bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Complete Genome Sequence of the Widely Studied Strain Bradyrhizobium betae PL7HG1
T
Reveals the Presence of Photosynthesis Genes and a Putative Plasmid
Authors: Cloutier Sylvie , Bromfield Eden S. P.
Published: November 2019

Here, we present the complete genome sequence of the widely studied strain
Bradyrhizobium betae
PL7HG1
T
, isolated from a tumor on the roots of sugar beet. The genome consists of a 7.2-Mbp circular chromosome containing key photosynthesis genes but not genes for nodulation and nitrogen fixation. A putative plasmid was also detected.
Complete Genome Sequence of Klebsiella pneumoniae Podophage Pylas
Authors: Powell Jeffery E. , Lessor Lauren , O’Leary Chandler , Gill Jason , Liu Mei
Published: November 2019

Carbapenemase-producingKlebsiella pneumoniaeis an important opportunistic pathogen due to its drug resistance. This study reports on the isolation and characterization of a podophage, named Pylas, infecting this bacterium. The complete genome of phage Pylas is described, and it is distantly related to the well-studied phage N4.
Geochemical and biological controls on the ecological relevance of total, dissolved, and colloidal forms of trace elements in large boreal rivers: review and case studies
Authors: Cuss C.W. , Glover C.N. , Javed M.B. , Nagel A. , Shotyk W.
Published: November 2019

The concentrations of trace elements (TEs) in large boreal rivers can fluctuate markedly due to changing water levels and flow rates associated with spring melt and variable contributions from tributaries and groundwaters, themselves having different compositions. These fluctuating and frequently high concentrations create regulatory challenges for protecting aquatic life. For example, water quality criteria do not account for changes in flow regimes that can result in TE levels that may exceed regulatory limits, and neither do they account for the markedly different lability and bioaccessibility of suspended solids. This review addresses the geochemical and biological processes that govern the lability and bioaccessibility of TEs in boreal rivers, with an emphasis on the challenges posed by the colloidal behaviour of many TEs, and their relationship to the dissolved fraction (i.e., <0.45 μm in size). After reviewing the processes and dynamics that give rise to the forms and behaviour of TEs in large boreal rivers, their relevance for aquatic organisms and the associated relationships between size and lability and bioaccessibility are discussed. The importance of biological variables and different forms of TEs for limiting lability and bioaccessibility are also addressed. Two case studies emphasize seasonal fluctuations and accompanying changes in the distribution of TE amongst different size fractions and associated colloidal species in large boreal rivers: the Northern Dvina and one of its tributaries, the Pinega River, both in Russia, and the Athabasca River in Alberta, Canada. Water quality in the Athabasca River is briefly discussed with respect to Canadian guidelines.
Characteristic of the algebraic traveling wave solutions for two extended (2 + 1)-dimensional Kadomtsev–Petviashvili equations
Authors: Liu Jian-Gen , Yang Xiao-Jun , Feng Yi-Ying
Published: November 2019

With the aid of the planar dynamical systems and invariant algebraic cure, all algebraic traveling wave solutions for two extended (2 + 1)-dimensional Kadomtsev–Petviashvili equations, which can be used to model shallow water waves with weakly nonlinear restoring forces and to describe waves in ferromagnetic media, were obtained. Meanwhile, some new rational solutions are also yielded through an invariant algebraic cure with two different traveling wave transformations for the first time. These results are an effective complement to existing knowledge. It can help us understand the mechanism of shallow water waves more deeply.
Spin-0 system of DKP equation in the background of a flat class of Gödel-type spacetime
Authors: Ahmed Faizuddin , Hassanabadi Hassan
Published: November 2019

In this paper, we investigate the Duffin–Kemmer–Petiau (DKP) equation for spin-0 system of charge-free particles in the background of a flat class of Gödel-type spacetimes, and evaluate the individual energy levels and corresponding wave functions in detail.
Kink scattering in hyperbolic models
Authors: Bazeia D. , Gomes Adalto R. , Nobrega K. Z. , Simas Fabiano C.
Published: November 2019

In this work, we study kink–antikink and antikink–kink collisions in hyperbolic models of fourth and sixth orders. We compared the patterns of scattering with known results from polynomial models of the same order. The hyperbolic models considered here tend to the polynomial [Formula: see text] and [Formula: see text] models in the limit of small values of the scalar field. We show that kinks and antikinks that interact hyperbolically with the fourth order differ sensibly from those governed by the polynomial [Formula: see text] model. The increasing of the order of interaction to the sixth order shows that the hyperbolic and polynomial models give intricate structures of scattering that differ only slightly. The dependence on the order of interaction is related to some characteristics of the models such as the potential of perturbations and the number of vibrational modes.
Antiresonance in electron transport through a four quantum dots system
Authors: He Zelong , Chen Kongfa , Bai Jiyuan , Li Yadong
Published: November 2019

A four quantum dots structure is designed. The influence of the interdot coupling strength, energy levels of quantum dots, magnetic flux and intradot Coulomb interactions on the conductance is discussed. An antiresonance point exactly emerges at the location of the energy level of side-coupled quantum dots (SCQD). The conversion between resonance band and antiresonance band can be achieved as parallel-coupled di-quantum dots with or without SCQD, which suggests a physical scheme of an effective quantum switch. The Breit–Wigner resonant and Fano antiresonant peaks may merge into one resonant band. By means of the mathematical formula, we analyze how the resonance band is formed. By varying intradot Coulomb interaction, the resonance band may evolve into a Fano antiresonance with an ultra-narrow width. This study provides theoretical basis for the design of quantum computing devices.
Numerical simulation and performance optimization of the centrifugal fan in a vacuum cleaner
Authors: Shen Yingying , Li Yao , Wang Haibo , Shen Wenzhong , Chen Yongliang , Si Haiqing
Published: November 2019

This paper focuses on the efficiency improvement of a centrifugal fan used in a vacuum cleaner. In order to check the performance of the centrifugal fan system, computational fluid dynamics (CFD) analysis is used. The numerical simulation with CFD tool is carried out with RNG [Formula: see text] two-equation turbulence model based on Reynolds-averaged Navier–Stokes equations. To perform the coupling between rotating impeller and stationary area, the multiple reference frame (MRF) model is used. The numerical results of the fan are validated against with experimental results and are found to be highly reliable. The design and optimization of diffuser and impeller of a centrifugal fan are realized by using numerical investigations. For reducing the kinetic energy loss inside the fan, a guide baffle is added to optimize diffuser. The optimization results show that overall efficiency of the fan is improved by 5.27% and considering the lower efficiency of impeller caused by blockage at the blade inlet, etc., the design of impeller with long-short blades is proposed. Several cases of affecting factors under different operating conditions are simulated. Relative length (denoted as [Formula: see text]) and circumferential position of short blades are chosen as design variables. It is found that the efficiency of a fan with a relative length of 0.7 can be increased by 9.34%, and the best circumferential position of short blades is between two adjacent long blades.
Study on fractal and island growth processes of thin films with a modified DLA model
Authors: Zhang Min , Zhou Xun , Deng Chaoyong
Published: November 2019

A modified diffusion-limited aggregation (DLA) model for two-dimensional (2D), three-dimensional (3D) fractal growth and 3D island growth was established based on the DLA model in this paper. The number of particles [Formula: see text] and the size of the box size [Formula: see text] (related to side length [Formula: see text]), which are related to film thickness, are considered in the study. The simulation results are a good reflection of the actual experimental results. The results show that the particle number and simulation box size can affect the fractal morphology and fractal dimension of the film, and also the 2D to 3D transformation. In addition, the critical particle number [Formula: see text] and the critical box size [Formula: see text] during the transformation process are also given.
A closed-loop readout interface for MEMS accelerometer with time-multiplexing electrostatic force feedback
Authors: Sun Zhi Yuan , Yin Liang , Yu Jian Hai
Published: November 2019

The noise and linearity performance of a MEMS accelerometer is a critical issue for land seismic acquisition applications. Incorporating closed-loop force feedback is an effective way to enhance those performances. However, additional electrode to exert the electrostatic force is typically not available and residue displacement of proof mass would introduce significant nonlinearity to the closed-loop transfer function, impairing the efficiency of the method. This paper proposes a switched-capacitor closed-loop readout interface for MEMS accelerometer which greatly alleviates those problem. First, the proposed system incorporates a time-multiplexing technique, thus the sensing and force feedback can be realized using the same electrode and get separated in time sequence. Furthermore, the cross-coupling of high-voltage feedback signal and weak sensing signal can be minimized. Second, a correlated double sampling (CDS) technique and a PID control mechanism is introduced in the loop. Thus, the two sources of residue displacement: interface mismatch and insufficient loop gain can be well-suppressed. The test results show that the proposed closed-loop MEMS accelerometer can achieve an SNR better than 120 dB, with an in-band noise spectral density lower than 500 ng/Hz[Formula: see text].
An Attribute-Weighted Bayes Classifier Based on Asymmetric Correlation Coefficient
Authors: Liu Jingxian , Zhang Yulin
Published: November 2019

In this research, an attribute-weighted one-dependence Bayes estimation algorithm based on the asymmetric correlation coefficient is proposed. The asymmetric correlation coefficients Tau_y and Lambda_y, respectively, are used to calculate the correlation between parent attributes and category labels, then the result of calculation is regarded as weight to the parent attribute. The algorithm is applied to eight types of different datasets including binary classification and multiple classification from the UCI database. By comparing the time complexity and classification accuracy, experimental results show that the algorithm can significantly improve the classification performance with less prediction error. In addition, several baseline methods such as KNN, ANN, logistic regression and SVM are used for comparison with the proposed method.
Learning Regular Expressions Using XCS-Based Classifier System
Authors: Rehman Hafiz Asadul , Iqbal Muhammad , Younas Irfan , Bashir Maryam
Published: November 2019

