Multiple machine learning methods aided virtual screening of Na(V)1.5 inhibitors

Na(v)1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion channel inhibitor screening. However, this method has disadvantages such as high technical difficulty, high cost and low speed. In this study, novel machine learning models to screen chemical blockers were developed to overcome the above shortage. The data from the ChEMBL Database were employed to establish the machine learning models. Firstly, six molecular fingerprints together with five machine learning algorithms were used to develop 30 classification models to predict effective inhibitors. A validation and a test set were used to evaluate the performance of the models. Subsequently, the privileged substructures tightly associated with the inhibition of the Na(v)1.5 ion channel were extracted using the bioalerts Python package. In the validation set, the RF-Graph model performed best. Similarly, RF-Graph produced the best result in the test set in which the Prediction Accuracy (Q) was 0.9309 and Matthew's correlation coefficient was 0.8627, further indicating the model had high classification ability. The results of the privileged substructures indicated Sulfa structures and fragments with large Steric hindrance tend to block Na(v)1.5. In the unsupervised learning task of identifying sulfa drugs, MACCS and Graph fingerprints had good results. In summary, effective machine learning models have been constructed which help to screen potential inhibitors of the Na(v)1.5 ion channel and key privileged substructures with high affinity were also extracted.Peer reviewe

A 4-gigabase physical map unlocks the structure and evolution of the complex genome of Aegilops tauschii, the wheat D-genome progenitor

The current limitations in genome sequencing technology require the construction of physical maps for high-quality draft sequences of large plant genomes, such as that of Aegilops tauschii, the wheat D-genome progenitor. To construct a physical map of the Ae. tauschii genome, we fingerprinted 461,706 bacterial artificial chromosome clones, assembled contigs, designed a 10K Ae. tauschii Infinium SNP array, constructed a 7,185-marker genetic map, and anchored on the map contigs totaling 4.03 Gb. Using whole genome shotgun reads, we extended the SNP marker sequences and found 17,093 genes and gene fragments. We showed that collinearity of the Ae. tauschii genes with Brachypodium distachyon, rice, and sorghum decreased with phylogenetic distance and that structural genome evolution rates have been high across all investigated lineages in subfamily Pooideae, including that of Brachypodieae. We obtained additional information about the evolution of the seven Triticeae chromosomes from 12 ancestral chromosomes and uncovered a pattern of centromere inactivation accompanying nested chromosome insertions in grasses. We showed that the density of noncollinear genes along the Ae. tauschii chromosomes positively correlates with recombination rates, suggested a cause, and showed that new genes, exemplified by disease resistance genes, are preferentially located in high-recombination chromosome regions

Genetic diversity at the Dhn3 locus in Turkish Hordeum spontaneum populations with comparative structural analyses

We analysed Hordeum spontaneum accessions from 21 different locations to understand the genetic diversity of HsDhn3 alleles and effects of single base mutations on the intrinsically disordered structure of the resulting polypeptide (HsDHN3). HsDHN3 was found to be YSK2-type with a low-frequency 6-aa deletion in the beginning of Exon 1. There is relatively high diversity in the intron region of HsDhn3 compared to the two exon regions. We have found subtle differences in K segments led to changes in amino acids chemical properties. Predictions for protein interaction profiles suggest the presence of a protein-binding site in HsDHN3 that coincides with the K1 segment. Comparison of DHN3 to closely related cereals showed that all of them contain a nuclear localization signal sequence flanking to the K1 segment and a novel conserved region located between the S and K1 segments [E(D/T)DGMGGR]. We found that H. vulgare, H. spontaneum, and Triticum urartu DHN3s have a greater number of phosphorylation sites for protein kinase C than other cereal species, which may be related to stress adaptation. Our results show that the nature and extent of mutations in the conserved segments of K1 and K2 are likely to be key factors in protection of cells

Implantation of Mouse Embryonic Stem Cell-Derived Cardiac Progenitor Cells Preserves Function of Infarcted Murine Hearts

Stem cell transplantation holds great promise for the treatment of myocardial infarction injury. We recently described the embryonic stem cell-derived cardiac progenitor cells (CPCs) capable of differentiating into cardiomyocytes, vascular endothelium, and smooth muscle. In this study, we hypothesized that transplanted CPCs will preserve function of the infarcted heart by participating in both muscle replacement and neovascularization. Differentiated CPCs formed functional electromechanical junctions with cardiomyocytes in vitro and conducted action potentials over cm-scale distances. When transplanted into infarcted mouse hearts, CPCs engrafted long-term in the infarct zone and surrounding myocardium without causing teratomas or arrhythmias. The grafted cells differentiated into cross-striated cardiomyocytes forming gap junctions with the host cells, while also contributing to neovascularization. Serial echocardiography and pressure-volume catheterization demonstrated attenuated ventricular dilatation and preserved left ventricular fractional shortening, systolic and diastolic function. Our results demonstrate that CPCs can engraft, differentiate, and preserve the functional output of the infarcted heart

Enhancing security behaviour by supporting the user

Although the role of users in maintaining security is regularly emphasized, this is often not matched by an accompanying level of support. Indeed, users are frequently given insufficient guidance to enable effective security choices and decisions, which can lead to perceived bad behaviour as a consequence. This paper discusses the forms of support that are possible, and seeks to investigate the effect of doing so in practice. Specifically, it presents findings from two experimental studies that investigate how variations in password meter usage and feedback can positively affect the resulting password choices. The first experiment examines the difference between passwords selected by unguided users versus those receiving guidance and alternative forms of feedback (ranging from a traditional password meter through to an emoji-based approach). The findings reveal a 30% drop in weak password choices between unguided and guided usage, with the varying meters then delivering up to 10% further improvement. The second experiment then considers variations in the form of feedback message that users may receive in addition to a meter-based rating. It is shown that by providing richer information (e.g. based upon the time required to crack a password, its relative ranking against other choices, or the probability of it being cracked), users are more motivated towards making strong choices and changing initially weak ones. While the specifics of the experimental findings were focused upon passwords, the discussion also considers the benefits that may be gained by applying the same principles of nudging and guidance to other areas of security in which users are often found to have weak behaviours

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001-2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37 +/- 180.84Tg (i.e., 532.02 +/- 99.71 g/m(2)) during 2001-2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo >DATsrc>MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo. (C) 2015 Elsevier Ltd. All rights reserved