bluuebunny/crossref_metadata_2025 huggingface dataset:
Long work hours of mothers and fathers are linked to increased risk for overweight and obesity among preschool children: longitudinal evidence from Germany
Authors: Li Jianghong , Kaiser Till , Pollmann-Schult Matthias , Strazdins Lyndall
Published: May 2019

Background

Most existing studies on maternal employment and childhood overweight/obesity are from the USA. They are predominantly cross-sectional and show a consistent linear association between the two. Less is known about the joint impact of fathers’ and mothers’ work hours on childhood overweight and obesity.

Objectives

To examine the impact of maternal and paternal work hours on overweight/obesity among children aged 1–6 years in Germany using longitudinal data.

Methods

Child body weight and height and their parents’ work hours were collected for 2413 children at ages 0–1, ages 2–3 and ages 5–6. Overweight and obesity was defined using the body mass index percentiles based on the Cole LMS-Method. Random effects model was conducted, adjusting for demographic, socioeconomic and health characteristics of parents and children.

Results

Compared with non-employment, when mothers worked 35 or more hours per week, the risk for child overweight and obesity increased among preschool children. When fathers worked 55 or more hours per week, this effect was strengthened and maternal part-time hours (24–34 per week) also became a risk for child overweight and obesity. The effect was mainly found in high-income families.

Conclusions

Both mothers’ and fathers’ long work hours matter to young children’s overweight status. Employment protection and work time regulation for both working parents during the first 6 years of the child’s life should be considered in future policy.
Cell of origin in diffuse large B-cell lymphoma in systemic lupus erythematosus: molecular and clinical factors associated with survival
Authors: Tessier-Cloutier Basile , Twa David DW , Baecklund Eva , Gascoyne Randy , Johnson Nathalie A , Backlin Carin , Kamen Diane L , Clarke Ann E , Ramsey-Goldman Rosalind , Lee Jennifer LF , Farinha Pedro , Bernatsky Sasha
Published: May 2019

Background

SLE is associated with increased risk of diffuse large B-cell lymphoma (DLBCL). DLBCL is routinely classified by cell of origin (COO), with germinal centre B-cell (GCB) being more common and indicating better prognosis in the general population. We studied COO subtyping in patients with SLE diagnosed with DLBCL and their survival.

Patients and methods

We evaluated 20 cases of SLE with DLBCL. Immunohistochemistry analysis was performed (BCL2, MYC, BCL6, CD10, CD20, FOXP1, GCET1, MUM1) in tissue microarrays. We examined associations between molecular and clinical features, including overall survival.

Results

Of the 20 DLBCL SLE cases, 12/20 cases (60%) were classified as non-GCB using Hans or Choi algorithms. MYC and BCL2 protein expression was positive in 6/20 (30%) and 8/20 (40%) SLE cases, respectively, with 2/20 (10%) co-expressing both markers. Seven (7/20) had only extranodal involvement at DLBCL diagnosis. As expected, non-GCB cases had worse survival. Cases presenting exclusively with extranodal disease were associated with shorter SLE duration and better survival despite higher BCL2 protein expression.

Conclusions

We present novel data characterising DLBCL in SLE. Sixty per cent of the DLBCL in patients with SLE were non-GCB. The nodal and extranodal distribution in SLE was similar to what is known in the general population, but extranodal disease occurred more often with short SLE duration and was associated with longer overall survival. More research on cancer in SLE is the key to further understanding the complex interplay between cancer and the immune system.
Are there bidirectional relationships between psychosocial work characteristics and depressive symptoms? A fixed effects analysis of Swedish national panel survey data
Authors: Åhlin Julia K , LaMontagne Anthony D , Magnusson Hanson Linda L
Published: May 2019

Objectives

Psychosocial work characteristics have been prospectively associated with depressive symptoms. However, methodological limitations have raised questions regarding causality. It is also unclear to what extent depressive symptoms affect the experience of the psychosocial work environment. We examined contemporaneous (measured simultaneously) and lagged bidirectional relationships between psychosocial work characteristics and depressive symptoms, simultaneously controlling for time-stable individual characteristics.

Methods

We included 3947 subjects in the Swedish Longitudinal Occupational Survey of Health (SLOSH), with self-reported job demands, control, social support, work efforts, rewards, procedural justice and depressive symptoms in four waves 2010–2016. We applied dynamic panel models with fixed effects, using structural equation modelling, adjusting for all time-stable individual characteristics such as personality and pre-employment factors.

Results

Higher levels of job demands, job demands in relation to control, work efforts and efforts in relation to rewards were contemporaneously associated with more depressive symptoms (standardised β: 0.18–0.25, p<0.001), while higher levels of workplace social support, rewards at work and procedural justice were associated with less depressive symptoms (β: −0.18, p<0.001,β: –0.16, p<0.001 and β: −0.09, p<0.01, respectively). In contrast, only work efforts predicted higher levels of depressive symptoms 2 years later (β: 0.05, p<0.05). No other lagged associations were found in any direction.

