bluuebunny/crossref_metadata_2025_split huggingface dataset:
Muscle morphology of the lower leg in ambulant children with spastic cerebral palsy
Authors: Pitcher Christian A. , Elliott Catherine M. , Valentine Jane P. , Stannage Katherine , Williams Sian A. , Shipman Peter J. , Reid Siobhán L. 
Published: July 2018

ABSTRACTIntroduction: In this study we aimed to determine the lower limb morphological characteristics of skeletal muscle of ambulant children with spastic cerebral palsy (CP) and typically developing (TD) children. Methods: Seventeen children with spastic diplegic CP (10 boys and 7 girls, 5–12 years of age, Gross Motor Function Classification System [GMFCS] level I or II) and 19 TD children (8 boys and 11 girls, 5–11 years of age) underwent lower limb T1‐weighted MRI. Morphological characteristics of the triceps surae, including muscle volume, anatomical cross‐sectional area, muscle length, and subcutaneous adipose tissue, were digitally quantified, and the proportional distribution calculated. Results: Children with GMFCS II had significantly reduced muscle volume, cross‐sectional area, and muscle length, and increased subcutaneous fat compared with TD children. Children classified as GMFCS II consistently exhibited the greatest deficits in all morphology variables. Discussion: Morphological variables were significantly different between the groups. These alterations have the potential to influence the functional capabilities of the triceps surae muscle group. Muscle Nerve 58:818–823, 2018
A prognostic model for the patient‐reported outcome of surgical treatment of carpal tunnel syndrome
Authors: Bowman Angela , Rudolfer Stephan , Weller Peter , Bland Jeremy D. P. 
Published: July 2018

ABSTRACTIntroduction: Many prognostic factors have been studied in carpal tunnel decompression, but most studies consider only a subset of variables. Methods: Three thousand three hundred thirty‐two operations were used to develop prognostic models, and 885 operations were used for validation. Outcome recorded on a Likert scale was dichotomized into success or failure. Modeling was performed with both logistic regression and artificial neural networks using 87 candidate variables. Results: Both approaches produced predictive multivariate models for outcome with areas under a receiver operating characteristic curve of 0.7 in the validation data set. Patients with moderately severe nerve conduction abnormalities, night waking, a family history of carpal tunnel syndrome, a good response to corticosteroid injection, and women have better outcomes. Greater functional impairment, diabetes, hypertension, and surgery on the dominant hand are associated with poorer outcomes. Discussion: A multivariate model partially predicts the outcome of carpal tunnel surgery, aids decision making, and helps to manage patient expectations. Muscle Nerve 58:784–789, 2018
Frequency of mental disorders among chronic pain patients with or without fibromyalgia in Japan
Authors: Miki Kenji , Nakae Aya , Shi Kenrin , Yasuda Yuka , Yamamori Hidenaga , Fujimoto Michiko , Ikeda Manabu , Shibata Masahiko , Yukioka Masao , Hashimoto Ryota 
Published: July 2018

AbstractAimTo explore the characteristics of psychiatric morbidity in chronic pain patients who present with or without fibromyalgia.MethodsPatients are referred to our chronic pain clinic from primary medical institutions, as we are a secondary medical institution. Although some patients have chronic pain, they have no clear organic disorder such as rheumatoid arthritis to account for the pain. Among the 367 new patients seen during the period from March 2009 to August 2012, 347 patients underwent psychiatric evaluation in face‐to‐face interviews with mental health specialists before a physical examination.ResultsOf the 347 patients examined, at least one psychiatric diagnosis was made for 94.6%. The average number of DSM‐IV‐TR diagnoses was 1.46 in the 330 chronic pain patients who had at least one psychiatric diagnosis. The breakdown of the number of psychodiagnoses was one in 60.8%, two in 27.1%, three in 4.9%, and more than three in 2.3% chronic pain patients with or without fibromyalgia. In fibromyalgia patients, the highest relative frequencies were found for somatoform disorders (76%), followed by dysthymic disorder (17%) and major depressive disorder (15%). In patients without fibromyalgia, the highest relative frequencies were found for somatoform disorders (64%), followed by major depressive disorder (15%) and dysthymic disorder (14%). Psychiatric disorders were found in 96.9% of fibromyalgia patients, and in 93.5% of chronic pain patients without fibromyalgia in Japan (no significant difference using chi‐square test).ConclusionResults show that chronic pain patients with or without fibromyalgia are extremely likely to be diagnosed with a psychiatric disorder.
Comments on the SN orbifold CFT in the large N-limit
Authors: Roumpedakis Konstantinos 
Published: July 2018

