bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lithium metal stripping beneath the solid electrolyte interphase
Authors: Shi Feifei , Pei Allen , Boyle David Thomas , Xie Jin , Yu Xiaoyun , Zhang Xiaokun , Cui Yi 
Published: August 2018

Significance
This study explores the stripping of lithium anodes under various current densities and in different liquid electrolyte systems. We discovered nanovoid formation between the lithium and the solid electrolyte interphase (SEI). Lithium polarization behavior has been systematically investigated with a three-electrode system and ultramicroelectrode. The diffusion and migration of lithium cations across the SEI have been determined to be the main contributors to the stripping overpotential. Two modes of stripping are proposed based on the passivation condition of lithium: stripping on passivated lithium and pitting on lithium after SEI layer breakdown. The present work provides a mechanistic explanation of Coulombic efficiency decay under high charging current density. We also demonstrate that metallurgical factors greatly accelerate the local dissolution of lithium.
Robust nanoscopy of a synaptic protein in living mice by organic-fluorophore labeling
Authors: Masch Jennifer-Magdalena , Steffens Heinz , Fischer Joachim , Engelhardt Johann , Hubrich Jasmine , Keller-Findeisen Jan , D’Este Elisa , Urban Nicolai T. , Grant Seth G. N. , Sahl Steffen J. , Kamin Dirk , Hell Stefan W. 
Published: August 2018

Significance
In vivo fluorescence microscopy with resolution well beyond the diffraction limit entails complexities that challenge the attainment of sufficient image brightness and contrast. These challenges have so far hampered investigations of the nanoscale distributions of synaptic proteins in the living mouse. Here, we describe a combination of stimulated emission depletion microscopy and endogenous protein labeling, providing high-quality in vivo data of the key scaffolding protein PSD95 at the postsynaptic membrane, which frequently appeared in extended distributions rather than as isolated nanoclusters. Operating in the far-red to near-IR wavelength range, this combination promises reduced photostress compared with prior in vivo nanoscopy at much shorter wavelengths.
Volatile element evolution of chondrules through time
Authors: Mahan Brandon , Moynier Frédéric , Siebert Julien , Gueguen Bleuenn , Agranier Arnaud , Pringle Emily A. , Bollard Jean , Connelly James N. , Bizzarro Martin 
Published: August 2018

SignificanceWe present time-anchored elemental abundance data for some of the Solar System’s first solids by tracking Pb−Pb dated chondrule compositions. Volatile element contents generally rise, while redox conditions (based on chondrule Mn/Na ratios) decline beginning ∼1 My after Solar System formation (∼4,567 Ma). These results reflect a continued rise in volatile element contents and their fugacities during chondrule recycling, and early water influx to the inner Solar System followed by its express removal. These observations support the early formation of Mars under oxidizing condition and Earth’s protracted growth under more reducing conditions in an environment increasing in volatile contents with time, while also calling into question the coupling of water and volatile elements during Solar System evolution.
Degradation and remobilization of endogenous retroviruses by recombination during the earliest stages of a germ-line invasion
Authors: Löber Ulrike , Hobbs Matthew , Dayaram Anisha , Tsangaras Kyriakos , Jones Kiersten , Alquezar-Planas David E. , Ishida Yasuko , Meers Joanne , Mayer Jens , Quedenau Claudia , Chen Wei , Johnson Rebecca N. , Timms Peter , Young Paul R. , Roca Alfred L. , Greenwood Alex D. 
Published: August 2018

SignificanceEndogenous retroviruses (ERVs) are proviral sequences that result from host germ-line invasion by exogenous retroviruses. The majority of ERVs are degraded. Using the koala retrovirus (KoRV) as a model system, we demonstrate that recombination with an ancient koala retroelement disables KoRV, and that recombination occurs frequently and early in the invasion process. Recombinant KoRVs (recKoRVs) are then able to proliferate in the koala germ line. This may in part explain the generally degraded nature of ERVs in vertebrate genomes and suggests that degradation via recombination is one of the earliest processes shaping retroviral genomic invasions.
Earing prediction of AA 2008-T4 with anisotropic Drucker yield function based on the second and third stress invariants
Authors: Zhang Saijun , Lou Yanshan , Yoon Jeong Whan 
Published: August 2018