Conclusions

After controlling for all time-invariant confounding, our results suggest that psychosocial work characteristics predominantly affect depressive symptoms immediately or with only a short time lag. Furthermore, we found no evidence of reverse causation. This indicates short-term causal associations, although the temporal precedence of psychosocial work characteristics remains uncertain.
High-Dimensional Least-Squares with Perfect Positive Correlation
Authors: Huang Zhiyong , Luo Ziyan , Xiu Naihua
Published: May 2019

The least-squares is a common and important method in linear regression. However, it often leads to overfitting phenomenon as dealing with high-dimensional problems, and various regularization schemes regarding prior information for specific problems are studied to make up such a deficiency. In the sense of Kendall’s [Formula: see text] from the community of nonparametric analysis, we establish a new model wherein the ordinary least-squares is equipped with perfect positive correlation constraint, sought to maintain the concordance of the rankings of the observations and the systematic components. By sorting the observations into an ascending order, we reduce the perfect positive correlation constraint into a linear inequality system. The resulting linearly constrained least-squares problem together with its dual problem is shown to be solvable. In particular, we introduce a mild assumption on the observations and the measurement matrix which rules out the zero vector from the optimal solution set. This indicates that our proposed model is statistically meaningful. To handle large-scale instances, we propose an efficient alternating direction method of multipliers (ADMM) to solve the proposed model from the dual perspective. The effectiveness of our model compared to ordinary least-squares is evaluated in terms of rank correlation coefficient between outputs and the systematic components, and the efficiency of our dual algorithm is demonstrated with the comparison to three efficient solvers via CVX in terms of computation time, solution accuracy and rank correlation coefficient.
12C isotope in relativistic cluster model
Authors: Roshanbakht N. , Shojaei M. R.
Published: May 2019

12C isotope composing 3[Formula: see text] cluster was investigated in this study. Therefore, 12C can be considered as a 3-body system. For studying the interactions in 3[Formula: see text] clusters, a central potential was applied. Jacobi relative coordinates were also employed and center of mass motion was removed. In this paper, the Klein–Gordon (K–G) equation was solved using Nikiforov–Uvarov potential. At the end, the energy spectrum and wave function of isotope 12C were determined and the results were compared with the experimental data which showed good coincidence reflecting the success of our model in prediction.
A DFT mechanistic and kinetic study on the reaction of phloroglucinol with •OH in different media: Hydrogen atom transfer versus oxidation
Authors: Otukile Kgalaletso P. , Kabanda Mwadham M.
Published: May 2019

A theoretical study on the reaction of phloroglucinol with •OH has been performed with the aim of elucidating the geometric, energetic and kinetic properties of the reaction as well as identifying the preferred reaction pathway. Three reaction mechanisms have been considered, namely, direct hydrogen atom abstraction, addition–elimination mechanism in the absence and in the presence of a base catalyst and oxidation mechanism in the absence and in the presence of O2. The study has been performed using the DFT/M06[Formula: see text]2X, DFT/BHHLYP and DFT/MPW1K methods in conjunction with either the 6-31++G(d,p) or the 6-311++G(3df,2p) basis set. The energetic parameters are influenced by the type of function utilized and the media in which the calculation is done. The direct hydrogen abstraction mechanism provides the smallest branching ratio with respect to the •OH addition mechanisms. The PG + •OH reaction under atmospheric conditions saturated with O2 would predominantly form tetrahydroxybenzene; the predominant product within the biological system would largely depend on physiological conditions; under pH [Formula: see text] 7 and with oxygen dissolved within the biological system, the preferred product would be tetrahydroxybenzene; however, if the reaction takes place in some part of the biological system where the pH [Formula: see text] 7, the preferred product would be the phenoxyl radical.
Seismic Control Strategy of a Multi-Story Subway Station Based on Probability Density Evolution Method
Authors: Liu Z. Q. , Chen Z. Y.
Published: May 2019

The method to protect the whole station structure by installing flexible devices at the column end has been proved to be effective in typical station structures. However, the damping effects and application of this method to multi-story subway station structures still need further study. In this paper, a stochastic analysis method, probability density evolution method (PDEM), is adopted to estimate the damping effect of a four-story subway station structure with lead rubber bearings (LRBs) installed in the central column. Stochastic analysis results show that the internal forces and plastic energy dissipation of columns installed LRBs are greatly reduced and the reliability is improved. Internal forces and plastic energy dissipation of columns without the installation of LRBs increase and the reliability decrease. There is little difference in structural deformation and plastic energy dissipation of structural components when LRB is installed in the middle of the column or at the column ends. When LRBs are installed only in some of the stories, the overall reliability of the structure is lower than that of the structure without LRB. When LRBs are installed in the columns of all stories, the structural reliability is higher than that of the structure without LRB. Based on the above results, to obtain better seismic control effect by installing LRBs, the multi-story subway station structure should be installed with LRBs in the columns of all stories, and LRBs can be installed at the upper, middle and lower end of the columns.
Force Reconstruction for Uncertain Structure Based on Interval Model and Second-Order Perturbation Theory
Authors: Li Xiaowang , Zhao Haitao , Huang Jiping , Chen Ji’an
Published: May 2019

