Cytokines in the Progression of Pancreatic β-Cell Dysfunction

The dysfunction of pancreatic β-cell and the reduction in β-cell mass are the decisive events in the progression of type 2 diabetes. There is increasing evidence that cytokines play important roles in the procedure of β-cell failure. Cytokines, such as IL-1β, IFN-γ, TNF-α, leptin, resistin, adiponectin, and visfatin, have been shown to diversely regulate pancreatic β-cell function. Recently, islet-derived cytokine PANcreatic DERived factor (PANDER or FAM3B) has also been demonstrated to be a regulator of islet β-cell function. The change in cytokine profile in islet and plasma is associated with pancreatic β-cell dysfunction and apoptosis. In this paper, we summarize and discuss the recent studies on the effects of certain important cytokines on pancreatic β-cell function. The imbalance in deleterious and protective cytokines plays pivotal roles in the development and progression of pancreatic β-cell dysfunction under insulin-resistant conditions

3-Eth­oxy-2-(1,3-thia­zol-2-yl)isoindolin-1-one

In the title compound, C13H12N2O2S, the dihedral angles between the isoindolone ring system and the thia­zole ring and the eth­oxy group are 6.50 (11) and 89.0 (2)°, respectively

The First Case of a Class I Glucose-6-phosphate Dehydrogenase Deficiency, G6PD Santiago de Cuba (1339 GA), in a Chinese Population as Found in a Survey for G6PD Deficiency in Northeastern and Central China

In Liaoning Province in northeastern China, we found a G6PD-deficient patient at the age of 3. By the classification of the World Health Organization, this patient was categorized as class I (very severe G6PD deficiency). When we investigated the G6PD gene of the patient, we found that he had a replacement of G to A at nucleotide 1339. As a result, the amino acid at position 447 should change from Gly to Arg. This replacement is known as G6PD Santiago de Cuba, because it was first discovered in a Cuban boy who showed heavy chronic anemia. Today, 28 G6PD variants have been reported in the Chinese population, and all are categorized as class II (severe deficiency) or class III (mild deficiency);in class II or III deficiency, anemia is not present in daily life, but hemolytic attack can occur when the carrier ingests certain oxidative medicines or foods. This is the first report of a G6PD-deficient Chinese patient in the category of class I. We intended to find other G6PD-deficient cases in northeastern China and tested several hundred blood samples, but no cases of G6PD deficiency were found (0/414). In central China, where falciparum malaria was endemic from the 1950s to 1970s, we found two G6PD-deficient cases (2/27) and the other members from their families whose variant type was G6PD Kaiping (1388GT), which is a common variant in the Chinese population.</p

Comparative effectiveness and safety of xiyanping with ribavirin for rotavirus enteritis therapy in childhood: A systematic review and meta-analysis

Purpose: To employ meta-analysis to assess the effectiveness and adverse events of Xiyanping and ribavirin in children with rotavirus enteritis.Methods: Searches included PubMed, Embase, Medline, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biology Medicine Database (CBM), China Science and Technology Journal Database (VIP database), and Wanfang database from inception to March 2017. Clinical indicators, with respect to the total effectiveness rate, fever time, duration of diarrhea, creatinine kinase MB isoenzyme (CK-MB), rotavirus (RV) negative conversion rate, and adverse reaction, were compared between Xiyanping and ribavirin groups.Results: Five-hundred and twenty-six records were obtained after searching the databases, and 18 studies (3557 participants) that met the inclusion criteria were included. All of them assessed total effectiveness rate, and two records evaluated RV negative conversion rate. There were significantly higher rates in the Xiyanping group than in the ribavirin group {OR = 3.76, 95 %CI (3.03 - 4.66), p &lt; 0.00001; OR = 2.68, 95 %CI (1.56 - 4.60), p = 0.0004}. Compared with ribavirin group, fever time, duration of diarrhea, and creatine kinase isoenzyme MB (CK-MB) were significantly lower in xiyanping group [MD = -1.23, 95 %CI (-1.64 to -0.81), p &lt; 0.00001; MD= -2.15, 95 %CI (-2.68 to -1.62), p &lt; 0.00001; MD = -16.90, 95 %CI (-17.23 to -16.57), p &lt; 0.00001}. Six studies reported adverse reactions, but there was no significant difference between xiyanping and ribavirin groups {OR = 1.44, 95 %CI (0.40 - 5.17), p = 0.58}.Conclusion: This review suggests that xiyanping is more effective than ribavirin in children suffering from rotavirus enteritis.Keywords: Ribavirin, Rotavirus enteritis, Systematic review, Virazole®, Xiyanpin

Design and Comprehensive Analysis of a Noise-Tolerant ZNN Model With Limited-Time Convergence for Time-Dependent Nonlinear Minimization

