Individual Variabilities in Adipose Stem Cell Proliferation,Gene Expression and Responses to Lipopolysaccharide Stimulation

Adipose stem cells (ASCs) are reported to play a role in normal physiology as well as in inflammation and disease. The objective of this work was to elucidate inter-individual differences in growth, gene expression and response to inflammatory stimuli in ASCs from different donors. Human ASC1 (male donor) and ASC2 (female donor) were purchased from Lonza (Walkersville, MD). Cell proliferation was determined by the sulforhodamine B assay. After time-dependent treatment of ASCs with or without bacterial lipopolysaccharide (LPS), marker gene mRNAs for proliferation, steroid hormones, and xenobiotic and immune pathways were determined using RT-PCR, and secreted cytokine levels in media were measured using the Bio-Plex cytokine assay kit. ASCs from both donors expressed androgen receptors but not estrogen receptors. ASC2 had a 2-fold higher proliferation rate and a 6-fold higher level of proliferation marker Ki67 mRNA than ASC1. ASC2 exhibited significantly greater fold induction of TNF-α and CCL2 by LPS compared to ASC1. TNF-α and GM-CSF protein levels were also significantly higher in the LPS-induced ASC2 media, but IL-6 secretion was higher in the LPS-induced ASC1 media. Our findings suggest that inter-individual variability and/or possible sex differences exist in ASCs, which may serve as a key determinant to inflammatory responses of ASCs.     

Effect of lactulose on biotransformation of isoflavone glycosides to aglycones in soymilk by lactobacilli

ABSTRACT:  Lactobacillus acidophilus 4461, L. acidophilus 4962, L. casei 290, and L. casei 2607 were used to hydrolyze isoflavone glycosides (IG) to biologically active forms—isoflavone aglycones (IA)—in soymilk (SM) prepared from soy protein isolate (SPI) and soymilk supplemented with 0.5% (w/v) of lactulose (SML). L. acidophilus 4461 utilized the highest level of lactulose (3.01 mg/mL) and L. acidophilus 4962 utilized the least (0.86 mg/mL) at 24 h of incubation. The pH values decreased to 4.00 to 5.00 in SML, while they remained relatively high (6.15 to 6.36) in SM. Supplementation with lactulose significantly ( P < 0.05) enhanced the viable counts of all the 4 Lactobacillus strains. At the end of incubation, the viable counts of Lactobacillus ranged from 8.08 to 8.25 log CFU/mL in SML compared to 6.99 to 7.11 log CFU/mL in SM. Supplementation with lactulose increased the biotransformation of IG to IA after 6 h of incubation. The presence of lactulose in the medium enhanced the biotransformation level of IG to IA by Lactobacillus up to 21.9%. The hydrolysis level of malonyl genistin and acetyl genistin in SML was much higher than in SM by all the 4 probiotic organisms. The biotransformation of IG to IA occurred rapidly during the 1st 12 h of incubation in both SML and SM. Among the 4 Lactobacillus strains, L. acidophilus 4461 biotransformed the highest level (88.8%) of IG to IA in SML compared to 68.2% in SM after 24 h of incubation.     

Influence of dynamic stimulation,visual perception and individual susceptibility to car sickness during controlled stop-and-go driving

Forschung im Ingenieurwesen - The enjoyment and usage of highly automated vehicles might be reduced by motion sickness. This study addresses the influencing factors of dynamic stimulation, visual...     

Photoresist coating methods for the integration of novel 3-D RF microstructures

This paper presents three coating methods of photoresist on large three-dimensional (3-D) topography surfaces. Two special methods, spray and electrodeposition (ED) are introduced and investigated for the fabrication of 3-D microstructures and RF-MEMS devices. Characteristics of each method as well as its advantage and disadvantages are outlined. A comparison is made to point out the most suitable coating method in terms of complexity, performance and type of application. The potential of these coating methods is demonstrated through several applications such as fabrication of multilevel micromachined structures and RF MEMS devices.     

