Cotunneling in the \nu = 5/2 fractional quantum Hall regime

We show that cotunneling in the 5/2 fractional quantum Hall regime allows us to test the Moore-Read wave function, proposed for this regime, and to probe the nature of the fractional charge carriers. We calculate the cotunneling current for electrons that tunnel between two quantum Hall edge states via a quantum dot and for quasiparticles with fractional charges e/4 and e/2 that tunnel via an antidot. While electron cotunneling is strongly suppressed, the quasiparticle tunneling shows signatures characteristic of the Moore-Read state. For comparison, we also consider cotunneling between Laughlin states, and find that electron transport between Moore-Read states and between Laughlin states at filling factor 1/3 have identical voltage dependences

High-resolution in situ hybridization analysis on the chromosomal interval 61C7-61C8 of Drosophila melanogaster reveals interbands as open chromatin domains

Eukaryotic chromatin is organized in contiguous domains that differ in protein binding, histone modifications, transcriptional activity, and in their degree of compaction. Genome-wide comparisons suggest that, overall, the chromatin organization is similar in different cells within an organism. Here, we compare the structure and activity of the 61C7-61C8 interval in polytene and diploid cells of Drosophila. By in situ hybridization on polytene chromosomes combined with high-resolution microscopy, we mapped the boundaries of the 61C7-8 interband and of the 61C7 and C8 band regions, respectively. Our results demonstrate that the 61C7-8 interband is significantly larger than estimated previously. This interband extends over 20 kbp and is in the range of the flanking band domains. It contains several active genes and therefore can be considered as an open chromatin domain. Comparing the 61C7-8 structure of Drosophila S2 cells and polytene salivary gland cells by ChIP for chromatin protein binding and histone modifications, we observe a highly consistent domain structure for the proximal 13 kbp of the domain in both cell types. However, the distal 7 kbp of the open domain differs in protein binding and histone modification between both tissues. The domain contains four protein-coding genes in the proximal part and two noncoding transcripts in the distal part. The differential transcriptional activity of one of the noncoding transcripts correlates with the observed differences in the chromatin structure between both tissues. The significance of our findings for the organization and structure of open chromatin domains will be discussed

Mikromagnetische Simulationen von kleinen Strukturen

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Targeting an Essential GTPase Obg for the Development of Broad-Spectrum Antibiotics

A promising new drug target for the development of novel broad-spectrum antibiotics is the highly conserved small GTPase Obg (YhbZ, CgtA), a protein essential for the survival of all bacteria including Neisseria gonorrhoeae (GC). GC is the agent of gonorrhea, a prevalent sexually transmitted disease resulting in serious consequences on reproductive and neonatal health. A preventive anti-gonorrhea vaccine does not exist, and options for effective antibiotic treatments are increasingly limited. To address the dire need for alternative antimicrobial strategies, we have designed and optimized a 384-well GTPase assay to identify inhibitors of Obg using as a model Obg protein from GC, ObgGC. The assay was validated with a pilot screen of 40,000 compounds and achieved an average Z’ value of 0.58 ± 0.02, which suggests a robust assay amenable to high-throughput screening. We developed secondary assessments for identified lead compounds that utilize the interaction between ObgGC and fluorescent guanine nucleotide analogs, mant-GTP and mant-GDP, and an ObgGC variant with multiple alterations in the G-domains that prevent nucleotide binding. To evaluate the broad-spectrum potential of ObgGC inhibitors, Obg proteins of Klebsiella pneumoniae and methicillin-resistant Staphylococcus aureus were assessed using the colorimetric and fluorescence-based activity assays. These approaches can be useful in identifying broad-spectrum Obg inhibitors and advancing the therapeutic battle against multidrug resistant bacteria

Lifelong learning in evolving graphs with limited labeled data and unseen class detection

Large-scale graph data in the real-world are often dynamic rather than static. The data are changing with new nodes, edges, and even classes appearing over time, such as in citation networks and research-and-development collaboration networks. Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data. In this work, we employ a two-step procedure to explore how GNNs can be incrementally adapted to new unseen graph data. First, we analyze the verge between transductive and inductive learning on standard benchmark datasets. After inductive pretraining, we add unlabeled data to the graph and show that the models are stable. Then, we explore the case of continually adding more and more labeled data, while considering cases, where not all past instances are annotated with class labels. Furthermore, we introduce new classes while the graph evolves and explore methods that automatically detect instances from previously unseen classes. In order to deal with evolving graphs in a principled way, we propose a lifelong learning framework for graph data along with an evaluation protocol. In this framework, we evaluate representative GNN architectures. We observe that implicit knowledge within model parameters becomes more important when explicit knowledge, i.e., data from past tasks, is limited. We find that in open-world node classification, the data from surprisingly few past tasks are sufficient to reach the performance reached by remembering data from all past tasks. In the challenging task of unseen class detection, we find that using a weighted cross-entropy loss is important for stabilit

BDNF Contributes to the Genetic Variance of Milk Fat Yield in German Holstein Cattle