Zeroing neural network (ZNN) is a powerful tool to address the mathematical and optimization problems broadly arisen in the science and engineering areas. The convergence and robustness are always co-pursued in ZNN. However, there exists no related work on the ZNN for time-dependent nonlinear minimization that achieves simultaneously limited-time convergence and inherently noise suppression. In this article, for the purpose of satisfying such two requirements, a limited-time robust neural network (LTRNN) is devised and presented to solve time-dependent nonlinear minimization under various external disturbances. Different from the previous ZNN model for this problem either with limited-time convergence or with noise suppression, the proposed LTRNN model simultaneously possesses such two characteristics. Besides, rigorous theoretical analyses are given to prove the superior performance of the LTRNN model when adopted to solve time-dependent nonlinear minimization under external disturbances. Comparative results also substantiate the effectiveness and advantages of LTRNN via solving a time-dependent nonlinear minimization problem

Quality Prediction and Control of Reducing Pipe Based on EOS-ELM-RPLS Mathematics Modeling Method

The inspection of inhomogeneous transverse and longitudinal wall thicknesses, which determines the quality of reducing pipe during the production of seamless steel reducing pipe, is lags and difficult to establish its mechanism model. Aiming at the problems, we proposed the quality prediction model of reducing pipe based on EOS-ELM-RPLS algorithm, which taking into account the production characteristics of its time-varying, nonlinearity, rapid intermission, and data echelon distribution. Key contents such as analysis of data time interval, solving of mean value, establishment of regression model, and model online prediction were introduced and the established prediction model was used in the quality prediction and iteration control of reducing pipe. It is shown through experiment and simulation that the prediction and iteration control method based on EOS-ELM-RPLS model can effectively improve the quality of steel reducing pipe, and, moreover, its maintenance cost was low and it has good characteristics of real time, reliability, and high accuracy

Output Strictly Passive Control of Uncertain Singular Neutral Systems

This paper concerns the problem of output strictly passive control for uncertain singular neutral systems. It introduces a new effective criterion to study the passivity of singular neutral systems. Compared with the previous approach, this criterion has no equality constraints. And the state feedback controller is designed so that the uncertain singular neutral systems are output strictly passive. In terms of a linear matrix inequality (LMI) and Lyapunov function, the strictly passive criterion is formulated. And the desired passive controller is given. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach

DocStormer: Revitalizing Multi-Degraded Colored Document Images to Pristine PDF

For capturing colored document images, e.g. posters and magazines, it is common that multiple degradations such as shadows, wrinkles, etc., are simultaneously introduced due to external factors. Restoring multi-degraded colored document images is a great challenge, yet overlooked, as most existing algorithms focus on enhancing color-ignored document images via binarization. Thus, we propose DocStormer, a novel algorithm designed to restore multi-degraded colored documents to their potential pristine PDF. The contributions are: firstly, we propose a "Perceive-then-Restore" paradigm with a reinforced transformer block, which more effectively encodes and utilizes the distribution of degradations. Secondly, we are the first to utilize GAN and pristine PDF magazine images to narrow the distribution gap between the enhanced results and PDF images, in pursuit of less degradation and better visual quality. Thirdly, we propose a non-parametric strategy, PFILI, which enables a smaller training scale and larger testing resolutions with acceptable detail trade-off, while saving memory and inference time. Fourthly, we are the first to propose a novel Multi-Degraded Colored Document image Enhancing dataset, named MD-CDE, for both training and evaluation. Experimental results show that the DocStormer exhibits superior performance, capable of revitalizing multi-degraded colored documents into their potential pristine digital versions, which fills the current academic gap from the perspective of method, data, and task

Machine Learning for Multi-Action Classification of Lower Limbs for BCI

Over the past two decades, significant progress has been made in brain-computer interfaces (BCIs), devices which enable direct communications between human brains and external devices. One of the prevalent control paradigms is motor imagery-based BCI (MI-BCI), by which users imagine specific actions to express their intentions. Left-hand and right-hand motor imageries are frequently used in the MI-BCI. If a third class is needed, the imagination of both feet is usually added. However, it is relatively rare to separate feet into left lower limb and right limb in MI-BCI systems. In addition, previous studies have demonstrated that real movements can be distinguished from one another via processing the electroencephalogram (EEG). Similarly, motor imagery (MI) and movement observations (MO) can also be distinguished from one another. However, classification of left lower limb actions and right lower limb actions between MI, Real Movement (RM), and MO actions, has not been thoroughly explored. To address these questions, we performed a comprehensive experiment to collect EEG under six actions (i.e., Left-MI, Right-MI, Left-RM, Right-RM, Left-MO, and Right-MO) and used three models (convolutional neural network [CNN], support vector machine [SVM], and a K-Nearest Neighbours [KNN]) to classify these actions. Our CNN achieved the highest performance (37.77%) in the classification of six actions. Although the performance of SVM (37.21%) and KNN (25.26%) was worse, it is still better than the chance level (16.67%). Our results suggest that it is possible to distinguish between these six lower limb actions. This study has implications for developing multi-class BCI systems and promoting the research of multiple-action classification