Caps, apps and other mobile traps

This report outlines the major policy and legal issues on mobile phone ownership for children and young people

Opportunities for information sharing: case studies

Personal information provided to government and non-government service providers is highly sensitive. Appropriate collection, management and storage of personal information are critical elements to citizen trust in the public sector. However, misconceptions about the frameworks governing sharing personal information can impact on the coordination of services, case management and policy development.   The NSW Department of Premier & Cabinet engaged the Social Policy Research Centre to develop three case studies that identified the challenges to sharing information appropriately, and the opportunities for better personal information sharing between government agencies and non-government organisations. Improved sharing of personal information in these areas can support more effective policy development, leading to improved service delivery performance and coordination.   The Social Policy Research Centre identified the legislative and policy framework for each case study, conducted qualitative research on the interpretation of this framework, and developed three case study reports

Phosphorylation of α-synuclein is crucial in compensating for proteasomal dysfunction

α-Synuclein can be degraded by both the ubiquitin-proteasomal system and the chaperone-lysosomal system. However, the switching mechanism between the two pathways is not clearly understood. In our study, we investigated the mutual association between the binding of α-synuclein to heat shock cognate 70 and the lysosomal translocation of α-synuclein. Tyrosine phosphorylation of Y136 on α-synuclein increased when it bound to heat shock protein 70. We also found that tyrosine phosphorylation of α-synuclein can be regulated by focal adhesion kinase pp125 and protein tyrosine phosphatase 1B. Furthermore, protein tyrosine phosphatase 1B inhibitor protected dopaminergic neurons against cell death and rescued rotarod performance in a Parkinson's disease animal model. This study provides evidence that the regulation of Y136 phosphorylation of α-synuclein can improve behavioral performance and protect against neuronal death by promoting the turnover of lysosomal degradation of α-synuclein. As a result, protein tyrosine phosphatase 1B inhibitor may be used as a potential therapeutic agent against Parkinson's disease

A pharmacokinetic study on red ginseng with furosemide in equine

Red ginseng (RG) is a popular ingredient in traditional Korean medicine that has various health benefits. It is commonly taken orally as a dietary supplement; however, its potential interactions with concomitantly administered drugs are unclear. In this study, we examined the pharmacokinetic interaction between furosemide and RG in equine plasma. Liquid chromatography with tandem mass spectrometry analysis was performed to evaluate ginsenosides in the plasma of horses after feeding them RG and furosemide and validate the results. A single bolus of furosemide (0.5 mg/kg) was administered intravenously to female horses that had consumed RG (600 mg/kg/day) every morning for 3 weeks (experimental group), and blood samples were collected from 0 to 24 h, analyzed, and compared with those from female horses that did not consume RG (control group). Four (20s)-protopanaxadiol ginsenosides (Rb1, Rb2, Rc, and Rd) were detected in the plasma. Rb1 and Rc individually showed a high concentration distribution in the plasma. The Cmax, AUC0−t, and AUC0−∞ of furosemide was significantly increased in the experimental group (p < 0.05), while the CL, Vz, and Vss was decreased (p < 0.05, p < 0.01). These changes indicate the potential for pharmacokinetic interactions between furosemide and RG

Fully Convolutional Networks with Multiscale 3D Filters and Transfer Learning for Change Detection in High Spatial Resolution Satellite Images

Remote sensing images having high spatial resolution are acquired, and large amounts of data are extracted from their region of interest. For processing these images, objects of various sizes, from very small neighborhoods to large regions composed of thousands of pixels, should be considered. To this end, this study proposes change detection method using transfer learning and recurrent fully convolutional networks with multiscale three-dimensional (3D) filters. The initial convolutional layer of the change detection network with multiscale 3D filters was designed to extract spatial and spectral features of materials having different sizes; the layer exploits pre-trained weights and biases of semantic segmentation network trained on an open benchmark dataset. The 3D filter sizes were defined in a specialized way to extract spatial and spectral information, and the optimal size of the filter was determined using highly accurate semantic segmentation results. To demonstrate the effectiveness of the proposed method, binary change detection was performed on images obtained from multi-temporal Korea multipurpose satellite-3A. Results revealed that the proposed method outperformed the traditional deep learning-based change detection methods and the change detection accuracy improved using multiscale 3D filters and transfer learning

Automatic Extraction of Optimal Endmembers from Airborne Hyperspectral Imagery Using Iterative Error Analysis (IEA) and Spectral Discrimination Measurements

Pure surface materials denoted by endmembers play an important role in hyperspectral processing in various fields. Many endmember extraction algorithms (EEAs) have been proposed to find appropriate endmember sets. Most studies involving the automatic extraction of appropriate endmembers without a priori information have focused on N-FINDR. Although there are many different versions of N-FINDR algorithms, computational complexity issues still remain and these algorithms cannot consider the case where spectrally mixed materials are extracted as final endmembers. A sequential endmember extraction-based algorithm may be more effective when the number of endmembers to be extracted is unknown. In this study, we propose a simple but accurate method to automatically determine the optimal endmembers using such a method. The proposed method consists of three steps for determining the proper number of endmembers and for removing endmembers that are repeated or contain mixed signatures using the Root Mean Square Error (RMSE) images obtained from Iterative Error Analysis (IEA) and spectral discrimination measurements. A synthetic hyperpsectral image and two different airborne images such as Airborne Imaging Spectrometer for Application (AISA) and Compact Airborne Spectrographic Imager (CASI) data were tested using the proposed method, and our experimental results indicate that the final endmember set contained all of the distinct signatures without redundant endmembers and errors from mixed materials