Evolutionary machine learning research aims to develop classifier systems that can solve complex and hard tasks. This paper addresses the problem of inferring a regular expression from a given set of strings for automating the task of information extraction. To the best of our knowledge, this paper is the first to propose the extension of accuracy-based classifier system XCS to learn the regular expressions for text extraction. This new system named as XCSREA includes tree-like code fragments to learn regular expressions. The genetic algorithm in action sets uses two-point crossover with uniform mutation and Roulette wheel parent selection method. Seven different datasets, each with three different lengths, are used to compare the performance of the proposed model with standard genetic programming (GP) approach. The experimental results demonstrate that XCSREA outperforms standard GP approach when sufficiently large numbers of classifiers are used.
An Experimental Analysis Method of Visual Performance on the Error Factors of Digital Information Interface
Authors: Wu Xiaoli , Li Yajun
Published: November 2019

As per global accident statistics, human error accounts for over 85% of accidents. Therefore, human error analysis of cognitive behavior of operators can be the key to solving information interface design problems of digital smart task monitoring interfaces. This paper proposes an analytical method based on psychological experiments introduced into task monitoring interfaces to study reactions to error factors. It uses psychological techniques to conduct experiments which evoke physiological reactions to various error factors under different sub-interfaces of the monitoring system and sub-task environments. The behavioral and eye tracking data demonstrate the association between the error factors and the information interface. Error factors arising in visual search are directly related to the layout of the task-interface, the information proximity–position, and the information features-volume. Our method opens up new approaches for design optimizations of visual information interfaces and introduces novel concepts for the introduction of interface design via error factor analysis.
Foreground Extraction and Motion Recognition Technology for Intelligent Video Surveillance
Authors: Yan Xuebo , Fan Yuemin
Published: November 2019

With the rapid development of computer technology and network technology, it has become possible to build a large-scale networked video surveillance system. The video surveillance system has become a new type of infrastructure necessary for modern cities. In this paper, the problem of foreground extraction and motion recognition in intelligent video surveillance is studied. The three key sub-problems, namely the extraction of motion foreground in video, the deblurring of motion foreground and the recognition of human motion, are studied and corresponding solutions are proposed. A background modeling technique based on video block is proposed. The background is modeled at the block level, which greatly reduces the spatial complexity of the algorithm. It solves the problem that the traditional Gaussian model (GMM) moving target enters the static state and is integrated into the background process. The target starts to move for a long time and there are ghosts and other problems, which reduce the processing efficiency of the lifting algorithm. The test results on the Weizmann dataset show that the proposed algorithm can achieve high human motion recognition accuracy and recognition with low computational complexity. The rate can reach 100%; the local constrained group sparse representation classification (LGSRC) model is used to classify it. The experimental results on Weizmann, KTH, UCF sports and other test datasets confirm the validity of the algorithm in this chapter. KNN, SRC voting classification accuracy.
Human Action Recognition Based on Multiple Features and Modified Deep Learning Model
Authors: Zhu Shaoping , Xiao Yongliang , Ma Weimin
Published: November 2019

In order to improve the accuracy of human action recognition in video and the computational efficiency of large data sets, an action recognition algorithm based on multiple features and modified deep learning model is proposed. First, the deep network pre-training process is used to learn and optimize the RBM parameters, and the deep belief nets (DBN) model is constructed through deep learning. Then, human 13 joint points and critical points of optical flow are automatically extracted by DBN model. Second, these more abstract and more effective human motion features are combined to represent human actions. Ultimately, the entire DBN network structure is fine-tuned by support vector machine (SVM) algorithm to classify human actions. We demonstrate that human 13 joint points and critical points of optical flow are two very effective human action characterizations, our proposed approach greatly reduces the required samples, and shortens the training time of the samples, can efficiently process large data sets and can effectively recognize novel actions. We performed experiments on the KTH data set, Weizmann data set, the ballet data set and UCF101 data set to evaluate the proposed method, the experiment results show that the average recognition accuracy is over 98%, which validates its effectiveness, and show that our results are stable, reliable, and significantly better than the results of two state-of-the-art approaches on four different data sets. So, it lays a good theoretical foundation for practical applications.
Particle Swarm Optimization Algorithm with Mutation Operator for Particle Filter Noise Reduction in Mechanical Fault Diagnosis
Authors: Chen Hanxin , Fan Dong Liang , Fang Lu , Huang Wenjian , Huang Jinmin , Cao Chenghao , Yang Liu , He Yibin , Zeng Li
Published: November 2019

In this paper, a new particle swarm optimization particle filter (NPSO-PF) algorithm is proposed, which is called particle cluster optimization particle filter algorithm with mutation operator, and is used for real-time filtering and noise reduction of nonlinear vibration signals. Because of its introduction of mutation operator, this algorithm overcomes the problem where by particle swarm optimization (PSO) algorithm easily falls into local optimal value, with a low calculation accuracy. At the same time, the distribution and diversity of particles in the sampling process are improved through the mutation operation. The defect of particle filter (PF) algorithm where the particles are poor and the utilization rate is not high is also solved. The mutation control function makes the particle set optimization process happen in the early and late stages, and improves the convergence speed of the particle set, which greatly reduces the running time of the whole algorithm. Simulation experiments show that compared with PF and PSO-PF algorithms, the proposed NPSO-PF algorithm has lower root mean square error, shorter running time, higher signal-to-noise ratio and more stable filtering performance. It is proved that the algorithm is suitable for real-time filtering and noise reduction processing of nonlinear signals.
Personalized Knowledge Recommendation Based on Knowledge Graph in Petroleum Exploration and Development
Authors: Huang Gang , Yuan Man , Li Chun-Sheng , Wei Yong-he
Published: November 2019

