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In air combat missions, unmanned combat aerial vehicles (UCAVs) must take strategic actions to establish combat advantages, enabling effective tracking and attacking of enemy UCAVs. Currently, a lot of reinforcement learning algorithms are applied to the air combat mission of unmanned fighter aircraft. However, most algorithms can only select policies based on the current state of both sides. This leads to the inability to effectively track and attack when the enemy performs large angle maneuvering. Additionally, these algorithms cannot adapt to different situations, resulting in the unmanned fighter aircraft being at a disadvantage in some cases. To solve these problems, this paper proposes predictive air combat decision model with segmented reward allocation for air combat tracking and attacking. On the basis of the air combat environment, we propose the prediction soft actor-critic (Pre-SAC) algorithm, which combines the prediction of enemy states with the states of UCAV for model training. This enables the UCAV to predict the next move of the enemy UCAV in advance and establish a greater air combat advantage for us. Furthermore, by adopting a segmented reward allocation model and combining it with the Pre-SAC algorithm, we propose the segmented reward allocation soft actor-critic (Sra-SAC) algorithm, which solves the problem of UCAVs being unable to adapt to different situations. The results show that the prediction-based segmented reward allocation the Sra-SAC algorithm outperforms the traditional soft actor-critic (SAC) algorithm in terms of overall reward, travel distance, and relative advantage. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method to recognize the digital modulation communication signals with alpha-stable noise over fading channels. Specifically, the probability density function of alpha-stable noise is determined by kernel density estimation, and the fading channel parameters are measured by utilizing the improved expectation conditional maximization algorithm. Then we leverage the compound hypothesis test model, which serves as a classifier, to implement modulation recognition. Simulation results show that the proposed method is robust to alpha-stable noise over fading channels. Moreover, the correct average recognition rates of the digital modulation communication signals under alpha-stable noise is more than 90%, when the generalized signal-to-noise ratio is 10dB. [ABSTRACT FROM AUTHOR]

Olivine (Fo80-88) from the Shitoukengde deposit exhibits low levels of Ca, Cr, and Al (< 220 ppm) and varying Ni content. The low Ca-Cr-Al contents in olivine and subsolidus temperatures (600–900 °C) indicated by olivine-spinel thermometers align with subsolidus equilibria, emphasizing substantial postcumulus modifications. Therefore, the postcumulus effect must be considered when applying olivine-spinel oxybarometers to intrusive rocks. Back-calculating the spinel Fe–Mg contents to magmatic temperature, the estimated oxidation fugacity (fO2) range between FQM − 1.5 and FQM − 3.0, approximately 0.5 to 1.5 ΔFQM more reduced compared to those calculated from the raw spinel composition. Moreover, the fO2 aligns with results obtained from the olivine-sulfide pair (FMQ − 3.0 to FMQ 0). The considerably reducing state and wide oxidation variation are consistent with the graphite occurrence within the reduced intervals and the systematic fO2 indicated by olivine V/Sc ratios. Combined with the wide olivine Ni range (200–1500 ppm) and the restricted Ni tenor in coexisting sulfides, those findings imply that the olivine-sulfide interaction was predominantly controlled by fO2. Diffusion modeling at magmatic temperatures reveals that the core-level Fe–Ni re-equilibration after crystallization requires hundreds of years. The homogeneous olivine composition suggests that re-equilibrium has been achieved in Shitoukengde. However, in fast cooling systems, olivine may record the status approaching olivine-sulfide equilibration, leading to extensive intragrain Ni variation (up to 1000 ppm). This study highlights that extreme Ni depletion in olivine from sulfide-bearing rocks is a sign of reducing conditions. Strongly Ni-rich olivine, such as those in the Kevitsa deposit, could result from interaction with high-Ni tenor sulfides at oxidizing conditions. [ABSTRACT FROM AUTHOR]

The modelling and analysis of appliance energy use (AEU) of residential buildings are important for energy consumption control, energy management and maintenance, building performance evaluation, and so on. Although some traditional machine learning methods have been applied to produce good prediction results, these models are usually not interpretable, in that they fail to explain how appliance factors make contributions to the variation of AEU individually and interactively. Explicitly knowing the role played by each of the appliance factors in explaining AEU, however, is very important for energy saving. Motivated by this observation, this study introduces an interpretable machine learning approach which is built upon the nonlinear autoregressive moving average with eXogenous inputs model. The advantage of the proposed model is that in comparison with other state-of-the-art machine learning methods, for example, feedforward neural network, recurrent neural network (e.g., gated recurrent unit), and long short-term memory network, the established model is not only able to produce more accurate energy use prediction, but more importantly, also fully transparent and physically interpretable, clearly and explicitly indicating which factors significantly affect the variation of AEU. The findings of this study provide meaningful insights for improving the AEU efficiency. [ABSTRACT FROM AUTHOR]

Fixed-wing unmanned aerial vehicles (UAVs) will play a vital role in forthcoming military conflicts. Effectively avoiding threats and improving the survivability of fixed-wing UAV in dynamic hostile environments are the keys to the success of combat missions. Hence, endowing fixed-wing UAVs with the ability to autonomously generate evasive maneuver is the primary problem that should be solved. With considering the threat of air-to-air missile attacks, this paper designs a novel hierarchical goal-guided learning (HGGL) method, which combines with traditional off-policy deep reinforcement learning (DRL) algorithms and endows the agent with the ability to evade a series of air-to-air missiles. The pivotal idea of the proposed algorithm is to use the hierarchical features of the goal, it improves the availability of training data to eliminate the limitation of the convergence rate of traditional DRL algorithms owing to sparse rewards. We demonstrate the performance of our algorithm in several simulation experiments. All experiments are applied on the XSimStudio platform. The results demonstrate that the proposed algorithm improves the convergence speed and outperforms the state-of-the-art traditional algorithms. [ABSTRACT FROM AUTHOR]

Data-driven fault detection techniques have attracted extensive attention in engineering, industry and many other areas in recent years. In many real applications, the following situation often occurs: data for certain types of faults (unseen faults) are not available to train models that are used for fault detection. Such a scenario can occur when data collection becomes highly time-consuming or destructive. To address this challenging problem, a novel fault detection method using zero-shot learning (ZSL) is proposed in this paper, which contains three phases: feature extraction, label embedding, and feature embedding. The method first extracts features from raw signals by applying a one-dimensional convolutional neural network (1D CNN), then builds semantic descriptions (human-defined) as fault attributes shared between seen faults and unseen faults, and finally uses a bi-linear compatibility function to find the highest-ranking fault type. The proposed semantic space based zero-shot learning with 1D CNN is called SSB-ZSL-1DCNN. The cosine distance is used to measure the similarity between feature embeddings and fault attributes. An important characteristic of SSB-ZSL-1DCNN is that the model, trained using only samples of seen faults, can be used to detect unseen defects. To evaluate the proposed method, two case studies are designed based on two well-known benchmarks (the Tennessee-Eastman chemical control process and the rolling bearing experiments at the Case Western Reserve University, respectively). The results demonstrate that the proposed method shows remarkable performance in detecting unseen faults. [ABSTRACT FROM AUTHOR]

