Matrine Reverses the Warburg Effect and Suppresses Colon Cancer Cell Growth via Negatively Regulating HIF-1α.

The Warburg effect is a peculiar feature of cancer’s metabolism, which is an attractive therapeutic target that could aim tumor cells while sparing normal tissue. Matrine is an alkaloid extracted from the herb root of a traditional Chinese medicine, Sophora flavescens Ait. Matrine has been reported to have selective cytotoxicity toward cancer cells but with elusive mechanisms. Here, we reported that matrine was able to reverse the Warburg effect (inhibiting glucose uptake and lactate production) and suppress the growth of human colon cancer cells in vitro and in vivo . Mechanistically, we revealed that matrine significantly decreased the messenger RNA (mRNA) and protein expression of HIF-1α, a critical transcription factor in reprogramming cancer metabolism toward the Warburg effect. As a result, the expression levels of GLUT1, HK2, and LDHA, the downstream targets of HIF-1α in regulating glucose metabolism, were dramatically inhibited by matrine. Moreover, this inhibitory effect of matrine was significantly attenuated when HIF-1α was knocked down or exogenous overexpressed in colon cancer cells. Together, our results revealed that matrine inhibits colon cancer cell growth via suppression of HIF-1α expression and its downstream regulation of Warburg effect. Matrine could be further developed as an antitumor agent targeting the HIF-1α-mediated Warburg effect for colon cancer treatment

Advanced Tracers in PET Imaging of Cardiovascular Disease

Cardiovascular disease is the leading cause of death worldwide. Molecular imaging with targeted tracers by positron emission tomography (PET) allows for the noninvasive detection and characterization of biological changes at the molecular level, leading to earlier disease detection, objective monitoring of therapies, and better prognostication of cardiovascular diseases progression. Here we review, the current role of PET in cardiovascular disease, with emphasize on tracers developed for PET imaging of cardiovascular diseases

The Impact of Rainfall Movement Direction on Urban Runoff Cannot Be Ignored in Urban Hydrologic Management

Urban floods have been exacerbated globally, associated with increasing spatial-temporal variations in rainfall. However, compared with rainfall variabilities of intensity and duration, the effect of rainfall movement direction is always ignored. Based on 1313 rainfall scenarios with different combinations of rainfall intensity and rainfall movement direction in the typically rainy city of Shenzhen in China, we find that the effect of rainfall movement direction on the peak runoff may reach up to 20%, which will decrease to less than 5% under heavy rainfall intensity conditions. In addition, our results show that the impact of rainfall movement direction is almost symmetrical and is associated with the direction of the river. The closer rainfall movement direction is to the Linear Directional Mean of rivers, the larger is the peak runoff of section. Our results reveal that rainfall movement direction is significant to urban peak runoff in the downstream reaches, which should be considered in urban hydrological analysis

Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables

Modern coupled power and water (CPW) systems exhibit increasing integration and interdependence, which challenges system performance to disasters and makes service restoration complex during post-disruption. Meanwhile, new technologies, such as small pumped-hydro storage (PHS) and rooftop renewables, are being widely installed and further deepen the interdependencies. To capture these features and improve overall performance, this paper proposes a coordinated restoration framework for a CPW system to respond to disruptions. The proposed CPW model comprises physical networks and mechanisms, considering available units, such as water desalination/treatment plants, pump stations and small PHS, in the water system, and rooftop renewables, distributed generators, in power system. The interdependencies are modeled through component-wise connections and consumer behavior, then grouped into three phases: production, distribution, and consumption. Aggregate service loss with respect to different consumer loads and time periods, is chosen as performance metric and to be minimized using network reconfiguration, energy/water dispatching, load curtailment, and operation management of components. A two-stage risk-averse stochastic programming is applied for reliable restoration and manage risks, to tackle the uncertainties in renewable power generations and water/power demands that affect method effectiveness. Finally, the method is implemented on a modified 33-bus/25-node CPW system, and the results demonstrate the effectiveness of the proposed restoration framework.National Research Foundation (NRF)This research is supported by the National Research Foundation Singapore (NRF) under its Campus for Research Excellence and Technological Enterprise (CREATE) programme

An enhanced equivalent circuit model of vanadium redox flow battery energy storage systems considering thermal effects

Thermal issue is one of the major concerns for safe, reliable, and efficient operation of the vanadium redox flow battery (VRB) energy storage systems. During the design of the operational strategy for a grid-connected VRB system, a suitable mathematical model is needed to predict the dynamic behaviors under various operating conditions. However, conventional VRB models usually neglect the impact of temperature variations on system performance. This work develops an enhanced VRB model with the consideration of the coupling effects between the electrochemical and the thermal behaviors. The proposed model consists of two equivalent circuits. First, the electrochemical behaviors of the VRB are modeled by a second-order RC network taking account of the effects of concentration variation of the vanadium ions and the electrochemical activation. Second, a third-order Cauer network is used to model the heat transfer process in the VRB system, and the dynamic thermal behaviors of stacks, pipes and heat exchangers are characterized. Well-designed experiments and particle swarm optimization algorithm are use to identify the parametric values of the developed model. The proposed modeling method was validated experimentally using a 5kW/3kWh VRB platform, and the results show that the model is capable of accurately predicting the VRB performance under variable temperature conditions. The developed coupled electro-thermal model is then used for simulating and analyzing the performance of a VRB system operated in conjunction with a wind power plant under real-world conditions

Spatial and Temporal Pattern of Rainstorms Based on Manifold Learning Algorithm

Identifying the patterns of rainstorms is essential for improving the precision and accuracy of flood forecasts and constructing flood disaster prevention systems. In this study, we used a manifold learning algorithm method of machine learning to analyze rainstorm patterns. We analyzed the spatial–temporal characteristics of heavy rain in Beijing and Shenzhen. The results showed a strong correlation between the spatial–temporal pattern of rainstorms and underlying topography in Beijing. However, in Shenzhen, the spatial–temporal distribution characteristics of rainstorms were more closely related to the source of water vapor causing the rainfall, and the variation in characteristics was more complex and diverse. This method may be used to quantitatively describe the development and dynamic spatial–temporal patterns of rainfall. In this study, we found that spatial–temporal rainfall distribution characteristics, extracted by machine learning technology could be explained by physical mechanisms consistent with the climatic characteristics and topographic conditions of the region

Synthesis and Evaluation of 18F-labeled Pyridaben Analogues for Myocardial Perfusion Imaging in Mice, Rats and Chinese mini-swine

Photograph of Sunflowers