In order to reconstruct the upper and lower bounds of dynamic excitations applied on the uncertain structure, an algorithm based on interval model and second-order perturbation theory is presented in this paper. First, interval model is built up by expressing the uncertain parameters of structure in interval form. Next according to second-order perturbation theory, structure characteristic matrices and input force vector are approximated as second-order Taylor polynomial expansion at the midpoint of uncertain parameters. After that the input force’s midpoint, first-order and second-order partial derivatives are respectively calculated by existing step-by-step integration method. Then addition and subtraction of the three components obtained in previous step are operated. Ultimately the upper and lower bounds of dynamic load can be identified. Numerical simulation results demonstrate this method is with the characteristic of high efficiency and precision. In addition, it is able to remain a relatively strong robustness under noise turbulence.
FEA-AI and AI-AI: Two-Way Deepnets for Real-Time Computations for Both Forward and Inverse Mechanics Problems
Authors: Liu G. R.
Published: May 2019

Recent breakthroughs in deep-learning algorithms enable dreams of artificial intelligence (AI) getting close to reality. AI-based technologies are now being developed rapidly, including service and industrial robots, autonomous and self-driving vehicles. This work proposes Two-Way Deepnets (TW-Deepnets) trained using the physics-law-based models such as finite element method (FEM), smoothed FEM (S-FEM), and meshfree models, for real-time computations of both forward and inverse mechanics problems of materials and structures. First, unique features of physics-law-based models and data-based models are analyzed in theory. The training characteristics of deepnets for forward problems governed by physics-laws are then investigated, when an FEM (or S-FEM) model is used as the trainer. The training convergence rates of such an FEM-AI model are examined in relation to the property of the system matrix of the FEM model for deepnets. Next, a study on the training characteristics of deepnets for inverse problems, when the forward FEM-trained AI Deepnets are used as the trainer to train an AI model for inverse analyses. Next, a discussion is conducted on the roles of regularization techniques to overcome the ill-posedness of inverse problems in deepnet structures for noisy data. Finally, TW-Deepnets (FEM-AI and AI-AI models) are presented for real-time analyses of both forward and inverse problems of materials and structures with high-dimensional parameter space. The major finding of this study is as follows: (1) The understandings on the fundamental features of both data-based and physics-based methods is critical for creations of novel game-changing computational methods, which take advantages of both types of methods; (2) The good property of the system matrix of FEM allows effective training of FEM-AI deepnets for forward mechanics problems; (3) Our new technique to training inverse deepnets using FEM-AI deepnets as a surrogate model offers an innovative means, to effectively train deepnets for solving inverse mechanics problems; (4) The TW-Deepnets is capable of performing real-time analysis of both forward and inverse problems of materials and structures with high-dimensional parameter spaces; (5) Such TW-Deepnets can be easily utilized by the mass: a transformative new concept of AI-enabling democratization of complicated computational technology in modeling and simulation.
A new characterization for classical Bernoulli–Euler elastic curves in Rn
Authors: Altin Ayşe
Published: May 2019

In this paper, we show that the velocity vector field of classical Bernoulli–Euler elastic curve is harmonic in [Formula: see text] space. We propose a new characterization for classical Bernoulli–Euler elastic curves and plot graphs of examples that satisfy this characterization.
Investigation of solvation and solvent coordination effects in iron porphyrin nitrosyls by infrared spectroelectrochemistry and DFT calculations
Authors: Rahman Md. Hafizur , Ryan Michael D.
Published: May 2019

Visible and infrared spectroelectrochemistry of Fe(OEPone)(NO) (H2OEPone = octaethylporphinone) were examined in methylene chloride and THF. The visible spectra of Fe(OEPone)(NO) were similar in both solvents. Unlike other ferrous porphyrin nitrosyls, a six-coordinate complex was formed with THF as a ligand. This led to two nitrosyl bands in the infrared spectrum. The absorbance of these bands depended on the concentration of THF in the solution. Solvation and coordination effects on the carbonyl and nitrosyl bands were observed for both the nitrosyl and reduced-nitrosyl complexes. DFT calculations were carried out to interpret the spectral changes.

Marquette University, Raynor Memorial Libraries, Chemistry Research Data: https://epublications.marquette.edu/chem_data/1/
Cobalt phthalocyanine-TiO2 nanocomposites for photocatalytic remediation of textile dyes under visible light irradiation
Authors: Dindaş Gizem Başaran , Şahin Zeynel , Cengiz Yatmaz H. , İşci Ümit
Published: May 2019

CoPc(COOH)[Formula: see text]-TiO[Formula: see text] nanocomposites to be used as efficient visible light photocatalysts were obtained by modifying TiO2 nanoparticles with cobalt(II) tetracarboxyphthalocyanine (CoPc(COOH)[Formula: see text]). The photocatalyst was then characterized by ultra-violet diffuse reflectance spectroscopy (UV-DRS), Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). The UV-DRS spectra showed that the absorbance spectrum of the modified catalyst was shifted to the visible region. Different textile dye solutions of Reactive Red 180, Acid Red 88 and Direct Orange 46 were efficiently degraded under visible light. Color removal rates were established to be 30%, 53% and 47% after 180 min for RR180, AR88 and DO46 dyes, respectively. The optimum catalyst concentration was determined to be 1 g/L of CoPc(COOH)[Formula: see text]-TiO[Formula: see text]. Development of the CoPc(COOH)[Formula: see text]-TiO[Formula: see text] nanocomposite photocatalyst enabled the utilization of visible light irradiation for efficient photodegradation of organic textile dye solutions.
Photocatalytic degradation of ofloxacin by ZnO/CsxWO3composite synthesized by two-step method: A kinetic study
Authors: Ning Wenwen , Zhao Zhihuan , Chang Honghong , Gu Zhanyong , Zhang Bing , Yin Shu , Fan Jimin
Published: May 2019