To assess the safety and efficacy of endovascular embolization techniques, we compared the short- to medium-term prognosis of coil embolization for symptomatic visceral aneurysms (SVAA) and asymptomatic visceral aneurysms (ASVAA) to identify risk factors associated with 30-day mortality. Explore the symptom profile and intrinsic associations of SVAA. A retrospective study of 66 consecutive patients at two tertiary care hospitals from 2010 to 2020 compared the short- to mid-term outcomes of 22 symptomatic VAAs and 44 asymptomatic VAAs treated with coil embolization. Univariate and log-rank tests were used to analyze the prognostic impact of SVAA and ASVAA. SVAA group had significantly higher 30-day mortality than ASVAA group (2(9.1%) vs 0, P = 0.042), both patients who died had symptomatic pseudoaneurysms. Perioperative complications such as end-organ ischemia (P = 0.293) and reintervention (P = 1) were similar in both groups. No difference in event-free survival was identified between the two groups (P = 0.900), but we found that the majority of pseudoaneurysms were SVAA (4/5) and that they had a much higher event rate than true aneurysms. In addition, dyslipidemia may be an influential factor in the development of VAA (P = 0.010). Coil embolization is a safe and effective method of treatment for VAA. Most pseudoaneurysms have symptoms such as abdominal pain and bleeding, and in view of their risk, more attention should be paid to symptomatic patients and the nature of the aneurysm should be determined as soon as possible to determine the next stage of treatment. [ABSTRACT FROM AUTHOR]

Although deep reinforcement learning (DRL) algorithms with experience replay have been used to solve many sequential learning problems, applications of DRL in real-world robotics still face some serious challenges, such as the problem of smooth movement. A robot's motion trajectory needs to be smoothly coded, with no sudden acceleration or jerk. In this paper, a novel hierarchical reinforcement learning control framework named the hierarchical dynamic movement primitive (HDMP) framework is proposed to achieve the smooth movement of robots. In contrast to traditional algorithms, the HDMP framework consists of two learning hierarchies: a lower-level controller learning hierarchy and an upper-level policy learning hierarchy. In the lower-level controller learning hierarchy, modified dynamic movement primitives (DMPs) are utilized to generate a smooth motion trajectory. In the upper-level policy learning hierarchy, an improved local proximal policy optimization (L-PPO) method is proposed to endow the robot with autonomous learning capabilities. The performance achieved with the HDMP algorithm has been evaluated in a classical reaching movement task based on a Sawyer robot. The experimental results demonstrate that the proposed HDMP algorithm can endow a robot with the ability to smoothly execute motor skills and learn autonomously. [ABSTRACT FROM AUTHOR]

The ground-state phases of spin-1 Bose–Einstein condensates with SU(3) spin–orbit (SO) coupling in a rotating annular potential are studied. Under the influence of SO coupling and spin-exchange interaction, lattice, stripe and other interesting phases are found in such a trap. When rotation is considered, we find coreless vortices and singular vortices can be generated simultaneously and isolated by a nearly horizontal vortex chain, whose number is mainly dominated by SO coupling strength and rotating frequency, respectively. [ABSTRACT FROM AUTHOR]

Electroencephalogram (EEG) signal analysis plays an essential role in detecting and understanding epileptic seizures. It is known that seizure processes are nonlinear and non-stationary, discriminating between rhythmic discharges and dynamic change is a challenging task in EEG-based seizure detection. In this paper, a new time-varying (TV) modeling framework, based on an autoregressive (AR) model structure, is proposed to characterize and analyze EEG signals. The TV parameters of the AR model are approximated through a multi-wavelet basis function expansion (MWBF) approach. An effective ultra-regularized orthogonal forward regression (UROFR) algorithm is employed to significantly reduce and refine the resulting expanded model. Given a time-varying process, the proposed TVAR–MWBF–UROFR method can generate a parsimonious TVAR model, based on which a high-resolution power spectrum density (PSD) estimation can be obtained. Informative features are then defined and extracted from the PSD estimation. The TVAR–MWBF–UROFR method is applied to a number of real EEG datasets; features obtained from these datasets are then used for seizure detection and classification. To make the results more accurate and reliable, a PCA algorithm is adopted to select the optimal feature subset, and a Bayesian optimization technique based on the Gaussian process is performed to determine the coefficients associated with each of the classifiers. The performance of the proposed method is tested on two benchmark datasets, and the experimental results indicate that TVAR–MWBF–UROFR outperforms the compared state-of-the-art classifiers in terms of accuracy, specificity, sensitivity and robustness. [ABSTRACT FROM AUTHOR]

Bilevel optimization has been recognized as one of the most difficult and challenging tasks to deal with because a solution to the upper level problem may be feasible only if it is also an optimal solution to the lower level problem. In recent years, evolutionary bilevel optimization has attracted increasing interest. In this paper, an efficient self-adaptive bilevel differential evolution (SABiLDE) with k-nearest neighbors (kNN) based interpolation is proposed to solve bilevel optimization problems. The kNN approximation is applied to estimate the optimal lower level variables for any newly generated upper candidates to improve the computational efficiency. A similarity based self-adaptive strategy for the dynamic control of lower level population size and search radius is introduced to further enhance the efficiency of the lower level function evaluations. A test set with 10 standard test problems and the SMD suite with controllable complexities are used to evaluate the performance of the proposed approach. Compared with four recent state-of-the-art methods, the numerical results produced by the proposed method are promising and show great potential for solving generic bilevel optimization problems. [ABSTRACT FROM AUTHOR]

Background: Aberrant activation of Wnt/β-catenin signaling by dysregulated post-translational protein modifications, especially ubiquitination is causally linked to cancer development and progression. Although Lys48-linked ubiquitination is known to regulate Wnt/β-catenin signaling, it remains largely obscure how other types of ubiquitination, such as linear ubiquitination governs its signaling activity. Methods: The expression and regulatory mechanism of linear ubiquitin chain assembly complex (LUBAC) on Wnt/β-catenin signaling was examined by immunoprecipitation, western blot and immunohistochemical staining. The ubiquitination status of β-catenin was detected by ubiquitination assay. The impacts of SHARPIN, a core component of LUBAC on malignant behaviors of gastric cancer cells were determined by various functional assays in vitro and in vivo. Results: Unlike a canonical role in promoting linear ubiquitination, SHARPIN specifically interacts with β-catenin to maintain its protein stability. Mechanistically, SHARPIN competes with the E3 ubiquitin ligase β-Trcp1 for β-catenin binding, thereby decreasing β-catenin ubiquitination levels to abolish its proteasomal degradation. Importantly, SHARPIN is required for invasiveness and malignant growth of gastric cancer cells in vitro and in vivo, a function that is largely dependent on its binding partner β-catenin. In line with these findings, elevated expression of SHARPIN in gastric cancer tissues is associated with disease malignancy and correlates with β-catenin expression levels. Conclusions: Our findings reveal a novel molecular link connecting linear ubiquitination machinery and Wnt/β-catenin signaling via SHARPIN-mediated stabilization of β-catenin. Targeting the linear ubiquitination-independent function of SHARPIN could be exploited to inhibit the hyperactive β-catenin signaling in a subset of human gastric cancers. [ABSTRACT FROM AUTHOR]

