLC) analysis. The mobile phase was eluted with an Agilent ZORBAX SB-C18 column (4.6 mm×5 mm, 5 µm), B was methanol and C was 0.1% glacial acetic acid-water as the mobile phase. The flow rate was 0.8 mL min-1, eluents was detected at 245 nm at column temperature of 30 °C. The orthogonal experiment and variance analysis were used to determine the optimum process of C. chinensis leaves by the comprehensive evaluation of the contents of myricetrin, quercitrin and afzelin. The results showed that the injection rates of myricetrin, quercitrin and afzelin were in the range of 0.4997-18.73 µg (r = 0.9997), 0.1392-5.218 µg (r = 0.9998) and 0.04582-1.718 µg (r = 0.9998), respectively. The optimum conditions were determined as follows: the concentration of extraction, 0.9 mol/L; the ultrasonic time, 50 min; the solid-liquid ratio, 1:30; the centrifugal speed, 5000 r/min, and the crushing ratio, 90 mesh. Under these optimal conditions, the average levels of myricetrin, quercitrin and afzelin were 8.6915, 1.5865 and 1.0920 (mg/g), respectively.

Spectrum Effect Relationship and Component Knock-Out in Angelica Dahurica Radix by High Performance Liquid Chromatography-Q Exactive Hybrid Quadrupole-Orbitrap Mass Spectrometer.

Different extracts of Angelica dahuricae were available for whitening or treating vitiligo clinically. They showed inhibitory or activating effects on tyrosinase, a rate-limiting enzyme of melanogenesis. This study aimed to identify active compounds on tyrosinase in water extract of Angelica dahurica Radix. We applied spectrum-effect relationship and component knock-out methods to make it clear. HPLC was used to obtain the specific chromatograms. The effects on tyrosinase activity were examined by measuring the oxidation rate of levodopa in vitro. Partial least squares method was used to examine the spectrum-effect relationships. The knocked-out samples were prepared by HPLC method, and the identification of knocked-out compounds was conducted by the high performance liquid chromatography-four stage rod-electrostatic field orbit trap high resolution mass spectrometry. Results showed that S6, S14, S18, S21, S35, S36, S37, S40, and S41 were positively correlated to inhibitory activity of Angelica dahuricae on tyrosinase whereas S9, S11, S8, S12, S22, and S30 were negatively correlated. When the concentration of each sample was 1 g·mL-1, equal to the amount of raw medicinal herbs, oxypeucedanin hydrate, imperatorin, cnidilin, and isoimperatorin had inhibitory effects on tyrosinase activity whereas byakangelicin and bergapten had activating effects.