Firstly, this paper designs the process of personalized recommendation method based on knowledge graph, and constructs user interest model. Second, the traditional personalized recommendation algorithms are studied and their advantages and disadvantages are analyzed. Finally, this paper focuses on the combination of knowledge graph and collaborative filtering recommendation algorithm. They are effective to solve the problem where [Formula: see text] value is difficult to be determined in the clustering process of traditional collaborative filtering recommendation algorithm as well as data sparsity and cold start, utilizing the ample semantic relation in knowledge graph. If we use RDF data, which is distributed by the E and P (Exploration and Development) database based on the petroleum E and P, to verify the validity of the algorithm, the result shows that collaborative filtering algorithm based on knowledge graph can build the users’ potential intentions by knowledge graph. It is enlightening to query the information of users. In this way, it expands the mind of users to accomplish the goal of recommendation. In this paper, a collaborative filtering algorithm based on domain knowledge atlas is proposed. By using knowledge graph to effectively classify and describe domain knowledge, the problems are solved including clustering and the cold start in traditional collaborative filtering recommendation algorithm. The better recommendation effect has been achieved.
Correction Tower: A General Embedding Method of the Error Recognition for the Knowledge Graph Correction
Authors: Abedini Farhad , Keyvanpour Mohammad Reza , Menhaj Mohammad Bagher
Published: November 2019

Today, knowledge graphs (KGs) are growing by enrichment and refinement methods. The enrichment and refinement can be gained using the correction and completion of the KG. The studies of the KG completion are rich, but less attention has been paid to the methods of the KG error correction. The correction methods are divided into embedding and nonembedding methods. Embedding correction methods have been recently introduced in which a KG is embedded into a vector space. Also, existing correction approaches focused on the recognition of the three types of errors, the outliers, inconsistencies and erroneous relations. One of the challenges is that most outlier correction methods can recognize only numeric outlier entities by nonembedding methods. On the other hand, inconsistency errors are recognized during the knowledge extraction step and existing methods of this field do not pay attention to the recognition of these errors as post-correction by embedding methods. Also, to correct erroneous relations, new embedding techniques have not been used. Since the errors of a KG are variant and there is no method to cover all of them, a new general correction method is proposed in this paper. This method is called correction tower in which these three error types are corrected in three trays. In this correction tower, a new configuration will be suggested to solve the above challenges. For this aim, a new embedding method is proposed for each tray. Finally, the evaluation results show that the proposed correction tower can improve the KG error correction methods and proposed configuration can outperform previous results.
Prediction of Cuttings Transport Behavior under Drill String Rotation Conditions in High-Inclination Section
Authors: Sun Shihui , Feng Jinyu , Hou Zhaokai , Yu Guoqing
Published: November 2019

Cuttings are likely to accumulate and eventually form a cuttings bed in the highly-deviated section, which usually lead to high friction and torque, slower rate of penetration, pipe stuck and other problems. It is therefore necessary to study cuttings transport mechanism and improve hole cleaning efficiency. In this study, the cuttings-transport behaviors with pipe rotation under turbulent flow conditions in the highly deviated eccentric section were numerically simulated based on Euler solid–fluid model and Realizable [Formula: see text]–[Formula: see text] model. The resulted numerical results were compared with available experimental data in reported literature to validate the algorithm, and good agreement was found. Under the conditions of drill string rotation, cuttings bed surface tilts in the direction of rotation and distributes asymmetrically in annulus. Drill string rotation, drilling fluid flow rate, cuttings diameter, cuttings injection concentration and drilling fluid viscosity affect the axial velocity of drilling fluid; whereas drilling fluid tangential velocity is mainly controlled by the rotational speed of drill string. Increase in value of drill string rotation, drilling fluid flow rate or hole inclination will increase cuttings migration velocity. Notably, drill string rotation reduces cuttings concentration and solid–fluid pressure loss, and their variations are dependent on inclination, cuttings injection concentration, cuttings diameter, drilling fluid velocity and viscosity. However, when a critical rotation speed is reached, no additional contribution is observed. The results can provide theoretical support for optimizing hole cleaning and realizing safety drilling of horizontal wells and extended reach wells.
An Efficient Uncertainty Measure-based Attribute Reduction Approach for Interval-valued Data with Missing Values
Authors: Shu Wenhao , Qian Wenbin , Xie Yonghong , Tang Zhaoping
Published: November 2019

Attribute reduction plays an important role in knowledge discovery and data mining. Confronted with data characterized by the interval and missing values in many data analysis tasks, it is interesting to research the attribute reduction for interval-valued data with missing values. Uncertainty measures can supply efficient viewpoints, which help us to disclose the substantive characteristics of such data. Therefore, this paper addresses the attribute reduction problem based on uncertainty measure for interval-valued data with missing values. At first, an uncertainty measure is provided for measuring candidate attributes, and then an efficient attribute reduction algorithm is developed for the interval-valued data with missing values. To improve the efficiency of attribute reduction, the objects that fall within the positive region are deleted from the whole object set in the process of selecting attributes. Finally, experimental results demonstrate that the proposed algorithm can find a subset of attributes in much shorter time than existing attribute reduction algorithms without losing the classification performance.
A Novel Algorithm for Group Decision Making Based on Continuous Optimal Aggregation Operator and Shapley Value
Authors: Lin Jian , Zhang Qiang , Meng Fanyong
Published: November 2019

