Search

The traditional Chinese medicine of fermented medicine may be under the involvement of multiple strains and the interaction between these microorganisms. Liu Shenqu (Massa Medicata Fermentata, MMF) is one of the most widely used fermented medicines, whose potential processing mechanism is still unclear. In this work, UPLC/MS and GNPS methods were employed to rapidly predict chemical compositions in MMF. Moreover, the dynamic changes of strains, chemical compositions and anti-inflammatory activity of MMF during fermentation process were investigated, and subsequently strains-chemical compositions-efficacy interactions were revealed by Pearson correlation analysis and partial least squares regression (PLSR) analysis. As a result, 24 components were identified, and the potential strains including Bacillus, Burkholderia_Caballeronia_Paraburkholderia, Enterobacter, Aspergillus heterocaryoticus, Rhizopus arrhizus, Kazachstania bulderi, which related to the production of anti-inflammatory active ingredients were exposed. These results demonstrated chemical compositions-strains-efficacy interactions during fermentation of MMF, and provide reference for the exploration of the processing mechanism of MMF.

We study the interaction effect of financial intermediaries and family ties on labor participation and employment type in China. Although existing studies examine these effects separately, we investigate the effects of both factors in one model. We give empirical evidence to support earlier arguments that family ties negatively affect labor force participation and positively affect self‐/family‐employment behavior and that financial development positively affects labor force participation. Departing from the extant literature, our results overall indicate a compensating effect of financial intermediaries for family ties in labor participation and employment type. We further argue that there are gender, urban/rural, and age differences in the role of financial intermediaries. The effect of financial intermediaries on the strength of family ties is more relevant for female, rural, and younger people compared to male, urban, and older people.

With the development and progress of carbon dioxide (CO2) capture and storage technology, the study of the flow assurance of CO2 in transmission pipelines needs to be further deepened. In this study, aiming at the gas‐phase transportation mode of CO2, first, a new prediction model of temperature, pressure as well as hydrate formation risk in buried CO2 transmission pipelines is established. Second, the model solving methods of differential discretization and piecewise iteration are introduced in detail. Third, model validation and sensitivity analysis of typical transmission parameters are performed. The results show that: (a) there is good agreement between the model prediction results and software simulation results. (b) The subcooling and the length of the hydrate formation region increase with the increase in the transmission rate. Appropriate increase in the CO2 transmission rate can reduce the risk of hydrate formation in CO2 transmission pipelines. (c) The subcooling and the length of the hydrate formation region decrease as the transmission temperature increases. In order to prevent hydrate risk in the CO2 transmission process, low transmission temperatures should be avoided. (d) The subcooling and the length of the hydrate‐formation area increase first and then decrease as the transmission pressure increases. Appropriate increase in CO2 transmission pressure is conducive to avoiding hydrate formation risk. This study provides basic theoretical guidance for optimizing transmission parameters and risk assessment of hydrate formation in CO2 transmission pipelines. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

The injection of supercritical CO2 coupled with superheated steam (SHS) for heavy oil recovery can improve development efficiency. In order to help oil fields to improve the efficiency of CO2 and SHS utilization we must predict the thermophysical properties at well bottom. Based on the mass, energy, and momentum conservation equations, a non‐isothermal pipe‐flow model is established considering heat exchange between the integral joint tubing (IJT) and annuli. Coupled with the transient thermal conduction model in stratum and the S‐R‐K real gas model, a comprehensive model is established for the mixture flow in concentric dual‐tubing wells (CDTW). The model is solved by a numerical method and an iteration technique. The results show that: (a) the accuracy of the temperature profile calculation has been greatly improved compared with the previous model; (b) the heat‐carrying capacity per unit mass of the mixture and heating efficiency decrease with increasing supercritical CO2 content; (c) when a temperature difference exists between the IJT and annuli, a rapid flow of thermal energy exists inside the CDTW, which causes a significant temperature change near the wellbore, but the influence of temperature change on pressure profiles is negligible. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd.

