HNCDB: An Integrated Gene and Drug Database for Head and Neck Cancer

Head and neck cancer (HNC) is the sixth most common cancer worldwide. Over the last decade, an enormous amount of well-annotated gene and drug data has accumulated for HNC. However, a comprehensive repository is not yet available. Here, we constructed the Head and Neck Cancer Database (HNCDB: http://hncdb.cancerbio.info) using text mining followed by manual curation of the literature to collect reliable information on the HNC-related genes and drugs. The high-throughput gene expression data for HNC were also integrated into HNCDB. HNCDB includes the following three separate but closely related components: “HNC GENE,” “Connectivity Map,” and “ANALYSIS.” The “HNC GENE” component contains comprehensive information for the 1,173 HNC-related genes manually curated from 2,564 publications. The “Connectivity Map” includes information on the potential connections between the 176 drugs manually curated from 2,032 publications and the 1,173 HNC-related genes. The “ANALYSIS” component allows users to conduct correlation, differential expression, and survival analyses in the 2,403 samples from 78 HNC gene expression datasets. Taken together, we believe that HNCDB will be of significant benefit for the HNC community and promote further advances for precision medicine research on HNC

The Voltage Stabilizing Control Strategy of Off-Grid Microgrid Cluster Bus Based on Adaptive Genetic Fuzzy Double Closed-Loop Control

In the off-grid microgrid cluster, the energy storage device is mainly charged and discharged to maintain the stability of the bus voltage and the system power balance. Generally, the voltage and current double closed-loop control and fuzzy control are adopted for the energy storage converter. The traditional double closed-loop control parameters and the scale factor and quantization factor in fuzzy control cannot be adjusted in real time during system operation, resulting in slower dynamic response and weak anti-interference ability of the system. In response to the above problems, this paper proposes an adaptive genetic fuzzy double closed-loop control, which can adjust the PI control parameters in real time by adjusting the quantization factor and the scale factor to optimize the control effect. The simulation platform is built in MATLAB/Simulink and the simulation results show that the adaptive genetic fuzzy double closed-loop control combines the advantages of fuzzy and PI control. Under different working conditions, the system has not only a fast dynamic response, small overshoot, and strong anti-interference ability but also good robustness

Research on Economic Optimization of Microgrid Cluster Based on Chaos Sparrow Search Algorithm

With the deepening of the power market reform on the retail side, it is of great significance to study the economic optimization of the microgrid cluster system. Aiming at the economics of the microgrid cluster, comprehensively considering the degradation cost of energy storage battery, the compensation cost of demand-side controllable loads dispatch, the electricity transaction cost between the microgrids, and the electricity transaction cost between the microgrid and the power distribution network of the microgrid cluster, we establish an optimal dispatch model for the microgrid cluster including wind turbines, photovoltaics, and energy storage batteries. At the same time, in view of the problem that the population diversity of the basic sparrow search algorithm decreases and it is easy to fall into local extremes in the later iterations of the basic sparrow search algorithm, a chaos sparrow search algorithm based on Bernoulli chaotic mapping, dynamic adaptive weighting, Cauchy mutation, and reverse learning is proposed, and different types of test functions are used to analyze the convergence effect of the algorithm, and the calculation effects of the sparrow algorithm, the particle swarm algorithm, the chaotic particle swarm, and the genetic algorithm are compared. The algorithm has higher convergence speed, higher accuracy, and better global optimization ability. Finally, through the calculation example, it is concluded that the benefit of the microgrid cluster is increased by nearly 20%, which verifies the effectiveness of the improvement

Synthesis and Biological Activity of trans-Tiliroside Derivatives as Potent Anti-Diabetic Agents

A set of novel trans-tiliroside derivatives were synthesized. The structures of the derivatives were identified by their IR, 1H-NMR, and MS spectra analysis. Their anti-diabetic activities were evaluated on the insulin resistant (IR) HepG2 cell model. As a result, compounds 7a, 7c, 7h, and trans-tiliroside exhibited significant glucose consumption-enhancing effects in IR-HepG2 cells compared with the positive control (metformin). This research provides useful clues for further design and discovery of anti-diabetic agents

Synthesis and Biological Activity of trans-Tiliroside Derivatives as Potent Anti-Diabetic Agents

A set of novel trans-tiliroside derivatives were synthesized. The structures of the derivatives were identified by their IR, 1H-NMR, and MS spectra analysis. Their anti-diabetic activities were evaluated on the insulin resistant (IR) HepG2 cell model. As a result, compounds 7a, 7c, 7h, and trans-tiliroside exhibited significant glucose consumption-enhancing effects in IR-HepG2 cells compared with the positive control (metformin). This research provides useful clues for further design and discovery of anti-diabetic agents