Interval linguistic preference relation is an effective tool for expressing experts’ preference in group decision making under uncertain linguistic environment. A new aggregation operator called continuous chi-square deviation based 2-tuple linguistic ordered weighted quasi-averaging (C-CDLOWQ) operator is proposed to transform the interval linguistic preference relations into precise linguistic preference relations. Some desirable properties and special cases of the C-CDLOWQ operator are analyzed in detail. To take the interactive phenomenon among experts into account, the Shapley weighting vector is presented to integrate the expected linguistic preference relations. The λ-fuzzy measure is employed to simplify the fuzzy measure on expert set. A CS-GDM algorithm is developed to group decision making with interval linguistic preference relations. The application in commercial investment problem is provided to illustrate the effectiveness of CS-GDM algorithm.
IMPROVING FLUORITE FLOTATION UNDER LOW TEMPERATURE AND NEUTRAL pH CONDITIONS
Authors: LI SHUOFU , GONG DAOZHEN , ZHANG WEI , LI GENZHUANG , JUE KOU
Published: November 2019

The authors provide insight into the problem of selective flotation of fluorite from quartz–fluorite ores. The flotation of fluorite mineral from ores by using acidized water glass as depressant has been studied for substitution of the commonly used depressant. It was found that the acidized water glass could achieve higher selectivity of fluorite minerals against gangue minerals in the fluorite flotation. The experimental results showed that YF collector has high selectivity in the flotation of fluoride for low-grade fluorite ores. The use of the YF collector also made it unnecessary to heat the pulp to a high temperature and achieved an acceptable reduction in the flotation temperature to [Formula: see text]C. The YF collector should be used in neutral pH to separate fluorite from gangue and it could also improve fluorite recovery and flotation rate.
Trade-off relations for operation entropy of complementary quantum channels
Authors: Czartowski Jakub , Braun Daniel , Życzkowski Karol
Published: November 2019

The entropy of a quantum operation, defined as the von Neumann entropy of the corresponding Choi–Jamiołkowski state, characterizes the coupling of the principal system with the environment. For any quantum channel acting on a state of a given size, one defines the complementary channel, which sends the input state into the state of the environment after the operation. Making use of subadditivity of entropy, we show that for any dimension the sum of both entropies is bounded from below. This result characterizes the trade-off between the information on the initial quantum state accessible to the principal system and the information leaking to the environment. For one qubit maps we describe the interpolating family of depolarizing maps, for which the sum of both entropies gives the lower boundary of the region allowed in the space spanned by both entropies.
Approximation algorithms for minimum power k backbone node r-connected subgraph problem in wireless sensor networks
Authors: Shetty D. Pushparaj , Lakshmi M. Prasanna
Published: November 2019

The minimum power assignment problem in a Wireless Sensor Network (WSN) is to assign transmission range to the nodes of the network with specified connectivity constraints minimizing the total power. This problem is termed as Strong Minimum Energy Topology (SMET) problem. Fault tolerance addresses the issue of a node or link failure in a WSN. So, with an objective of achieving high connectivity, we consider SMET problem with an additional property, i.e., the resultant network must satisfy the property of two or high connectivity. Minimum Power [Formula: see text]-Connected Subgraph (MP[Formula: see text]CS) problem is to contrive an [Formula: see text]-connected network with minimum power. Minimum Power [Formula: see text]-Connected Subgraph (MP2CS) problem is proved to be NP -hard. Minimum Power [Formula: see text] Backbone node [Formula: see text]-Connected Subgraph (MP[Formula: see text]B[Formula: see text]CS) problem is a special case of MP[Formula: see text]CS problem, which seeks a power assignment satisfying [Formula: see text]-connectivity with [Formula: see text] backbone nodes. We study MP[Formula: see text]B[Formula: see text]CS problem for [Formula: see text] backbone nodes, [Formula: see text]-connectivity and derive the approximation ratios. We also propose an algorithm of approximation ratio [Formula: see text], for Minimum Power [Formula: see text] Backbone node 3-Connected Subgraph (MP[Formula: see text]B3CS) problem for [Formula: see text] that runs in [Formula: see text] time and generalize for the case [Formula: see text] for any [Formula: see text] and [Formula: see text].
Mitochondrial-specific autophagy linked to mitochondrial dysfunction following traumatic freeze injury in mice
Authors: Nichenko Anna S. , Southern W. Michael , Tehrani Kayvan Forouhesh , Qualls Anita E. , Flemington Alexandra B. , Mercer Grant H. , Yin Amelia , Mortensen Luke J. , Yin Hang , Call Jarrod A.
Published: November 2019