The composite of ZnO/CsxWO3with heterojunction was prepared by a two-step solvothermal method and the degradation of ofloxacin solution under full-spectrum light irradiation was carried out to evaluate the performance. The composites were characterized by XRD, SEM, EDS and UV-Vis-NIR reflectance. The result shows that the prepared composite has an ideal optical absorption in the spectral region of 200–2500[Formula: see text]nm and higher photocatalytic performance compared with ZnO and CsxWO3. Moreover, [Formula: see text], [Formula: see text]OH and [Formula: see text][Formula: see text] radicals are determined to be the active species. It is suggested that the heterojunction between ZnO and CsxWO3for ZnO/CsxWO3composite is important for improving the charge separation and thus restraining the recombination of photogenerated electrons and holes. Photodegradation of ofloxacin catalyzed by ZnO/CsxWO3followed the first-order kinetics and the degradation rate of ZnO/2CsxWO3was about two times higher than those of CsxWO3and ZnO.
Architectural Modeling for Managing Risks in Forming an Alliance
Authors: Cook Matthew , Mo John P. T.
Published: May 2019

Many large and highly complex engineering projects present enormous technical and financial risks to organizations. This is especially true in the defence industry where budgets can potentially run into billions and the project lifecycle may extend over many years. In frequent cases, such projects are too much for a single organization to undertake. One option that is becoming ubiquitous across contemporary defence projects is to spread the risk by forming an alliance between several organizations. Unfortunately, forming an alliance between potentially competing organizations brings its own set of challenges and risks. The operating conditions of the business environment are characterized by frequent changes in products, services, processes, organizations, markets, supply and distribution networks. The partners need to work together as an entity to achieve a goal but the relationships within the alliance are often disrupted by the established practices, culture and motivation of the individual companies. This paper starts by examining how risks can essentially multiply when an alliance is formed and what potential impacts these risks have on project success. A novel 3PE method for modeling the structure of an alliance with the three elements being product, people, process, and their interactions is proposed within an alliance environment. This methodology is then used to calculate the increase in interactions between the 3Ps with the introduction of more organizations to the alliance. By examining each of the elements and their interactions, risks are identified, and the key drivers are exposed. Finally, a case study is presented that illustrates how the architectural model can be used to estimate the probability of failure of the alliance.
Family Instability in the Lives of American Children
Authors: Cavanagh Shannon E. , Fomby Paula
Published: May 2019

Scholars have long looked to family composition to understand child well-being. The study of family instability, or the experience of repeated changes in parents’ union status during childhood, represents a recent advance in this field that takes into account the dynamic nature of contemporary family organization and considers its implications for children's adjustment and development. We review some of the structural and cultural factors that have contributed to rising levels of family instability and highlight the emergence of national data to measure it. We then review the perspective that guides much of the scholarship on family instability and critically assess the contributions of this work to the understanding of child well-being. We close by suggesting new directions for research, with a call for work that broadens the conceptualization and measurement of contemporary children's family systems and home environments as well as the mechanisms that explain why—or whether—instability matters.
Aging Populations, Mortality, and Life Expectancy
Authors: Crimmins Eileen M. , Zhang Yuan S.
Published: May 2019

Life expectancy has long been seen as an indicator of the quality of life as well as the health of a population. Recent trends in US life expectancy show growing inequality in life expectancy for some socioeconomic and geographic groupings but diminishing inequality by race and gender. For example, while African Americans had gains in life expectancy, non-Hispanic white women with low levels of education experienced drops. Overall, the United States continues to fall behind other countries in terms of life expectancy. One reason is our growing mortality in midlife from so-called deaths of despair. Public health programs cannot eliminate these adverse trends if they are not also accompanied by social policies supporting economic opportunity for US families.
Solar powered monitoring system development for smart farming and Internet of Thing applications
Authors: chung wen-yaw
Published: May 2019

This paper is mainly aimed to develop a solar powered hand-held monitoring system for real-time crop-growth multiple environment parameter sensing and ZigBee-based wireless data transmission for Internet of Thing (IoT) applications. The proposed solar powered system successfully built a Wireless Sensor Network (WSN) for quality agriculture application by using the ZigBee technology standard and TI’s CC2530 chip. Commercially available sensors were utilized specifically for temperature, humidity, soil moisture, light, chlorophyll, and CO2 monitoring. With the consideration and advantages of low power, low cost and multi-node capabilities, we chose ZigBee-based wireless network to transmit data into the cloud system for further data processing and analysis. When the sensors and Zigbee transmission system are set up, the data obtained through the human machine interface on the host will be sent to the cloud database established by MySQL in XAMPP. The management and data storage of the cloud database are both processed under the phpMyAdmin system. In addition, we use another program in XAMPP - Apache HTTP Server to set up the php website. Finally, this database of the sensing information will be used for assessment and evaluation of the environmental condition, data log recording, risk management and decision making. These resources can feed back to farmer’s cell phones through a decision support system. The experimental design and field test were verified in Tai-Yuan Organic farm located in Tao-Yuan County, Taiwan. The system will have a potential to be deployed into an open-field or green-house based farm to improve the optimized crop cultivation and increase the harvest yield.
Generation of Water Waves Using Momentum Source Wave‐Maker Applied to a RANS Solver
Authors: Feng Xing , Wu Wanqing
Published: May 2019

