Multifunctional semi-interpenetrating polymer network-nanoencapsulated cathode materials for high-performance lithium-ion batteries

As a promising power source to boost up advent of next-generation ubiquitous era, high-energy density lithium-ion batteries with reliable electrochemical properties are urgently requested. Development of the advanced lithium ion-batteries, however, is staggering with thorny problems of performance deterioration and safety failures. This formidable challenge is highly concerned with electrochemical/thermal instability at electrode material-liquid electrolyte interface, in addition to structural/chemical deficiency of major cell components. Herein, as a new concept of surface engineering to address the abovementioned interfacial issue, multifunctional conformal nanoencapsulating layer based on semi-interpenetrating polymer network (semi-IPN) is presented. This unusual semi-IPN nanoencapsulating layer is composed of thermally-cured polyimide (PI) and polyvinyl pyrrolidone (PVP) bearing Lewis basic site. Owing to the combined effects of morphological uniqueness and chemical functionality (scavenging hydrofluoric acid that poses as a critical threat to trigger unwanted side reactions), the PI/PVP semi-IPN nanoencapsulated-cathode materials enable significant improvement in electrochemical performance and thermal stability of lithium-ion batteries.open

Conductive Cellulose Composites with Low Percolation Threshold for 3D Printed Electronics

We are reporting a 3D printable composite paste having strong thixotropic rheology. The composite has been designed and investigated with highly conductive silver nanowires. The optimized electrical percolation threshold from both simulation and experiment is shown from 0.7 vol. % of silver nanowires which is significantly lower than other composites using conductive nano-materials. Reliable conductivity of 1.19 × 102 S/cm has been achieved from the demonstrated 3D printable composite with 1.9 vol. % loading of silver nanowires. Utilizing the high conductivity of the printable composites, 3D printing of designed battery electrode pastes is demonstrated. Rheology study shows superior printability of the electrode pastes aided by the cellulose\u27s strong thixotropic rheology. The designed anode, electrolyte, and cathode pastes are sequentially printed to form a three-layered lithium battery for the demonstration of a charging profile. This study opens opportunities of 3D printable conductive materials to create printed electronics with the next generation additive manufacturing process

Regulation of mitochondrial morphogenesis by annexin a6.

Mitochondrial homeostasis is critical in meeting cellular energy demands, shaping calcium signals and determining susceptibility to apoptosis. Here we report a role for anxA6 in the regulation of mitochondrial morphogenesis, and show that in cells lacking anxA6 mitochondria are fragmented, respiration is impaired and mitochondrial membrane potential is reduced. In fibroblasts from AnxA6(-/-) mice, mitochondrial Ca(2+) uptake is reduced and cytosolic Ca(2+) transients are elevated. These observations led us to investigate possible interactions between anxA6 and proteins with roles in mitochondrial fusion and fission. We found that anxA6 associates with Drp1 and that mitochondrial fragmentation in AnxA6(-/-) fibroblasts was prevented by the Drp1 inhibitor mdivi-1. In normal cells elevation of intracellular Ca(2+) disrupted the interaction between anxA6 and Drp1, displacing anxA6 to the plasma membrane and promoting mitochondrial fission. Our results suggest that anxA6 inhibits Drp1 activity, and that Ca(2+)-binding to anxA6 relieves this inhibition to permit Drp1-mediated mitochondrial fission

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Comparative structural bioinformatics analysis of Bacillus amyloliquefaciens chemotaxis proteins within Bacillus subtilis group

Chemotaxis is a process in which bacteria sense their chemical environment and move towards more favorable conditions. Since plant colonization by bacteria is a multifaceted process which requires a response to the complex chemical environment, a finely tuned and sensitive chemotaxis system is needed. Members of the Bacillus subtilis group including Bacillus amyloliquefaciens are industrially important, for example, as bio-pesticides. The group exhibits plant growth-promoting characteristics, with different specificity towards certain host plants. Therefore, we hypothesize that while the principal molecular mechanisms of bacterial chemotaxis may be conserved, the bacterial chemotaxis system may need an evolutionary tweaking to adapt it to specific requirements, particularly in the process of evolution of free-living soil organisms, towards plant colonization behaviour. To date, almost nothing is known about what parts of the chemotaxis proteins are subjected to positive amino acid substitutions, involved in adjusting the chemotaxis system of bacteria during speciation. In this novel study, positively selected and purified sites of chemotaxis proteins were calculated, and these residues were mapped onto homology models that were built for the chemotaxis proteins, in an attempt to understand the spatial evolution of the chemotaxis proteins. Various positively selected amino acids were identified in semi-conserved regions of the proteins away from the known active sites

Association analysis identifies 65 new breast cancer risk loci

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH Grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combining of the GWAS data was supported in part by The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE, part of the GAME-ON initiative)

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs

Combined measurement of the Higgs boson mass from the H → γγ and H → ZZ∗ → 4ℓ decay channels with the ATLAS detector using √s = 7, 8, and 13 TeV pp collision data

A measurement of the mass of the Higgs boson combining the H → Z Z ∗ → 4 ℓ and H → γ γ decay channels is presented. The result is based on 140     fb − 1 of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a center-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, performed at center-of-mass energies of 7 and 8 TeV, yielding a Higgs boson mass of 125.11 ± 0.09 ( stat ) ± 0.06 ( syst ) = 125.11 ± 0.11     GeV . This corresponds to a 0.09% precision achieved on this fundamental parameter of the Standard Model of particle physics