The pathological features of patients with polycythemia vera can manifest as thrombosis, and arterial thrombosis can be the primary symptom similarly [[2]]. Thrombotic events are the main complications of patients with PV, and peripheral arterial thrombosis occurs in approximately 2% of PV patients and accounts for about 10-20% of all thrombotic events [[3]]. Dear Editor, Polycythemia vera (PV) is a myeloproliferative disorder characterized by excessive erythrocytosis, leukocytosis, and bone marrow hypercellularity [[1]]. [Extracted from the article]

The Wiener nonlinear system is composed of a linear dynamic subsystem in series with a static nonlinear subsystem. This type of system is widely found in the petroleum, chemistry, thermal and other process industries. It is of great significance to obtain the parameter estimates of the Wiener systems. This paper studies the identification problem of the Wiener time delay nonlinear system. Based on the gradient search principle, a stochastic gradient identification algorithm and a gradient-based iterative identification algorithm are derived. Furthermore, a linearly decreasing weight particle swarm iterative identification algorithm is also proposed for the discussed Wiener time delay systems. Finally, a numerical example and two application cases are given for validating the feasibility of the three identification methods. The results demonstrate that the three algorithms can identify the unknown parameters of the Wiener model effectively. Moreover, the linearly decreasing weight particle swarm iterative identification algorithm behaves much better than the stochastic gradient and the gradient-based iterative algorithms in accuracy and convergence speed. [ABSTRACT FROM AUTHOR]

Bimodal classification of idiopathic chronic pancreatitis (ICP) into early-onset (<35 years) and late-onset (>35 years) ICP was proposed in 1994 based on a study of 66 patients. However, bimodal distribution wasn't sufficiently demonstrated. Our objective was to examine the validity and relevance of the age-based bimodal classification of ICP. We analyzed the distribution of age at onset of ICP in our cohort of 1633 patients admitted to our center from January 2000 to December 2013. Classify ICP patients into early-onset ICP(a) and late-onset ICP(a) according to different cut-off values (cut-off value, a = 15, 25, 35, 45, 55, 65 years old) for age at onset. Compare clinical characteristics of early-onset ICP(a) and late-onset ICP(a). We found slightly right skewed distribution of age at onset for ICP in our cohort. There were differences between early-onset and late-onset ICP with respect to basic clinical characteristics and development of key clinical events regardless of the cut off age at onset i.e. 15, 25, 35, 45 or even higher. The validity of the bimodal classification of early-onset and late-onset ICP could not be established in our large patient cohort and therefore such a classification needs to be reconsidered. [ABSTRACT FROM AUTHOR]

Inflammation plays a critical role in the development of abdominal aortic aneurysm (AAA). Chemokine receptor CXCR2 mediates inflammatory cell chemotaxis in several diseases. However, the role of CXCR2 in AAA and the underlying mechanisms remain unknown. In this study, we found that the CXCR2 expressions in AAA tissues from human and angiotensin II (Ang II)-infused apolipoprotein E knockout (Apo E−/−) mice were significantly increased. The pharmacological inhibition of CXCR2 (SB265610) markedly reduced Ang II-induced AAA formation. Furthermore, SB265610 treatment significantly reduced collagen deposition, elastin degradation, the metal matrix metalloprotease expression and accumulation of macrophage cells. In conclusion, these results showed CXCR2 plays a pathogenic role in AAA formation. Inhibition of CXCR2 pathway may represent a novel therapeutic approach to treat AAA. [ABSTRACT FROM AUTHOR]

System identification and data-driven modeling techniques have seen ubiquitous applications in the past decades. In particular, parametric modeling methodologies such as linear and nonlinear autoregressive with exogenous input models (ARX and NARX) and other similar and related model types have been preferably applied to handle diverse data-driven modeling problems due to their easy-to-compute linear-in-the-parameter structure, which allows the resultant models to be easily interpreted. In recent years, several variations of the NARX methodology have been proposed that improve the performance of the original algorithm. Nevertheless, in most cases, NARX models are applied to regression problems where all output variables involve continuous or discrete-time sequences sampled from a continuous process, and little attention has been paid to classification problems where the output signal is a binary sequence. Therefore, we developed a novel classification algorithm that combines the NARX methodology with logistic regression and the proposed method is referred to as logistic-NARX model. Such a combination is advantageous since the NARX methodology helps to deal with the multicollinearity problem while the logistic regression produces a model that predicts categorical outcomes. Furthermore, the NARX approach allows for the inclusion of lagged terms and interactions between them in a straight forward manner resulting in interpretable models where users can identify which input variables play an important role individually and/or interactively in the classification process, something that is not achievable using other classification techniques like random forests, support vector machines, and k-nearest neighbors. The efficiency of the proposed method is tested with five case studies. [ABSTRACT FROM AUTHOR]

The Atlantic meridional overturning circulation (AMOC), an important component of the climate system, has only been directly measured since the RAPID array’s installation across the Atlantic at 26°N in 2004. This has shown that the AMOC strength is highly variable on monthly timescales; however, after an abrupt, short-lived, halving of the strength of the AMOC early in 2010, its mean has remained ~ 15% below its pre-2010 level. To attempt to understand the reasons for this variability, we use a control systems identification approach to model the AMOC, with the RAPID data of 2004-2017 providing a trial and test data set. After testing to find the environmental variables, and systems model, that allow us to best match the RAPID observations, we reconstruct AMOC variation back to 1980. Our reconstruction suggests that there is inter-decadal variability in the strength of the AMOC, with periods of both weaker flow than recently, and flow strengths similar to the late 2000s, since 1980. Recent signs of weakening may therefore not reflect the beginning of a sustained decline. It is also shown that there may be predictive power for AMOC variability of around 6 months, as ocean density contrasts between the source and sink regions for the North Atlantic Drift, with lags up to 6 months, are found to be important components of the systems model. [ABSTRACT FROM AUTHOR]

