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Objectives : Studies have demonstrated that CK2 is engaged in CD4+ T cell proliferation and activation. We investigated the potential involvement of CK2 in the pathogenesis of rheumatoid arthritis (RA). Methods Peripheral blood and synovial fluid mononuclear cells (PBMC and SFMC) of RA patients, as well as splenocytes of collagen-induced arthritis (CIA) mice were treated with different doses of CK2 inhibitor CX4945 in vitro. Then, the Th1, Th2, Th17, and Treg cell responses were analyzed. In addition, CIA mice were administrated with CX4945 via oral gavage. Accordingly, the arthritis scores, bone destruction, tissue damage, and the CD4+ T cell subsets were assessed. Results The expression of CK2 was upregulated in CD4+ T cells under RA circumstance. In vitro CX4945 treatment significantly inhibited the Th1 and Th17 cell responses, while promoted the Th2 cell responses in RA patient PBMC, SFMC and CIA mouse splenocytes, dampening IFN-γ and IL-17A production. Moreover, administration of CX4945 ameliorated the severity of arthritis in CIA mice, along with decreased Th1 and Th17 cells. However, CX4945 seemed to have minimal effect on RA Treg cells. Conclusion CK2 serves as an important regulator of the Th1 and Th17 cell axes in RA, thus contributing to the disease aggravation.

The shortage of fossil fuels is actually a major economic issue in the context of increasing energy demand. Renewable energies are thus gaining in importance. For instance, microalgae-based fuels are viewed as an alternative. Microalgae are microscopic unicellular plants, which typically grow in marine and freshwater environments. They are fast growing, have high photosynthetic efficiency, and have relatively small land requirement and water consumption in comparison with conventional land crops biofuels. Nonetheless, selling biofuels is still limited by high cost. Here, we review biofuel production from microalgae, including cultivation, harvesting, drying, extraction and conversion of microalgal lipids. Cost issues may be solved by upstream and downstream measures: (1) upstream measures, in which highly productive strains are obtained by strain selection, genetic engineering and metabolic engineering, and (2) downstream measures, in which high biofuels yields are obtained by enhancing the cellular lipid content and by advanced conversion of microalgal biomass to biofuels. Maximum biomass and high biofuels production can be achieved by two-stage culture strategies, which is a win–win approach because it solves the conflicts between cell growth and biomass accumulation.

Background Lupus nephritis (LN) is an inflammation of the kidneys and is a major cause of mortality in systemic lupus erythaematosus (SLE) patients. In addition, Th17/Treg balance is one of the most important factors that can promote the development of LN. It has been reported that vasoactive intestinal peptide (VIP) is associated with the downregulation of both inflammatory and autoimmune diseases through regulating T lymphocyte balance. Therefore, the aim of this study was to determine the role of VIP in modulating Th17/Treg balance in LN. Methods LN was induced in BALB/c female mice by injection pristane. After 3 months, mice were randomly divided into four groups: control, VIP + control, LN and VIP + LN. Autoantibody levels were tested by ELISA. The distribution of Th17/Treg cells in vivo and in vitro was detected by FC. Renal tissues were examined by PASM and DIF for pathology and Foxp3+CD3+. The mRNA and protein expression levels of pro- and anti-inflammatory cytokines were detected by qRT-PCR and western blotting. Results VIP can improve renal injury by regulating Th17/Treg imbalance in LN mice. Proteinuria, renal function defects and autoantibodies were significantly decreased, and Th17/Treg cell balance was restored in VIP compared with LN mice. In addition, VIP improved renal lesions by promoting the expression of Foxp3+CD3+ in renal tissue. Furthermore, VIP downregulated the mRNA and protein expression of IL-17, IL-6 and upregulated Foxp3, IL-10 expression. Conclusions VIP reduced LN proteinuria and renal function defects and restored the Th17/Treg cell balance. Furthermore, VIP also downregulated autoantibody and inflammatory cytokine expression and upregulated Foxp3 and IL-10 expression.

