Development of an estimative model for the optimal tack coat dosage based on aggregate gradation of hot mix asphalt pavements

In this work the performance of tack coats on asphalt pavement layers is analysed. Adjustment models based on experimental measurements were implemented, relating surface layer macro-texture and aggregate content larger than 8 mm. The best fits were obtained with a Gompertz model, which follows the expected physical macro-texture changes outside the test range. Shear strength was analysed, through prediction curves of each evaluated tack coat dosage, with an optimum tack coat performance for aggregate contents larger than 8 mm between 45% and 50%, and no relevant influence of the tack coat dosage used.The authors would like to acknowledge the support provided by the Technologic Research Construction Group (GITECO) and the Group of Roads of Santander at Cantabria University for the development of tests and samples. We would also like to thank the company Emilio Bolado S.L. and the Society for the Development of Cantabria Region (SODERCAN) for the material provided, and the DID Research Department from the Austral University of Chile for the support

Towards the clinical implementation of pharmacogenetics in bipolar disorder.

BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

Oligonucleotide Sequence Motifs as Nucleosome Positioning Signals

To gain a better understanding of the sequence patterns that characterize positioned nucleosomes, we first performed an analysis of the periodicities of the 256 tetranucleotides in a yeast genome-wide library of nucleosomal DNA sequences that was prepared by in vitro reconstitution. The approach entailed the identification and analysis of 24 unique tetranucleotides that were defined by 8 consensus sequences. These consensus sequences were shown to be responsible for most if not all of the tetranucleotide and dinucleotide periodicities displayed by the entire library, demonstrating that the periodicities of dinucleotides that characterize the yeast genome are, in actuality, due primarily to the 8 consensus sequences. A novel combination of experimental and bioinformatic approaches was then used to show that these tetranucleotides are important for preferred formation of nucleosomes at specific sites along DNA in vitro. These results were then compared to tetranucleotide patterns in genome-wide in vivo libraries from yeast and C. elegans in order to assess the contributions of DNA sequence in the control of nucleosome residency in the cell. These comparisons revealed striking similarities in the tetranucleotide occurrence profiles that are likely to be involved in nucleosome positioning in both in vitro and in vivo libraries, suggesting that DNA sequence is an important factor in the control of nucleosome placement in vivo. However, the strengths of the tetranucleotide periodicities were 3–4 fold higher in the in vitro as compared to the in vivo libraries, which implies that DNA sequence plays less of a role in dictating nucleosome positions in vivo. The results of this study have important implications for models of sequence-dependent positioning since they suggest that a defined subset of tetranucleotides is involved in preferred nucleosome occupancy and that these tetranucleotides are the major source of the dinucleotide periodicities that are characteristic of positioned nucleosomes

Novel role of Y1 receptors in coordinated regulation of bone and energy homeostasis

The importance of neuropeptide Y (NPY) and Y2 receptors in the regulation of bone and energy homeostasis has recently been demonstrated. However, the contributions of the other Y receptors are less clear. Here we show that Y1 receptors are expressed on osteoblastic cells. Moreover, bone and adipose tissue mass are elevated in Y1-/- mice with a generalized increase in bone formation on cortical and cancellous surfaces. Importantly, the inhibitory effects of NPY on bone marrow stromal cells in vitro are absent in cells derived from Y1-/- mice, indicating a direct action of NPY on bone cells via this Y receptor. Interestingly, in contrast to Y2 receptor or germ line Y1 receptor deletion, conditional deletion of hypothalamic Y1 receptors in adult mice did not alter bone homeostasis, food intake, or adiposity. Furthermore, deletion of both Y1 and Y2 receptors did not produce additive effects in bone or adiposity. Thus Y1 receptor pathways act powerfully to inhibit bone production and adiposity by nonhypothalamic pathways, with potentially direct effects on bone tissue through a single pathway with Y2 receptors

Conditional deletion of hypothalamic Y2 receptors reverts gonadectomy-induced bone loss in adult mice

