Ruthenium oxide-carbon-based nanofiller-reinforced conducting polymer nanocomposites and their supercapacitor applications.

In this review article, we have presented for the first time the new applications of supercapacitor technologies and working principles of the family of RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites. Our review focuses on pseudocapacitors and symmetric and asymmetric supercapacitors. Over the last years, the supercapacitors as a new technology in energy storage systems have attracted more and more attention. They have some unique characteristics such as fast charge/discharge capability, high energy and power densities, and long stability. However, the need for economic, compatible, and easy synthesis materials for supercapacitors have led to the development of RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites with RuO2. Therefore, the aim of this manuscript was to review RuO2-carbon-based nanofiller-reinforced conducting polymer nanocomposites with RuO2 over the last 17 years

Radiotherapy to the prostate for men with metastatic prostate cancer in the UK and Switzerland: Long-term results from the STAMPEDE randomised controlled trial.

BACKGROUND: STAMPEDE has previously reported that radiotherapy (RT) to the prostate improved overall survival (OS) for patients with newly diagnosed prostate cancer with low metastatic burden, but not those with high-burden disease. In this final analysis, we report long-term findings on the primary outcome measure of OS and on the secondary outcome measures of symptomatic local events, RT toxicity events, and quality of life (QoL). METHODS AND FINDINGS: Patients were randomised at secondary care sites in the United Kingdom and Switzerland between January 2013 and September 2016, with 1:1 stratified allocation: 1,029 to standard of care (SOC) and 1,032 to SOC+RT. No masking of the treatment allocation was employed. A total of 1,939 had metastatic burden classifiable, with 42% low burden and 58% high burden, balanced by treatment allocation. Intention-to-treat (ITT) analyses used Cox regression and flexible parametric models (FPMs), adjusted for stratification factors age, nodal involvement, the World Health Organization (WHO) performance status, regular aspirin or nonsteroidal anti-inflammatory drug (NSAID) use, and planned docetaxel use. QoL in the first 2 years on trial was assessed using prospectively collected patient responses to QLQ-30 questionnaire. Patients were followed for a median of 61.3 months. Prostate RT improved OS in patients with low, but not high, metastatic burden (respectively: 202 deaths in SOC versus 156 in SOC+RT, hazard ratio (HR) = 0·64, 95% CI 0.52, 0.79, p < 0.001; 375 SOC versus 386 SOC+RT, HR = 1.11, 95% CI 0.96, 1.28, p = 0·164; interaction p < 0.001). No evidence of difference in time to symptomatic local events was found. There was no evidence of difference in Global QoL or QLQ-30 Summary Score. Long-term urinary toxicity of grade 3 or worse was reported for 10 SOC and 10 SOC+RT; long-term bowel toxicity of grade 3 or worse was reported for 15 and 11, respectively. CONCLUSIONS: Prostate RT improves OS, without detriment in QoL, in men with low-burden, newly diagnosed, metastatic prostate cancer, indicating that it should be recommended as a SOC. TRIAL REGISTRATION: ClinicalTrials.gov NCT00268476, ISRCTN.com ISRCTN78818544

A Combinatorial Approach to Detect Coevolved Amino Acid Networks in Protein Families of Variable Divergence

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence

Bayesian Inference for Genomic Data Integration Reduces Misclassification Rate in Predicting Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable predictions. Noticeably, false positive rates can be as high as >80%. Error correction from each generating source can be both time-consuming and inefficient due to the difficulty of covering the errors from multiple levels of data processing procedures within a single test. We propose a novel Bayesian integration method, deemed nonparametric Bayes ensemble learning (NBEL), to lower the misclassification rate (both false positives and negatives) through automatically up-weighting data sources that are most informative, while down-weighting less informative and biased sources. Extensive studies indicate that NBEL is significantly more robust than the classic naïve Bayes to unreliable, error-prone and contaminated data. On a large human data set our NBEL approach predicts many more PPIs than naïve Bayes. This suggests that previous studies may have large numbers of not only false positives but also false negatives. The validation on two human PPIs datasets having high quality supports our observations. Our experiments demonstrate that it is feasible to predict high-throughput PPIs computationally with substantially reduced false positives and false negatives. The ability of predicting large numbers of PPIs both reliably and automatically may inspire people to use computational approaches to correct data errors in general, and may speed up PPIs prediction with high quality. Such a reliable prediction may provide a solid platform to other studies such as protein functions prediction and roles of PPIs in disease susceptibility

On computational approaches for size-and-shape distributions from sedimentation velocity analytical ultracentrifugation

Sedimentation velocity analytical ultracentrifugation has become a very popular technique to study size distributions and interactions of macromolecules. Recently, a method termed two-dimensional spectrum analysis (2DSA) for the determination of size-and-shape distributions was described by Demeler and colleagues (Eur Biophys J 2009). It is based on novel ideas conceived for fitting the integral equations of the size-and-shape distribution to experimental data, illustrated with an example but provided without proof of the principle of the algorithm. In the present work, we examine the 2DSA algorithm by comparison with the mathematical reference frame and simple well-known numerical concepts for solving Fredholm integral equations, and test the key assumptions underlying the 2DSA method in an example application. While the 2DSA appears computationally excessively wasteful, key elements also appear to be in conflict with mathematical results. This raises doubts about the correctness of the results from 2DSA analysis

Study of novel rosin-based biomaterials for pharmaceutical coating

The film forming and coating properties of Glycerol ester of maleic rosin (GMR) and Pentaerythritol ester of maleic rosin (PMR) were investigated. The 2 rosin-based biomaterials were initially characterized in terms of their physicochemical properties, molecular weight (Mw), and glass transition temperature (Tg). Films were produced by solvent evaporation technique on a mercury substrate. Dibutyl sebacate plasticized and nonplasticized films were characterized by mechanical (tensile zzzz strength, percentage elongation, and Young's modulus), water vapor transmission (WVT), and moisture absorption parameters. Plasticization was found to increase film elongation and decrease the Young's modulus, making the films more flexible and thereby reducing the brittleness. Poor rates of WVT and percentage moisture absorption were demonstrated by various film formulations. Diclofenac sodium-layered pellets coated with GMR and PMR film formulations showed sustained drug release for up to 10 hours. The release rate was influenced by the extent of plasticization and coating level. The results obtained in the study demonstrate the utility of novel rosin-based biomaterials for pharmaceutical coating and sustained-release drug delivery systems