AbstractWe elaborate on various aspects of the conformal field theory of the symmetric orbifold. We collect various results that have appeared in the literature, and we present a coherent picture of the operator content of this CFT, relying on the orbifold extension of the Virasoro algebra. We then focus on the largeN-limit of this theory, discuss the OPE of two twist operators, and find various selection rules. We review how to calculate four-point functions of twist operators, and we write down the most general four-point function in the covering space for largeN.We show that it depends on some functions that obey a set of algebraic equations, that resemble the scattering equations. Finally, we provide a recipe on how to calculate correlation functions with insertions of the orbifold Virasoro generators.
The Condition of Eruption Column Collapse: 1. A Reference Model Based on Analytical Solutions
Authors: Koyaguchi Takehiro , Suzuki Yujiro J. 
Published: July 2018

AbstractThe critical condition at which an eruption column collapses to generate a pyroclastic flow (the column collapse condition) generally depends on magmatic properties, crater shape (radius, depth, and opening angle), and the magma supply rate through the volcanic conduit. Here we propose a reference model for the column collapse condition based on analytical solutions of a one‐dimensional (1‐D) eruption column model and a quasi‐1‐D conduit flow model, which considers the effects of the crater. In the reference model, the column collapse condition is expressed by a single surface in a dimensionless parameter space related to magma discharge rate, magma supply rate (per unit area) at the crater base, and the ratio of the cross‐sectional areas at the top and base of the crater. The dependence of the column collapse condition on magmatic properties is included in the normalization factors of these dimensionless parameters. Previous criteria for the column collapse condition, which were based on the relationship between water content and magma discharge rate and that between magma discharge rate and crater radius, are regarded as part of, or a projection of, the present reference model. The reference model provides a framework for a comprehensive analysis of the diverse scenarios resulting in column collapse during explosive eruptions.
A Test of the Tropical 200‐ to 300‐hPa Warming Rate in Climate Models
Authors: McKitrick Ross , Christy John 
Published: July 2018

AbstractOverall climate sensitivity to CO2 doubling in a general circulation model results from a complex system of parameterizations in combination with the underlying model structure. We refer to this as the model's major hypothesis, and we assume it to be testable. We explain four criteria that a valid test should meet: measurability, specificity, independence, and uniqueness. We argue that temperature change in the tropical 200‐ to 300‐hPa layer meets these criteria. Comparing modeled to observed trends over the past 60 years using a persistence‐robust variance estimator shows that all models warm more rapidly than observations and in the majority of individual cases the discrepancy is statistically significant. We argue that this provides informative evidence against the major hypothesis in most current climate models.
Alternating Trench Advance and Retreat: Insights From Paleozoic Magmatism in the Eastern Tianshan, Central Asian Orogenic Belt
Authors: Zhang Yunying , Sun Min , Yuan Chao , Long Xiaoping , Jiang Yingde , Li Pengfei , Huang Zongying , Du Long 
Published: July 2018

AbstractAccretionary orogens generally involve trench advance and retreat, recognition of which is critical to understand the thermal evolution and geodynamics of the lithosphere. A systematic study has been conducted on the Silurian to Carboniferous volcanic rocks from the Dananhu‐Harlik arc in the Chinese eastern Tianshan. Three distinct episodes of volcanism have been recognized: Late Silurian normal andesite, high Sr/Y andesite and sanukitoid, Late Devonian bimodal high‐alumina basalt and dacite, and Early Carboniferous high‐alumina basalt. These magmatism experienced variable degrees of interaction between a depleted mantle wedge and subducting slab‐/sediment‐derived fluid/melt. Combining with previous geological data, we propose that the Dananhu‐Harlik arc was formed by the northward subduction of the North Tianshan Ocean (NTO), different from the traditional southward subduction of the Junggar Ocean, which was likely subducted northward to account for the East Junggar arc system. Temporal changes in Ce/Y of basalts and Ho/Yb of felsic rocks in the Dananhu‐Harlik arc imply that the arc crust underwent episodic thickening and thinning, which probably reflect the trench advance/retreat processes. The high Ce/Y and Ho/Yb ratios in the Late Ordovician to Devonian and Late Carboniferous correspond to two phases of trench advance. Conversely, the low Ce/Y and Ho/Yb ratios in the Early Carboniferous record a period of trench retreat, which caused the splitting of the Dananhu‐Harlik arc and formation of the Bogda back‐arc basin. Meanwhile, a southward subduction initiated along the south margin of the NTO, producing the Yamansu arc. Late Carboniferous bipolar subduction of the NTO led to its final closure.
Conditional generative adversarial network for gene expression inference
Authors: Wang Xiaoqian , Ghasedi Dizaji Kamran , Huang Heng 
Published: July 2018