Abstract
This paper applies anisotropic Drucker yield function [14] (Lou and Yoon, 2018, Int. J. Plasticity 101, 125-55) to predict earing profile after cup deep drawing of AA 2008-T4. The new yield function is implemented into ABAQUS/Explicit using semi-implicit integration algorithm to calculate the increment of plastic strain. Both associated and non-associated flow rules are incorporated in this study. The predicted anisotropy and cup height profile are compared with the experimental results and those predicted from the Hill48, Yld91 and Yld2004-18p yield functions. It is observed that the earing profile predicted from the new yield function shows high accuracy. The computation time is also compared to investigate the computation cost of different yield functions. The comparison reveals that it takes the shortest time for the Hill48 function, the anisotropic Drucker yield function reduces 30%∼40% of computation cost compared with the Yld91 and Yld2004-18p functions. It is concluded from the simulation of cup deep drawing that the new yield function can provide high accurate numerical analysis of plastic deformation for anisotropic metals with competitive computation cost.
Impact of similarity metrics on single-cell RNA-seq data clustering
Authors: Kim Taiyun , Chen Irene Rui , Lin Yingxin , Wang Andy Yi-Yang , Yang Jean Yee Hwa , Yang Pengyi 
Published: August 2018

AbstractAdvances in high-throughput sequencing on single-cell gene expressions [single-cell RNA sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from complex samples. A common goal in scRNA-seq data analysis is to discover and characterise cell types, typically through clustering methods. The quality of the clustering therefore plays a critical role in biological discovery. While numerous clustering algorithms have been proposed for scRNA-seq data, fundamentally they all rely on a similarity metric for categorising individual cells. Although several studies have compared the performance of various clustering algorithms for scRNA-seq data, currently there is no benchmark of different similarity metrics and their influence on scRNA-seq data clustering. Here, we compared a panel of similarity metrics on clustering a collection of annotated scRNA-seq datasets. Within each dataset, a stratified subsampling procedure was applied and an array of evaluation measures was employed to assess the similarity metrics. This produced a highly reliable and reproducible consensus on their performance assessment. Overall, we found that correlation-based metrics (e.g. Pearson’s correlation) outperformed distance-based metrics (e.g. Euclidean distance). To test if the use of correlation-based metrics can benefit the recently published clustering techniques for scRNA-seq data, we modified a state-of-the-art kernel-based clustering algorithm (SIMLR) using Pearson’s correlation as a similarity measure and found significant performance improvement over Euclidean distance on scRNA-seq data clustering. These findings demonstrate the importance of similarity metrics in clustering scRNA-seq data and highlight Pearson’s correlation as a favourable choice. Further comparison on different scRNA-seq library preparation protocols suggests that they may also affect clustering performance. Finally, the benchmarking framework is available at http://www.maths.usyd.edu.au/u/SMS/bioinformatics/software.html.
Global importance of RNA secondary structures in protein-coding sequences
Authors: Fricke Markus , Gerst Ruman , Ibrahim Bashar , Niepmann Michael , Marz Manja 
Published: August 2018

Abstract

Motivation
The protein-coding sequences of messenger RNAs are the linear template for translation of the gene sequence into protein. Nevertheless, the RNA can also form secondary structures by intramolecular base-pairing.

Results
We show that the nucleotide distribution within codons is biased in all taxa of life on a global scale. Thereby, RNA secondary structures that require base-pairing between the position 1 of a codon with the position 1 of an opposing codon (here named RNA secondary structure class c1) are under-represented. We conclude that this bias may result from the co-evolution of codon sequence and mRNA secondary structure, suggesting that RNA secondary structures are generally important in protein-coding regions of mRNAs. The above result also implies that codon position 2 has a smaller influence on the amino acid choice than codon position 1.