Nowadays, as the development of Computational Fluid Dynamics (CFD) and the numerical wave tank (NWT) has advanced, numerical analysis has become increasingly useful and powerful for the ship designing and ship hydrodynamics. In this study, a momentum source wave‐maker and an analytical relaxation wave absorber were embedded into 2D RANS equation model with RSM turbulence closure scheme to establish the NWT for ship designing and hydrodynamics. The VOF (volume‐of‐fluid) method was applied to accurately capture the water free surface. The body force‐weighted scheme is chosen for pressure interpolation and the second order upwind scheme for discretization of the momentum equation. In order to calculate convection and diffusion fluxes through the control volume faces, PISO algorithm is adopted for pressure‐velocity coupling. The momentum source function for wave generation and the analytical relaxation function for wave absorption were deduced for constructing the NWT (numerical wave tank). The proposed NWT was then validated by the laboratory measurements of Umeyama and the analytical solution, indicating that the constructed NWT is effective and accurate.
Stroke Induces a BDNF-Dependent Improvement in Cognitive Flexibility in Aged Mice
Authors: Houlton Josh , Zhou Lisa Y. Y. , Barwick Deanna , Gowing Emma K. , Clarkson Andrew N.
Published: May 2019

Stroke remains a leading cause of disability worldwide. Recently, we have established an animal model of stroke that results in delayed impairment in spatial memory, allowing us to better investigate cognitive deficits. Young and aged brains show different recovery profiles after stroke; therefore, we assessed aged-related differences in poststroke cognition. As neurotrophic support diminishes with age, we also investigated the involvement of brain-derived neurotrophic factor (BDNF) in these differences. Young (3-6 months old) and aged (16-21 months old) mice were trained in operant touchscreen chambers to complete a visual pairwise discrimination (VD) task. Stroke or sham surgery was induced using the photothrombotic model to induce a bilateral prefrontal cortex stroke. Five days poststroke, an additional cohort of aged stroke animals were treated with intracerebral hydrogels loaded with the BDNF decoy, TrkB-Fc. Following treatment, animals underwent the reversal and rereversal task to identify stroke-induced cognitive deficits at days 17 and 37 poststroke, respectively. Assessment of sham animals using Cox regression and log-rank analyses showed aged mice exhibit an increased impairment on VD reversal and rereversal learning compared to young controls. Stroke to young mice revealed no impairment on either task. In contrast, stroke to aged mice facilitated a significant improvement in reversal learning, which was dampened in the presence of the BDNF decoy, TrkB-Fc. In addition, aged stroke control animals required significantly less consecutive days and correction trials to master the reversal task, relative to aged shams, an effect dampened by TrkB-Fc. Our findings support age-related differences in recovery of cognitive function after stroke. Interestingly, aged stroke animals outperformed their sham counterparts, suggesting reopening of a critical window for recovery that is being mediated by BDNF.
Long Noncoding RNA H19 Participates in the Regulation of Adipose-Derived Stem Cells Cartilage Differentiation
Authors: Pang Hai-lin , Zhao Qian-qian , Ma Yu , Song Yong-li , Min Jie , Lu Jian-rong , Li Hang , Zhao Da-qing
Published: May 2019

Adipose-derived stem cells (ADSCs) are multipotent and have received increasing attention for their applications in medicine. Cell-based therapies are optimal for diseases with loss or damage to tissues or organs. ADSCs and bone marrow mesenchymal stem cells (BMSCs) can differentiate into many cell lineages. Because of their advantages in accessibility and volume, ADSCs are regarded as a desirable alternative to BMSCs. In this study, we focused on the chondrocytic differentiation potential of ADSCs and the underlying mechanism. We found that the long noncoding RNA H19 plays an important role in this process. Overexpression of H19 in ADSCs induced differentiation towards chondrocytes. H19 is abundantly expressed during embryonic development and downregulated after birth, implying its regulatory role in determining cell fate. However, in our experiments, H19 exerted its regulatory function during cartilage differentiation of ADSCs through competing miRNA regulation of STAT2.
p53-Mediated PI3K/AKT/mTOR Pathway Played a Role in PtoxDpt-Induced EMT Inhibition in Liver Cancer Cell Lines
Authors: Li Yongli , Wang Tingting , Sun Yanjie , Huang Tengfei , Li Cuiping , Fu Yun , Li Yichun , Li Changzheng
Published: May 2019

