bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antimicrobial resistance in non-O157 Shiga-toxin producing Escherichia coli
Authors: Gentle Amy , Jenkins Claire , Day Martin , Greig David , Painset Anais , Do Nascimento Vivienne 
Published: April 2019

Objectives
Shiga toxin-producing Escherichia coli (STEC) are zoonotic pathogens that cause severe gastrointestinal disease in humans. Monitoring antimicrobial resistance (AMR) in STEC from symptomatic human cases may provide evidence for the extent of transmission of resistant strains and resistance genes from ruminants to humans. The aim of this study was to assess AMR in non-O157 STEC in England and Wales between 2014 and 2016, and to compare phenotypic and Whole Genome Sequencing (WGS) derived AMR profiles.

Methods
Six hundred and fifty-three non-O157 STEC isolates were analysed. WGS and bioinformatic analysis were performed on 457 isolates in the top 10 Clonal Complexes (CC) (193 were excluded on the basis of CC) and phenotypic susceptibility typing via breakpoint and minimum inhibitory concentration testing was undertaken on 100 isolates exhibiting resistance to at least one antimicrobial.

Results
Of 457 isolates, 332 lacked identifiable resistance genes and were predicted to be fully susceptible to 11 diverse classes of antimicrobials, 125 were found to carry one or more resistance genes and 83 were multi-drug resistant. Four isolates were identified as extended-spectrum b-lactamase-producers. In total, 46 different genes were detected – which conferred resistance to 8 different antibiotic classes. An overall concordance of 97.5  % was demonstrated between the two methods.

Conclusions
Phenotypic and genome-derived AMR comparisons showed good correlation for non-O157 STEC. This has added to the evidence base to support the use of genotypic approaches for antimicrobial susceptibility typing, to replace phenotypic typing for surveillance purposes, and guide clinical decision making in the more distant future.
Simple study designs in ecology produce inaccurate estimates of biodiversity responses
Authors: Christie Alec P. , Amano Tatsuya , Martin Philip A. , Shackelford Gorm E. , Simmons Benno I. , Sutherland William J. 
Published: April 2019

AbstractEcologists use a wide range of study designs to estimate the impact of interventions or threats but there are no quantitative comparisons of their accuracy. For example, while it is accepted that simpler designs, such as After (sampling sites post-impact without a control), Before-After (BA) and Control-Impact (CI), are less robust than Randomised Controlled Trials (RCT) and Before-After Control-Impact (BACI) designs, it is not known how much less accurate they are.We simulate a step-change response of a population to an environmental impact using empirically-derived estimates of the major parameters. We use five ecological study designs to estimate the effect of this impact and evaluate each one by determining the percentage of simulations in which they accurately estimate the direction and magnitude of the environmental impact. We also simulate different numbers of replicates and assess several accuracy thresholds.We demonstrate that BACI designs could be 1.1-1.5 times more accurate than RCTs, 2.9-4.1 times more accurate than BA, 3.8-5.6 times more accurate than CI, and 6.8-10.8 times more accurate than After designs, when estimating to within ±30% of the true effect (depending on the sample size). We also found that increasing sample size substantially increases the accuracy of BACI designs but only increases the precision of simpler designs around a biased estimate; only by using more robust designs can accuracy increase. Modestly increasing replication of both control and impact sites also increased the accuracy of BACI designs more than substantially increasing replicates in just one of these groups.We argue that investment into using more robust designs in ecology, where possible, is extremely worthwhile given the inaccuracy of simpler designs, even when using large sample sizes. Based on our results we propose a weighting system that quantitatively ranks the accuracy of studies based on their study design and the number of replicates used. We hope these ‘accuracy weights’ enable researchers to better account for study design in evidence synthesis when assessing the reliability of a range of studies using a variety of designs.
Beat-based and memory-based temporal expectations in rhythm: similar perceptual effects, different underlying mechanisms
Authors: Bouwer Fleur L. , Honing Henkjan , Slagter Heleen A. 
Published: April 2019

AbstractPredicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task relevant or task irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that while beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.
Neurostructural Heterogeneity in Youth with Internalizing Symptoms
Authors: Kaczkurkin Antonia N. , Sotiras Aristeidis , Baller Erica B. , Calkins Monica E. , Chand Ganesh B. , Cui Zaixu , Erus Guray , Fan Yong , Gur Raquel E. , Gur Ruben C. , Moore Tyler M. , Roalf David R. , Rosen Adon F.G. , Ruparel Kosha , Shinohara Russell T. , Varol Erdem , Wolf Daniel H. , Davatzikos Christos , Satterthwaite Theodore D. 
Published: April 2019