The objective of this study was to interrogate the link between mitochondrial dysfunction and mitochondrial-specific autophagy in skeletal muscle. C57BL/6J mice were used to establish a time course of mitochondrial function and autophagy induction after fatigue ( n = 12), eccentric contraction-induced injury ( n = 20), or traumatic freeze injury (FI, n = 28); only FI resulted in a combination of mitochondrial dysfunction, i.e., decreased mitochondrial respiration, and autophagy induction. Moving forward, we tested the hypothesis that mitochondrial-specific autophagy is important for the timely recovery of mitochondrial function after FI. Following FI, there is a significant increase in several mitochondrial-specific autophagy-related protein contents including dynamin-related protein 1 (Drp1), BCL1 interacting protein (BNIP3), Pink1, and Parkin (~2-fold, P < 0.02). Also, mitochondrial-enriched fractions from FI muscles showed microtubule-associated protein light chain B1 (LC3)II colocalization suggesting autophagosome assembly around the damaged mitochondrial. Unc-51 like autophagy activating kinase (Ulk1) is considered necessary for mitochondrial-specific autophagy and herein we utilized a mouse model with Ulk1 deficiency in adult skeletal muscle ( myogenin-Cre). While Ulk1 knockouts had contractile weakness compared with littermate controls (−27%, P < 0.02), the recovery of mitochondrial function was not different, and this may be due in part to a partial rescue of Ulk1 protein content within the regenerating muscle tissue of knockouts from differentiated satellite cells in which Ulk1 was not genetically altered via myogenin-Cre. Lastly, autophagy flux was significantly less in injured versus uninjured muscles (−26%, P < 0.02) despite the increase in autophagy-related protein content. This suggests autophagy flux is not upregulated to match increases in autophagy machinery after injury and represents a potential bottleneck in the clearance of damaged mitochondria by autophagy.
Regulating ENaC’s gate
Authors: Kleyman Thomas R. , Eaton Douglas C.
Published: November 2019

Epithelial Na+ channels (ENaCs) are members of a family of cation channels that function as sensors of the extracellular environment. ENaCs are activated by specific proteases in the biosynthetic pathway and at the cell surface and remove embedded inhibitory tracts, which allows channels to transition to higher open-probability states. Resolved structures of ENaC and an acid-sensing ion channel revealed highly organized extracellular regions. Within the periphery of ENaC subunits are unique domains formed by antiparallel β-strands containing the inhibitory tracts and protease cleavage sites. ENaCs are inhibited by Na+ binding to specific extracellular site(s), which promotes channel transition to a lower open-probability state. Specific inositol phospholipids and channel modification by Cys-palmitoylation enhance channel open probability. How these regulatory factors interact in a concerted manner to influence channel open probability is an important question that has not been resolved. These various factors are reviewed, and the impact of specific factors on human disorders is discussed.
Psychological Stress and Cellular Aging in Cancer: A Meta-Analysis
Authors: Kruk Joanna , Aboul-Enein Basil Hassan , Bernstein Joshua , Gronostaj Magdalena
Published: November 2019

Background. Epidemiological evidence continues to accumulate on the effect of psychosocial and behavioral factors in relation to cancer risk, progression, and mortality.Material and Methods. This article presents the current evidence on the relationship between psychological stress and the risk of cancer and cellular aging process. Ten databases were searched to identify publications up to September 2019. References from retrieved articles were also reviewed. We included nine review papers and 26 cohort or case-control studies based on inclusion/exclusion criteria.Results. Results of previously published review articles did not show consistent evidence for the association between cancer risk and psychological stress, while previous evidence is stronger regarding the role of chronic psychological stress on cancer growth and metastasis and aging. In seven observational studies, severe life events, anxiety, depression, insufficient social support perception, or avoiding coping strategy were significantly associated with breast cancer risk. For other specific types of cancer, 11 studies reported increased risk factors for stressful life events, and two others found increased mortality or a decline in treatment adherence.Conclusions. Recent epidemiological evidence generally suggests psychosocial factors may be considered risk factors for specific types of cancer and play a key role in the cellular aging process. Understanding molecular mechanisms of the stress interaction is important in cancer management and prevention. The psychological stressors should be considered when developing or evaluating change in psychosocial practice.
Interleukin-6 from Adipose-Derived Stem Cells Promotes Tissue Repair by the Increase of Cell Proliferation and Hair Follicles in Ischemia/Reperfusion-Treated Skin Flaps
Authors: Pu Chi-Ming , Chen Ya-Chun , Chen Yu-Chen , Lee Tzu-Lin , Peng Yu-Sen , Chen Shun-Hua , Yen Yu-Hsiu , Chien Chung-Liang , Hsieh Jung-Hsien , Chen Yuh-Lien
Published: November 2019