Nitrite (NO2−) contamination of water can severely impact the health of aquatic life and is a major concern for commercial aquaculture. In order to study the effect of nitrite on Aristichthys nobilis, we investigated the oxygen-carrying capacity, NF-κB/HIF-1α pathway, and the gill tissue structure under nitrite stress. In the current study, bighead carp (initial weight 180.05 ± 0.092 g) were exposed to nitrite (48.634 mg/L) for 96 h and then for 96 h recovery test. After nitrite exposure for 6 h, hypoxia-inducible factor-1α (HIF-1α) and nuclear factor-κB (NF-κB) mRNA expression increased significantly in the gill of bighead carp (P < 0.05). After nitrite exposure for 12 h, hemoglobin (Hb) and methemoglobin reductase (MHBR) content in blood decreased significantly (P < 0.05); TLR4 mRNA expression increased significantly (P < 0.05). After nitrite exposure for 24 h, methemoglobin (MetHb) content increased significantly (P < 0.05). After recovery test, all the indicators except TLR4 mRNA expression level recovered to initial level. In conclusion, nitrite exposure can affect hemoglobin dynamics, as oxidization of nitrite by hemoglobin results in the reduction of Hb to MetHb leading to hypoxia and nitrite exposure can also result into gill tissue damage. In the face of nitrite exposure, NF-κB and HIF-1α mRNA expression level increased immediately to protect the body from oxidative damage and eased hypoxic condition caused by nitrite. It was also observed that nitrite damage is recoverable in Aristichthys nobilis, but it may be need more than 96 h. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of recursive identification of Wiener nonlinear systems whose linear subsystems are observable state-space models. The maximum likelihood principle and the recursive identification technique are employed to develop a recursive maximum likelihood identification algorithm which estimates the unknown parameters and the system states interactively. In comparison with the developed recursive maximum likelihood algorithm, a recursive generalized least squares algorithm is also proposed for identification of such Wiener systems. The performance of the developed algorithms is validated by two illustrative examples. [ABSTRACT FROM AUTHOR]

Aiming at the sequential and nonlinear characteristics of power quality data over a long time span, a set of PQ evaluation and early warning system on DG distribution network based on deep learning is proposed. The intelligent power distribution network power quality monitoring and early warning system aims to realize the monitoring and forecasting and early warning functions of multiple indicators of power quality in the distribution network. First, we use the sliding window to convert the power quality data into a number of square graphs with time as the scale; second, we use the feature extraction advantage of (Convolutional Neural Network, CNN) to extract the features of each square graph sample and extract it. The characteristic information is transformed into the input of (Long Short Term Memory, LSTM) in a time series sequence; finally, according to the output of CNN-LSTM is used to complete the power quality data prediction of the active distribution network. Through an IEEE 13-node active distribution network simulation example with distributed power sources, this method decouples the feature extraction, analysis, and prediction tasks of power quality data and simplifies the prediction work. Compared with the selected control model, it is significantly to improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

Radiotherapy induces and promotes innate and adaptive immunity in which host STING plays an important role. However, radioresistance in irradiated tumors can also develop, resulting in relapse. Here we report a mechanism by which extrinsic resistance develops after local ablative radiation that relies on the immunosuppressive action of STING. The STING/type I interferon pathway enhances suppressive inflammation in tumors by recruiting myeloid cells in part via the CCR2 pathway. Germ-line knockouts of CCR2 or treatment with an anti-CCR2 antibody results in blockade of radiation-induced MDSC infiltration. Treatment with anti-CCR2 antibody alleviates immunosuppression following activation of the STING pathway, enhancing the anti-tumor effects of STING agonists and radiotherapy. We propose that radiation-induced STING activation is immunosuppressive due to (monocytic) M-MDSC infiltration, which results in tumor radioresistance. Furthermore, the immunosuppressive effects of radiotherapy and STING agonists can be abrogated in humans by a translational strategy involving anti-CCR2 antibody treatment to improve radiotherapy. [ABSTRACT FROM AUTHOR]

Enterovirus 71 (EV71) is one of the major causative agents of hand, foot and mouth disease (HFMD), which mainly occurs in children. Children with EV71 infection can develop severe neurological diseases. Heat shock protein 78 (HSP78) facilitates proper protein folding during viral propagation and is induced during virus infection. Nevertheless, the role that HSP78 plays during EV71 infection is still unclear. In this study, recombinant HSP78 protein was expressed in a prokaryotic expression system and used for exploring the interaction between HSP78 and EV71 propagation. Detection using a mouse immune anti-HSP78 serum in ELISA and western blot demonstrated that the recombinant HSP78 antigen is highly immunogenic. Furthermore, the recombinant HSP78 protein was able to bind to EV71 VP1 and intensified the cytopathic effect and viral propagation during EV71 infection, while the immune serum had a counteractive effect. However, knockdown of the HSP78 gene in Vero cells before EV71 infection did not result in a reduced virus titer. In addition, HSP78 on the cell surface was upregulated in human neuroblastoma cells (SK-N-SH) infected with EV71. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the prognostic value and pathobiological significance of Glasgow microenvironment score (GMS), a parameter based on tumor stroma percentage and inflammatory cell infiltration, in gastric cancer. Methods: A total of 225 cases of gastric cancer were histologically reviewed, and GMS was evaluated for each case. The association between GMS and patients' survival was investigated. Then the relationship between GMS and mismatch repair (MMR) status, Epstein-Barr virus (EBV) infection were determined using immunohistochemistry (IHC) and in situ hybridization, and the expression of PD1/PD-L1 was examined. Furthermore, the amount of cancer-associated fibroblasts (CAFs), the content and maturity of collagen components were detected using IHC, Picrosirius Red staining and second harmonic generation imaging. Results: GMS was significantly associated with clinical outcomes of gastric cancer, and multivariate analysis indicated that GMS was an independent factor (HR 1.725, P = 0.002). Low GMS was a manifestation of better prognosis and inflammatory tumor microenvironment, which was related to MMR deficiency ( P = 0.042) and EBV infection ( P = 0.032), and within this microenvironment, expression of PD-L1 in carcinoma cells ( P = 0.030) or in inflammatory cells ( P = 0.029) was significantly higher. In contrast, high GMS linked to a poorer survival and desmoplastic stroma, in which there existed markedly increased CAFs and collagen deposition. Conclusion: GMS can serve as a useful prognostic factor for gastric cancer, and according to GMS, the tumor microenvironment in this cancer type may be partially classified as inflammatory or desmoplastic microenvironment that possesses different pathobiological features. [ABSTRACT FROM AUTHOR]