Supplementary information
Supplementary data are available at Bioinformatics online.
LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics
Authors: Fahy Eoin , Alvarez-Jarreta Jorge , Brasher Christopher J , Nguyen An , Hawksworth Jade I , Rodrigues Patricia , Meckelmann Sven , Allen Stuart M , O'Donnell Valerie B 
Published: August 2018

Abstract

Summary
We present LipidFinder online, hosted on the LIPID MAPS website, as a liquid chromatography/mass spectrometry (LC/MS) workflow comprising peak filtering, MS searching and statistical analysis components, highly customized for interrogating lipidomic data. The online interface of LipidFinder includes several innovations such as comprehensive parameter tuning, a MS search engine employing in-house customized, curated and computationally generated databases and multiple reporting/display options. A set of integrated statistical analysis tools which enable users to identify those features which are significantly-altered under the selected experimental conditions, thereby greatly reducing the complexity of the peaklist prior to MS searching is included. LipidFinder is presented as a highly flexible, extensible user-friendly online workflow which leverages the lipidomics knowledge base and resources of the LIPID MAPS website, long recognized as a leading global lipidomics portal.

Availability and implementation
LipidFinder on LIPID MAPS is available at: http://www.lipidmaps.org/data/LF.
GlycanAnalyzer: software for automated interpretation of N-glycan profiles after exoglycosidase digestions
Authors: Walsh Ian , Nguyen-Khuong Terry , Wongtrakul-Kish Katherine , Tay Shi Jie , Chew Daniel , José Tasha , Taron Christopher H , Rudd Pauline M 
Published: August 2018

Abstract

Summary
Many eukaryotic proteins are modified by N-glycans. Liquid chromatography (ultra-performance –UPLC and high-performance–HPLC) coupled with mass spectrometry (MS) is conventionally used to characterize N-glycan structures. Software can automatically assign glycan structures by matching their observed retention times and masses with standardized values in reference databases. However, more precise confirmation of N-glycan structures can be derived using exoglycosidases, enzymes that remove specific monosaccharides from glycans. Exoglycosidase removal of monosaccharides results in signature peak shifts, in both UPLC and MS1, yielding an effective way to verify N-glycan structure with high detail (down to the position and isomeric linkage of each monosaccharide). Because manual interpretation of exoglycosidase data is complex and time consuming, we developed GlycanAnalyzer, a web application that pattern matches N-glycan peak shifts following exoglycosidase digestion and automates structure assignments. GlycanAnalyzer significantly improves assignment accuracy over other auto-assignment methods on tests with a monoclonal antibody and four glycan standards (100% versus 82% for the next best software). By automating data interpretation, GlycanAnalyzer enables the easier use of exoglycosidases to precisely define N-glycan structure.

Availability and implementation
http://glycananalyzer.neb.com. Datasets available online.

Supplementary information
Supplementary data are available at Bioinformatics online.
KEDDY: a knowledge-based statistical gene set test method to detect differential functional protein–protein interactions
Authors: Jung Sungwon 
Published: August 2018

AbstractMotivationIdentifying differential patterns between conditions is a popular approach to understanding the discrepancy between different biological contexts. Although many statistical tests were proposed for identifying gene sets with differential patterns based on different definitions of differentiality, few methods were suggested to identify gene sets with differential functional protein networks due to computational complexity.ResultsWe propose a method of Knowledge-based Evaluation of Dependency DifferentialitY (KEDDY), which is a statistical test for differential functional protein networks of a set of genes between two conditions with utilizing known functional protein–protein interaction information. Unlike other approaches focused on differential expressions of individual genes or differentiality of individual interactions, KEDDY compares two conditions by evaluating the probability distributions of functional protein networks based on known functional protein–protein interactions. The method has been evaluated and compared with previous methods through simulation studies, where KEDDY achieves significantly improved performance in accuracy and speed than the previous method that does not use prior knowledge and better performance in identifying gene sets with differential interactions than other methods evaluating changes in gene expressions. Applications to cancer data sets show that KEDDY identifies alternative cancer subtype-related differential gene sets compared to other differential expression-based methods, and the results also provide detailed gene regulatory information that drives the differentiality of the gene sets.Availability and implementationThe Java implementation of KEDDY is freely available to non-commercial users at https://sites.google.com/site/sjunggsm/keddy.Supplementary informationSupplementary data are available at Bioinformatics online.
Processing of big heterogeneous genomic datasets for tertiary analysis of Next Generation Sequencing data
Authors: Masseroli Marco , Canakoglu Arif , Pinoli Pietro , Kaitoua Abdulrahman , Gulino Andrea , Horlova Olha , Nanni Luca , Bernasconi Anna , Perna Stefano , Stamoulakatou Eirini , Ceri Stefano 
Published: August 2018

