Transposable elements modulate human RNA abundance and splicing via specific RNA-protein interactions

Background: Transposable elements (TEs) have significantly influenced the evolution of transcriptional regulatory networks in the human genome. Post-transcriptional regulation of human genes by TE-derived sequences has been observed in specific contexts, but has yet to be systematically and comprehensively investigated. Here, we study a collection of 75 CLIP-Seq experiments mapping the RNA binding sites for a diverse set of 51 human proteins to explore the role of TEs in post-transcriptional regulation of human mRNAs and lncRNAs via RNA-protein interactions. Results: We detect widespread interactions between RNA binding proteins (RBPs) and many families of TE-derived sequence in the CLIP-Seq data. Further, alignment coverage peaks on specific positions of the TE consensus sequences, illuminating a diversity of TE-specific RBP binding motifs. Evidence of binding and conservation of these motifs in the nonrepetitive transcriptome suggests that TEs have generally appropriated existing sequence preferences of the RBPs. Depletion assays for numerous RBPs show that TE-derived binding sites affect transcript abundance and splicing similarly to nonrepetitive sites. However, in a few cases the effect of RBP binding depends on the specific TE family bound; for example, the ubiquitously expressed RBP HuR confers transcript stability unless bound to an Alu element. Conclusions: Our meta-analysis suggests a widespread role for TEs in shaping RNA-protein regulatory networks in the human genome. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0537-5) contains supplementary material, which is available to authorized users

A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models

The use of mixed frequency data is now common in many applications, ranging from the analysis of high frequency financial time series to large cross-sections of macroeconomic time series. In this article, we show how state space methods can easily facilitate both estimation and inference in these settings. After presenting a unified treatment of the state space approach to mixed frequency data modeling, we provide a series of applications to demonstrate how our MATLAB toolbox can make the estimation and post-processing of these models straightforward

Absorption Efficiencies of Forsterite. I: DDA Explorations in Grain Shape and Size

We compute the absorption efficiency (Qabs) of forsterite using the discrete dipole approximation (DDA) in order to identify and describe what characteristics of crystal grain shape and size are important to the shape, peak location, and relative strength of spectral features in the 8-40 {\mu}m wavelength range. Using the DDSCAT code, we compute Qabs for non-spherical polyhedral grain shapes with a_eff = 0.1 {\mu}m. The shape characteristics identified are: 1) elongation/reduction along one of three crystallographic axes; 2) asymmetry, such that all three crystallographic axes are of different lengths; and 3) the presence of crystalline faces that are not parallel to a specific crystallographic axis, e.g., non-rectangular prisms and (di)pyramids. Elongation/reduction dominates the locations and shapes of spectral features near 10, 11, 16, 23.5, 27, and 33.5 {\mu}m, while asymmetry and tips are secondary shape effects. Increasing grain sizes (0.1-1.0 {\mu}m) shifts the 10, 11 {\mu}m features systematically towards longer wavelengths and relative to the 11 {\mu}m feature increases the strengths and slightly broadens the longer wavelength features. Seven spectral shape classes are established for crystallographic a-, b-, and c-axes and include columnar and platelet shapes plus non-elongated or equant grain shapes. The spectral shape classes and the effects of grain size have practical application in identifying or excluding columnar, platelet or equant forsterite grain shapes in astrophysical environs. Identification of the shape characteristics of forsterite from 8-40 {\mu}m spectra provides a potential means to probe the temperatures at which forsterite formed.Comment: 55 pages, 15 figure

Quake: quality-aware detection and correction of sequencing errors

We introduce Quake, a program to detect and correct errors in DNA sequencing reads. Using a maximum likelihood approach incorporating quality values and nucleotide specific miscall rates, Quake achieves the highest accuracy on realistically simulated reads. We further demonstrate substantial improvements in de novo assembly and SNP detection after using Quake. Quake can be used for any size project, including more than one billion human reads, and is freely available as open source software from http://www.cbcb.umd.edu/software/quake

Therapeutic efficacy of intravenously administered transferrin-conjugated dendriplexes on prostate carcinomas

Aim: Improved treatments for prostate cancer are critically needed in order to overcome metastasis and lethal recurrence. Intravenously administered gene therapy would be an attractive anticancer treatment strategy; however, the lack of suitable carrier systems able to selectively deliver therapeutic genes to tumors has so far limited this investigation. Given that transferrin receptors are overexpressed on prostate cancer cells, the purpose of this study is to determine whether transferrin-conjugated dendriplexes encoding TNF-α, TNF-related apoptosis-inducing ligand and IL-12 would suppress the growth of prostate cancer cell lines in vitro and in vivo. Materials & methods: Transferrin-conjugated dendriplexes encoding TNF-α, TNF-related apoptosis-inducing ligand and IL-12 were intravenously administered to mice bearing subcutaneous PC-3 and DU145 tumors. Results: The administration of the transferrin-conjugated generation 3 diaminobutyric polypropylenimine dendriplex encoding TNF-α resulted in tumor suppression for 60% of PC-3 and 50% of DU145 prostate tumors. Conclusion: These dendriplexes hold great potential as a novel approach for prostate cancer therapy

