A magnetic solid phase extraction microfluidic chip coupled with gas chromatography-mass spectrometry for the determination of polycyclic aromatic hydrocarbons in aqueous samples.

In this paper, we designed and manufactured a reliable magnetic solid phase extraction (MSPE) microfluidic chip for determination of polycyclic aromatic hydrocarbons (PAHs) in water combined with gas chromatography-mass spectrometry. Sample loading, washing and elution are implemented with microinjection pump and integrated on a single chip, which reduced manual operation. Magnets were used to fix octadecyl/phenyl bifunctional Fe3O4@SiO2 extractant to avoid the design of weir structure in extraction chamber. The whole microfluidic chip was simple and low cost. Based on the microfluidic chip extraction platform, the on-chip MSPE method for the determination of PAHs was optimized and established. The results showed that this method required only 2 mL of sample, 2 mg of extractant, and 50 µL of elution organic solvent for whole on-chip MSPE process, which was environmentally friendly and consistent with green chemistry. Method verification results were displayed which the linear range of five PAHs was between 1-100 ng/mL with good linearity (R2≥ 0.9985), and the detection limits (S/N = 3) were 0.08-0.26 ng/mL. The RSDs of intra-day precision (n=6) and inter-day precision (n=9) for PAHs were less than 6.1 % and 7.2 %, respectively. Enrichment factors were determined to be 31.3-37.7. The recoveries of river water, tap water, bottle water, waste water and urine at three spiked levels were in the range of 89.9% to 113.7% and the matrix effect values were between 83.8% to 109.6%. The extraction platform has the advantages of accurate analysis, simple design and cost-effective, which is conducive to the widespread use of microfluidic chips.

Robust H∞ Pinning Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks.

This article focuses on the robust H∞ synchronization of two types of coupled reaction-diffusion neural networks with multiple state and spatial diffusion couplings by utilizing pinning adaptive control strategies. First, based on the Lyapunov functional combined with inequality techniques, several sufficient conditions are formulated to ensure H∞ synchronization for these two networks with parameter uncertainties. Moreover, node-based pinning adaptive control strategies are devised to address the robust H∞ synchronization problem. In addition, some criteria of H∞ synchronization for these two networks under parameter uncertainties are developed via edge-based pinning adaptive controllers. Finally, two numerical examples are presented to verify our results.

Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.

This paper addresses fixed-time output synchronization problems for two types of complex dynamical networks with multi-weights (CDNMWs) by using two types of adaptive control methods. Firstly, complex dynamical networks with multiple state and output couplings are respectively presented. Secondly, several fixed-time output synchronization criteria for these two networks are formulated based on Lyapunov functional and inequality techniques. Thirdly, by employing two types of adaptive control methods, fixed-time output synchronization issues of these two networks are dealt with. At last, the analytical results are verified by two numerical simulations.

Finite-Time Passivity and Synchronization of Multi-Weighted Complex Dynamical Networks Under PD Control.

This article focuses on finite-time passivity (FTP) and finite-time synchronization (FTS) for complex dynamical networks with multiple state/derivative couplings based on the proportional-derivative (PD) control method. Several criteria of FTP for complex dynamical networks with multiple state couplings (CDNMSCs) are formulated by utilizing the PD controller and constructing an appropriate Lyapunov function. Furthermore, FTP is further used to investigate the FTS in CDNMSCs under the PD controller. In addition, the FTP and FTS for complex dynamical networks with multiple derivative couplings (CDNMDCs) are also studied by exploiting the PD control method and some inequality techniques. Finally, two numerical examples are worked out to demonstrate the validity of the presented PD controllers.

Lag H∞ synchronization of coupled neural networks with multiple state couplings and multiple delayed state couplings.

This paper mainly focuses on the lag H∞ synchronization problem of coupled neural networks with multiple state or delayed state couplings. On one hand, by exploiting state feedback controller and Lyapunov functional, a criterion of lag H∞ synchronization for coupled neural networks with multiple state couplings (CNNMSCs) is insured, and lag H∞ synchronization problem in CNNMSCs is also coped with based on the adaptive state feedback controller. On the other hand, we explore the lag H∞ synchronization for coupled neural networks with multiple delayed state couplings (CNNMDSCs) by utilizing similar control strategies. At last, two numerical examples are presented to verify the effectiveness and correctness of lag H∞ synchronization for CNNMSCs and CNNMDSCs.

SOCS3 Genetic Polymorphism Is Associated With Clinical Features and Prognosis of Hepatocellular Carcinoma Patients Receiving Hepatectomy.

Previous studies showed that suppressor of cytokine signaling 3 (SOCS3) protein is associated with incidence and progression of hepatocellular carcinoma (HCC); however, the association between the genetic polymorphism of SOCS3 gene and HCC remains unknown. A total of 254 HCC patients and 354 healthy controls were enrolled. All HCC patients underwent partial hepatectomy as initial treatment and were followed. Three SOCS3 gene polymorphisms, namely, rs4969170 A>G, rs8064821 C>T, and rs12953258 C>A were determined. Our data show that the rs4969170 A>G polymorphism dramatically affects the susceptibility to HCC in our cohorts. Logistic regression analyses revealed that the rs4969170 GG is a risk factor for HCC after the adjustment with confounding factors. The rs4969170A>G polymorphism is also associated with the clinical features of HCC patients and predicts the postoperative relapse-free survival and overall survival. The rs4969170GG genotype carrier had a worse prognosis than the rs4969170AG and rs4969170AA carrier. Our findings suggest that the rs4969170A>G polymorphism of SOCS3 gene may be used as a prognostic predictor for HCC patients who underwent surgical treatment.