bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tourette syndrome: clinical spectrum, mechanisms and personalized treatments
Authors: Hartmann Andreas , Worbe Yulia 
Published: May 2018

Purpose of review
To describe recent advances regarding the disease spectrum in Tourette syndrome, offer new mechanistic insights into tic generation and provide clues for personalized treatments in this disorder.

Recent findings
Apart from tics, which define Tourette syndrome, comorbidities are the rule and not the exception. They significantly define clinical presentation, disease severity and quality of life. Recent studies have highlighted the importance of screening for depression, anxiety and autism spectrum disorders in Tourette syndrome. Regarding the mechanisms of tic generation, computational models begin to emerge and provide important clues regarding the cerebral regions and networks involved, as well as information on the nature of neurotransmitter signaling, for instance phasic versus tonic dopamine release. Also, these models may inform on generation or termination of premonitory urges which underlie tic generation. Finally, personalized treatments in Tourette syndrome are both necessary because of the width of the clinical spectrum, making every patient unique from a symptom-oriented perspective; yet, difficult to achieve because of the lack of large prospective cohorts which may inform on prognostic factors and disease-modifying interventions. However, interesting developments, especially in the fields of behavioral therapy and deep brain stimulation, deserve mention and pave the way for tailored treatments in Tourette syndrome.

Summary
The recent literature offers interesting clues that sharpen our understanding of comorbidities in Tourette disorder and thereby its clinical spectrum, offers insights into the cerebral networks underlying tic generation and cautiously announces personalized interventions for Tourette disorder patients based on their symptom profile.
Movement disorders in mitochondrial disease: a clinicopathological correlation
Authors: Flønes Irene H. , Tzoulis Charalampos 
Published: May 2018

Purpose of review
The scope of this review is to give an updated account of movement disorders associated with mitochondrial disease, with a particular focus on recently discovered clinicopathological correlations.

Recent findings
Movement disorders are common clinical manifestations of mitochondrial diseases, in part because of the high vulnerability of neurons controlling motor circuits to mitochondrial respiratory dysfunction and energy failure. Intriguingly, the clinicopathological correlations of movement disorders in mitochondrial disease do not always conform to established neurophysiological knowledge. In particular, nearly complete substantia nigra degeneration and nigrostriatal denervation can occur without being accompanied by any of the clinical signs traditionally associated with parkinsonism. This apparent paradox, may be because of compensation by concomitant impairment of other motor circuits involving the cerebellum and thalamus.

Summary
Movement disorders commonly accompany mitochondrial disease and may show paradoxical clinical−anatomical correlations. Further research is warranted in order to elucidate the mechanisms underlying the phenotypic expression of movement disorders in mitochondrial disease. This knowledge will advance our understanding of the pathogenesis of movement disorders in a broader clinical and pathophysiological context.
The Shifting Landscape of Disease-Modifying Therapies for Relapsing Multiple Sclerosis
Authors: Burton Jodie M. , Freedman Mark S. 
Published: May 2018

Background:Multiple sclerosis (MS) is the most common nontraumatic neurological disorder of young adults, and roughly 85% of patients present with the relapsing form of the disease. Over the past 2 decades, the treatment arsenal for relapsing MS has expanded and evolved from mildly effective and relatively benign injectable agents to potent cell-depleting monoclonal agents. The latter have the potential to achieve disease remission coupled with risk of moderate to severe adverse events with which all MS care providers will need to acquaint themselves.Methods:This review is based on a detailed assessment of MS pivotal trials, extension studies, and expert reviews of the agents discussed.Results/Conclusions:The following review should aid those practitioners directly and indirectly involved in the care of MS patients in understanding the benefits and risks associated with the medications they prescribe.
Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes
Authors: Tanaka Naoaki , Papadelis Christos , Tamilia Eleonora , Madsen Joseph R. , Pearl Phillip L. , Stufflebeam Steven M. 
Published: May 2018

Introduction:
This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis.

Methods:
We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25.

Results:
The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group.