Early Clinical Detection of Pharmacologic Response in Insulin Action in a Nondiabetic Insulin-Resistant Population

AbstractBackgroundInsulin resistance heightens the risk for type 2 diabetes mellitus and cardiovascular disease. Amelioration of insulin resistance may reduce this risk. The thiazolidinedone class of insulin sensitizers improves insulin action in individuals with insulin-resistant diabetes and nondiabetic individuals. However, there are few reports on the time of onset of such effects independent of reversal of glucotoxicity.ObjectiveThe goal of our study was to test whether the thiazolidinedione pioglitazone has prominent early metabolic effects that can be detected in an obese, nondiabetic, insulin-resistant population.MethodsWe conducted a randomized, double-blind, placebo-controlled, parallel-group trial in men with nondiabetic insulin resistance using a hyperinsulinemic euglycemic clamp technique (at low and high doses of insulin at 10 and 40 mU/m2/min, respectively). The patients were given 30 mg daily oral pioglitazone or placebo for 28 days. Patients underwent a baseline clamp before initiation of treatment, and again at 14 and 28 days of treatment.ResultsCompared with placebo, under high-dose hyperinsulinemia, pioglitazone led to significant increases in glucose disposal rates (GDR) of 1.29 mg/kg/min (90% CI, 0.43–2.15; 39%; P=0.008) that were detectable at 2 weeks of treatment and persisted at 4 weeks of treatment. Under low-dose hyperinsulinemia, significant increases in GDR of 0.40 mg/kg/min (90% CI, 0.17–0.62; 95%; P=0.003) were observed at 4 weeks of treatment. These responses were accompanied by robust suppression of free fatty acids under hyperinsulinemic conditions, and by significant increases in circulating basal total adiponectin at 2 and 4 weeks of treatment.ConclusionsSignificant changes in insulin action across multiple insulin-sensitive tissues can be detected within 2 weeks of initiation of insulin-sensitizing therapy with pioglitazone in obese patients with nondiabetic insulin resistance. ClinicalTrials.gov identifier: NCT01115712

Advancing the speed, sensitivity and accuracy of biomolecular detection using multi-length-scale engineering

Rapid progress in identifying disease biomarkers has increased the importance of creating high-performance detection technologies. Over the last decade, the design of many detection platforms has focused on either the nano or micro length scale. Here, we review recent strategies that combine nano- and microscale materials and devices to produce large improvements in detection sensitivity, speed and accuracy, allowing previously undetectable biomarkers to be identified in clinical samples. Microsensors that incorporate nanoscale features can now rapidly detect disease-related nucleic acids expressed in patient samples. New microdevices that separate large clinical samples into nanocompartments allow precise quantitation of analytes, and microfluidic systems that utilize nanoscale binding events can detect rare cancer cells in the bloodstream more accurately than before. These advances will lead to faster and more reliable clinical diagnostic devices

The Influence of Cyber-Sexual Assault on the Mental Health Outcomes of Survivors

Researchers examined data collected from the only national sample of cyber-sexual assault (CBSA) survivors (N = 97; 3.75\% response rate to the online survey) using three valid instruments that measure symptomology of sexual assault. We found that participants scored high across each of the inventories, indicating CBSA survivors respond in ways that are similar to sexual assault survivors concerning emotional dysregulation, depression, and post-traumatic stress symptomology, particularly if they had a history of sexual assault. Implications for counselors are reviewed, and clinical recommendations are offered

Finding the optimal background subtraction algorithm for EuroHockey 2015 video

Background subtraction is a classic step in a vision-based localization and tracking workflow. Previous studies have compared background subtraction algorithms on publicly available datasets; however comparisons were made only with manually optimized parameters. The aim of this research was to identify the optimal background subtraction algorithm for a set of field hockey videos captured at EuroHockey 2015. Particle Swarm Optimization was applied to find the optimal background subtraction algorithm. The objective function was the F-score, i.e. the harmonic mean of precision and recall. The precision and recall were calculated using the output of the background subtraction algorithm and gold standard labeled images. The training dataset consisted of 15 x 13 second field hockey video segments. The test data consisted of 5 x 13 second field hockey video segments. The video segments were chosen to be representative of the teams present at the tournament, the times of day the matches were played and the weather conditions experienced. Each segment was 960 pixels x 540 pixels and had 10 ground truth labeled frames. Eight commonly used background subtraction algorithms were considered. Results suggest that a background subtraction algorithm must use optimized parameters for a valid comparison of performance. Particle Swarm Optimization is an appropriate method to undertake this optimization. The optimal algorithm, Temporal Median, achieved an F-score of 0.791 on the test dataset, suggesting it generalizes to the rest of the video footage captured at EuroHockey 2015