Herein is a first effort to systematically study the significance of carbon-sulfur (C-S) and carbon-amine (C-NH) bonds on the antitumor proliferation activity of podophyllum derivatives and their precise mechanism of apoptosis. Compared with the derivative modified by a C-NH bond, the derivative modified by a C-S bond exhibited superior antitumor activity, the inhibition activity of target proteins tubulin or Topo II, cell cycle arrest, and apoptosis induction. Antitumor mechanistic studies showed that the death receptor and the mitochondrial apoptotic pathways were simultaneously activated by the C-S bond modified aromatic heterocyclic podophyllum derivatives with a higher cellular uptake percentage of 60-90% and induction of a higher level of reactive oxygen species (ROS). Only the mitochondrial apoptotic pathway was activated by the C-NH bond modified aromatic heterocyclic podophyllum derivatives, with a lower cellular uptake percentage of 40-50%. This study provided insight into effects of the C-S and C-NH bond modification on the improvement of the antitumor activity of Podophyllum derivatives. [ABSTRACT FROM AUTHOR]

System identification has been applied in diverse areas over past decades. In particular, parametric modelling approaches such as linear and nonlinear autoregressive with exogenous inputs models have been extensively used due to the transparency of the model structure. Model structure detection aims to identify parsimonious models by ranking a set of candidate model terms using some dependency metrics, which evaluate how the inclusion of an individual candidate model term affects the prediction of the desired output signal. The commonly used dependency metrics such as correlation function and mutual information may not work well in some cases, and therefore, there are always uncertainties in model parameter estimates. Thus, there is a need to introduce a new model structure detection scheme to deal with uncertainties in parameter estimation. In this work, a distance correlation metric is implemented and incorporated with a bagging method. The combination of these two implementations enhances the performance of existing forward selection approaches in that it provides the interpretability of nonlinear dependency and an insightful uncertainty analysis for model parameter estimates. The new scheme is referred as bagging forward orthogonal regression using distance correlation (BFOR-dCor) algorithm. A comparison of the performance of the new BFOR-dCor algorithm with benchmark algorithms using metrics like error reduction ratio, mutual information, or the Reversible Jump Markov Chain Monte Carlo method has been carried out in dealing with several numerical case studies. For ease of analysis, the discussion is restricted to polynomial models that can be expressed in a linear-in-the-parameters form. [ABSTRACT FROM AUTHOR]

The enhancement technique for color medical images is conductive to improve the resolution and accuracy of the original image. A new enhancement method combining the Young-Helmholtz (Y-H) transformation with the adaptive equalization of intensity numbers matrix histogram is proposed in this paper. The adaptive histogram equalization method is applied to strengthen the details, enhance the contrast, and suppress the noise of the original image effectively. The enhanced image can be displayed in the red-greenblue (RGB) color space through inverse Y-H transformation with the same hue and saturation. The experiment results demonstrate that the method has the enhancement effect with low computational complexity, which provides the foundation for the medical diagnosis and further processing of medical images. [ABSTRACT FROM AUTHOR]

Aim:To establish a method for efficient expression and purification of the human serotonin type 3A receptor (5-HT3A) that is suitable for structural studies.Methods:Codon-optimized cDNA of human 5-HT3A was inserted into a modified BacMam vector, which contained an IgG leader sequence, an 8×His tag linked with two-Maltose Binding Proteins (MBP), and a TEV protease cleavage site. The BacMam construct was used to generate baculoviruses for expression of 5-HT3A in HEK293F cells. The proteins were solubilized from the membrane with the detergent C12E 9, and purified using MBP affinity chromatography. The affinity tag was removed by TEV protease treatment and immobilized metal ion affinity chromatography. The receptors were further purified by size-exclusion chromatography (SEC). Western blot and SDS-PAGE were used to detect 5-HT3A during purification. The purified receptor was used in crystallization and analyzed with negative stain electron microscopy (EM).Results:The BacMam system yielded 0.5 milligram of the human 5-HT3A receptor per liter of cells. MBP affinity purification resulted in good yields with high purity and homogeneity. SEC profiles indicated that the purified receptors were pentameric. No protein crystals were obtained; however, a reconstructed 3D density map generated from the negative stain EM data fitted well with the mouse 5-HT3A structure.Conclusion:With the BacMam system, robust expression of the human 5-HT3A receptor is obtained, which is monodisperse, therefore enabling 3D reconstruction of an EM map. This method is suitable for high-throughput screening of different constructs, thus facilitating structural and biochemical studies of the 5-HT3A receptor. [ABSTRACT FROM AUTHOR]

We have investigated the electronic structure and magnetic properties of Ba and Mn co-doped LaZnAsO using density functional theory within the generalised gradient approximation (GGA)+U schemes. We have shown that the ground state magnetic structure of Mn-doped LaZnAsO is antiferromagnetic while Ba and Mn co-doped LaZnAsO is ferromagnetic. The origin of the Mn-Mn exchange mechanism is discussed. [ABSTRACT FROM AUTHOR]

Aim:A large number of drug-induced long QT syndromes are ascribed to blockage of hERG potassium channels. The aim of this study was to construct novel computational models to predict compounds blocking hERG channels.Methods:Doddareddy's hERG blockage data containing 2644 compounds were used, which divided into training (2389) and test (255) sets. Laplacian-corrected Bayesian classification models were constructed using Discovery Studio. The models were internally validated with the training set of compounds, and then applied to the test set for validation. Doddareddy's experimentally validated dataset with 60 compounds was used for external test set validation.Results:A Bayesian classification model considering the effects of four molecular properties (Mw, PPSA, ALogP and pKa_basic) as well as extended-connectivity fingerprints (ECFP_14) exhibited a global accuracy (91%), parameter sensitivity (90%) and specificity (92%) in the test set validation, and a global accuracy (58%), parameter sensitivity (61%) and specificity (57%) in the external test set validation.Conclusion:The novel model is better than those in the literatures for predicting compounds blocking hERG channels, and can be used for large-scale prediction. [ABSTRACT FROM AUTHOR]

Background: In patients with esophageal squamous cell carcinoma (ESCC), pathologic examination allows T2 tumors to be further subclassified according to whether the circular or longitudinal muscle layers are invaded. Therefore, we aimed to investigate whether subclassifying the T2 stages can aid in determining the prognosis for patients with ESCC. Methods: The clinical and pathologic characteristics of 85 ESCC patients with T2 tumors who underwent thoracoscopic esophagectomy between 2008 and 2013 were retrospectively analyzed. Univariate and multivariate analyses were performed to identify prognostic factors. The Kaplan-Meier method was used to compare survival differences with respect to each prognostic factor. Results: Thirty-nine patients had tumors invading the circular muscle layer and were designated as having T2a disease. The remaining 46 patients had T2b disease, with tumors invading the longitudinal muscle layer. The overall 1-, 3-, and 5-year survival rates were 96.1, 53.8, and 36.4 %, respectively, with a median survival of 39.0 months. Univariate analysis indicated that sex, smoking history, grade, location, and tumor length did not significantly influence on survival. Only T stage ( P = 0.017) and N stage ( P = 0.003) were associated with survival. The results of multivariate Cox proportional hazard regression analysis showed that T stage ( P = 0.045) and N stage ( P = 0.003) were independent prognostic factors. Conclusions: N stage and subclassified T stage are independent prognostic factors in patients with T2 tumors. Therefore, we concluded that T2 tumors can be subclassified further into T2a and T2b stages, and patients with different T2 stages may have different prognoses. [ABSTRACT FROM AUTHOR]

The yellow dwarf disease associated with phytoplasmas is one of the most devastating diseases of mulberry and the pathogenesis involved in the disease is poorly understood. To analyze the molecular mechanisms mediating gene expression in mulberry-phytoplasma interaction, the comprehensive sRNA changes of mulberry leaf in response to phytoplasma-infection were examined. A total of 164 conserved miRNAs and 23 novel miRNAs were identified, and 62 conserved miRNAs and 13 novel miRNAs were found to be involved in the response to phytoplasma-infection. Meanwhile, target genes of the responsive miRNAs were identified by sequencing of the degradome library. In addition, the endogenous siRNAs were sequenced, and their expression profiles were characterized. Interestingly, we found that phytoplasma infection induced the accumulation of mul-miR393-5p which was resulted from the increased transcription ofMulMIR393A, and mul-miR393-5p most likely initiate the biogenesis of siRNAs from TIR1 transcript. Based on the results, we can conclude that phytoplasma-responsive sRNAs modulate multiple hormone pathways and play crucial roles in the regulation of development and metabolism. These responsive sRNAs may work cooperatively in the response to phytoplasma-infection and be responsible for some symptoms in the infected plants. [ABSTRACT FROM AUTHOR]

We aimed to evaluate the interference of 50 Hz extremely low frequency electromagnetic field (ELF-EMF) occupational exposure on the neurobehavior tests of workers performing tour-inspection close to transformers and distribution power lines. Occupational short-term 'spot' measurements were carried out. 310 inspection workers and 300 logistics staff were selected as exposure and control. The neurobehavior tests were performed through computer-based neurobehavior evaluation system, including mental arithmetic, curve coincide, simple visual reaction time, visual retention, auditory digit span and pursuit aiming. In 500 kV areas electric field intensity at 71.98 % of total measured 590 spots were above 5 kV/m (national occupational standard), while in 220 kV areas electric field intensity at 15.69 % of total 701 spots were above 5 kV/m. Magnetic field flux density at all the spots was below 1,000 μT (ICNIRP occupational standard). The neurobehavior score changes showed no statistical significance. Results of neurobehavior tests among different age, seniority groups showed no significant changes. Neurobehavior changes caused by daily repeated ELF-EMF exposure were not observed in the current study. [ABSTRACT FROM AUTHOR]

This paper discusses the identification problems of Hammerstein controlled autoregressive autoregressive (CARAR) systems using the maximum likelihood principle and Newton optimization method. A Newton recursive algorithm and a Newton iterative algorithm using the maximum likelihood principle are presented. The simulation results show that the proposed algorithms can effectively estimate the parameters of the Hammerstein CARAR systems. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer stem cells (CSCs), which require activation of Wnt signaling to maintain their self-renewal and tumorigenicity, are proposed to be critical targets for effective therapy of gastric carcinomas. Gene therapies that are delivered by adenovirus of serotype 5 (Ad5) or chimeric 5/35(Ad5/35) adenovirus have shown promise for treating various cancers. Here we aimed to develop a gene therapy strategy that targeted gastric CSCs (CD44⁺ cells).Methods: CD44⁺ cells were isolated by fluorescence activated cell sorting from both primary gastric cancer cells and cell lines. Expression of adenovirus receptors was examined in CD44⁺ and CD44⁻ cells. A potent Wnt antagonist Dickkopf-1 (DKK1) was delivered into CD44⁺ cells using Ad5/35 (Ad5/35-DKK1). The therapeutic outcomes were evaluated.Results: Expression of Coxsakievirus adenovirus receptor for Ad5 was significantly reduced, while abundance of CD46, the receptor for Ad5/35, was slightly higher in CD44⁺ cells. Accordingly, CD44⁺ cells were sensitive to Ad5/35 infection, but not to Ad5. Ad5/35-DKK1 introduced DKK1 into CD44⁺ cells and deactivated endogenous Wnt/β-catenin signaling efficiently. Overexpression of DKK1 inhibited survival, anchorage-independent colony formation, and invasion of CD44⁺ cells, which were restored by a GSK-3 specific inhibitor BIO-acetoxime. More importantly, introduction of DKK1 abrogated the tumorigenicity of CD44⁺ cells in vivo. However, Ad5/35-DKK1 only showed minimal cytotoxicity to normal tissue-derived cells, L-02 and GES-1.Conclusions: We developed, for the first time, a novel Ad5/35-DKK1-based approach to abrogate Wnt signaling in CSCs and demonstrated that gastric CSC-targeting gene therapy was effective in preclinical experiments. [ABSTRACT FROM AUTHOR]

We report a case of pulmonary adenofibroma, a rare benign soft-tissue tumor characterized by a combination of glandular and spindle stromal elements, in a 55-year-old man. This case is interesting because of the unusual X-ray and computed tomography (CT) imaging findings of a well-defined, subpleural soft-tissue nodule in the inferior lobe of the left lung, which showed no enhancement after contrast scan. The tumor was resected completely via video-assisted thoracoscopy. Microscopic and immunohistochemical examinations supported the diagnosis of a benign pulmonary adenofibroma. The patient remains well with no evidence of recurrence 16 months after surgery. Although the imaging findings were nonspecific, adenofibroma may be one of diagnostic inclusions of soft-tissue nodules of the lung in middle-aged patients. [ABSTRACT FROM AUTHOR]

Aim:To investigate the molecular mechanisms underlying the influence of DNA polymerase from different genotypes of hepatitis B virus (HBV) on the binding affinity of adefovir (ADV).Methods:Computational approaches, including homology modeling, docking, MD simulation and MM/PBSA free energy analyses were used.Results:Sequence analyses revealed that residue 238 near the binding pocket was not only a polymorphic site but also a genotype-specific site (His238 in genotype B; Asn238 in genotype C). The calculated binding free-energy supported the hypothesis that the polymerase from HBV genotype C was more sensitive to ADV than that from genotype B. By using MD simulation trajectory analysis, binding free energy decomposition and alanine scanning, some energy variation in the residues around the binding pocket was observed. Both the alanine mutations at residues 236 and 238 led to an increase of the energy difference between genotypes C and B (ΔΔGC-B), suggesting that these residues contributed to the genotype-associated antiviral variability with regard to the interaction with ADV.Conclusion:The results support the hypothesis that the HBV genotype C polymerase is more sensitive to ADV than that from genotype B. Moreover, residue N236 and the polymorphic site 238 play important roles in contributing to the higher sensitivity of genotype C over B in the interaction with ADV. [ABSTRACT FROM AUTHOR]