Conclusions:
Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.
Modeling genome-wide evolution of catalytic turnover rates: Strong epistasis shaped modern enzyme kinetics
Authors: Heckmann David , Zielinski Daniel C. , Palsson Bernhard O. 
Published: May 2018

AbstractSystems biology describes cellular phenotypes as properties that emerge from the complex interactions of individual system components. Little is known about how these interactions have affected the evolution of metabolic enzymes. To address this question, we combine genome-scale metabolic modelling with population genetics models to simulate the evolution of enzyme turnover numbers (kcats) from a theoretical ancestor with inefficient enzymes. This systems view of biochemical evolution reveals strong epistatic interactions between metabolic genes that shape evolutionary trajectories and influence the magnitude of evolvedkcats. A small number of biophysically constrained enzymes suffice to induce diminishing returns epistasis that prevents enzymes from developing higherkcats in all reactions and keeps the organism far from the potential fitness optimum. In addition, multifunctional enzymes cause synergistic epistasis that slows down adaptation. The resulting fitness landscape is smooth and causeskcatevolution to be convergent. Predictedkcatparameters show a significant correlation with experimental data onin vitroandin vivoturnover rates, validating our modelling approach. Our analysis thus suggests that enzyme evolution can be predicted on a genome scale and reveals the mechanisms by which evolutionary forces shape modernkcats and the whole of cell metabolism.
Gene Set Overlap: An Impediment to Achieving High Specificity in Over-representation Analysis
Authors: Maleki Farhad , Kusalik Anthony J. 
Published: May 2018

AbstractGene set analysis methods are widely used to analyze data from high-throughput “omics” technologies. One drawback of these methods is their low specificity or high false positive rate. Over-representation analysis is one of the most commonly used gene set analysis methods. In this paper, we propose a systematic approach to investigate the hypothesis that gene set overlap is an underlying cause of low specificity in over-representation analysis. We quantify gene set overlap and show that it is a ubiquitous phenomenon across gene set databases. Statistical analysis indicates a strong negative correlation between gene set overlap and the specificity of over-representation analysis. We conclude that gene set overlap is an underlying cause of the low specificity. This result highlights the importance of considering gene set overlap in gene set analysis and explains the lack of specificity of methods that ignore gene set overlap. This research also establishes the direction for developing new gene set analysis methods.
Escherichia coliZipA organizes FtsZ polymers into dynamic ring-like protofilament structures
Authors: Krupka Marcin , Sobrinos-Sanguino Marta , Jiménez Mercedes , Rivas Germán , Margolin William 
Published: May 2018

ABSTRACTZipA is an essential cell division protein inEscherichia coli. Together with FtsA, ZipA tethers dynamic polymers of FtsZ to the cytoplasmic membrane, and these polymers are required to guide synthesis of the cell division septum. This dynamic behavior of FtsZ has been reconstituted on planar lipid surfacesin vitro, visible as GTP-dependent chiral vortices several hundred nm in diameter, when anchored by FtsA or when fused to an artificial membrane binding domain. However, these dynamics largely vanish when ZipA is used to tether FtsZ polymers to lipids at high surface densities. This, along with somein vitrostudies in solution, has led to the prevailing notion that ZipA reduces FtsZ dynamics by enhancing bundling of FtsZ filaments. Here, we show that this is not the case. When lower, more physiological levels of the soluble, cytoplasmic domain of ZipA (sZipA) were attached to lipids, FtsZ assembled into highly dynamic vortices similar to those assembled with FtsA or other membrane anchors. Notably, at either high or low surface densities, ZipA did not stimulate lateral interactions between FtsZ protofilaments. We also usedE. colimutants that are either deficient or proficient in FtsZ bundling to provide evidence that ZipA does not directly promote bundling of FtsZ filamentsin vivo. Together, our results suggest that ZipA does not dampen FtsZ dynamics as previously thought, and instead may act as a passive membrane attachment for FtsZ filaments as they treadmill.IMPORTANCEBacterial cells use a membrane-attached ring of proteins to mark and guide formation of a division septum at mid-cell that forms a wall separating the two daughter cells and allows cells to divide. The key protein in this ring is FtsZ, a homolog of tubulin that forms dynamic polymers. Here, we use electron microscopy and confocal fluorescence imaging to show that one of the proteins required to attach FtsZ polymers to the membrane duringE. colicell division, ZipA, can promote dynamic swirls of FtsZ on a lipid surfacein vitro. Importantly, these swirls are only observed when ZipA is present at low, physiologically relevant surface densities. Although ZipA has been thought to enhance bundling of FtsZ polymers, we find little evidence for bundlingin vitro. In addition, we present several lines ofin vivoevidence indicating that ZipA does not act to directly bundle FtsZ polymers.
Beyond the SNP threshold: identifying outbreak clusters using inferred transmissions
Authors: Stimson James , Gardy Jennifer , Mathema Barun , Crudu Valeriu , Cohen Ted , Colijn Caroline 
Published: May 2018

