Mcfaddenbloch5345

RNA-RNA inter- and intramolecular interactions are fundamental for numerous biological processes. While there are reasonable approaches to map RNA secondary structures genome-wide, understanding how different RNAs interact to carry out their regulatory functions requires mapping of intermolecular base pairs. Recently, different strategies to detect RNA-RNA duplexes in living cells, so called direct duplex detection (DDD) methods, have been developed. Common to all is the Psoralen-mediated in vivo RNA crosslinking followed by RNA Proximity Ligation to join the two interacting RNA strands. Sequencing of the RNA via classical RNA-seq and subsequent specialised bioinformatic analyses the result in the prediction of inter- and intramolecular RNA-RNA interactions. Existing approaches adapt standard RNA-seq analysis pipelines, but often neglect inherent features of RNA-RNA interactions that are useful for filtering and statistical assessment. Here we present RNAnue, a general pipeline for the inference of RNA-RNA interactions from DDD experiments that takes into account hybridisation potential and statistical significance to improve prediction accuracy. We applied RNAnue to data from different DDD studies and compared our results to those of the original methods. This showed that RNAnue performs better in terms of quantity and quality of predictions.

Androgen deficiency is common among prostate cancer survivors, but many guidelines consider history of prostate cancer a contraindication for testosterone replacement. We determined the safety and efficacy of a selective androgen receptor modulator (OPK-88004) in symptomatic, testosterone-deficient men who had undergone radical prostatectomy for low-grade, organ-confined prostate cancer.

In this placebo-controlled, randomized, double-blind trial, 114 men, ≥19 years of age, who had undergone radical prostatectomy for low-grade, organ-localized prostate cancer, undetectable PSA (<0.1 ng/mL) for ≥2 years after radical prostatectomy and testosterone deficiency were randomized in stages to placebo or 1, 5, or 15 mg OPK-88004 daily for 12 weeks. Outcomes included PSA recurrence, sexual activity, sexual desire, erectile function, body composition, muscle strength and physical function measures, mood, fatigue, and bone markers.

Participants were on average 67.5 years of age and had severe sexual dysfunction ate cancer. OPK-88004 increased lean body mass and decreased fat mass but did not improve sexual symptoms or physical performance.

Severe hypertriglyceridemia (fasting triglycerides (TG) concentration ≥ 10 mmol/L) can be caused by multifactorial chylomicronemia syndrome (MCS) or familial chylomicronemia syndrome (FCS). Both conditions are associated with an increased risk of acute pancreatitis. The clinical differences between MCS patients with or without a rare variant in TG-related genes have never been studied.

To compare the clinical and biochemical characteristics of FCS, positive-MCS patients and negative-MCS patients, as well as to investigate the predictors of acute pancreatitis in MCS patients.

All patients referred at the clinic for severe hypertriglyceridemia underwent genetic testing for the 5 canonical genes involved in TG metabolism (LPL, APOC2, GPIHBP1, APOA5, and LMF1) using next-generation sequencing.

A total of 53 variant negative-MCS, 22 variant positive-MCS and 28 FCS subjects were included in this retrospective cross-sectional study. A significant difference was observed in the prevalence of pancreatitis (9%,lomicronemia, identification of higher-risk MCS patients that would benefit from additional treatment is primordial.The large majority of chromosome damage produced by ionizing radiations takes the form of exchange aberrations. For simple exchanges between two chromosomes, multi-fluor fluorescence in situ hybridization (mFISH) studies confirm that the dose response to X rays or gamma rays is quasi-linear with dose. This result is in seeming conflict with generalized theories of radiation action that depend on the interaction of lesions as the source of curvature in dose-response relationships. A qualitative explanation for such "linearization" had been previously proposed but lacked quantitative support. The essence of this explanation is that during the rejoining of radiogenic chromosome breaks, competition for breaks (CFB) between different aberration types often results in formation of complex exchange aberrations at the expense of simple reciprocal exchange events. This process becomes more likely at high radiation doses, where the number of contemporaneous breaks is high and complex exchanges involving multiple breaks become possible. Here we provide mathematical support for this CFB concept under the assumption that the mean and variance for exchange complexity increase with radiation dose.Comprehensive, predictive computational models have significant potential for science, bioengineering, and medicine. One promising way to achieve more predictive models is to combine submodels of multiple subsystems. To capture the multiple scales of biology, these submodels will likely require multiple modeling frameworks and simulation algorithms. Several community resources are already available for working with many of these frameworks and algorithms. However, the variety and sheer number of these resources make it challenging to find and use appropriate tools for each model, especially for novice modelers and experimentalists. To make these resources easier to use, we developed RunBioSimulations (https//run.biosimulations.org), a single web application for executing a broad range of models. ALKBH5 inhibitor 2 molecular weight RunBioSimulations leverages community resources, including BioSimulators, a new open registry of simulation tools. These resources currently enable RunBioSimulations to execute nine frameworks and 44 algorithms, and they make RunBioSimulations extensible to additional frameworks and algorithms. RunBioSimulations also provides features for sharing simulations and interactively visualizing their results. We anticipate that RunBioSimulations will foster reproducibility, stimulate collaboration, and ultimately facilitate the creation of more predictive models.