Glycogen synthase kinase 3 beta (GSK-3β) is considered as a promising drug target for the treatment of Alzheimer's disease (AD). In the present study, two compound libraries were selected for virtual screening based on pharmacophore models of GSK-3β to discover new inhibitors. Nine potential hits were retained for biological investigation and four of these compounds showed GSK-3β inhibitory activity (with the IC50 values in sub-micromolar range on GSK-3β). Compounds 6 and 9 have good safety. They do not have any significant in vitro cytotoxicity against PC12 and SH-SY5Y neuroblastoma cells at concentrations up to 90 μM. Based on the inhibitory activity and druggability properties, compound 8 is the preferred molecule, and it is a promising lead for the development of the GSK-3β inhibitors for reducing the abnormal hyperphosphorylation of tau protein and relieving AD.

Two similar Dracocephalum species, namely, Dracocephalum tanguticum Maxim and Dracocephalum moldavica L, are commonly used as ethnic medicines in China. Here we describe a strategy of combining high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry, as well as fingerprints and chemometrics for characterization and discrimination of chemical constituents on the two herbs. A total of 49 compounds including 33 flavonoids, 5 phenylethanol glycosides, 1 coumarin glycoside, 8 organic acids, and 2 other types of compounds were unambiguously or tentatively identified from the two Dracocephalum species. Among the compounds identified, 26 were characterized for the first time and 4 compounds, rosmarinic acid (7), salvianolic acid B (10), luteoloside (22), diosmetin-7-O-glucoside (28), were inferred as common constituents for the two herbs. Flavonoids featured in these two Dracocephalum species while their types presented significant differences. Acacetin (45) and acacetin glycosides (acatetin-7-O-glucuronide (30), acacetin-7-O-(6"-O-malonyl) glucoside (33), buddleoside (34), tilianin (35), and agastachoside (42)) were detected only in D. moldavica, which can be used to discriminate two herbal medicines. In addition, six characteristic constitutes in D. tanguticum were simultaneously quantified. Moreover, the induced chemometrics methods including similarity analysis and hierarchical clustering analysis were successfully applied for origin discrimination and quality evaluation of D. tanguticum and D. moldavica.

A method of total ion chromatogram combined with chemometrics and mass defect filter was established for the prediction of active ingredients in Picrasma quassioides samples. The total ion chromatogram data of 28 batches were pretreated with wavelet transformation and correlation optimized warping to correct baseline drifts and retention time shifts. Then partial least squares regression was applied to construct a regression model to bridge the total ion chromatogram fingerprints and the antitumor activity of P. quassioides. Finally, the regression coefficients were used to predict the active peaks in total ion chromatogram fingerprints. In this strategy, mass defect filter was employed to classify and characterize the active peaks from a chemical point of view. A total of 17 constituents were predicted as the potential active compounds, 16 of which were identified as alkaloids by this developed approach. The results showed that the established method was not only simple and easy to operate, but also suitable to predict ultraviolet undetectable compounds and provide chemical information for the prediction of active compounds in herbs.

Porous structure Li[Ni1/3Co1/3Mn1/3]O2 has been synthesized via a facile carbonate co-precipitation method using Li2CO3 as template and lithium-source. The physical and electrochemical properties of the materials were examined by many characterizations including TGA, XRD, SEM, EDS, TEM, BET, CV, EIS and galvanostatic charge-discharge cycling. The results indicate that the as-synthesized materials by this novel method own a well-ordered layered structure α-NaFeO2 [space group: R-3m(166)], porous morphology, and an average primary particle size of about 150 nm. The porous material exhibits larger specific surface area and delivers a high initial capacity of 169.9 mAh·g−1 at 0.1 C (1 C=180 mA·g−1) between 2.7 and 4.3 V, and 126.4, 115.7 mAh·g−1 are still respectively reached at high rate of 10 C and 20 C. After 100 charge-discharge cycles at 1 C, the capacity retention is 93.3%, indicating the excellent cycling stability.

