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Lipid-lowering is one of the most effective methods of prevention and treatment for cardiovascular diseases. However, most clinical lipid-lowering drugs have adverse effects and cannot achieve the desired efficacy in some complex hyperlipidemia patients, so it is of great significance to develop safe and effective novel lipid-lowering drugs. In the course of our project aimed at discovering the chemical novelty and bioactive natural products of marine-derived actinomycetes, we found that the organic crude extracts (OCEs) of Nocardiopsis sp. ZHD001 exhibited strong in vivo efficacies in reducing weight gain, lowering LDL-C, TC, and TG levels, and improving HDL-C levels in high-fat-diet-fed mice models. Chemical investigations of the active OCEs led to identifying two new sphydrofuran-derived compounds (1–2) and one known 2-methyl-4-(1-glycerol)-furan (3). Their structures were elucidated by the analysis of HRESIMS, 1D and 2D NMR spectroscopic data, and ECD calculations. Among these compounds, compound 1 represents a novel rearranged sphydrofuran-derived derivative. Bioactivity evaluations of these pure compounds showed that all the compounds exhibited significant lipid-lowering activity with lower cytotoxicity in vitro compared to simvastatin. Our results demonstrate that sphydrofuran-derived derivatives might be promising candidates for lipid-lowering drugs. [ABSTRACT FROM AUTHOR]

In this paper, we present a new microfluidic microwave sensor loaded with a star-slotted patch for detecting the quality of edible oil. The relative dielectric permittivity and the quality of edible oil will change after being heated at a high temperature. Therefore, the quality of edible oil can be detected by measuring the relative dielectric permittivity of edible oil. The sensor is used to determine the edible oil with different dielectric permittivity by measuring the resonance frequency offset of the input reflection coefficient, which operates at 2.68 GHz. This sensor is designed based on a resonant approach to provide the best sensing accuracy and is implemented using a substrate integrated waveguide structure combined with a pentagonal slot antenna operating at 2.3~2.9 GHz. It can detect greasy liquids with the real part of the complex permittivity ranging from two to three. [ABSTRACT FROM AUTHOR]

Debris flow is one of the most frequently occurring geological disasters in Jilin province, China, and such disasters often result in the loss of human life and property. The objective of this study is to propose and verify an information fusion (IF) method in order to improve the factors controlling debris flow as well as the accuracy of the debris flow susceptibility map. Nine layers of factors controlling debris flow (i.e., topography, elevation, annual precipitation, distance to water system, slope angle, slope aspect, population density, lithology and vegetation coverage) were taken as the predictors. The controlling factors were improved by using the IF method. Based on the original controlling factors and the improved controlling factors, debris flow susceptibility maps were developed while using the statistical index (SI) model, the analytic hierarchy process (AHP) model, the random forest (RF) model, and their four integrated models. The results were compared using receiver operating characteristic (ROC) curve, and the spatial consistency of the debris flow susceptibility maps was analyzed while using Spearman's rank correlation coefficients. The results show that the IF method that was used to improve the controlling factors can effectively enhance the performance of the debris flow susceptibility maps, with the IF-SI-RF model exhibiting the best performance in terms of debris flow susceptibility mapping. [ABSTRACT FROM AUTHOR]

Landslides are one of the most frequent geomorphic hazards, and they often result in the loss of property and human life in the Changbai Mountain area (CMA), Northeast China. The objective of this study was to produce and compare landslide susceptibility maps for the CMA using an information content model (ICM) with three knowledge-driven methods (the artificial hierarchy process with the ICM (AHP-ICM), the entropy weight method with the ICM (EWM-ICM), and the rough set with the ICM (RS-ICM)) and to explore the influence of different knowledge-driven methods for a series of parameters on the accuracy of landslide susceptibility mapping (LSM). In this research, the landslide inventory data (145 landslides) were randomly divided into a training dataset: 70% (81 landslides) were used for training the models and 30% (35 landslides) were used for validation. In addition, 13 layers of landslide conditioning factors, namely, altitude, slope gradient, slope aspect, lithology, distance to faults, distance to roads, distance to rivers, annual precipitation, land type, normalized difference vegetation index (NDVI), topographic wetness index (TWI), plan curvature, and profile curvature, were taken as independent, causal predictors. Landslide susceptibility maps were developed using the ICM, RS-ICM, AHP-ICM, and EWM-ICM, in which weights were assigned to every conditioning factor. The resultant susceptibility was validated using the area under the ROC curve (AUC) method. The success accuracies of the landslide susceptibility maps produced by the ICM, RS-ICM, AHP-ICM, and EWM-ICM methods were 0.931, 0.939, 0.912, and 0.883, respectively, with prediction accuracy rates of 0.926, 0.927, 0.917, and 0.878 for the ICM, RS-ICM, AHP-ICM, and EWM-ICM, respectively. Hence, it can be concluded that the four models used in this study gave close results, with the RS-ICM exhibiting the best performance in landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]

As debris flow is one of the most destructive natural disasters in many parts of the world, the assessment and management of future debris flows with proper forecasting methods are crucial for the safety of life and property. So increasing attention has been paid to the forecasting methods on debris flows. A debris flow forecasting method based on the rainfall-unstable soil coupling mechanism (R-USCM) is presented in the current study. This method is based on the debris flow formation mechanism. The density of sediment is introduced as an evaluation index to determine the susceptibility of debris flow occurrence. The forecasting method includes two phases: (1) rainfall and soil coupling and (2) runoff and unstable soil coupling. Scoops3D, a three-dimensional (3D) model for analyzing slope stability, was introduced into the debris flow forecasting method. In order to test the forecasting accuracy of this method, Jiaohe County was selected as a research area, and the serious debris flow disasters attributed to strong rainfall on 20 July 2017 were taken as the research case. By comparing the forecasting results with the debris flow distribution map for Jiaohe County, the method based on the R-USCM is feasible for forecasting debris flows at the regional scale. The application of the Scoops3D model can more reasonably analyze the slope stability than the traditional two dimensional (2D) method and improve the forecasting ability of debris flows. [ABSTRACT FROM AUTHOR]