AbstractWhole genome sequencing (WGS) is increasingly used to aid in understanding pathogen transmission [1]. Very often the number of single nucleotide polymorphisms (SNPs) separating isolates collected during an epidemiological study are used to identify sets of cases that are potentially linked by direct transmission. However, there is little agreement in the literature as to what an appropriate SNP cut-off threshold should be, or indeed whether a simple SNP threshold is appropriate for identifying sets of isolates to be treated as “transmission clusters”. The SNP thresholds that have been adopted for inferring transmission vary widely even for one pathogen. As an alternative to reliance on a strict SNP threshold, we suggest that the key inferential target when studying the spread of an infectious disease is the number of transmission events separating cases. Here we describe a new framework for deciding whether two pathogen genomes should be considered as part of the same transmission cluster, based jointly on the number of SNP differences and the length of time over which those differences have accumulated. Our approach allows us to probabilistically characterize the number of inferred transmission events that separate cases. We show how this framework can be modified to consider variable mutation rates across the genome (e.g. SNPs associated with drug resistance) and we indicate how the methodology can be extended to incorporate epidemiological data such as spatial proximity. We use recent data collected from tuberculosis studies from British Columbia, Canada and the Republic of Moldova to apply and compare our clustering method to the SNP threshold approach. In the British Columbia data, different cases break off from the main clusters as cut-off thresholds are lowered; the transmission-based method obtains slightly different clusters than the SNP cut-offs. For the Moldova data, straightforward application of the methods shows no appreciable difference, but when we take into account the fact that resistance conferring sites likely do not follow the same mutation clock as most sites due to selection, the transmission-based approach differs from the SNP cut-off method. Outbreak simulations confirm that our transmission based method is at least as good at identifying direct transmissions as a SNP cut-off. We conclude that the new method is a promising step towards establishing a more robust identification of outbreaks.
Genome rearrangements and selection in multi-chromosome bacteria Burkholderia spp
Authors: Bochkareva Olga O , Moroz Elena V , Davydov Iakov I , Gelfand Mikhail S 
Published: May 2018

AbstractBackgroundThe genus Burkholderia consists of species that occupy remarkably diverse ecological niches. Its best known members are important pathogens, B. mallei and B. pseudomallei, which cause glanders and melioidosis, respectively. Burkholderia genomes are unusual due to their multichromosomal organization.ResultsWe performed integrated genomic analysis of 127 Burkholderia strains. The pan-genome is open with the saturation to be reached between 86,000 and 88,000 genes. The reconstructed rearrangements indicate a strong avoidance of intra-replichore inversions that is likely caused by selection against the transfer of large groups of genes between the leading and the lagging strands. Translocated genes also tend to retain their position in the leading or the lagging strand, and this selection is stronger for large syntenies. Integrated reconstruction of chromosome rearrangements in the context of strains phylogeny reveals parallel rearrangements that may indicate inversion-based phase variation and integration of new genomic islands. In particular, we detected parallel inversions in the second chromosomes of B. pseudomallei with breakpoints formed by genes encoding membrane components of multidrug resistance complex, that may be linked to a phase variation mechanism. Two genomic islands, spreading horizontally between chromosomes, were detected in the B. cepacia group.ConclusionsThis study demonstrates the power of integrated analysis of pan-genomes, chromosome rearrangements, and selection regimes. Non-random inversion patterns indicate selective pressure, inversions are particularly frequent in a recent pathogen B. mallei, and, together with periods of positive selection at other branches, may indicate adaptation to new niches. One such adaptation could be a possible phase variation mechanism in B. pseudomallei.
Neurodynamics-based leader-follower formation tracking of multiple nonholonomic vehicles
Authors: Yi Guo , Mao Jianxu , Wang Yaonan , Zhang Hui , Miao Zhiqiang 
Published: May 2018

Purpose
The purpose of this paper is to consider the leader-following formation control problem for nonholonomic vehicles based on a novel biologically inspired neurodynamics approach.

Design/methodology/approach
The interactions among the networked multi-vehicle system is modeled by an undirected graph. First, a distributed estimation law is proposed for each follower vehicle to estimate the state including the position, orientation and linear velocity of the leader. Then, a distributed formation tracking control law is designed based on the estimated state of the leader, where a bio-inspired neural dynamic is introduced to solve the impractical velocity jumps problem. Explicit stability and convergence analyses are presented using Lyapunov tools.

Findings
The effectiveness and efficiency of the proposed control law are demonstrated by numerical simulations and physical vehicle experiments. Consequently, the proposed protocol can successfully achieve the desired formation under connected topologies while tracking the trajectory generated by the leader.