Epithelial-mesenchymal transition (EMT) involves metastasis and drug resistance; thus, a new EMT reversing agent is required. It has shown that wild-type p53 can reverse EMT back to epithelial characteristics, and iron chelator acting as a p53 inducer has been demonstrated. Moreover, recent study revealed that etoposide could also inhibit EMT. Therefore, combination of etoposide with iron chelator might achieve better inhibition of EMT. To this end, we prepared di-2-pyridineketone hydrazone dithiocarbamate S-propionate podophyllotoxin ester (PtoxDpt) that combined the podophyllotoxin (Ptox) structural unit (etoposide) with the dithiocarbamate unit (iron chelator) through the hybridization strategy. The resulting PtoxDpt inherited characteristics from parent structural units, acting as both the p53 inducer and topoisomerase II inhibitor. In addition, the PtoxDpt exhibited significant inhibition in migration and invasion, which correlated with downregulation of matrix metalloproteinase (MMP). More importantly, PtoxDpt could inhibit EMT in the absence or presence of TGF-β1, concomitant to the ROS production, and the additional evidence revealed that PtoxDpt downregulated AKT/mTOR through upregulation of p53, indicating that PtoxDpt induced EMT inhibition through the p53/PI3K/AKT/mTOR pathway.
NFE2L3 Inhibition Induces Cell Cycle Arrest at the G0/G1 Phase in Colorectal Cancer Cells through Downregulating CCND1 and pRb1-ser807/811
Authors: Zhang Lihua , Hu Dong-Li , Tang Baiyou , Cheng Yu , Jiao Chuan , Cheng Lin , Tan Zhi-Rong , Zhou Hong-Hao
Published: May 2019

The molecular mechanism for colorectal cancer to develop remains unelucidated. To find biomarkers related to colorectal cancer development, we analyzed the gene expression profile of 380 colorectal cancer patients and 51 healthy controls by R software. Finally, 1579 upregulated differential expression genes (DEGs) and 3218 downregulated DEGs were identified. Then, the top 20 upregulated DEGs were compared with 181 upregulated DEGs that we reported previously, and 11 overlapped DEGs were found. NFE2L3 (nuclear factor, erythroid 2-like 3) was among those overlapped DEGs and was rarely reported in colorectal cancer. Real-time polymerase chain reaction (PCR) results showed that higher NFE2L3 expression levels were identified in paired tumor samples than in paratumor samples (48 paired samples). Flow cytometry analysis revealed that the cell cycle was arrested at the G0/G1 phase after inhibition of NFE2L3 in both HCT116 and SW480 cell lines. Western blot detection showed that CCND1 and phosphorylated Rb transcriptional corepressor 1 at ser-807/811 (pRb1-ser807/811) expression levels were downregulated when NFE2L3 was inhibited in those two cell lines. A significant positive correlation was observed between NFE2L3 and CCND1 expression levels in colorectal tissue samples. These evidences indicate that downregulation of NFE2L3 induces cell cycle arrest at the G0/G1 phase through downregulation of CCND1 and pRb1-ser807/811.
Exploring Spatiotemporal Complexity of a Predator‐Prey System with Migration and Diffusion by a Three‐Chain Coupled Map Lattice
Authors: Huang Tousheng , Zhang Huayong , Cong Xuebing , Pan Ge , Zhang Xiumin , Liu Zhao
Published: May 2019

The topic of utilizing coupled map lattice to investigate complex spatiotemporal dynamics has attracted a lot of interest. For exploring the spatiotemporal complexity of a predator‐prey system with migration and diffusion, a new three‐chain coupled map lattice model is developed in this research. Based on Turing instability analysis, pattern formation conditions for the predator‐prey system are derived. Via numerical simulation, rich Turing patterns are found with subtle self‐organized structures under diffusion‐driven and migration‐driven mechanisms. With the variation of migration rates, the predator‐prey system exhibits a gradual dynamical transition from diffusion‐driven patterns to migration‐driven patterns. Moreover, new results, the self‐organization of non‐Turing patterns, are also revealed. We find that even in the cases where the nonspatial predator‐prey system reaches collapse, the migration can still drive pattern self‐organization. These non‐Turing patterns suggest many new possible ways for the coexistence of predator and prey in space, under the effects of migration and diffusion.
Personalized Movie Summarization Using Deep CNN‐Assisted Facial Expression Recognition
Authors: Ul Haq Ijaz , Ullah Amin , Muhammad Khan , Lee Mi Young , Baik Sung Wook
Published: May 2019

Personalized movie summarization is demand of the current era due to an exponential growth in movies production. The employed methods for movies summarization fail to satisfy the user’s requirements due to the subjective nature of movies data. Therefore, in this paper, we present a user‐preference based movie summarization scheme. First, we segmented movie into shots using a novel entropy‐based shots segmentation mechanism. Next, temporal saliency of shots is computed, resulting in highly salient shots in which character faces are detected. The resultant shots are then forward propagated to our trained deep CNN model for facial expression recognition (FER) to analyze the emotional state of the characters. The final summary is generated based on user‐preferred emotional moments from the seven emotions, i.e., afraid, angry, disgust, happy, neutral, sad, and surprise. The subjective evaluation over five Hollywood movies proves the effectiveness of our proposed scheme in terms of user satisfaction. Furthermore, the objective evaluation verifies the superiority of the proposed scheme over state‐of‐the‐art movie summarization methods.
Metabolic and Epigenetic Action Mechanisms of Antidiabetic Medicinal Plants
Authors: Shanak Siba , Saad Bashar , Zaid Hilal
Published: May 2019