Background Australia has the highest incidence of skin cancer in the world, a preventable disease caused primarily by exposure to ultraviolet radiation (UVR) in sunlight. Health promotion strategies play a significant role in sun protection. Objectives To assess the understanding of a population sample as to the time of year that the sun was ‘at its most burning’ in Melbourne, Australia. Methods A cross-sectional study was performed using questionnaires completed at corporate skin checks, conducted on 668 participants during 2011 to 2013. Results Only a minority (n = 82, 12%) gave the correct theoretical answer; the summer solstice or 21–22 December, while another 38% (n = 254) correctly named December and January as the times when the UVR is actually highest. In all, 18% (n = 122) said February was the month when the temperature is hottest and 170 (25%) either mentioned the period May–August when UVR is negligible in Melbourne or had no idea, including saying ‘all year round’. There was no significant difference in this knowledge between different age groups. Conclusion One-quarter of participants did not understand that sunburn was related to high levels of UVR, which occur in summer. Almost one-fifth associated the heat of February with the highest UVR. Understanding these concepts is important for Australians residing in cooler parts of southern Australia, as UVR levels may be high and yet the temperature may be relatively cool. There needs to be more emphasis on UVR in sun awareness campaigns to prompt sun-protective behaviour.

The effect of radioactive UO2 (2+) on the oxygen-transporting capability of hemoglobin-based oxygen carriers has been investigated in vitro. The hemoglobin (Hb) microspheres fabricated by the porous template covalent layer-by-layer (LbL) assembly were utilized as artificial oxygen carriers and blood substitutes. Magnetic nanoparticles of iron oxide (Fe3 O4 ) were loaded in porous CaCO3 particles for magnetically assisted chemical separation (MACS). Through the adsorption spectrum of magnetic Hb microspheres after adsorbing UO2 (2+) , it was found that UO2 (2+) was highly loaded in the magnetic Hb microspheres, and it shows that the presence of UO2 (2+) in vivo destroys the structure and oxygen-transporting capability of Hb microspheres. In view of the high adsorption capacity of UO2 (2+) , the as-assembled magnetic Hb microspheres can be considered as a novel, highly effective adsorbent for removing metal toxins from radiation-contaminated bodies, or from nuclear-power reactor effluent before discharge into the environment.

Meconopsis horridula Hook.f. Thoms has been used as a traditional Tibetan medicine to clear away heat, relieve pain, and mobilize static blood. In this study, a reliable method based on high-performance liquid chromatography with diode array detection and electrospray ionization quadrupole time-of-flight tandem mass spectrometry was established for the identification of components in this herb. A total of 40 compounds (including 17 flavonoids, 15 alkaloids, and eight phenylpropanoids) were identified or tentatively identified. Among them, 17 components were identified in the herb for the first time. Compound 39 appears to be a novel compound, which is confirmed as 3-(kaempferol-8-yl)-2,3-epoxyflavanone by NMR spectroscopy and mass spectrometry. Moreover, seven major constituents were simultaneously quantified by the developed high-performance liquid chromatography with tandem triple-quadrupole mass spectrometry method. The quantitative method was validated and quality parameters were established. The study provides a comprehensive approach for understanding this herbal medicine.

YiGan San (YGS) has long been used in traditional Japanese and Chinese folk medicine and serves as a potent and novel therapeutic agent to treat Alzheimer's disease. In the present study, a rapid and sensitive method based on HPLC coupled with diode-array detection and quadrupole TOF MS (Q-TOF-MS) was designed to reveal the chemical constituents of YGS. Thirty-six compounds were identified and assigned in YGS, including 14 alkaloids, nine γ-lactones, six flavonoids, three triterpenoid saponinares, two small molecular organic acids, and two other types of compounds. In addition, the accurate fragment weight and MS/MS fragmentation reactions of a subtype indole alkaloid in Uncariae ramulus cum uncis were summarized for the first time to realize rapid identification without reference substances. For the first time, 11 major constituents were comprehensively quantified with a HPLC coupled with triple-quadrupole MS method. A three-section switch was used to realize such multicomponent identification. The contents of saikosaponin B2 and isoliquiritin, which produce anti-inflammatory and antidepressant-like effects, were extremely different, up to 700 times, in two sources of YGS. The developed qualitative and quantitative method was proved to be precise, accurate, and reproducible.