Injury to podocytes leads to proteinuria, a hallmark of most glomerular diseases as well as being associated with the progression of kidney disease. Activation of the Wnt/β-catenin pathway is associated with the pathogenesis of podocyte dysfunction and can play a role in renal injury. Furthermore, the expression of fractalkine (FKN) induced by lipopolysaccharides (LPS) is also one of crucial inflammation factors closely related to renal tissue damage. The aim of this study is to explore the mechanism of LPS-induced FKN expression leading to podocyte injury and contribute to acute kidney injury (AKI) through regulation of Wnt/β-catenin pathway. An AKI model was established for in vivo experiments and blood was collected for serum BUN and Cr measurement, and histopathological features of the kidneys were studied by PASM and IHC staining. For in vitro experiments, a mouse podocyte cell line was stimulated with different concentrations of LPS for 24 and 48 h after which podocyte viability and apoptosis of cells were evaluated. The expression of podocyte-specific markers, FKN and Wnt/β-catenin pathway mRNA and protein was detected in mice and cells by using qRT-PCR and western blotting. LPS induced the expression of FKN and activation of the Wnt/β-catenin pathway, leading to a decrease of podocyte-specific proteins which resulted in poor renal pathology and dysfunction in the AKI mouse model. Moreover, LPS treatment significantly decreased cell viability and induced podocyte apoptosis in a dose-dependent manner that causes changes in the expression of podocyte-specific proteins through activation of FKN and the Wnt/β-catenin pathway. Thus, the expression of FKN and Wnt/β-catenin pathway by LPS is closely associated with podocyte damage or loss and could therefore account for progressive AKI. Our findings indicate that LPS induce podocyte injury and contribute to the pathogenesis of AKI by upregulating the expression of FKN and Wnt/β-catenin pathway.

Doped semiconductors supporting localized surface plasmon resonances, such as nonstoichiometric copper chalcogenides Cu2–xSe, have been intensively researched for their potential applications in photoacoustic imaging and photothermal therapy. For these self-doped nanoparticles, their physicochemical attributes such as size and surface chemistry will not only affect their cellular uptake and biodistribution but also influence their own optical properties. Thus, optimization of the physicochemical properties is crucial for their nanobio-applications. Through a seeded growth approach, aqueous phase synthesis of monodisperse Cu2–xSe with various sizes has been developed for the first time. Taking three different sized Cu2–xSe NPs (35, 65, and 105 nm in diameter) as examples, their size-dependent optical cross-section, photothermal property, and cellular cytotoxicity have been investigated, and the 65 nm one displays the largest optical cross-section at 21.57 L g–1 cm–1 and best photothermal property per unit ...

Active control of nanocrystal optical and electrical properties is crucial for many of their applications. By electrochemical (de)lithiation of Cu2-xSe, a highly doped semiconductor, dynamic and reversible manipulation of its NIR plasmonics has been achieved. Spectroelectrochemistry results show that NIR plasmon red-shifted and reduced in intensity during lithiation, which can be reversed with perfect on-off switching over 100 cycles. Electrochemical impedance spectroscopy reveals that a Faradaic redox process during Cu2-xSe (de)lithiation is responsible for the optical modulation, rather than simple capacitive charging. XPS analysis identifies a reversible change in the redox state of selenide anion but not copper cation, consistent with DFT calculations. Our findings open up new possibilities for dynamical manipulation of vacancy-induced surface plasmon resonances and have important implications for their use in NIR optical switching and functional circuits.

Microplastics (MPs) pollution has been increasingly investigated in marine and freshwater environments, even in atmosphere in China. Current literatures show that MPs contamination is highly related to human activities and geomorphology. Higher MPs occurrences were detected in freshwaters than those in seawaters in China. Furthermore, the abundance of MPs was influenced by many factors, including sampling method, unit of measurement, characteristics of sampling area, and others. Currently, investigating the condition of MPs occurrences and distribution on a broader scale and developing standardized protocol, along with basic toxicological research, will help to address crucial knowledge gaps regarding MPs pollution, their interaction with other pollutants and ecological consequences on individual, population or ecosystem levels in the environment. Meanwhile, this review calls for more efforts to be made for better and scientifically sound risk management for mitigation of MPs pollution in China.

Autonomous driving cars need highly complex hardware and software systems, which require high performance computing platforms in order to enable a real time AI-based perception and decision making pipeline. The industry has been exploring various in-vehicle accelerators such as GPUs, ASICs and FPGAs. Yet the autonomous driving platform design is far from mature when taking into account of system reliability, redundancy and higher level of autonomy. In this work, we propose a hybrid computing system design, which integrates a GPU as the primary computing system and a FPGA as a secondary system. This hybrid system architecture has multiple advantages: 1) The FPGA can be constantly running as a complementary system with very short latency, helping to detect main system failure and anomalous behavior, contributing to system functionality verification and reliability. 2) If the primary system fails (mostly from sensor or interconnection error), the FPGA will quickly detect the failure and run a safe-mode task with a subset of sensors. 3) The FPGA can be used as an independent computing system to run extra algorithm components to improve the overall system autonomy. For example, FPGA can handle driver monitoring tasks while GPU focuses on driving functions. Together they can boost the driving function from L2 (constantly requires driver’s attention) to L3 (allows driver to mind off for 10 seconds). This paper defines how such a system works, discusses various use cases and potential design challenges, and shares some initial results and insights about how to make such a system deliver the maximum value for autonomous driving.

Upland and paddy soils, as well as corn samples, were collected in the selenosis area of Naore Village, Ziyang County, Shaanxi Province, China. A five-step sequential extraction procedure was used for selenium (Se) fractionation, including soluble Se, exchangeable Se and carbonate-bound Se, iron and manganese oxide-bound Se, organic matter-bound Se, and the residual Se fraction. Species of soluble Se in upland soils included Se(-2), Se(4+), and Se(6+). The results showed that soluble Se and exchangeable Se fractions accounted for less than 1% of the total Se in the upland soil, but approximately 16.1% in the paddy soil. Concentrations of residual Se were lower than those of iron and manganese oxide-bound Se and organic matter-bound Se in both upland and paddy soils. Iron- and manganese oxide-bound Se was the dominant fractions in upland soil, whereas organic matter-bound Se abounded in paddy soil. Concentrations (mg kg(-1)) of Se in the corn samples ranged from 0.05 to 14.5 in seed, 0.31 to 12.3in root, 0.09 to 9.15 in stalk, and 0.16 to 36.15 in leaf. Path analysis indicated that soluble Se(6+) significantly (P

In this paper, a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients is presented. A parametric logarithmic law, i.e., the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics are discussed in this paper, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Qfactor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. The results of our extensive experiments demonstrate the effectiveness of the proposed statistical model.

This paper presents a novel steganalysis scheme to effectively attack the JPEG steganographic schemes. The proposed method exploits the correlations between block-DCT coefficients in both intra-block and inter-block sense. We use Markov empirical transition matrices to capture these dependencies. The experimental results demonstrate that the proposed scheme is superior to the existing steganalyzers in attacking OutGuess, F5, and MB1.

This paper1 presents a novel pattern classification scheme: Class-wise Non-Principal Component Analysis (CNPCA), which utilizes the distribution characteristics of the samples in each class. The Euclidean distance in the subspace spanned by the eigenvectors associated with smallest eigenvalues in each class, named CNPCA distance, is adopted as the classification criterion. The number of the smallest eigenvalues is selected in such a way that the classification error in a given database is minimized. It is a constant for the database and can be determined by experiment. The CNPCA classification scheme usually outperforms other classification schemes under the situations of high computational complexity (associated with high dimensionality of features and/or calculation of inverse variance matrix) or high classification error rate (e.g., owing to the scattering of between-class being less than that of within-class). The experiments have demonstrated that this method is promising in practical applications.

This paper presents a Bhattacharyya distance based feature selection method, which utilizes a recursive algorithm to obtain the optimal dimension reduction matrix in terms of the minimum upper bound of classification error under normal distribution for multi-class classification problem. In our scheme, PCA is incorporated as a pre-processing to reduce the intractably heavy computation burden of the recursive algorithm. The superior experimental results on the handwritten-digit recognition with the MNIST database and the steganalysis applications have demonstrated the effectiveness of our proposed method.

This paper presents a novel feature selection scheme based on the upper bound of Bayes error under normal distribution for the multi-class dimension reduction problem. The upper bound of Bayes error in the multi-class problem is represented by the sum of the upper bound of Bayes error of every two-class pair. In order to obtain an accurate solution of the feature selection transform matrix in term of the minimum upper bound of Bayes error, a recursive algorithm based on gradient method is developed. The principal component analysis (PCA) is used as a pre-processing to reduce the intractably heavy computation burden of the recursive algorithm. The superior experimental results on the handwritten digit recognition with the MNIST database demonstrate the effectiveness of our proposed method

In this paper, we present a real-time adaptive streaming video platform. This platform is fully compliant with the Internet Streaming Media Alliance Implementation Specification. It has been used for experiments of Real-time video streaming and transcoding via unicast and multicast over heterogeneous networks. One of the examples of streaming video over a lossy channel is given, and a simple and efficient scheme for the packet loss recovery is presented.