Aim:This study was conducted to test the selectivity of DC031050 on cardiac and neuronal potassium channels.Methods:Human ether-à-go-go related gene (hERG), KCNQ and Kv1.2 channels were expressed in CHO cells. The delayed rectifier potassium current (IK) was recorded from dissociated hippocampal pyramidal neurons of neonatal rats. Whole-cell voltage patch clamp was used to record the voltage-activated potassium currents. Drug-containing solution was delivered using a RSC-100 Rapid Solution Changer.Results:Both DC031050 and dofetilide potently inhibited hERG currents with IC50 values of 2.3±1.0 and 17.9±1.2 nmol/L, respectively. DC031050 inhibited the IK current with an IC50 value of 2.7±1.5 μmol/L, which was >1000 times the concentration required to inhibit hERG current. DC031050 at 3 μmol/L did not significantly affect the voltage-dependence of the steady activation, steady inactivation of IK, or the rate of IK from inactivation. Intracellular application of DC031050 (5 μmol/L) was insufficient to inhibit IK. DC031050 up to 10 μmol/L had no effects on KCNQ2 and Kv1.2 channel currents.Conclusion:DC031050 is a highly selective hERG potassium channel blocker with a substantial safety margin of activity over neuronal potassium channels, thus holds significant potential for therapeutic application as a class III antiarrhythmic agent. [ABSTRACT FROM AUTHOR]

A novel symmetrical chirped beam splitter based on a binary blazed grating is proposed, which adopts the fully-etched grating structure compatible with the current fabrication facilities for CMOS technology and convenient for integration and manufacture process. This structure can realize nearly equal-power splitting operation under the condition of TE polarization incidence. When the absolutely normal incidence occurs at the wavelength of 1580 nm, the coupling efficiencies of the left and the right branches are 43.627% and 43.753%, respectively. Moreover, this structure has the tolerances of 20 nm in etched depth and 3° in incident angle, which is rather convenient to manufacture facility. [ABSTRACT FROM AUTHOR]

Aim:Activating transcription factor 6 (ATF6) is a key signal transducer of endoplasmic reticulum stress (ER stress). This study was conducted to clarify the potential role of ATF6 in the insulin signaling pathway under chronic ER stress.Methods:ER stress of HEK293 cells was induced with tunicamycin (2 μg/mL). The cells were transfected with ATF6α or ATF6β. The phosphorylation level of insulin receptor (IR) was analyzed using Western blot. The changes in ER stress and ERK signaling pathways were explored using Western blot and quantitative real-time PCR.Results:Tunicamycin-induced chronic ER stress attenuated IR tyrosine phosphorylation in a time-dependent manner, whereas over-expression of ATF6 protected IR from desensitization. ATF6 modulation of IR suppression was associated with insulin-stimulated extracellular signal-regulated kinase (ERK) phosphorylation. The treatment of the cells with a specific ERK inhibitor U0126 (10 μmol/L) mimicked the effect of ATF6 over-expression and restored the insulin-stimulated IR phosphorylation. The treatment of the cells with the ERK activator epidermal growth factor (EGF, 200 ng/mL) decreased the protection effect of ATF6 on IR.Conclusion:Our results demonstrate that ATF6 may serve as a potential therapeutic target for the treatment of insulin resistance and type 2 diabetes. [ABSTRACT FROM AUTHOR]

Infection with hepatitis B virus (HBV) is a major cause of liver diseases such as cirrhosis and hepatocellular carcinoma. In our previous studies, we identified indole derivatives that have anti-HBV activities. In this study, we optimize a series of 5-hydroxy-1 H-indole-3-carboxylates, which exhibited potent anti-HBV activities, using three-dimensional quantitative structure-activity relationship (3D QSAR) studies with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The lowest energy conformation of compound 3, which exhibited the most potent anti-HBV activity, obtained from systematic search was used as the template for alignment. The best predictions were obtained with the CoMFA standard model ( q = 0.689, r = 0.965, SEE = 0.082, F = 148.751) and with CoMSIA combined steric, electrostatic, hydrophobic and H-bond acceptor fields ( q = 0.578, r = 0.973, SEE = 0.078, F = 100.342). Both models were validated by an external test set of six compounds giving satisfactory prediction. Based on the clues derived from CoMFA and CoMSIA models and their contour maps, another three compounds were designed and synthesized. Pharmacological assay demonstrated that the newly synthesized compounds possessed more potent anti-HBV activities than before (IC: compound 35a is 3.1 μmol/l, compound 3 is 4.1 μmol/l). Combining the clues derived from the 3D QSAR studies and from further validation of the 3D QSAR models, the activities of the newly synthesized indole derivatives were well accounted for. Furthermore, this showed that the CoMFA and CoMSIA models proved to have good predictive ability. [ABSTRACT FROM AUTHOR]

The significance of BmK CT, a key chlorotoxin-like peptide isolated from the scorpion venom of Buthus martensii Karsch, is a novel blocker of the chloride ion channel and matrix metalloproteinase-2 (MMP-2). Site-directed mutagenesis of BmK CT, wound healing assay, gelatin zymography assay and computational simulation highlight the importance of electrostatic contribution to BmK CT-MMP-2 catalytic domain complex and a model of BmK CT-MMP-2 catalytic domain complex is therefore proposed. This is the first documentation of the structural mechanism of in the inhibition of glioma cell migration by BmK CT and may lead to the molecular design of specific inhibitors of MMP-2. [ABSTRACT FROM AUTHOR]

To understand the mechanism by which early insulin therapy improves insulin sensitivity in type 2 diabetes, we investigated endoplasmic reticulum (ER) stress in the liver of type 2 diabetic rats. A high fat diet plus a low dose of streptozotocin (STZ) in Sprague-Dawley (SD) rats was implemented to create an animal model mimicking diabetes. After 3 weeks of insulin treatment, the rats were examined for insulin sensitivity and ER stress in the liver. To investigate insulin sensitivity within the liver, serine phosphorylation of IRS-1 (Ser307) and Akt (Ser473) and expression of gluconeogenic genes, PEPCK and G6Pase, were tested. Protein levels of ER stress markers, such as immunoglobulin binding protein (Bip), inositol-requiring protein 1 alpha (IRE1α), and unspliced and spliced x-box binding protein-1 (XBP-1), were determined to assess ER stress. In the diabetic (DM) group, IRS-1 phosphorylation was increased ( P < 0.05), Akt phosphorylation was reduced ( P < 0.05), expression of PEPCK and G6Pase was elevated ( P < 0.05), and ER stress markers were up-regulated ( P < 0.05) relative to the non-diabetic rats. In the insulin (INS) therapy group, all of aforementioned changes were attenuated or reversed ( P < 0.05). In addition, c-Jun N-terminal kinase (JNK) activity and SREBP-1 expression were decreased ( P < 0.05). Adipose tissue mass was increased ( P < 0.05). These data suggest that short-term insulin therapy relieved ER stress and enhanced insulin sensitivity in the liver of diabetic rats. The mechanism is likely related to fat redistribution from liver to adipose tissue. These cellular and molecular responses may represent a mechanism for improvement of insulin sensitivity in type 2 diabetic rats by insulin therapy. [ABSTRACT FROM AUTHOR]