Abstract

Motivation
We previously proposed a paradigm shift in genomic data management, based on the Genomic Data Model (GDM) for mediating existing data formats and on the GenoMetric Query Language (GMQL) for supporting, at a high level of abstraction, data extraction and the most common data-driven computations required by tertiary data analysis of Next Generation Sequencing datasets. Here, we present a new GMQL-based system with enhanced accessibility, portability, scalability and performance.

Results
The new system has a well-designed modular architecture featuring: (i) an intermediate representation supporting many different implementations (including Spark, Flink and SciDB); (ii) a high-level technology-independent repository abstraction, supporting different repository technologies (e.g., local file system, Hadoop File System, database or others); (iii) several system interfaces, including a user-friendly Web-based interface, a Web Service interface, and a programmatic interface for Python language. Biological use case examples, using public ENCODE, Roadmap Epigenomics and TCGA datasets, demonstrate the relevance of our work.

Availability and implementation
The GMQL system is freely available for non-commercial use as open source project at: http://www.bioinformatics.deib.polimi.it/GMQLsystem/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Precision Surveillance for Viral Respiratory Pathogens: Virome Capture Sequencing for the Detection and Genomic Characterization of Severe Acute Respiratory Infection in Uganda
Authors: Cummings Matthew J , Tokarz Rafal , Bakamutumaho Barnabas , Kayiwa John , Byaruhanga Timothy , Owor Nicholas , Namagambo Barbara , Wolf Allison , Mathema Barun , Lutwama Julius J , Schluger Neil W , Lipkin W Ian , O’Donnell Max R 
Published: August 2018

Abstract

Background
Precision public health is a novel set of methods to target disease prevention and mitigation interventions to high-risk subpopulations. We applied a precision public health strategy to syndromic surveillance for severe acute respiratory infection (SARI) in Uganda by combining spatiotemporal analytics with genomic sequencing to detect and characterize viral respiratory pathogens with epidemic potential.

Methods
Using a national surveillance network we identified patients with unexplained, influenza-negative SARI from 2010 to 2015. Spatiotemporal analyses were performed retrospectively to identify clusters of unexplained SARI. Within clusters, respiratory viruses were detected and characterized in naso- and oropharyngeal swab samples using a novel oligonucleotide probe capture (VirCapSeq-VERT) and high-throughput sequencing platform. Linkage to conventional epidemiologic strategies further characterized transmission dynamics of identified pathogens.

Results
Among 2901 unexplained SARI cases, 9 clusters were detected, accounting for 301 (10.4%) cases. Clusters were more likely to occur in urban areas and during biannual rainy seasons. Within detected clusters, we identified an unrecognized outbreak of measles-associated SARI; sequence analysis implicated cocirculation of endemic genotype B3 and genotype D4 likely imported from England. We also detected a likely nosocomial SARI cluster associated with a novel picobirnavirus most closely related to swine and dromedary viruses.

Conclusions
Using a precision approach to public health surveillance, we detected and characterized the genomics of vaccine-preventable and zoonotic respiratory viruses associated with clusters of severe respiratory infections in Uganda. Future studies are needed to assess the feasibility, scalability, and impact of applying similar approaches during real-time public health surveillance in low-income settings.
Deployment and Smokeless Tobacco Use Among Active Duty Service Members in the U.S. Military
Authors: Lin Jie , Zhu Kangmin , Soliván-Ortiz Aida M , Larsen Stacy L , Schneid Thomas R , Shriver Craig D , Lee Sukhyung 
Published: August 2018

Abstract

Introduction
The prevalence of smokeless tobacco use among U.S. active duty service members has been much higher than in the U.S. general population. The association between deployment and smokeless tobacco use has not been well studied. We investigated the association between deployment and smokeless tobacco use among U.S. active duty service members. We also evaluated the modification effects from other factors related to smokeless tobacco use on the deployment-smokeless tobacco use association.