Abstract

Motivation
The rapid progress of gene expression profiling has facilitated the prosperity of recent biological studies in various fields, where gene expression data characterizes various cell conditions and regulatory mechanisms under different experimental circumstances. Despite the widespread application of gene expression profiling and advances in high-throughput technologies, profiling in genome-wide level is still expensive and difficult. Previous studies found that high correlation exists in the expression pattern of different genes, such that a small subset of genes can be informative to approximately describe the entire transcriptome. In the Library of Integrated Network-based Cell-Signature program, a set of ∼1000 landmark genes have been identified that contain ∼80% information of the whole genome and can be used to predict the expression of remaining genes. For a cost-effective profiling strategy, traditional methods measure the profiles of landmark genes and then infer the expression of other target genes via linear models. However, linear models do not have the capacity to capture the non-linear associations in gene regulatory networks.

Results
As a flexible model with high representative power, deep learning models provide an alternate to interpret the complex relation among genes. In this paper, we propose a deep learning architecture for the inference of target gene expression profiles. We construct a novel conditional generative adversarial network by incorporating both the adversarial and ℓ1-norm loss terms in our model. Unlike the smooth and blurry predictions resulted by mean squared error objective, the coupled adversarial and ℓ1-norm loss function leads to more accurate and sharp predictions. We validate our method under two different settings and find consistent and significant improvements over all the comparing methods.
Noise peak filtering in multi-dimensional NMR spectra using convolutional neural networks
Authors: Kobayashi Naohiro , Hattori Yoshikazu , Nagata Takashi , Shinya Shoko , Güntert Peter , Kojima Chojiro , Fujiwara Toshimichi 
Published: July 2018

Abstract

Motivation
Multi-dimensional NMR spectra are generally used for NMR signal assignment and structure analysis. There are several programs that can achieve highly automated NMR signal assignments and structure analysis. On the other hand, NMR spectra tend to have a large number of noise peaks even for data acquired with good sample and machine conditions, and it is still difficult to eliminate these noise peaks.

Results
We have developed a method to eliminate noise peaks using convolutional neural networks, implemented in the program package Filt_Robot. The filtering accuracy of Filt_Robot was around 90–95% when applied to 2D and 3D NMR spectra, and the numbers of resulting non-noise peaks were close to those in corresponding manually prepared peaks lists. The filtering can strongly enhance automated NMR spectra analysis.

Availability and implementation
The full package of the program, documents and example data are available from http://bmrbdep.pdbj.org/en/nmr_tool_box/Filt_Robot.html.

Supplementary information
Supplementary data are available at Bioinformatics online.
Fast characterization of segmental duplications in genome assemblies
Authors: Numanagić Ibrahim , Gökkaya Alim S , Zhang Lillian , Berger Bonnie , Alkan Can , Hach Faraz 
Published: July 2018

AbstractMotivationSegmental duplications (SDs) or low-copy repeats, are segments of DNA &gt; 1 Kbp with high sequence identity that are copied to other regions of the genome. SDs are among the most important sources of evolution, a common cause of genomic structural variation and several are associated with diseases of genomic origin including schizophrenia and autism. Despite their functional importance, SDs present one of the major hurdles for de novo genome assembly due to the ambiguity they cause in building and traversing both state-of-the-art overlap-layout-consensus and de Bruijn graphs. This causes SD regions to be misassembled, collapsed into a unique representation, or completely missing from assembled reference genomes for various organisms. In turn, this missing or incorrect information limits our ability to fully understand the evolution and the architecture of the genomes. Despite the essential need to accurately characterize SDs in assemblies, there has been only one tool that was developed for this purpose, called Whole-Genome Assembly Comparison (WGAC); its primary goal is SD detection. WGAC is comprised of several steps that employ different tools and custom scripts, which makes this strategy difficult and time consuming to use. Thus there is still a need for algorithms to characterize within-assembly SDs quickly, accurately, and in a user friendly manner.ResultsHere we introduce SEgmental Duplication Evaluation Framework (SEDEF) to rapidly detect SDs through sophisticated filtering strategies based on Jaccard similarity and local chaining. We show that SEDEF accurately detects SDs while maintaining substantial speed up over WGAC that translates into practical run times of minutes instead of weeks. Notably, our algorithm captures up to 25% ‘pairwise error’ between segments, whereas previous studies focused on only 10%, allowing us to more deeply track the evolutionary history of the genome.Availability and implementationSEDEF is available at https://github.com/vpc-ccg/sedef.
Towards an accurate and efficient heuristic for species/gene tree co-estimation
Authors: Wang Yaxuan , Nakhleh Luay 
Published: July 2018