Originality/value
This paper proposes a neurodynamics-based leader–follower formation tracking algorithm for multiple nonholonomic vehicles.
An electrochemical method based on OCP fluctuations for anti-corrosion alloy composition optimization
Authors: Chen Mindong , Zhang Huijie , Chen Liang , Fu Dongmei 
Published: May 2018

Purpose
An electrochemical method based on the open circuit potential (OCP) fluctuations was put forward. It can be used to optimize the alloy compositions for improving the corrosion resistance of rust layer.

Design/methodology/approach
The potential trends and potential fluctuations of carbon steels in seawater were separated by Hodrick–Prescott filter. The Spearman correlation coefficient and max information coefficient were used to explore the correlation of alloy compositions and potential fluctuations.

Findings
After long-term immersion, potential fluctuation resistance (PFR) can be used to characterize the corrosion resistance of metals and its rust layers. In the 1,500 to 2,500 h exposure period, Fe, C and S compositions have strong negative correlations, whereas PFR and P composition have weak negative correlations. Mn, Cu and Ti alloy compositions help the rust layer of carbon steels have higher PFRs. These elements that exhibit higher PFRs in this period have been confirmed to have the effect on improving the corrosion resistance of rust layer.

Originality/value
A new computing method for alloy composition optimization of carbon steels based on the OCP fluctuations was put forward. This method combines electrochemical monitoring with the long-term actual seawater environmental tests of various carbon steels.
The mechanism and effectiveness of credit scoring of P2P lending platform
Authors: Li Qiang , Chen Liwen , Zeng Yong 
Published: May 2018

Purpose
The purpose of this paper is to investigate the mechanism how the platform obtains and uses undisclosed information to determine individual borrowers’ credit score and to examine the effectiveness of credit scoring in predicting default. The motivation stems from the fact that there is little evidence about the role of P2P platform, which has been positioned as a kind of information intermediary.

Design/methodology/approach
Using a sample of 5,176 unsecured P2P loans having expired before December 31, 2015 on Renrendai.com and an approach of two-stage regression, the paper first estimates the undisclosed information embedded in credit score by regressing credit score on four types of public information about a borrower’s creditworthiness. Then, the authors use a Logit regression to examine the role of the excess information in predicting the default probability.

Findings
The certification information provided by the platform is the most important determinant for a borrower’s credit score and the undisclosed information embedded in credit score can predict the loan performance better than the public information of posted listings. Moreover, the predictive ability of the undisclosed information is better for high-risk borrowers than for low-risk ones.

Research limitations/implications
Providing a credit score for each individual is a way for P2P platforms to play an information intermediary role. More evidence about whether or how a platform plays its role are worthy to be exploited by investigating a platform’s operating policies in detail and doing cross-platform comparative studies.

Practical implications
The results about the effect of various types of information on loan performance can provide an insightful guidance for P2P platforms to optimize their mechanism on information disclosure and credit scoring.

Originality/value
The existing literature mainly focuses on the effects of information voluntarily disclosed by borrowers and the behaviors of investors on P2P lending outcomes. The paper highlights the information intermediary role played by the platform and presents empirical evidence that credit scoring for individual borrowers is a way for P2P platforms to promote the direct lending for individual.
Empirical differences between the overnight and day trading hour returns
Authors: DU Juan 
Published: May 2018

Purpose
The purpose of this paper is to provide a stable model which covers market information of return to examine the empirical differences between the returns during night and day in Chinese commodity futures market.

Design/methodology/approach
Commodity indices are constructed using principal components analysis to represent the market returns for day and night trading in the Chinese commodity futures market. Then VAR models are employed to predict the commodity indices’ returns and squared returns.

Findings
The symmetric VAR model failed to model the market returns since the asymmetric effects of positive and negative returns are not taken into account. By allowing asymmetric behavior among positive and negative variables, asymmetric VAR model is utilized to trace the leading effect of overnight returns to daytime trading returns. However, the symmetric VAR model outperforms the asymmetric model when evaluating the predictive power of squared returns during night trading hours. Two major results based on asymmetric model for the return are: There is a 6-day leading effect of nighttime return to daytime return in Chinese commodity futures market. It is risky to hold day trading position overnight.

Research limitations/implications
Asymmetric VAR model provides a new approach to forecasting the direction of price movement.

Practical implications
Investment managers are able to create a stable portfolio contains major market information. Day and night traders are likely to gain some suggestions to discover arbitrage opportunities.

Social implications
Since there is no commodity futures index in China, the method for creating indices for Chinese commodity futures is provided to market regulators.

Originality/value
Combining principal component analysis and asymmetric VAR model provides a stable and predictable model to obtain market information.