ABSTRACTInternalizing disorders such as anxiety and depression are the most common psychiatric disorders, frequently begin in youth, and exhibit marked heterogeneity in treatment response and clinical course. It is increasingly recognized that symptom-based classification approaches to internalizing disorders do not align with underlying neurobiology. An alternative to classifying psychopathology based on clinical symptoms is to identify neurobiologically-informed subtypes based on brain imaging data. We used a recently developed semi-supervised machine learning method (HYDRA) to delineate patterns of neurobiological heterogeneity within youth with internalizing symptoms using structural imaging data collected at 3T from a large community-based sample of 1,141 youth. Using volume and cortical thickness, cross-validation methods indicated a highly stable solution (ARI=.66; permutation-basedpfdr< .001) and identified two subtypes of internalizing youth. Subtype 1, defined by smaller brain volumes and reduced cortical thickness, was marked by impaired cognitive performance and higher levels of psychopathology than both Subtype 2 and typically developing youth. Using resting-state fMRI and diffusion images not considered during clustering, we found that Subtype 1 also showed reduced amplitudes of low-frequency fluctuations in fronto-limbic regions at rest, as well as reduced fractional anisotropy in white matter tracts such as the parahippocampal cingulum bundle and the uncinate fasciculus. In contrast, Subtype 2 showed intact cognitive performance, greater volume, cortical thickness, and amplitudes during rest compared to Subtype 1 and typically developing youth, despite still showing clinically significant levels of psychopathology. Identification of biologically-grounded subtypes of internalizing disorders may assist in targeting early interventions and assessing longitudinal prognosis.
Revisiting the regulation of the capsular polysaccharide biosynthesis gene cluster inStaphylococcus aureus
Authors: Keinhörster Daniela , Salzer Andrea , Duque-Jaramillo Alejandra , George Shilpa E. , Marincola Gabriella , Lee Jean C. , Weidenmaier Christopher , Wolz Christiane 
Published: April 2019

AbstractInStaphylococcus aureus, the capsular polysaccharide (CP) protects against phagocytosis, but also hinders adherence to endothelial cells and matrix proteins. Its biosynthesis is tightly controlled resulting in a heterogeneous phenotype within a population and CP being mainly detectable in non-growing cells. Capsular biosynthesis genes are encoded by a conservedcapA-Poperon whose expression is driven by an upstream promoter element (Pcap) in front ofcapA. The organization of Pcapis poorly understood, as is the interplay of different regulators that influence the early-Off/late-Heterogeneouscaptranscription pattern. Here, we demonstrate that Pcapcontains a main SigB-dependent promoter. The SigB consensus motif overlaps with a previously described inverted repeat that is crucial forcapexpression. The essentiality of the inverted repeat is derived from this region acting as a SigB binding site rather than as an operator site for the proposedcapactivators RbsR and MsaB. Furthermore, Pcapcontains an extensive upstream region harboring a weak SigA-dependent promoter and binding sites for thecaprepressors SaeR, CodY and Rot. We show that heterogeneous CP synthesis is determined by the combination of SigB activity and repressor binding to the upstream region. The direct SigB dependency and the upstream repressors are also sufficient to explain the temporal gene expression pattern at the transcriptional level. However, CP synthesis remains growth phase-dependent even whencapAtranscription is rendered constitutive, suggesting additional post-transcriptional regulatory circuits. Thus, the interference of multiple repressors with SigB-dependent promoter activity as well as post-transcriptional mechanisms ensure the appropriate regulation of CP synthesis.ImportanceThe majority of bacterial pathogens produce an array of polysaccharides on their surface which are important virulence factors and thus serve as attractive vaccine candidates. However, the synthesis and assembly of these structures is highly variable and tightly regulated at various levels. In the human pathogenStaphylococcus aureus, the synthesis of the capsular polysaccharide (CP) is dependent on a complex regulatory network which ensures that CP is produced only in a fraction of stationary phase cells. Here, we determined main regulators that drive the peculiar CP expression pattern. We found that the interplay of the transcriptional repressors Sae, CodY and Rot with the alternative Sigma factor B is responsible for early-Off/late-Heterogeneous expression at the transcriptional level. The data also implicates post-transcriptional mechanisms that may act to avoid conflict in precursor usage by machineries involved in either synthesis of CP or other glycopolymers in growing bacterial cells.
HAMAP rules as SPARQL A portable annotation pipeline for genomes and proteomes
Authors: Bolleman Jerven , de Castro Eduoard , Baratin Delphine , Gehant Sebastien , Cuche Beatrice A. , Auchincloss Andrea H. , Coudert Elisabeth , Hulo Chantal , Masson Patrick , Pedruzzi Ivo , Rivoire Catherine , Xenarios Ioannis , Redaschi Nicole , Bridge Alan 
Published: April 2019

