rMAPS: RNA map analysis and plotting server for alternative exon regulation.

RNA-binding proteins (RBPs) play a critical role in the regulation of alternative splicing (AS), a prevalent mechanism for generating transcriptomic and proteomic diversity in eukaryotic cells. Studies have shown that AS can be regulated by RBPs in a binding-site-position dependent manner. Depending on where RBPs bind, splicing of an alternative exon can be enhanced or suppressed. Therefore, spatial analyses of RBP motifs and binding sites around alternative exons will help elucidate splicing regulation by RBPs. The development of high-throughput sequencing technologies has allowed transcriptome-wide analyses of AS and RBP-RNA interactions. Given a set of differentially regulated alternative exons obtained from RNA sequencing (RNA-seq) experiments, the rMAPS web server (http://rmaps.cecsresearch.org) performs motif analyses of RBPs in the vicinity of alternatively spliced exons and creates RNA maps that depict the spatial patterns of RBP motifs. Similarly, rMAPS can also perform spatial analyses of RBP-RNA binding sites identified by cross-linking immunoprecipitation sequencing (CLIP-seq) experiments. We anticipate rMAPS will be a useful tool for elucidating RBP regulation of alternative exon splicing using high-throughput sequencing data

DPRP: a database of phenotype-specific regulatory programs derived from transcription factor binding data

Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we constructed a database of phenotype-specific regulatory programs (DPRP, http://syslab.nchu.edu.tw/DPRP/) derived from the integrative analysis of TF binding data and gene expression data. DPRP provides three methods: the Fisher's Exact Test, the Kolmogorov-Smirnov test and the BASE algorithm to facilitate the application of gene expression data for generating new hypotheses on transcriptional regulatory programs in biological and clinical studies

DiseaseConnect: a comprehensive web server for mechanism-based disease–disease connections

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms. Connecting diseases with similar pathological mechanisms could inspire novel strategies on the effective repositioning of existing drugs and therapies. Although there have been several studies attempting to generate disease connectivity networks, they have not yet utilized the enormous and rapidly growing public repositories of disease-related omics data and literature, two primary resources capable of providing insights into disease connections at an unprecedented level of detail. Our DiseaseConnect, the first public web server, integrates comprehensive omics and literature data, including a large amount of gene expression data, Genome-Wide Association Studies catalog, and text-mined knowledge, to discover disease–disease connectivity via common molecular mechanisms. Moreover, the clinical comorbidity data and a comprehensive compilation of known drug–disease relationships are additionally utilized for advancing the understanding of the disease landscape and for facilitating the mechanism-based development of new drug treatments

The Minnesota Haptic Function Test

Haptic loss severely compromises the fine motor control of many daily manual tasks. Today, no widely accepted assessment protocols of haptic function are in clinical use. This is primarily due to the scarcity of fast, objective measures capable of characterizing mild to severe forms of haptic dysfunction with appropriate resolution. This study introduces a novel curvature-perception assessment system called the Minnesota Haptic Function Test™ that seeks to overcome the shortcomings of current clinical assessments.Aims: The purpose of this study was threefold: (1) apply the test to a sample of young healthy adults to establish test-specific adult norms for haptic sensitivity and acuity; (2) establish the reliability of this instrument; (3) demonstrate clinical efficacy in a limited sample of cancer survivors who may exhibit haptic dysfunction due to chemotherapy-induced peripheral neuropathy.Method: Participants manually explored two curved surfaces successively and made verbal judgments about their curvature. A Bayesian-based adaptive algorithm selected presented stimulus pairs based on a subject’s previous responses, which ensured fast convergence toward a threshold. Haptic sensitivity was assessed by obtaining detection thresholds in 26 adults (19–34 years). Haptic acuity was assessed by obtaining just-noticeable-difference thresholds in a second sample of 28 adults (19–25 years). Nine cancer survivors (18–25 years) with suspected peripheral neuropathy completed the acuity assessment. Test-retest reliability of the algorithm was calculated.Results: First, the test yielded values that are consistent with those reported in the literature. Mean detection threshold for curvature of the healthy adults was 0.782 (SD ± 0.320 m−1). The corresponding mean discrimination threshold was 1.030 (SD ± 0.462 m−1). Second, test-retest reliability of the algorithm was assessed in a simulation, yielding an average correlation between repeated simulated thresholds of r = 0.93. Third, the test documented that 86% of the cancer survivors had acuity thresholds above the 75th percentile of the normative cohort, and 29% had thresholds above the normal range, indicating that the instrument can detect and differentiate between unaffected perception, and mild or more severe forms of haptic loss.Conclusion: We here provide evidence that this new method to assess haptic perception of curvature is valid, reliable, and clinically practicable

miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions

MicroRNAs (miRNAs) are small non-coding RNA molecules capable of negatively regulating gene expression to control many cellular mechanisms. The miRTarBase database (http://mirtarbase.mbc.nctu.edu.tw/) provides the most current and comprehensive information of experimentally validated miRNA-target interactions. The database was launched in 2010 with data sources for >100 published studies in the identification of miRNA targets, molecular networks of miRNA targets and systems biology, and the current release (2013, version 4) includes significant expansions and enhancements over the initial release (2010, version 1). This article reports the current status of and recent improvements to the database, including (i) a 14-fold increase to miRNA-target interaction entries, (ii) a miRNA-target network, (iii) expression profile of miRNA and its target gene, (iv) miRNA target-associated diseases and (v) additional utilities including an upgrade reminder and an error reporting/user feedback system

Neuroprotective Effects of San-Huang-Xie-Xin-Tang in the MPP+/MPTP Models of Parkinson's Disease In Vitro and In Vivo

San-Huang-Xie-Xin-Tang (SHXT), composed of Coptidis rhizoma, Scutellariae radix, and Rhei rhizoma, is a traditional Chinese medicine used for complementary and alternative therapy of cardiovascular and neurodegenerative diseases via its anti-inflammatory and antioxidative effects. The aim of this study is to investigate the protective effects of SHXT in the 1–methyl–4–phenylpyridinium (MPP+)/1–methyl–4–phenyl–1,2,3,6–tetrahydropyridine (MPTP) models of Parkinson's disease. Rat primary mesencephalic neurons and mouse Parkinson disease model were used in this study. Oxidative stress was induced by MPP+ in vitro and MPTP in vivo. In MPP+-treated mesencephalic neuron cultures, SHXT significantly increased the numbers of TH-positive neurons. SHXT reduced apoptotic signals (cytochrome and caspase) and apoptotic death. MPP+-induced gp91phox activation and ROS production were attenuated by SHXT. In addition, SHXT increased the levels of GSH and SOD in MPP+-treated neurons. In MPTP animal model, SHXT markedly increased TH-positive neurons in the substantia nigra pars compacta (SNpc) and improved motor activity of mice. In conclusion, the present results reveal the evidence that SHXT possesses beneficial protection against MPTP-induced neurotoxicity in this model of Parkinson's disease via its antioxidative and antiapoptotic effects. SHXT might be a potentially alternative and complementary medicine for neuroprotection

Combining Auto-Encoder with LSTM for WiFi-Based Fingerprint Positioning

Author's accepted manuscript.Although indoor positioning has long been investigated by various means, its accuracy remains concern. Several recent studies have applied machine learning algorithms to explore wireless fidelity (WiFi)-based positioning. In this paper, we propose a novel deep learning model which concatenates an auto-encoder with a long short term memory (LSTM) network for the purpose of WiFi fingerprint positioning. We first employ an auto-encoder to extract representative latent codes of fingerprints. Such an extraction is proven to be more reliable than simply using a deep neural network to extract representative features since a latent code can be reverted back to its original input. Then, a sequence of latent codes are injected into an LSTM network to identify location. To assess the accuracy and effectiveness of our model, we perform extensive real-life experiments.acceptedVersio

Dynamic Instrumentation Framework for Operating System Telemetry

Adding new telemetry to mobile operating systems (OS) requires changing code and pushing updated binaries to field devices, which can have a substantial lag before new telemetry reaches an adequate number of field devices. This hampers the optimization and debugging of operating systems and the apps they host. This disclosure describes a dynamic instrumentation framework that enables rapid pushing of new telemetry configurations to field devices. The configurations can identify parts of the mobile OS (and apps running thereon) to be inspected and specifications on how to extract information from the identified parts. In contrast to existing techniques of disseminating new binaries, configurations pushed to devices enable telemetry collection without requiring changes to the kernel or user-space code running on the device. The resulting mechanism retains comprehensive metrics-collection abilities without the need to push updated binaries. The mechanism can be used to rapidly collect newly defined metrics at scale. The results of telemetry can be sent to a server in a secure, private, and performant manner