Reduction in levels of sex hormones at menopause in women is associated with two common, major outcomes, the accumulation of white adipose tissue, and the progressive loss of bone because of excess osteoclastic bone resorption exceeding osteoblastic bone formation. Current antiresorptive therapies can reduce osteoclastic activity but have only limited capacity to stimulate osteoblastic bone formation and restore lost skeletal mass. Likewise, the availability of effective pharmacological weight loss treatments is currently limited. Here we demonstrate that conditional deletion of hypothalamic neuropeptide Y2 receptors can prevent ongoing bone loss in sex hormone-deficient adult male and female mice. This benefit is attributable solely to activation of an anabolic osteoblastic bone formation response that counterbalances persistent elevation of bone resorption, suggesting the Y2-mediated anabolic pathway to be independent of sex hormones. Furthermore, the increase in fat mass that typically occurs after ovariectomy is prevented by germ line deletion of Y2 receptors, whereas in male mice body weight and fat mass were consistently lower than wild-type regardless of sex hormone status. Therefore, this study indicates a role for Y2 receptors in the accumulation of adipose tissue in the hypogonadal state and demonstrates that hypothalamic Y2 receptors constitutively restrain osteoblastic activity even in the absence of sex hormones. The increase in bone formation after release of this tonic inhibition suggests a promising new avenue for osteoporosis treatment

Organizational Heterogeneity of Vertebrate Genomes

Genomes of higher eukaryotes are mosaics of segments with various structural, functional, and evolutionary properties. The availability of whole-genome sequences allows the investigation of their structure as “texts” using different statistical and computational methods. One such method, referred to as Compositional Spectra (CS) analysis, is based on scoring the occurrences of fixed-length oligonucleotides (k-mers) in the target DNA sequence. CS analysis allows generating species- or region-specific characteristics of the genome, regardless of their length and the presence of coding DNA. In this study, we consider the heterogeneity of vertebrate genomes as a joint effect of regional variation in sequence organization superimposed on the differences in nucleotide composition. We estimated compositional and organizational heterogeneity of genome and chromosome sequences separately and found that both heterogeneity types vary widely among genomes as well as among chromosomes in all investigated taxonomic groups. The high correspondence of heterogeneity scores obtained on three genome fractions, coding, repetitive, and the remaining part of the noncoding DNA (the genome dark matter - GDM) allows the assumption that CS-heterogeneity may have functional relevance to genome regulation. Of special interest for such interpretation is the fact that natural GDM sequences display the highest deviation from the corresponding reshuffled sequences

CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains

Recent developments in electrophysiological and optical recording techniques enable the simultaneous observation of large numbers of neurons. A meaningful interpretation of the resulting multivariate data, however, presents a serious challenge. In particular, the estimation of higher-order correlations that characterize the cooperative dynamics of groups of neurons is impeded by the combinatorial explosion of the parameter space. The resulting requirements with respect to sample size and recording time has rendered the detection of coordinated neuronal groups exceedingly difficult. Here we describe a novel approach to infer higher-order correlations in massively parallel spike trains that is less susceptible to these problems. Based on the superimposed activity of all recorded neurons, the cumulant-based inference of higher-order correlations (CuBIC) presented here exploits the fact that the absence of higher-order correlations imposes also strong constraints on correlations of lower order. Thus, estimates of only few lower-order cumulants suffice to infer higher-order correlations in the population. As a consequence, CuBIC is much better compatible with the constraints of in vivo recordings than previous approaches, which is shown by a systematic analysis of its parameter dependence

EVpedia: a community web portal for extracellular vesicles research

Motivation: Extracellular vesicles (EVs) are spherical bilayered proteolipids, harboring various bioactive molecules. Due to the complexity of the vesicular nomenclatures and components, online searches for EV-related publications and vesicular components are currently challenging. Results: We present an improved version of EVpedia, a public database for EVs research. This community web portal contains a database of publications and vesicular components, identification of orthologous vesicular components, bioinformatic tools and a personalized function. EVpedia includes 6879 publications, 172 080 vesicular components from 263 high-throughput datasets, and has been accessed more than 65 000 times from more than 750 cities. In addition, about 350 members from 73 international research groups have participated in developing EVpedia. This free web-based database might serve as a useful resource to stimulate the emerging field of EV research.X1110478Ysciescopu

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.This research was financially supported by the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant Number: NSC102-2911-I-008-001). Also, it was supported by Chung-Shan Institute of Science and Technology in Taiwan (Grant Numbers: CSIST-095-V301 and CSIST-095-V302) and National Natural Science Foundation of China (Grant Number: 51475342)