AbstractMotivationGenome and proteome annotation pipelines are generally custom built and therefore not easily reusable by other groups, which leads to duplication of effort, increased costs, and suboptimal results. One cost-effective way to increase the data quality in public databases is to encourage the adoption of annotation standards and technological solutions that enable the sharing of biological knowledge and tools for genome and proteome annotation.ResultsWe have translated the rules of our HAMAP proteome annotation pipeline to queries in the W3C standard SPARQL 1.1 syntax and applied them with two off-the-shelf SPARQL engines to UniProtKB/Swiss-Prot protein sequences described in RDF format. This approach is applicable to any genome or proteome annotation pipeline and greatly simplifies their reuse.AvailabilityHAMAP SPARQL rules and documentation are freely available for download from the HAMAP FTP site ftp://ftp.expasy.org/databases/hamap/hamapsparql.tar.gz under a CC-BY-ND 4.0 license. The annotations generated by the rules are under the CC-BY 4.0 license.Contacthamap@sib.swissSupplementary informationSupplementary data are included at the end of this document.
cT-DNA in Linaria vulgaris L. is multicopy, inverted and homogenized
Authors: Vladimirov Ivan A. , Pavlova Olga A. , Polev Dmitrii E. , Bogomaz Denis I. 
Published: April 2019

AbstractThe phenomenon of evolutionary fixation of agrobacterial sequences (cT-DNA or cellular transferred DNA) in plant genomes is well known in nature. It was previously considered, that all of cT-DNA-containing species, except Linaria vulgaris, have multiple inverted cT-DNA repeats. Deep studying of general features of cT-DNA brings us closer to understanding the causes and mechanisms of its fixation in plants genomes. We combined multiple long-range PCR with genome walking for studying extended structure of cT-DNA. Using digital PCR method, we estimated copy number of cT-DNA elements. NGS with low covering allows us to develop a set of microsatellite markers, also used for copy number estimation. According to new data, cT-DNA elements in L. vulgaris form an inverted complex repeat of two simple direct repeats. After cT-DNA integration, cT-DNA sequence duplication events took place at least two times. The phenomenon of concerted evolution of cT-DNA sequences as well as some details of this process have been shown for the first time.We have shown, that L. vulgaris, as well as other cT-DNA containing species, has inverted structure of repeats. This fact indicates possible existence of some general causes and mechanisms of cT-DNA fixation in plant genomes during evolution.
coMethDMR: Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies
Authors: Gomez Lissette , Odom Gabriel J. , Young Juan I. , Martin Eden R. , Liu Lizhong , Chen Xi , Griswold Anthony J. , Gao Zhen , Zhang Lanyu , Wang Lily 
Published: April 2019

ABSTRACTRecent technology has made it possible to measure DNA methylation profiles in a cost-effective and comprehensive genome-wide manner using array-based technology for epigenome-wide association studies. However, identifying differentially methylated regions (DMRs) remains a challenging task because of the complexities in DNA methylation data. Supervised methods typically focus on the regions that contain consecutive highly significantly differentially methylated CpGs in the genome, but may lack power for detecting small but consistent changes when few CpGs pass stringent significance threshold after multiple comparison. Unsupervised methods group CpGs based on genomic annotations first and then test them against phenotype, but may lack specificity because the regional boundaries of methylation are often not well defined. We present coMethDMR, a flexible, powerful, and accurate tool for identifying DMRs. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first. Next, coMethDMR tests association between methylation levels within the sub-region and phenotype via a random coefficient mixed effects model that models both variations between CpG sites within the region and differential methylation simultaneously. coMethDMR offers well-controlled Type I error rate, improved specificity, focused testing of targeted genomic regions, and is available as an open-source R package.
Probing dynamical cortical gating of attention with concurrent TMS-EEG
Authors: Okazaki Yuka O. , Mizuno Yuji , Kitajo Keiich 
Published: April 2019