Folium Turpiniae has been used as a traditional Chinese medicine for the treatment of abscesses, fevers, gastric ulcers, and inflammations. This paper describes a strategy of combining HPLC with photodiode array detection and quadrupole TOF-MS, as well as phytochemical and chemometrics analysis for the characterization, isolation, and simultaneous quantification of the chemical constituents of Folium Turpiniae. 19 constituents were identified, namely, 11 flavonoids, seven gallic acid derivates, and quinic acid. Among them, 15 compounds were identified in this herbal medicine for the first time; compound 10 appears to be novel and was isolated and confirmed as ellagic acid-3-O-α-L-rhamnopyranoside by NMR spectroscopy and MS. In addition, nine marker compounds, namely gallic acid (2), ellagic acid-3-O-α-L-rhamnopyranoside (10), apigenin-7-O-(2''-rhamnosyl)gentiobioside (11), ellagic acid (12), luteolin-7-O-β-D-neohesperidoside (13), ligustroflavone (14), 4'-O-methylellagic acid-3-O-α-L-rhamnopyranoside (16), rhoifolin (17), and neobudofficide (18), were quantified simultaneously in ten batches of Folium Turpiniae collected from different regions. Moreover, hierarchical clustering analysis and principal component analysis indicated that both samples from Hubei (S1) and Guangxi (S3) provinces showed apparent differences from the others. Samples from Jiangxi province (S2, S4, and S7-10) possessed similar properties and therefore belong to the same group.

Three hiherto unknown phenylpropanoid compounds, namely (7S,8R)-1-(1-ethoxy-2-hydroxypropyl)-2-methoxy-3,4-(methylenedioxy)benzene (1), (7S,8S)-1-(1-ethoxy-2-hydroxypropyl)-2-methoxy-3,4-(methylenedioxy)benzene (2), and (7S,8R)-1-(1-methoxy-2-hydroxypropyl)-2-methoxy-3,4-(methylenedioxy)benzene (3), along with 12 known compounds (4 - 15) were obtained from the extract of whole plant of Chloranthus anhuiensis. Among them, 7 and 13 were obtained from nature for the first time. The structures of these natural compounds were characterized by extensive spectroscopic analysis and calculated electronic circular dichroism (ECD) data. Furthermore, their cytotoxic and neuroprotective activities were evaluated using MDA-MB-231, 4T1, HepG2, and PC12 cell lines. Compounds 8 and 13 exhibited moderate cytotoxic activities against MDA-MB-231 cell line with the IC50 values of 39.7 and 25.8 μm, respectively. And all the isolated compounds have no neuroprotective activities.

Porous Li[Ni1/3Co1/3Mn1/3]O2 is synthesized by a carbonate co-precipitation method from an aqueous mixture of Ni(NO3)2, Co(NO3)2, Mn(OAc)2, Li2CO3 as template and lithium source, NH4HCO3, and NH3·H2O as precipitator and chelating agent (100 °C for 12 h, calcination at 550 °C for 6 h, sintering at 900 °C for 10 h in air).

This paper presents an advanced analytical neuro–space mapping (neuro-SM) technique for accurate and efficient modeling of transistor devices. This is an improvement over the existing neuro-SM, which aims to use neural networks to map a given approximate device model towards an accurate model. The proposed neuro-SM retains the ability of the existing neuro-SM in modifying the voltage relationship between the given approximate device model and the accurate model. The proposed technique can also map the current relationship between the given model and the accurate model. In this way, the proposed neuro-SM can produce improved accuracy over the existing neuro-SM. In addition, analytical formulas of mapping and sensitivities of the direct current, small-signal S parameter, and large-signal harmonic of the proposed neuro-SM model with respect to mapping parameters and coarse-model parameters are also derived. The sensitivity analysis can be used with a gradient-based training technique to improve the model training efficiency. The validity and efficiency of the proposed approach are verified through 2 transistor modeling examples and use of the proposed neuro-SM models in a large-signal behavior analysis of an amplifier.