The polarization hysteresis loops as well as the initial curves of ferroelectric films with 180° domain boundaries perpendicular to the film surface are simulated based on an extensive time-dependent Ginzburg-Landau model. The result shows that the curve and loop strongly depend on the frequency ω of the applied electric field, the effective mass density ρ, and the viscosity coefficient K of the material, however, the constant ωK/ ρ can induce the same curve and loop. The hysteresis area of the saturated loop is increased with field amplitude, which is consistent with the previous experimental observation. In addition, it is found that the latent domains in the film can result in a remarkable decrease in the remanent polarization and coercive field. [ABSTRACT FROM AUTHOR]

Glucokinase (GCK) acts as a glucose sensor and regulates β-cell insulin secretion. The heterozygous mutations in the gene encoding GCK cause a reduction of the enzyme activity, which results in a monogenic form of diabetes, maturity-onset diabetes of the young. In the present study, we identified and functionally characterized a novel missense mutation in the GCK gene, which results in a protein mutation Glu → Lys (E339K), from a Chinese family with hyperglycemia. The same GCK mutation that co-segregated with diabetes phenotype was identified in five members of this family but was not found in 200 healthy control individuals. We expressed and affinity-purified the GCK proteins from bacterial expression system that carries mutation (E339K) and fused to glutathione S-transferase. The expressed GCK protein was subjected to the measurement of its biochemical effects of the missense mutation on GCK activity. Our results showed that the mutation reduced the GCK protein yield. The enzymatic kinetics and the thermal stability analysis on the recombinant GCK proteins revealed that the mutation inactivates enzyme kinetics and severely impaired the GCK protein stability. [ABSTRACT FROM AUTHOR]

The aim of this study is to assess the oxidative stress status in diabetes mellitus (DM) and diabetic nephropathy. The study group comprised 40 control subjects, 40 type 2 DM patients without complications and 37 diabetic nephropathies. Compared with control subjects, superoxide dismutase, glutathione peroxidase, catalase, vitamin C were decreased ( P < 0.01). There was a significant increase in serum malondialdehyde (MDA), conjugated diene (CD), advanced oxidation protein products (AOPP), protein carbonyl (PC) and 8-hydroxy-2′-deoxyguanosine (8-OHdG) in diabetes patients when compared with normal subjects ( P < 0.01). Moreover, these indexes were much higher in diabetic nephropathy than that of diabetic patients without vascular complications ( P < 0.05, P < 0.01). There was a significant correlation between the serum glucose levels and PC, 8-OHdG ( P < 0.05, P < 0.01). There were highly significant positive correlation of CD and MDA, AOPP and PC ( P < 0.01). Plasma AOPP levels had a significant correlation with PC levels ( P < 0.01). Our findings suggested that diabetes patients have more severe oxidative stress than normal persons and higher oxidative stress in diabetic nephropathy than those in patients without complications. Oxidative stress may play an important intermediary role in the pathogenesis of diabetes complications. [ABSTRACT FROM AUTHOR]

5′ untranslated regions (UTRs) are important sequence elements that modulate the expression of genes. Using the β-glucuronidase ( GUS) reporter gene driven by the GluC promoter for the rice-seed storage-protein glutelin, we evaluated the potential of the 5′-UTRs of six seed storage-protein genes in enhancing the expression levels of the foreign gene in stable transgenic rice lines. All of the 5′-UTRs significantly enhanced the expression level of the GluC promoter without altering its expression pattern. The 5′-UTRs of Glb- 1 and GluA- 1 increased the expression of GUS by about 3.36- and 3.11-fold, respectively. The two 5′-UTRs downstream of the Glb- 1, OsAct2 and CMV35S promoters also increased GUS expression level in stable transgenic rice lines or in transient expression protoplasts. Therefore, the enhancements were independent of the promoter sequence. Real-time quantitative RT-PCR analysis showed that the increase in protein production was not accompanied by alteration in mRNA levels, which suggests that the enhancements were due to increasing the translational efficiencies of the mRNA. The 5′-UTRs of Glb- 1 and GluA- 1, when combined with strong promoters, might be ideal candidates for high production of recombinant proteins in rice seeds. [ABSTRACT FROM AUTHOR]

Ciliate Euplotes octocarinatus centrin (EoCen) is a member of the EF-hand superfamily of calcium-binding proteins. It has been proven, using Tb as a fluorescence probe, that EoCen has four calcium-binding sites. The sensitized emission arises from nonradiative energy transfer between the three tyrosine residues (Tyr46, Tyr72, and Tyr79) of the N-terminal half and the bound Tb ions. To determine the most critical of the three tyrosine residues for the process of fluorescence resonance energy transfer, six mutants of the N-terminal domain of EoCen, which contain one (N-Tyr46/N-Tyr72/N-Tyr79) or two (N-Y46F/N-Y72F/N-Y79F) tyrosine residues, were obtained by site-directed mutagenesis. The aromatic residue-sensitized Tb fluorescence of N-Y79F was most affected, displaying a 50% reduction compared with wild-type N-EoCen. Among the tyrosines, Tyr79 is the shortest mean distance from the protein-bound Tb (at sites I/II), as calculated via the Förster mechanism. The steady-state and time-resolved fluorescence parameters of the wild-type N-EoCen and the three double mutants suggest that Tyr79, which exists in a hydrophobic environment, has the highest quantum yield and a relatively long average lifetime. The decay of Tyr79 is the least heterogeneous among the three tyrosine residues. In addition, molecular modeling shows that a critical hydrogen bond is formed between the 4-hydroxyl group of Tyr79 and the oxygen from the side chains of the residue Asn39. Kinetic experiments on tyrosine and Tb fluorescence demonstrate that tyrosine fluorescence quenching is largely due to the self-assembly of EoCen, and that the quenching degrees of the mutants differ. Resonance light scattering and crosslinking analysis carried out on the full-length single mutants (Y46F, Y72F, and Y79F) showed that Tyr79 also plays the most important role in the Tb-dependent self-assembly of EoCen among the three tyrosines. [ABSTRACT FROM AUTHOR]