Abstract

Motivation
Species and gene trees represent how species and individual loci within their genomes evolve from their most recent common ancestors. These trees are central to addressing several questions in biology relating to, among other issues, species conservation, trait evolution and gene function. Consequently, their accurate inference from genomic data is a major endeavor. One approach to their inference is to co-estimate species and gene trees from genome-wide data. Indeed, Bayesian methods based on this approach already exist. However, these methods are very slow, limiting their applicability to datasets with small numbers of taxa. The more commonly used approach is to first infer gene trees individually, and then use gene tree estimates to infer the species tree. Methods in this category rely significantly on the accuracy of the gene trees which is often not high when the dataset includes closely related species.

Results
In this work, we introduce a simple, yet effective, iterative method for co-estimating gene and species trees from sequence data of multiple, unlinked loci. In every iteration, the method estimates a species tree, uses it as a generative process to simulate a collection of gene trees, and then selects gene trees for the individual loci from among the simulated gene trees by making use of the sequence data. We demonstrate the accuracy and efficiency of our method on simulated as well as biological data, and compare them to those of existing competing methods.

Availability and implementation
The method has been implemented in PhyloNet, which is publicly available at http://bioinfocs.rice.edu/phylonet.
Single cell network analysis with a mixture of Nested Effects Models
Authors: Pirkl Martin , Beerenwinkel Niko 
Published: July 2018

AbstractMotivationNew technologies allow for the elaborate measurement of different traits of single cells under genetic perturbations. These interventional data promise to elucidate intra-cellular networks in unprecedented detail and further help to improve treatment of diseases like cancer. However, cell populations can be very heterogeneous.ResultsWe developed a mixture of Nested Effects Models (M&NEM) for single-cell data to simultaneously identify different cellular subpopulations and their corresponding causal networks to explain the heterogeneity in a cell population. For inference, we assign each cell to a network with a certain probability and iteratively update the optimal networks and cell probabilities in an Expectation Maximization scheme. We validate our method in the controlled setting of a simulation study and apply it to three data sets of pooled CRISPR screens generated previously by two novel experimental techniques, namely Crop-Seq and Perturb-Seq.Availability and implementationThe mixture Nested Effects Model (M&NEM) is available as the R-package mnem at https://github.com/cbg-ethz/mnem/.Supplementary informationSupplementary data are available at Bioinformatics online.
RNAvista: a webserver to assess RNA secondary structures with non-canonical base pairs
Authors: Antczak Maciej , Zablocki Marcin , Zok Tomasz , Rybarczyk Agnieszka , Blazewicz Jacek , Szachniuk Marta 
Published: July 2018

Abstract

Motivation
In the study of 3D RNA structure, information about non-canonical interactions between nucleobases is increasingly important. Specialized databases support investigation of this issue based on experimental data, and several programs can annotate non-canonical base pairs in the RNA 3D structure. However, predicting the extended RNA secondary structure which describes both canonical and non-canonical interactions remains difficult.

Results
Here, we present RNAvista that allows predicting an extended RNA secondary structure from sequence or from the list enumerating canonical base pairs only. RNAvista is implemented as a publicly available webserver with user-friendly interface. It runs on all major web browsers.