Diabetes is a predominant metabolic disease nowadays due to the off-beam lifestyle of diet and reduced physical activity. Complications of the illness include the gene-environment interactions and the downstream genetic and epigenetic consequences, e.g., cardiovascular diseases, tumor progression, retinopathy, nephropathy, neuropathy, polydipsia, polyphagia, polyuria, and weight loss. This review sheds the light on the mechanistic insights of antidiabetic medicinal plants in targeting key organs and tissues involved in regulating blood glucose homeostasis including the pancreas, liver, muscles, adipose tissues, and glucose absorption in the intestine. Diabetes is also involved in modulating major epigenetic pathways such as DNA methylation and histone modification. In this respect, we will discuss the phytochemicals as current and future epigenetic drugs in the treatment of diabetes. In addition, several proteins are common targets for the treatment of diabetes. Some phytochemicals are expected to directly interact with these targets. We lastly uncover modeling studies that predict such plausible interactions. In conclusion, this review article presents the mechanistic insight of phytochemicals in the treatment of diabetes by combining both the cellular systems biology and molecular modeling.
Online Monitoring Technique of Power Condition for Inverter‐Fed Motor Driven Hydraulic System
Authors: Gu Lichen , Shi Yuan
Published: May 2019

As a new type of global energy‐saving transmission mode, frequency conversion hydraulic drive system has been widely used. Since hydraulic systems become more complex and transfer more power, operating accidents often occur unexpectedly. Therefore, online monitoring of the running state of the hydraulic system is significant during its long‐term operation. The pressure, flow, and vibration signals obtained by traditional monitoring methods are nonstationary and susceptible to disturbance. In order to solve this problem, a method of monitoring power condition of the motor driven hydraulic system based on input voltage and current of the motor is proposed. The present study uses the amplitude and phase information of the voltage and current signals on the stator side of the AC motor to form a dynamic power circle graph and extracts feature information from the graph to monitor the power state and its dynamic change process of the hydraulic system. Results obtained from experiments conducted under different frequencies and loads indicate that the proposed method can realize the online monitoring successfully and effectively. Furthermore, the method has another advantage of monitoring the dynamic power change process of the hydraulic drive system and the power matching process between the motor and the system load condition in a visualized way.
Advances in Tumor-Stroma Interactions: Emerging Role of Cytokine Network in Colorectal and Pancreatic Cancer
Authors: Bazzichetto Chiara , Conciatori Fabiana , Falcone Italia , Cognetti Francesco , Milella Michele , Ciuffreda Ludovica
Published: May 2019

Cytokines are a family of soluble factors (Growth Factors (GFs), chemokines, angiogenic factors, and interferons), which regulate a wide range of mechanisms in both physiological and pathological conditions, such as tumor cell growth and progression, angiogenesis, and metastasis. In recent years, the growing interest in developing new cancer targeted therapies has been accompanied by the effort to characterize Tumor Microenvironment (TME) and Tumor-Stroma Interactions (TSI). The connection between tumor and stroma is now well established and, in the last decade, evidence from genetic, pharmacological, and epidemiological data supported the importance of microenvironment in tumor progression. However, several of the mechanisms behind TSI and their implication in tumor progression remain still unclear and it is crucial to establish their potential in determining pharmacological response. Many studies have demonstrated that cytokines network can profoundly affect TME, thus displaying potential therapeutic efficacy in both preclinical and clinical models. The goal of this review is to give an overview of the most relevant cytokines involved in colorectal and pancreatic cancer progression and their implication in drug response.
Real-Time Mobile Emotional Content Player Using Smartphone Camera-Based PPG Measurement
Authors: Lee Haena , Kim Dong Keun
Published: May 2019

A real-time mobile content player was developed that can recognize and reflect emotions in real time using a smartphone. To determine effective awareness, a photoplethysmogram (PPG), which is a biological signal, was measured to recognize emotional changes in users presented with content intended to induce an emotional response. To avoid the need for a separate sensor to measure the PPG, PPG signals were extracted from the red (R) values of images acquired by the rear camera of a smartphone. To reflect an emotion, the saturation (S) and brightness (V) levels, which are related to the ambience of a content, are changed to reflect the emotional changes of the user within the content itself in real time. Arousal- and relaxation-inducing scenarios were conducted to validate the effectiveness. The samplet-test results show that the average peak-to-peak interval (PPI), which is the time interval between the peaks of PPG signals, was significantly low when viewing the content under the arousal-inducing scenario as compared to when watching regular content, and it was determined that the emotion of the user was led to a state of arousal. Ten university students (five males and five females) participated in the experiment. The users had no cardiac disease and were asked not to drink or smoke before the experiment. The average PPI was significantly higher when the content was viewed in the relaxation-inducing scenario compared to regular content, and it was determined that the emotion of the user was induced to a state of relaxation. The designed emotional content player was confirmed to be an interactive system, in which the video content and user concurrently affect each other through the system.
Periodontitis and Rheumatoid Arthritis: The Same Inflammatory Mediators?
Authors: Ceccarelli Fulvia , Saccucci Matteo , Di Carlo Gabriele , Lucchetti Ramona , Pilloni Andrea , Pranno Nicola , Luzzi Valeria , Valesini Guido , Polimeni Antonella
Published: May 2019