Open dumping site in Asian developing countries: a potential source of polychlorinated dibenz-p-dioxins and polychlorinated dibenzofurans

Open landfill dumping areas for municipal wastes in Asian developing countries have recently received particular attention with regard to environmental pollution problems. Because of the uncontrolled burning of solid wastes, elevated contamination by various toxic chemicals including dioxins and related compounds in these dumping sites has been anticipated. In this study, concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), and coplanar polychlorinated biphenyls (PCBs) were determined in soils from dumping sites in the Philippines, Cambodia, India, and Vietnam. Residue concentrations of PCDD/Fs and coplanar PCBs in dumping site soils were apparently greater than those in soils collected in agricultural or urban areas far from dumping sites, suggesting that dumping sites are potential sources of PCDD/Fs and related compounds. Observed PCDD/F concentrations in soils from dumping sites in the Philippines and Cambodia were comparable or higher than those reported for dioxin-contaminated locations in the world (e.g., near the municipal waste incinerators and open landfill dumping sites). Homologue profiles of PCDD/Fs in dumping site soils from the Philippines and, to a lesser extent, from Cambodia and India reflected patterns of samples representing typical emissions, while profiles of agricultural or urban soils were similar to those of typical environmental sinks. This result suggests recent formation of PCDD/Fs in dumping site areas and that open dumping sites are a potential source of dioxins in Asian developing countries. Uncontrolled combustions of solid wastes by waste pickers, generation of methane gas, and low-temperature burning can be major factors for the formation of dioxins in dumping sites. Elevated fluxes of PCDD/Fs to soils in dumping sites were encountered in the Philippines, Cambodia, India, and Vietnam-Hanoi, and these levels were higher than those reported for other countries. Considerable loading rates of PCDD/Fs in the dumping sites of these countries were observed, ranging from 20 to 3900 mg/yr (0.12-35 mg TEQ/yr). PCDD/F concentrations in some soil samples from the Philippines, Cambodia, India, and Vietnam-Hanoi exceeded environmental guideline values, suggesting potential health effects on humans and wildlife living near these dumping sites. The estimated intakes of dioxins via soil ingestion and dermal exposure for children were higher than those for adults, suggesting greater risk of dioxin exposure for children in dumping sites. To our knowledge, this is the first comprehensive study on PCDD/Fs contamination in open dumping sites of Asian developing countries. On the basis of the result of this study, we have addressed a new environmental issue that open dumping sites are potential sources of PCDD/Fs and related compounds, and dioxin contamination in dumping sites may become a key environmental problem in developing countries.     

Applying Wide & Deep Learning Model for Android Malware Classification

Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model.     

Stock-Price Forecasting Based on XGBoost and LSTM

Using time-series data analysis for stock-price forecasting (SPF) is complex and challenging because many factors can influence stock prices (e.g., inflation, seasonality, economic policy, societal behaviors). Such factors can be analyzed over time for SPF. Machine learning and deep learning have been shown to obtain better forecasts of stock prices than traditional approaches. This study, therefore, proposed a method to enhance the performance of an SPF system based on advanced machine learning and deep learning approaches. First, we applied extreme gradient boosting as a feature-selection technique to extract important features from high-dimensional time-series data and remove redundant features. Then, we fed selected features into a deep long short-term memory (LSTM) network to forecast stock prices. The deep LSTM network was used to reflect the temporal nature of the input time series and fully exploit future contextual information. The complex structure enables this network to capture more stochasticity within the stock price. The method does not change when applied to stock data or Forex data. Experimental results based on a Forex dataset covering 2008–2018 showed that our approach outperformed the baseline autoregressive integrated moving average approach with regard to mean absolute error, mean squared error, and root-mean-square error.     

Visualization of diversity in large multivariate data sets

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.     

Fabrication of tungsten oxide photoanode by doctor blade technique and investigation on its photocatalytic operation mechanism

WO₃ is a potential material candidate for construction of photoanode for solar driven water splitting. In this work, μm-thick porous WO₃ photoanode is prepared by depositing a stable ink made of WO₃ nanoparticles and Aristoflex velvet polymer in water using the doctor blade technique, followed by a sintering in air. The nature of WO₃ nanoparticles, its loading mass on F-doped tin oxide electrode as well as sintering temperature are examined in order to optimize the photocatalytic activity of the resultant WO₃ photoanode. The operation of WO₃ photoanode is investigated by varying the light illumination direction and light incident intensity as well as changing the nature of the electrolyte. Dissolved tungsten in electrolyte is quantified by ICP-MS providing insights into the influences of electrolyte nature and operating conditions to the corrosion of WO₃. It is proposed that the H₂O₂ and OH^. radical generated as by-products of the photo-driven water oxidation on the photoanode surface are harmful species that accelerate the dissolution of WO₃.