Availability and implementation
http://rnavista.cs.put.poznan.pl
Kmer-db: instant evolutionary distance estimation
Authors: Deorowicz Sebastian , Gudyś Adam , Długosz Maciej , Kokot Marek , Danek Agnieszka 
Published: July 2018

Abstract

Summary
Kmer-db is a new tool for estimating evolutionary relationship on the basis of k-mers extracted from genomes or sequencing reads. Thanks to an efficient data structure and parallel implementation, our software estimates distances between 40 715 pathogens in &lt;7 min (on a modern workstation), 26 times faster than Mash, its main competitor.

Availability and implementation
https://github.com/refresh-bio/kmer-db and http://sun.aei.polsl.pl/REFRESH/kmer-db.

Supplementary information
Supplementary data are available at Bioinformatics online.
A Prospective, Open-label, Randomized Trial of Doxycycline Versus Azithromycin for the Treatment of Uncomplicated Murine Typhus
Authors: Newton Paul N , Keolouangkhot Valy , Lee Sue J , Choumlivong Khamla , Sisouphone Siho , Choumlivong Khamloune , Vongsouvath Manivanh , Mayxay Mayfong , Chansamouth Vilada , Davong Viengmon , Phommasone Koukeo , Sirisouk Joy , Blacksell Stuart D , Nawtaisong Pruksa , Moore Catrin E , Castonguay-Vanier Josée , Dittrich Sabine , Rattanavong Sayaphet , Chang Ko , Darasavath Chirapha , Rattanavong Oudayvone , Paris Daniel H , Phetsouvanh Rattanaphone 
Published: July 2018

Abstract

Background
Murine typhus, or infection with Rickettsia typhi, is a global but neglected disease without randomized clinical trials to guide antibiotic therapy.

Methods
A prospective, open, randomized trial was conducted in nonpregnant, consenting inpatient adults with rapid diagnostic test evidence of uncomplicated murine typhus at 2 hospitals in Vientiane, Laos. Patients were randomized to 7 days (D7) or 3 days (D3) of oral doxycycline or 3 days of oral azithromycin (A3). Primary outcome measures were fever clearance time and frequencies of treatment failure and relapse.

Results
Between 2004 and 2009, the study enrolled 216 patients (72 per arm); 158 (73.2%) had serology/polymerase chain reaction (PCR)–confirmed murine typhus, and 52 (24.1%) were R. typhi PCR positive. The risk of treatment failure was greater for regimen A3 (22.5%; 16 of 71 patients) than for D3 (4.2%; 3 of 71) or D7 (1.4%; 1 of 71) (P &lt; .001). Among R. typhi PCR–positive patients, the area under the time-temperature curve and the fever clearance time were significantly higher for A3 than for D3 (1.8- and 1.9-fold higher, respectively; P = .005) and D7 (1.5- and 1.6-fold higher; P = .02). No patients returned with PCR-confirmed R. typhi relapse.

Conclusion
In Lao adults, azithromycin is inferior to doxycycline as oral therapy for uncomplicated murine typhus. For doxycycline, 3- and 7-day regimens have similar efficacy. Azithromycin use in murine typhus should be reconsidered. Investigation of genomic and phenotypic markers of R. typhi azithromycin resistance is needed.

Clinical Trial Registration
ISRCTN47812566.
Optimal error estimates of the unilateral contact problem in a curved and smooth boundary domain by the penalty method
Authors: Dione Ibrahima 
Published: July 2018

Abstract
We consider linear finite elements to approximate the elasticity equations with unilateral contact boundary conditions, in a bounded two- or three-dimensional domain with curved and smooth boundary. We use the penalty method to weakly impose these boundary conditions. We establish an error estimate in the energy norm with respect to the mesh size $h$ and the penalty parameter $\varepsilon $. Assuming $\boldsymbol{H}^{\frac{3}{2}+\nu }\left (\varOmega \right )$ regularity of the solution, $0 &lt; \nu \leq \frac{1}{2}$, we obtain an $\mathcal{O}\,(h^{\frac{1}{2}+\nu } + \varepsilon ^{\frac{1}{2}+\nu })$ convergence rate. Therefore, if the penalty parameter is chosen as $\varepsilon (h) := ch^{\theta }$ with $0 &lt; \theta \leq 1$, we obtain an $\mathcal{O}\,(h^{\theta (\frac{1}{2}+\nu )})$ convergence rate. Thus, the optimal linear convergence rate is obtained when $\varepsilon $ behaves like $h$ (that is, $\theta = 1$) and $\nu = \frac{1}{2}$. We present a numerical example to illustrate the theoretical analysis.