The strict link between periodontitis (PD) and rheumatoid arthritis (RA) has been widely demonstrated by several studies. PD is significantly more frequent in RA patients in comparison with healthy subjects: this prevalence is higher in individuals at the earliest stages of disease and in seropositive patients. This is probably related to the role ofP. gingivalisin inducing citrullination and leading to the development of the new antigens. Despite the many studies conducted on this topic, there is very little data available concerning the possibility to use the same biomarkers to evaluate both RA and PD patients. The aim of the review is to summarize this issue. Starting from genetic factors, data from literature demonstrated the association between HLA-DRB1 alleles and PD susceptibility, similar to RA patients; moreover, SE-positive patients showed simultaneously structural damage to the wrist and periodontal sites. Contrasting results are available concerning other genetic polymorphisms. Moreover, the possible role of proinflammatory cytokines, such as TNF and IL6 and autoantibodies, specifically anticyclic citrullinated peptide antibodies, has been examined, suggesting the need to perform further studies to better define this issue.
Engineering of L-Plastin Peptide-Loaded Biodegradable Nanoparticles for Sustained Delivery and Suppression of Osteoclast Function In Vitro
Authors: Majumdar Sunipa , Wadajkar Aniket S. , Aljohani Hanan , Reynolds Mark A. , Kim Anthony J. , Chellaiah Meenakshi
Published: May 2019

We have recently demonstrated that a small molecular weight amino-terminal peptide of L-plastin (10 amino acids; “MARGSVSDEE”) suppressed the phosphorylation of endogenous L-plastin. Therefore, the formation of nascent sealing zones (NSZs) and bone resorption are reduced. The aim of this study was to develop a biodegradable and biocompatible PLGA nanocarrier that could be loaded with the L-plastin peptide of interest and determine the efficacy in vitro in osteoclast cultures. L-plastin MARGSVSDEE (P1) and scrambled control (P3) peptide-loaded PLGA-PEG nanoparticles (NP1 and NP3, respectively) were synthesized by double emulsion technique. The biological effect of nanoparticles on osteoclasts was evaluated by immunoprecipitation, immunoblotting, rhodamine-phalloidin staining of actin filaments, and pit forming assays. Physical characterization of well-dispersed NP1 and NP3 demonstrated ~130-150 nm size, < 0.07 polydispersity index, ~-3 mV ζ-potential, and a sustained release of the peptide for three weeks. Biological characterization in osteoclast cultures demonstrated the following: NP1 significantly reduced (a) endogenous L-plastin phosphorylation; (b) formation of NSZs and sealing rings; (c) resorption. However, the assembly of podosomes which are critical for cell adhesion was not affected. L-plastin peptide-loaded PLGA-PEG nanocarriers have promising potential for the treatment of diseases associated with bone loss. Future studies will use this sustained release of peptide strategy to systematically suppress osteoclast bone resorption activity in vivo in mouse models demonstrating bone loss.
Metabolism Is a Key Regulator of Induced Pluripotent Stem Cell Reprogramming
Authors: Spyrou James , Gardner David K. , Harvey Alexandra J.
Published: May 2019

Reprogramming to pluripotency involves drastic restructuring of both metabolism and the epigenome. However, induced pluripotent stem cells (iPSC) retain transcriptional memory, epigenetic memory, and metabolic memory from their somatic cells of origin and acquire aberrant characteristics distinct from either other pluripotent cells or parental cells, reflecting incomplete reprogramming. As a critical link between the microenvironment and regulation of the epigenome, nutrient availability likely plays a significant role in the retention of somatic cell memory by iPSC. Significantly, relative nutrient availability impacts iPSC reprogramming efficiency, epigenetic regulation and cell fate, and differentially alters their ability to respond to physiological stimuli. The significance of metabolites during the reprogramming process is central to further elucidating how iPSC retain somatic cell characteristics and optimising culture conditions to generate iPSC with physiological phenotypes to ensure their reliable use in basic research and clinical applications. This review serves to integrate studies on iPSC reprogramming, memory retention and metabolism, and identifies areas in which current knowledge is limited.
Power Spectral Density and Functional Connectivity Changes due to a Sensorimotor Neurofeedback Training: A Preliminary Study
Authors: Terrasa Juan L. , Alba Guzmán , Cifre Ignacio , Rey Beatriz , Montoya Pedro , Muñoz Miguel A.
Published: May 2019

Neurofeedback is a form of neuromodulation based on learning to modify some aspects of cortical activity. Sensorimotor rhythm (SMR) oscillation is one of the most used frequency bands in neurofeedback. Several studies have shown that subjects can learn to modulate SMR power to control output devices, but little is known about possible related changes in brain networks. The aim of this study was to investigate the enhanced performance and changes in EEG power spectral density at somatosensory cerebral areas due to a bidirectional modulation-based SMR neurofeedback training. Furthermore, we also analyzed the functional changes in somatosensory areas during resting state induced by the training as exploratory procedure. A six-session neurofeedback protocol based on learning to synchronize and desynchronize (modulate) the SMR was implemented. Moreover, half of the participants were enrolled in two functional magnetic resonance imaging resting-state sessions (before and after the training). At the end of the training, participants showed a successful performance enhancement, an increase in SMR power specific to somatosensory locations, and higher functional connectivity between areas associated with somatosensory activity in resting state. Our research increases the better understanding of the relation between EEG neuromodulation and functional changes and the use of SMR training in clinical practice.