Change Detection in Hyperspectral Images Using Recurrent 3D Fully Convolutional Networks

Hyperspectral change detection (CD) can be effectively performed using deep-learning networks. Although these approaches require qualified training samples, it is difficult to obtain ground-truth data in the real world. Preserving spatial information during training is difficult due to structural limitations. To solve such problems, our study proposed a novel CD method for hyperspectral images (HSIs), including sample generation and a deep-learning network, called the recurrent three-dimensional (3D) fully convolutional network (Re3FCN), which merged the advantages of a 3D fully convolutional network (FCN) and a convolutional long short-term memory (ConvLSTM). Principal component analysis (PCA) and the spectral correlation angle (SCA) were used to generate training samples with high probabilities of being changed or unchanged. The strategy assisted in training fewer samples of representative feature expression. The Re3FCN was mainly comprised of spectral⁻spatial and temporal modules. Particularly, a spectral⁻spatial module with a 3D convolutional layer extracts the spectral⁻spatial features from the HSIs simultaneously, whilst a temporal module with ConvLSTM records and analyzes the multi-temporal HSI change information. The study first proposed a simple and effective method to generate samples for network training. This method can be applied effectively to cases with no training samples. Re3FCN can perform end-to-end detection for binary and multiple changes. Moreover, Re3FCN can receive multi-temporal HSIs directly as input without learning the characteristics of multiple changes. Finally, the network could extract joint spectral⁻spatial⁻temporal features and it preserved the spatial structure during the learning process through the fully convolutional structure. This study was the first to use a 3D FCN and a ConvLSTM for the remote-sensing CD. To demonstrate the effectiveness of the proposed CD method, we performed binary and multi-class CD experiments. Results revealed that the Re3FCN outperformed the other conventional methods, such as change vector analysis, iteratively reweighted multivariate alteration detection, PCA-SCA, FCN, and the combination of 2D convolutional layers-fully connected LSTM

Genome-wide hepatic DNA methylation changes in high-fat diet-induced obese mice

BACKGROUND/OBJECTIVES: A high-fat diet (HFD) induces obesity, which is a major risk factor for cardiovascular disease and cancer, while a calorie-restricted diet can extend life span by reducing the risk of these diseases. It is known that health effects of diet are partially conveyed through epigenetic mechanism including DNA methylation. In this study, we investigated the genome-wide hepatic DNA methylation to identify the epigenetic effects of HFD-induced obesity.MATERIALS AND METHODS: Seven-week-old male C57BL/6 mice were fed control diet (CD), calorie-restricted control diet (CRCD), or HFD for 16 weeks (after one week of acclimation to the control diet). Food intake, body weight, and liver weight were measured. Hepatic triacylglycerol and cholesterol levels were determined using enzymatic colorimetric methods. Changes in genome-wide DNA methylation were determined by a DNA methylation microarray method combined with methylated DNA immunoprecipitation. The level of transcription of individual genes was measured by real-time PCR.RESULTS: The DNA methylation statuses of genes in biological networks related to lipid metabolism and hepatic steatosis were influenced by HFD-induced obesity. In HFD group, a proinflammatory Casp1 (Caspase 1) gene had hypomethylated CpG sites at the 1.5-kb upstream region of its transcription start site (TSS), and its mRNA level was higher compared with that in CD group. Additionally, an energy metabolism-associated gene Ndufb9 (NADH dehydrogenase 1 beta subcomplex 9) in HFD group had hypermethylated CpG sites at the 2.6-kb downstream region of its TSS, and its mRNA level was lower compared with that in CRCD group.CONCLUSIONS: HFD alters DNA methylation profiles in genes associated with liver lipid metabolism and hepatic steatosis. The methylation statuses of Casp1 and Ndufb9 were particularly influenced by the HFD. The expression of these genes in HFD differed significantly compared with CD and CRCD, respectively, suggesting that the expressions of Casp1 and Ndufb9 in liver were regulated by their methylation statuses.</p

Percutaneous Mechanical Thrombectomy of Submassive Pulmonary Embolism and Extensive Deep Venous Thrombosis for Early Thrombus Removal

Traditional treatment with anticoagulation in nonfatal submassive pulmonary embolism can result in serious sequelae of chronic thromboembolic pulmonary hypertension or poor exercise tolerance, and functional impairment. To prevent long-term complications in previously healthy young patients, other treatment options to actively resolve existing thrombi should be considered. Despite recommendations for use in only severe clinical presentations, endovascular interventional techniques could serve as suitable treatment options for such patients. Here we report the case of a previously healthy 23-year-old female with submassive pulmonary embolism and extensive deep vein thrombosis in the inferior vena cava down to the right popliteal vein. The patient was initially treated with catheter-directed thrombolysis. However, she continued to show extensive venous thrombosis and pulmonary embolism. Percutaneous thrombectomy and aspiration using an AngioJet successfully removed the main pulmonary artery embolism and venous thrombus. The patient’s recovery was uneventful, and 3-month follow-up showed no signs of recurrence or discomfort