Underground construction projects such as tunnel construction are at high risk of water-induced disasters. Because this type of disaster poses a serious threat to worker safety and productivity, instruments and methods that can accurately detect the water source are critical. In this study, a water detection instrument that combines Magnetic Resonance Sounding (MRS) and Time-domain Electromagnetic Method (TEM) techniques to yield a joint MRS-TEM interpretation method was developed for narrow underground spaces such as tunnels. Joint modules including a transmitter and receiver were developed based on a dual-purpose and modular design concept to minimize the size and weight of the instrument and consequently facilitate transportation and measurement. Additionally, wireless control and communication technology was implemented to enable inter-module cooperation and simplify instrument wiring, and wireless synchronization was accomplished by implementing a Global Positioning System (GPS)-based timing scheme. The effectiveness and reliability of the instrument were verified via indoor laboratory tests and field measurement signal tests. Furthermore, the practicability of the combined instrument and its interpretation method was verified via a field case performed in a tunnel in Hubei, China. [ABSTRACT FROM AUTHOR]

Due to its unique sensitivity to hydrogen protons, magnetic resonance sounding (MRS) is the only geophysical method that directly detects water and can provide nondestructive information on subsurface aquifer properties. The relationship between the surface MRS signal and the location and characteristics of aquifers using large-coil (typically 50-150 m) sensors has been discussed based on forward modelling and experiments. However, few researchers have studied underground MRS using a small-coil sensor. In this paper, a parametric study and a large-scale physical model test were conducted to shed light on the critical response characteristics of underground MRS using a small-coil sensor. The effects of the size and number of turns of the transmitter coil and receiver coil, the geomagnetic declination, the geomagnetic inclination, and the position, thickness, and water content of a water-bearing structure on the performance of the underground MRS were studied based on numerical simulations. Furthermore, we derived the kernel function and underground MRS signal curves for a water-bearing structure model based on the simulations. Finally, a large-scale physical model test on underground MRS using a small-coil sensor was performed using a physical test system for geological prediction of tunnels at Shandong University. The results show that the inversion results of the physical model test were in good agreement with the physical prototype results. Using both numerical modeling and physical model tests, this study showed that underground MRS using a small-coil sensor can be used to predict water-bearing structures in underground engineering., Competing Interests: The authors declare no conflict of interest.

Two prenylated indole alkaloids were isolated from the ethyl acetate extracts of a marine-derived fungus Penicillium sp. NH-SL and one of them exhibited potent cytotoxic activity against mouse hepa 1c1c7 cells. In order to detect other bioactive analogs, we used liquid chromatogram tandem mass spectrometry (LC-MS/MS) to analyze the mass spectrometric characteristics of the isolated compounds as well as the crude extracts. As a result, three other analogs were detected, and their structures were deduced according to the similar fragmentation patterns. This is the first systematic report on the mass spectrometric characteristics of prenylated indole derivatives.

Bromodomains (BRD) are readers of the epigenetic code that regulate gene transcription through their recognition of acetyl-lysine modified histone tails. Recently, bromodomain-containing proteins such as BRD4 have been demonstrated to be druggable through the discovery of potent inhibitors. These protein-protein interaction inhibitors have the potential to modulate multiple diseases by their profound anti-inflammatory and antiproliferative effects. In order to explore new BRD4 inhibitors as well as lead compounds for the development of new drugs, the secondary metabolites of Alternaria sp. NH-F6, a fungus isolated from deep-sea sediment samples, were analyzed systematically. Five new compounds including two new perylenequinones ( 1 - 2 ), one new alternaric acid ( 3 ), 2-( N -vinylacetamide)-4-hydroxymethyl-3-ene-butyrolactone ( 4 ), one new cerebroside ( 5 ), together with 19 known compounds ( 6 - 24 ) were isolated from the ethyl acetate extracts of this strain. Their structures were elucidated using nuclear magnetic resonance (NMR) and high resolution electrospray ionization mass spectrometry (HR-ESI-MS) analyses. Finally, all these compounds were evaluated for their inhibitory activity against BRD4 protein, and compound 2 exhibited a potent inhibition rate of 88.1% at a concentration of 10 µM. This research provides a new BRD4 inhibitor which may possess potential antitumoral, antiviral, or anti-inflammatory pharmaceutical values.

Aromatase represents an important target for the treatment of hormone-dependent breast cancer. In the present study, nine alkaloids from the dichloromethane extract of Corydalis yanhusuo were identified by liquid chromatography tandem mass spectrometry (LC-MS/MS) and tested for their aromatase binding activities using an ultrafiltration LC-MS method by investigating the differences of peak areas of compounds before and after incubations with aromatase. It was demonstrated that the quaternary protoberberine alkaloids and the tertiary protoberberine alkaloids exhibited potent aromatase binding activities. The quaternary ammonium group and the methyl group at C-13 position of tertiary protoberberine alkaloids might be necessary for the activity. The findings should provide guidance for the discovery of potential aromatase inhibitors from natural products.