AbstractBackgroundAttention facilitates gating of information from the sending brain area to receiving areas, with this being achieved by dynamical change in effective connectivity between cortices. However, it is difficult to assess effective connectivity, which refers to the causal influence of one cortical area on another.ObjectiveThe aim of this study is to directly probe the effective connectivity between cortical areas, which is modulated by covertly shifted attention, excluding the thalamic influence.MethodsTranscranial magnetic stimulation (TMS) was used to directly perturb the right retinotopic visual cortex in task-relevant (TR) and task-irrelevant (TIR) networks, and the impact of this was tracked to other areas by concurrent use of electroencephalography (EEG).ResultsKey finding was that TMS to the TR hemisphere led to a stronger evoked potential than did
stimulation to the TIR hemisphere. Moreover, stronger beta- and gamma-band effective connectivities assessed as lagged phase synchronizations between stimulated areas and other areas were observed when TMS was delivered to the TR area. These effects were more enhanced when they preceded more prominent alpha lateralization, which is known to be associated with gating information.ConclusionOur results indicate that attention-regulated cortical excitability and feedforward dynamical effective connectivity can be probed by direct cortical stimulation to the TR or TIR area, thereby bypassing thalamic gating. These results bear out the idea that TMS-EEG could help to characterize changes in the functional architecture of brain networks that are required for rapid adaptation to the environment or due to brain diseases.HighlightsAttention-regulated cortical excitability and effective connectivity were probed by TMS-EEG.Stronger TMS evoked potentials were observed in the task-relevant visual hemisphere.Strong effective connectivity between task-relevant visual cortex and other areas were found.
Effects of compassion training on brain responses to suffering others
Authors: Ashar Yoni K. , Andrews-Hanna Jessica R. , Halifax Joan , Dimidjian Sona , Wager Tor D. 
Published: April 2019

AbstractWhat are the active ingredients and brain mechanisms of compassion training? To address these questions, we conducted a three-armed randomized trial (N = 57) of compassion meditation (CM). We compared a four-week CM program delivered by smartphone application to i) a placebo condition, in which participants inhaled sham oxytocin, which they were told would enhance compassion, and ii) a familiarity control condition, designed to control for increased familiarity with suffering others. Functional MRI was collected while participants listened to narratives describing suffering others at pre- and post-intervention. CM increased brain responses to suffering others in the medial orbitofrontal cortex (mOFC) relative to both the placebo and familiarity control conditions, and in the nucleus accumbens relative to the familiarity control condition. Results support the specific efficacy of CM beyond effects of expectancy, demand characteristics, and increased familiarity with suffering others, and implicate affective and motivational pathways as brain mechanisms of CM.Author NoteFunded by the John Templeton Foundation’s Positive Neuroscience project (PIs Wager and Dimidjian), with additional support from NIH R01 R01DA035484 (PI Wager). Gratitude to research assistants Jenifer Mutari, Robin Kay, Scott Meyers, Nicholas Peterson, and Brandin Williams for help with data collection.
DRPnet - Automated Particle Picking in Cryo-Electron Micrographs using Deep Regression
Authors: Nguyen Nguyen P. , Gotberg Jacob , Ersoy Ilker , Bunyak Filiz , White Tommi 
Published: April 2019

AbstractSelection of individual protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based method to automatically detect particle centers from cryoEM micrographs. This is a challenging task because of the low signal-to-noise ratio of cryoEM micrographs and the size, shape, and grayscale-level variations in particles. We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. Particles are detected by the first network, a fully convolutional regression network (FCRN), which maps the particle image to a continuous distance map that acts like a probability density function of particle centers. Particles identified by FCRN are further refined (or classified) to reduce false particle detections by the second CNN. This approach, entitled Deep Regression Picker Network or “DRPnet”, is simple but very effective in recognizing different grayscale patterns corresponding to 2D views of 3D particles. Our experiments showed that DRPnet’s first CNN pretrained with one dataset can be used to detect particles from a different datasets without retraining. The performance of this network can be further improved by re-training the network using specific particle datasets. The second network, a classification convolutional neural network, is used to refine detection results by identifying false detections. The proposed fully automated “deep regression” system, DRPnet, pretrained with TRPV1 (EMPIAR-10005) [1], and tested onβ-galactosidase (EMPIAR-10017) [2] andβ-galactosidase (EMPIAR-10061) [3], was then compared to RELION’s interactive particle picking. Preliminary experiments resulted in comparable or better particle picking performance with drastically reduced user interactions and improved processing time.
Disentangling unity from diversity in developmental psychopathology
Authors: Mendes Lorenna Sena Teixeira , Polanczyk Guilherme Vanoni , Rohde Luis Augusto , Salum Giovanni Abrahão 
Published: April 2019

AbstractDevelopmental psychopathology has been a fruitful space for the investigation of the validity of multidimensionality. Nonetheless, previous studies in the field have not tested a model with a fine-grained division within the internalizing and externalizing spectra that also accounts for the contribution of a general psychopathology factor. The aim of this study is to test the validity and reliability of a theoretically-driven bifactor model with one general dimension and ten specific dimensions of psychopathology: fear, somatic complaints, distressful thoughts, low mood, low motivation/energy, inattention-hyperactivity, temper loss, aggression, noncompliance, and low concern for others. Our study evaluated 2,511 children aged 6-14 years-old from the Brazilian High-Risk Cohort for Psychiatric Disorders. There was support for the model in terms of its fit to the data, reliability, and external validity. Our findings highlight the potential of combined fine-grained approaches with models disentangling unity from diversity in developmental psychopathology.