The gene encoding the brain-derived neurotrophic factor (BDNF) has been repeatedly associated with human obesity. As such, it could also contribute to the regulation of energy partitioning and the amount of secreted milk fat during lactation, which plays an important role in milk production in dairy cattle. Therefore, we performed an association study using estimated breeding values (EBVs) of bulls and yield deviations of German Holstein dairy cattle to test the effect of BDNF on milk fat yield (FY). A highly significant effect (corrected p-value = 3.362 × 10−4) was identified for an SNP 168 kb up-stream of the BDNF transcription start. The association tests provided evidence for an additive allele effect of 5.13 kg of fat per lactation on the EBV for milk FY in bulls and 6.80 kg of fat of the own production performance in cows explaining 1.72 and 0.60% of the phenotypic variance in the analyzed populations, respectively. The analyses of bulls and cows consistently showed three haplotype groups that differed significantly from each other, suggesting at least two different mutations in the BDNF region affecting the milk FY. The FY increasing alleles also had low but significant positive effects on protein and total milk yield which suggests a general role of the BDNF region in energy partitioning, rather than a specific regulation of fat synthesis. The results obtained in dairy cattle suggest similar effects of BDNF on milk composition in other species, including man

Demonstrating the high Voc potential of PEDOT:PSS/c-Si heterojunctions on solar cells

In this study, we demonstrate the high surface passivation quality of PEDOT:PSS/c-Si junctions for the first time on solar cell level, reaching a record high Voc value of 688 mV after full-area metallization of the PEDOT:PSS. We achieve this by combining the PEDOT:PSS hole-selective layer at the rear of the crystalline silicon wafer with a well-passivating electron-selective a-Si:H(i/n) layer stack at the front. Our results clearly prove the excellent hole selectivity of PEDOT:PSS on crystalline silicon. © 2017 The Authors. Published by Elsevier Ltd

Functional and Structural Studies on the \u3cem\u3eNeisseria gonorrhoeae\u3c/em\u3e GmhA, the First Enzyme in the \u3cem\u3eglycero-manno\u3c/em\u3e-heptose Biosynthesis Pathways, Demonstrate a Critical Role in Lipooligosaccharide Synthesis and Gonococcal Viability

Sedoheptulose-7-phosphate isomerase, GmhA, is the first enzyme in the biosynthesis of nucleotide-activated-glycero-manno-heptoses and an attractive, yet underexploited, target for development of broad-spectrum antibiotics. We demonstrated that GmhA homologs in Neisseria gonorrhoeae and N. meningitidis (hereafter called GmhAGC and GmhANM, respectively) were interchangeable proteins essential for lipooligosaccharide (LOS) synthesis, and their depletion had adverse effects on neisserial viability. In contrast, the Escherichia coli ortholog failed to complement GmhAGC depletion. Furthermore, we showed that GmhAGC is a cytoplasmic enzyme with induced expression at mid-logarithmic phase, upon iron deprivation and anaerobiosis, and conserved in contemporary gonococcal clinical isolates including the 2016 WHO reference strains. The untagged GmhAGCcrystallized as a tetramer in the closed conformation with four zinc ions in the active site, supporting that this is most likely the catalytically active conformation of the enzyme. Finally, site-directed mutagenesis studies showed that the active site residues E65 and H183 were important for LOS synthesis but not for GmhAGC function in bacterial viability. Our studies bring insights into the importance and mechanism of action of GmhA and may ultimately facilitate targeting the enzyme with small molecule inhibitors

Surface Slip During Large Owens Valley Fault Earthquakes

The 1872 Owens Valley earthquake is the third largest known historical earthquake in California. Relatively sparse field data and a complex rupture trace, however, inhibited attempts to fully resolve the slip distribution and reconcile the total moment release. We present a new, comprehensive record of surface slip based on lidar and field investigation, documenting 162 new measurements of laterally and vertically displaced landforms for 1872 and prehistoric Owens Valley earthquakes. Our lidar analysis uses a newly developed analytical tool to measure fault slip based on cross‐correlation of sublinear topographic features and to produce a uniquely shaped probability density function (PDF) for each measurement. Stacking PDFs along strike to form cumulative offset probability distribution plots (COPDs) highlights common values corresponding to single and multiple‐event displacements. Lateral offsets for 1872 vary systematically from ∼1.0 to 6.0 m and average 3.3 ± 1.1 m (2σ). Vertical offsets are predominantly east‐down between ∼0.1 and 2.4 m, with a mean of 0.8 ± 0.5 m. The average lateral‐to‐vertical ratio compiled at specific sites is ∼6:1. Summing displacements across subparallel, overlapping rupture traces implies a maximum of 7–11 m and net average of 4.4 ± 1.5 m, corresponding to a geologic Mw ∼7.5 for the 1872 event. We attribute progressively higher‐offset lateral COPD peaks at 7.1 ± 2.0 m, 12.8 ± 1.5 m, and 16.6 ± 1.4 m to three earlier large surface ruptures. Evaluating cumulative displacements in context with previously dated landforms in Owens Valley suggests relatively modest rates of fault slip, averaging between ∼0.6 and 1.6 mm/yr (1σ) over the late Quaternary