Materials and Methods
Eligible active duty service members stationed at two military installations (Fort Bragg, NC, USA and Lackland Air Force Base, TX, USA) were recruited from July 2015 to May 2016. Each participant completed a self-administered questionnaire. Multivariable logistic regression was used to assess the association between deployment and smokeless tobacco use and estimated odds ratio (OR) and 95% confidence interval (CI). Stratified analysis was performed to evaluate modification effects from other commonly known factors related to smokeless tobacco use in military, specifically, cigarette smoking status, use among family members (family history of use), perception of harm, and use among military peers.

Results
Out of 2,465 study participants who completed the questionnaire, 548 were smokeless tobacco users. Service members who had been deployed to a combat zone had 1.39 fold (95% CI = 1.03–1.87) increased odds of using smokeless tobacco than those who never deployed to a combat zone. The odds of smokeless tobacco use among those who had been deployed once, twice, three times and four or more times to a combat zone were 1.27 (95% CI = 0.91–1.78), 1.30 (95% CI = 0.85–1.99), 2.49 (95% CI = 1.45–4.28), and 2.88 (95% CI = 1.71–4.86), respectively, with a significant dose–response trend (p for trend &lt;0.0001). Further, subjects who served in combat units during deployment exhibited more than two-fold increased odds of use as compared with those who had never been deployed (OR = 2.03, 95% CI = 1.41–2.93). In stratified analysis, the association between deployment and smokeless tobacco use was only present among subjects who never smoked cigarettes, those without family history of smokeless tobacco use, and those who had low perception of harm of use.

Conclusions
Military deployment was associated with smokeless tobacco use among active service members. However, the influence of military deployment on smokeless tobacco use was not equally strong on all service members. Subjects who never smoked cigarettes, who had no family history of use and who had low perception of harm were the most susceptible subgroups to deployment-related smokeless tobacco use. This study has implications to identify high-risk subgroups to reduce smokeless tobacco use in the U.S. military.
Flying in Cyberspace: Policing Global Travel Fraud
Authors: Hutchings Alice 
Published: August 2018

Abstract
Airline tickets that have been obtained illicitly represent a truly global crime. The travel industry and law enforcement have been attempting to address travel fraud for some time. Airline tickets can be obtained using various cybercrime methods. They are traded and advertised on online blackmarkets and through fraudulent travel agencies. This research is qualitative in nature, informed by interviews with law enforcement and industry stakeholders, as well as the analysis of a marketplace where fraudulently obtained tickets are traded. This research considers: the nature of the criminal market for fraudulently obtained tickets, the involvement of co-offending and organized crime, the geographic nature of travel fraud, and the ways in which those supplying fraudulently obtained tickets try to avoid detection. Also considered is how the nature of travel fraud has changed over time, ways in which it may continue to change, and the challenges faced by law enforcement.
Precision Physical Therapy: Exercise, the Epigenome, and the Heritability of Environmentally Modified Traits
Authors: Woelfel Jessica R , Dudley-Javoroski Shauna , Shields Richard K 
Published: August 2018

AbstractOne of the newest frontiers of physical therapy is the field of epigenetics, which examines how pervasive environmental factors such as exercise regulate the expression of genes. The epigenome may be one of the most powerful systems through which exercise exerts its beneficial effects on health and longevity. Large epidemiology studies show that individuals who regularly exercise demonstrate a lower “epigenetic age,” experience fewer metabolic diseases, and enjoy greater longevity. However, the dose, mode, intensity, and duration of exercise required to achieve a healthy epigenetic profile is unknown. As experts in exercise prescription, physical therapists are ideally suited to contribute to the discovery of this dose-response relationship. This perspective makes a case for the genesis of “precision physical therapy,” which capitalizes on epigenetic discoveries to optimize exercise-based interventions. Summarized here is the emerging body of knowledge supporting epigenetic adaptations to exercise in humans, including the intriguing possibility that these environmentally modified traits could be passed down to offspring. In the future, it is likely that epigenetic data will enhance our understanding of individual disease risk and individual response to prescribed exercise. The profession of physical therapy must be alert to new epigenetic knowledge that can enhance the specificity and efficacy of movement-based treatments.