The most common postoperative complication after reconstructive surgery is flap necrosis. Adipose-derived stem cells (ADSCs) and their secretomes are reported to mediate skin repair. This study was designed to investigate whether conditioned media from ADSCs (ADSC-CM) protects ischemia/reperfusion- (I/R-) induced injury in skin flaps by promoting cell proliferation and increasing the number of hair follicles. The mouse flap model of ischemia was ligating the long thoracic vessels for 3 h, followed by blood reperfusion. ADSC-CM was administered to the flaps, and their survival was observed on postoperative day 5. ADSC-CM treatment led to a significant increase in cell proliferation and the number of hair follicles. IL-6 levels in the lysate and CM from ADSCs were significantly higher than those from Hs68 fibroblasts. Furthermore, a strong decrease in cell proliferation and the number of hair follicles was observed after treatment with IL-6-neutralizing antibodies or si-IL-6-ADSC. In addition, ADSC transplantation increased flap repair, cell proliferation, and hair follicle number in I/R injury of IL-6-knockout mice. In conclusion, IL-6 secreted from ADSCs promotes the survival of I/R-induced flaps by increasing cell proliferation and the number of hair follicles. ADSCs represent a promising therapy for preventing skin flap necrosis following reconstructive and plastic surgery.
Anti-TNF-α Monoclonal Antibody Therapy Improves Anemia through Downregulating Hepatocyte Hepcidin Expression in Inflammatory Bowel Disease
Authors: Shu Weigang , Pang Zhi , Xu Chunjin , Lin Jian , Li Gengfeng , Wu Wei , Sun Suofeng , Li Junxiang , Li Xiuling , Liu Zhanju
Published: November 2019

Anemia is one of the most common complications in patients with inflammatory bowel disease (IBD). Hepcidin as a key regulator of iron metabolism is pivotal in mediating the occurrence of anemia of chronic disease. Herein, we analyzed the levels of hepcidin in sera from IBD patients by enzyme-linked immunosorbent assay and investigated its potential role in regulating the anemia in IBD. We observed that the levels of serum hepcidin were increased in active IBD patients compared with those in remitted IBD patients and healthy controls and that serum hepcidin was associated with disease activity, CRP, and ESR, respectively. Importantly, we found that the increased levels of serum hepcidin were positively correlated with the severity of anemia and the imbalance of iron metabolism in anemic UC and CD patients. Proinflammatory factors (e.g., IL-6, IL-17, and TNF-α) were positively correlated with the concentrations of serum hepcidin in IBD patients. Interestingly, hepcidin was found to be decreased in patients with Crohn’s disease after successful therapy with anti-TNF-α mAb (i.e., infliximab), indicating the underlying association between TNF-α and hepcidin expression. To investigate the specific mechanisms involved, we cultured LO2 and HepG2 cell lines in vitro under stimulation with TNF-α and observed that the levels of hepcidin mRNA were markedly upregulated in caspase-3/8- and NF-κB-dependent manners. Therefore, our data suggest that TNF-α stimulates the expression of hepcidin in IBD patients, resulting in aggravated anemia and that blockage of TNF-α or the caspase-3/8 and NF-κB pathways could downregulate hepcidin expression. This study provides inspiration for the therapy and management of anemia in IBD.
Ziziphus spina-christi Leaf Extract Suppressed Mercury Chloride-Induced Nephrotoxicity via Nrf2-Antioxidant Pathway Activation and Inhibition of Inflammatory and Apoptotic Signaling
Authors: Almeer Rafa S. , Albasher Gadah , Alotibi Fatimah , Alarifi Saud , Ali Daoud , Alkahtani Saad
Published: November 2019

Exposure to heavy metals, including mercury chloride (HgCl2), is associated with severe health problems. This study was designed to investigate HgCl2-induced nephrotoxicity and evaluate the protective role of Ziziphus spina-christi leaf extract (ZSCLE). Four randomly selected groups containing seven rats were used. For a period of 28 days, the control group was administered 0.9% saline solution; the second group was administered 300 mg/kg ZSCLE; the third group was administered 0.4 mg/kg HgCl2 dissolved in 0.9% physiological saline solution; and the fourth group was administered an oral supplement of 300 mg/kg ZSCLE one hour after HgCl2 administration. HgCl2 intoxication resulted in Hg accumulation in renal tissue; decreases in body weight, kidney index, and glutathione content and superoxide dismutase, catalase, glutathione peroxidase, and glutathione reductase activities; increases in creatinine, urea, Kim-1 expression, lipid peroxidation, and nitric oxide production; suppression of the Nrf2-antioxidant response pathway; upregulation of Il1β, Tnfα, and Nos2; and potentiation of proapoptotic activity. ZSCLE exerted beneficial effects against mercury-induced renal toxicity and significantly reversed these alterations to near normal values. These effects resulted from its chelation and antioxidant, anti-inflammatory, and antiapoptotic activities. ZSCLE may prevent or minimize the pathological changes induced by mercury in the kidney.
Modulation of O-GlcNAcylation Regulates Autophagy in Cortical Astrocytes
Authors: Rahman Md. Ataur , Hwang Hongik , Cho Yoonjeong , Rhim Hyewhon
Published: November 2019

The addition of O-linked β-N-acetylglucosamine (O-GlcNAcylation) to serine and threonine residues is a common posttranslational modification of intracellular proteins which modulates protein functions and neurodegenerative diseases, controlled by a single pair of enzymes, O-GlcNAcase (OGA), and O-GlcNAcylation transferase (OGT). Autophagy is a cellular recycling pathway activated by stress and nutrient signaling; however, the mechanism by which O-GlcNAcylation modification regulates autophagy in cortical astrocytes is poorly understood. Here, we report that increased O-GlcNAcylation by the suppression of OGA activity using thiamet-G and OGA siRNA did not affect autophagy, whereas decreased O-GlcNAcylation caused by OGT inhibition by alloxan and OGT siRNA increased autophagy. OGT inhibitor and siRNA accumulated LC3 puncta, and cotreatment with chloroquine (CQ), an autophagy inhibitor, significantly increased LC3 puncta and LC3-II protein, confirming that decreased O-GlcNAcylation promotes autophagic flux. In particular, we found that OGT knockdown increases the fusion between autophagosomes as well as lysosomes and stimulates autophagy to promote lysosomal-associated membrane protein 1 (LAMP-1). Additionally, decreasing O-GlcNAcylation by treatment with alloxan, OGT siRNA, and OGA overexpression significantly decreased the level of autophagy substrate SQSTM1/p62, indicating that autophagic degradation was activated. Together, our study reveals a mechanism by which the modulation of O-GlcNAcylation modification regulates autophagy in mouse cortical astrocytes.
Polyalthia longifolia Extract Triggers ER Stress in Prostate Cancer Cells Concomitant with Induction of Apoptosis: Insights from In Vitro and In Vivo Studies
Authors: Afolabi Saheed O. , Olorundare Olufunke E. , Babatunde Abiola , Albrecht Ralph M. , Koketsu Mamoru , Syed Deeba N. , Mukhtar Hasan
Published: November 2019

Plant-based therapies are being explored to prevent or treat several cancer types. The antioxidant properties of Polyalthia longifolia plant are well established. In our previous work, we demonstrated the presence of cytotoxic compounds in the methanol extract of Polyalthia longifolia (MEP) with potent activity against human leukemia cells. In the present study, we evaluated the efficacy of MEP against prostate cancer (PCa) and established the molecular basis of its effect in in vitro and in vivo models. We observed that MEP treatment resulted in a significant decrease in the growth and viability of PCa cells, associated with arrest in the G1/S phase of the cell cycle. Apoptosis was confirmed as the primary mode of MEP-induced cell death through activation of the intrinsic apoptotic machinery. Proteomic and biochemical studies identified BiP as an important target of MEP with the activation of the ER stress pathway, as a potential mechanism driving MEP-induced apoptosis. The extract exhibited strong efficacy in the PCa xenograft mouse model with significant inhibition of tumor growth and reduced tumor burden. Taken together, our findings indicate that MEP-induced apoptosis in PCa cells concomitant with the activation of the ER stress pathways results in the inhibition of tumor growth, in vitro and in vivo. Our studies provide initial evidence of the efficacy of MEP against PCa and advocate for in-depth studies in other preclinical models for its possible use in clinical settings.
lncRNA AK054386 Functions as a ceRNA to Sequester miR-199 and Induce Sustained Endoplasmic Reticulum Stress in Hepatic Reperfusion Injury
Authors: Dai Binghua , Qiao Liang , Zhang Mingke , Cheng Lipeng , Zhang Ling , Geng Li , Shi Changying , Zhang Minfeng , Sui Chengjun , Shen Weifeng , Sun Yanfu , Chen Qian , Hui Dong , Wang Yue , Yang Jiamei
Published: November 2019

Hepatic ischemia-reperfusion injury (IRI) is a very complex pathological process that is often associated with liver trauma and surgery, especially liver transplantation surgery. Although endoplasmic reticulum stress (ERS) plays a role in this process, the posttranscriptional regulators and the underlying mechanisms are still unclear. Here, we report that the lncRNA AK054386 was increased in hepatic IRI models. Furthermore, AK054386 can act as a “competing endogenous RNA (ceRNA)” and regulate ERS-related factors by binding and sequestering miR-199, which was shown to inhibit ERS in our previous report. Increased expression of AK054386, which might be mediated by activated NF-κB, resulted in sustained ERS and increased cell apoptosis and death in hepatic IRI mouse and cellular models. In contrast, AK054386 inhibition had protective effects on these models. Our data indicate that AK054386 and miR-199 are critical players in hepatic IRI, and we broadened the scope regarding ceRNA mechanisms. We hope that our results will improve the understanding of hepatic IRI and may provide potential therapeutic targets.
Mensuração da fidelidade de intervenções em saúde mental baseadas na escola
Authors: Garcia Douglas , Schneider Daniela Ribeiro , Cruz Roberto Moraes
Published: November 2019

Objetivo: caracterizar a mensuração da fidelidade de intervenções em saúde mental em crianças de escolas do ensino fundamental primário. Os dados foram levantados nas bases de dados ERIC, LILACS, APA, PubMed, Scopus, SciELO e Web of Science. Foram incluídos 45 artigos empíricos, publicados entre 2007 e 2016, os quais foram analisados em relação a categorias definidas previamente. Os resultados indicam variações na definição, dimensionalidade e forma de mensuração da fidelidade, havendo poucos indicadores de validade e precisão dos instrumentos, o que pode enviesar a avaliação do processo de implementação e a validade interna dos resultados das intervenções.