Atomic force microscopy cantilever dynamics in liquid in the presence of tip sample interaction

We analyze the dynamics of an atomic force microscopy (AFM) cantilever oscillating in liquid at subnanometer amplitude in the presence of tip-sample interaction. We present AFM measurements of oscillatory solvation forces for octamethylcyclotetrasiloxane on highly oriented pyrolitic graphite and compare them to a harmonic oscillator model that incorporates the effect of the finite driving force for a typical AFM configuration with acoustic driving. In contrast to the general belief, we find—in both experiments and modeling—that the tip-sample interaction gives rise to a pronounced signature in the phase at driving frequencies well below resonance

Confinement-dependent damping in a layered liquid

We present atomic force microscopy (AFM) measurements of the conservative oscillatory solvation forces and the damping in confined films of octamethylcyclotetrasiloxane using small amplitude modulation with magnetic driving. We find distinct maxima in the interaction damping upon probing the discrete molecular layers, supporting earlier observations of the same phenomenon using AFM with an acoustic driving scheme. The maxima in the damping are located at the same tip–surface separation as the maxima in the conservative oscillatory interaction stiffnes

The Muonium Atom as a Probe of Physics beyond the Standard Model

The observed interactions between particles are not fully explained in the successful theoretical description of the standard model to date. Due to the close confinement of the bound state muonium ($M = \mu^+ e^-$) can be used as an ideal probe of quantum electrodynamics and weak interaction and also for a search for additional interactions between leptons. Of special interest is the lepton number violating process of sponteanous conversion of muonium to antimuonium.Comment: 15 pages,6 figure

Comparison of sequencing methods and data processing pipelines for whole genome sequencing and minority single nucleotide variant (mSNV) analysis during an influenza A/H5N8 outbreak

As high-throughput sequencing technologies are becoming more widely adopted for analysing pathogens in disease outbreaks there needs to be assurance that the different sequencing technologies and approaches to data analysis will yield reliable and comparable results. Conversely, understanding where agreement cannot be achieved provides insight into the limitations of these approaches and also allows efforts to be focused on areas of the process that need improvement. This manuscript describes the next-generation sequencing of three closely related viruses, each analysed using different sequencing strategies, sequencing instruments and data processing pipelines. In order to determine the comparability of consensus sequences and minority (sub-consensus) single nucleotide variant (mSNV) identification, the biological samples, the sequence data from 3 sequencing platforms and the *.bam quality-trimmed alignment files of raw data of 3 influenza A/H5N8 viruses were shared. This analysis demonstrated that variation in the final result could be attributed to all stages in the process, but the most critical were the well-known homopolymer errors introduced by 454 sequencing, and the alignment processes in the different data processing pipelines which affected the consistency of mSNV detection. However, homopolymer errors aside, there was generally a good agreement between consensus sequences that were obtained for all combinations of sequencing platforms and data processing pipelines. Nevertheless, minority variant analysis will need a different level of careful standardization and awareness about the possible limitations, as shown in this study

DN interaction from meson exchange

A model of the DN interaction is presented which is developed in close analogy to the meson-exchange KbarN potential of the Juelich group utilizing SU(4) symmetry constraints. The main ingredients of the interaction are provided by vector meson (rho, omega) exchange and higher-order box diagrams involving D*N, D\Delta, and D*\Delta intermediate states. The coupling of DN to the pi-Lambda_c and pi-Sigma_c channels is taken into account. The interaction model generates the Lambda_c(2595) resonance dynamically as a DN quasi-bound state. Results for DN total and differential cross sections are presented and compared with predictions of an interaction model that is based on the leading-order Weinberg-Tomozawa term. Some features of the Lambda_c(2595) resonance are discussed and the role of the near-by pi-Sigma_c threshold is emphasized. Selected predictions of the orginal KbarN model are reported too. Specifically, it is pointed out that the model generates two poles in the partial wave corresponding to the Lambda(1405) resonance.Comment: 14 pages, 8 figure

Department of Defense prostate cancer clinical trials consortium: A new instrument for prostate cancer clinical research

Background: In 2005, the US Department of Defense, through the US Army Medical Research and Materiel Command, Office of the Congressionally Directed Medical Research Programs, created a funding mechanism to form a clinical trials consortium to conduct phase I and II studies in prostate cancer. This is the first report of the Prostate Cancer Clinical Trials Consortium (PCCTC). Patients and Methods: The Department of Defense award supports a consortium of 10 prostate cancer research centers. Memorial Sloan-Kettering Cancer Center was awarded the Coordinating Center grant for the consortium and charged with creating an infrastructure to conduct early-phase multicenter clinical trials. Each participating center was required to introduce ≥ 1 clinical trial per year and maintain accrual of a minimum of 35 patients per year. Results: The PCCTC was launched in 2006 and now encompasses 10 leading prostate cancer research centers. Fifty-one trials have been opened, and 1386 patients have been accrued at member sites. Members share an online clinical trial management system for protocol tracking, electronic data capture, and data storage. A legal framework has been instituted, and standard operating procedures, an administrative structure, editorial support, centralized budgeting, and mechanisms for scientific review are established. Conclusion: The PCCTC fulfills a congressional directive to create a clinical trials instrument dedicated to early-phase prostate cancer studies. The member institutions have built an administrative, informatics, legal, financial, statistical, and scientific infrastructure to support this endeavor. Clinical trials are open and accruing in excess of federally mandated goals

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants