bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lewy pathology in Parkinson’s disease consists of a crowded organellar, membranous medley
Authors: Shahmoradian Sarah H. , Lewis Amanda J. , Genoud Christel , Hench Jürgen , Moors Tim , Navarro Paula P. , Castaño-Díez Daniel , Schweighauser Gabriel , Graff-Meyer Alexandra , Goldie Kenneth N. , Sütterlin Rosmarie , Huisman Evelien , Ingrassia Angela , de Gier Yvonne , Rozemuller Annemieke J.M. , Wang Jing , De Paepe Anne , Erny Johannes , Staempfli Andreas , Hoernschemeyer Joerg , Großerüschkamp Frederik , Niedieker Daniel , El-Mashtoly Samir F. , Quadri Marialuisa , van IJcken Wilfred F.J. , Bonifati Vincenzo , Gerwert Klaus , Bohrmann Bernd , Frank Stephan , Britschgi Markus , Stahlberg Henning , van de Berg Wilma D. J. , Lauer Matthias E. 
Published: May 2017

SummaryParkinson’s disease, the most common age-related movement disorder, is a progressive neurodegenerative disease with unclear etiology. Key neuropathological hallmarks are Lewy bodies and Lewy neurites, which are neuronal inclusions that are immunopositive for the protein α-synuclein. In-depth ultrastructural analysis of this Lewy pathology is crucial to understanding pathogenesis and progression of the disease. Using correlative light and electron microscopy/tomography on brain tissue from five Parkinson’s disease brain donors, we identified α-synuclein immunopositive Lewy pathology and could show that the majority of these features including Lewy bodies and Lewy neurites primarily consists of a crowded membranous medley of vesicular structures and dysmorphic organelles. Only a small fraction of observed Lewy bodies contained predominant proteinaceous filaments, as previously described. The crowding of organellar components was confirmed by STED- based super-resolution microscopy, and high lipid content within the α-synuclein immunopositive inclusions was corroborated by confocal imaging, CARS/FTIR imaging and lipidomics. Applying this correlative high-resolution imaging and biophysical approach, we discovered in the postmortem brain of Parkinson’s patients a subcellular protein-lipid compartmentalization not previously described in Lewy pathology.
Defocus and magnification dependent variation of TEM image astigmatism
Authors: Yan Rui , Li Kunpeng , Jiang Wen 
Published: May 2017

AbstractDaily alignment of the microscope is a prerequisite to reaching optimal illumination lens and imaging lens conditions for high resolution imaging in cryo-EM. In contrast to the dramatic progress in automated image acquisition and post-image processing techniques, less attention has been paid to the improvement of microscope alignment before data collection. In this study, we have employed our recently published tool,s2stigmator, to study how image astigmatism varies with the imaging conditions (e.g. defocus, magnification). We have found that the large change of defocus/magnification between visual correction of astigmatism and subsequent data collection tasks, or even during data collection will inevitably result in undesirable residual astigmatism in the final images. Furthermore, the dependence of astigmatism on the imaging conditions varies significantly from time to time, so that it cannot be reliably compensated by pre-calibration of the microscope. These findings have essentially invalidated a basic assumption of current cryo-EM imaging strategies that assumes invariant astigmatism for different defocuses/magnifications used in the microscope alignment stage and the final data acquisition stage. Based on these findings, we recommend the same magnification and the median defocus of the intended defocus range for final data collection are used in the objective lens astigmatism correction task during microscope alignment and in the focus mode of the iterative low-dose imaging. It is also desirable to develop a fast, accurate method that can perform dynamic correction of the astigmatism for different intended defocuses during automated imaging.
Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States
Authors: Carlson Colin J. , Dougherty Eric , Boots Mike , Getz Wayne , Ryan Sadie 
Published: May 2017

ABSTRACTEcologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States, a region of high model conflict. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the unacceptable and often undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.
Speaq 2.0: A Complete Workflow for High-Throughput 1D NMR Spectra Processing And Quantification
Authors: Beirnaert Charlie , Meysman Pieter , Vu Trung Nghia , Hermans Nina , Apers Sandra , Pieters Luc , Covaci Adrian , Laukens Kris 
Published: May 2017

AbstractNuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. This has the effect that its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq).Author summaryWe present speaq 2.0: a user friendly workflow for processing NMR spectra quickly and easily. By limiting the need for user interaction and allowing the construction of workflows by combining R functions, metabolomics data analysis becomes fully reproducible and shareable. Such advances are critical for the future of the metabolomics field as it needs to move towards a fully open-science approach. This is no trivial goal as many researchers are still using black-box commercial software that often requires manually doing several steps, thus hampering reproducibility. To encourage the shift towards open source, we deliberately made our method usable for anyone with the most basic of R experience, something that is easily acquired. speaq 2.0 allows a stand-alone analysis from spectra to statistical analysis. In addition, the package can be combined with existing tools to improve performance, as it provides a superior peak picking method compared to the standard binning approach.
SAVER: Gene expression recovery for UMI-based single cell RNA sequencing
Authors: Huang Mo , Wang Jingshu , Torre Eduardo , Dueck Hannah , Shaffer Sydney , Bonasio Roberto , Murray John , Raj Arjun , Li Mingyao , Zhang Nancy R. 
Published: May 2017

AbstractRapid advances in massively parallel single cell RNA sequencing (scRNA-seq) is paving the way for high-resolution single cell profiling of biological samples. In most scRNA-seq studies, only a small fraction of the transcripts present in each cell are sequenced. The efficiency, that is, the proportion of transcripts in the cell that are sequenced, can be especially low in highly parallelized experiments where the number of reads allocated for each cell is small. This leads to unreliable quantification of lowly and moderately expressed genes, resulting in extremely sparse data and hindering downstream analysis. To address this challenge, we introduce SAVER (Single-cell Analysis Via Expression Recovery), an expression recovery method for scRNA-seq that borrows information across genes and cells to impute the zeros as well as to improve the expression estimates for all genes. We show, by comparison to RNA fluorescence in situ hybridization (FISH) and by data down-sampling experiments, that SAVER reliably recovers cell-specific gene expression concentrations, cross-cell gene expression distributions, and gene-to-gene and cell-to-cell correlations. This improves the power and accuracy of any downstream analysis involving genes with low to moderate expression.
Computerizing Trail Making Test for long-term cognitive self-assessment
Authors: Zeng Zhiwei , Miao Chunyan , Leung Cyril , Shen Zhiqi 
Published: May 2017

Purpose
This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.

Design/methodology/approach
The authors propose a divide-and-combine (DAC) approach for generating different instances of TMT that can be used in repeated assessments with nearly no discernible practice effects. In the DAC approach, partial trails are generated separately in different layers and then combined to form a complete TMT trail.

Findings
The proposed approach was implemented in a computerized test application called iTMT. A pilot study was conducted to evaluate iTMT. The results show that the instances of TMT generated by the DAC approach had an adequate level of difficulty. iTMT also achieved a stronger construct validity, higher test–retest reliability and significantly reduced practice effects than existing computerized tests.

Originality/value
The preliminary results suggest that iTMT is suitable for long-term monitoring of cognitive abilities. By supporting self-assessment, iTMT also can help to crowdsource the assessment processes, which need to be administered by healthcare professionals conventionally, to the patients themselves.
Application of keyword extraction on MOOC resources
Authors: Jiang Zhuoxuan , Miao Chunyan , Li Xiaoming 
Published: May 2017

Purpose
Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Design/methodology/approach
Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

Findings
From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Research limitations/implications
Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

Practical implications
The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

Originality/value
This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.
The nature and value of knowledge
Authors: De Toni Alberto Felice , Fornasier Andrea , Nonino Fabio 
Published: May 2017

Purpose
This paper aims to explain and discuss the complex nature and value of knowledge as an exploitable resource for business.

Design/methodology/approach
The authors propose a conceptual explanation of knowledge based on three pillars: the plurality of its nature, understood to be conservative, multipliable and generative, its contextual value and the duality of carrier incorporating business knowledge, objects or processes. After conceptualizing the nature of knowledge, the authors offer a metaphor based on the classic transformation from “potential” to “kinetic” energy in an inclined plane assuming that the conservative nature of knowledge makes it act as energy.

Findings
The metaphor uses the concept of potential and kinetic energy: if energy is only potential, it has a potential value not yet effective, whereas if the potential energy (knowledge) becomes kinetic energy (products and/or services), it generates business value. In addition, business value is a function of the speed acquired and caused by the angle of inclined plan, namely, the company’s business model. Knowledge is the source of the value and can be maintained and regenerated only through continuous investments. Several years later the value extraction reaches a null value of the company (potential energy) which will cease to act (kinetic energy) for triggering both the value generated and the value extracted.

Originality/value
The paper proposes an initial attempt to explain the meaning of the transformation of knowledge using a metaphor derived from physics. The metaphor of the energy of knowledge clearly depicts the managerial dilemma of balancing a company’s resources for both the generating and extracting value. Similarly, future study should try to associate other knowledge peculiarities to physical phenomena.
Customer engagement within multiple new media and broader business ecosystem – a holistic perspective
Authors: Yuan Soe-Tsyr Daphne , Chou Szu-Yu , Yang Wei-Cheng , Wu Cheng-An , Huang Chih-Teng 
Published: May 2017

Purpose
Customer engagement (customers’ behavioral manifestations going beyond customer-firm purchase transactions) has been regarded as strategic imperatives for generating enhanced corporate performance. The plethora of new media has provided customers with different options to interact with firms and other customers. However, the primacy of value-laden interactive customer relationships and value co-creation raises challenges for firms and customers, especially in the context of broader business ecosystems such as brand partnership for extending value co-creation. This study aims to explore how customer engagement with well-designed choreograph of various new media’s channels can increase the value co-creation extent in the context of broader business ecosystems, resulting in higher levels service offerings, experiences and innovation.

Design/methodology/approach
This exploratory study presents a new framework of customer engagement that holistically integrates the elements of multiple new media and broader business ecosystem, stimulating a virtuous circle of realizing customer engagement toward superior results or innovations. The framework considers new media’s different information service and technologies (e.g. search engine, social recommender, social media) that can be properly choreographed to achieve a virtuous customer engagement circle.

Findings
This paper uses an exemplar framework's instantiation – an information technology enabled engagement platform (called iEngagement) – that can demonstrate how to empower the central companies together with their eco-stakeholders to holistically perform customer engagement utilizing new media toward fruitful customer engagement.

Originality/value
This exploratory study is among the first that addresses the theory and practice of customer engagement within multiple new media and broader business ecosystem. This paper presents a customer engagement framework and an exemplified engagement platform that holistically integrate the elements of multiple new media and broader business ecosystem, for stimulating a virtuous circle of realizing customer engagement toward superior results or innovations.
Analysing capital structure of spanish chemical companies using self-organizing maps
Authors: Camara-Turull Xavier , Fernández-Izquierdo María Ángeles , Sorrosal-Forradellas M. Teresa 
Published: May 2017

PurposeThis paper aims to analyses the capital structure of the Spanish chemical industry during the period between 1999 and 2013, with a twofold objective. First, to determine whether the assumptions of pecking order theory are fulfilled throughout the study's timeframe. Second, by using data covering the years before the crisis and the worst years thereof, this study shows how the crisis has affected the capital structure of the companies included in this sample.Design/methodology/approachA particular kind of unsupervised neural network, self-organizing maps, is applied. This methodology allows to cluster firms avoiding the need to establish relationships between the different variables involved in the problem beforehand.FindingsCompanies are clustered into groups with different degrees of accomplishment of the pecking order theory. The hypothesis about risk is the one that experience a greater variation in the period before and after the crisis. Moreover, companies' capital structure has been lightly disrupted by the crisis.Originality/valueThe originality of this paper lies in applying an unprecedented methodology to the problem of capital structure. Therefore, the capital structure problem can be approached without setting any function relationship previously.
Aspergillus fumigatus in cystic fibrosis: An update on immune interactions and molecular diagnostics in allergic bronchopulmonary aspergillosis
Authors: Carsin A. , Romain T. , Ranque S. , Reynaud‐Gaubert M. , Dubus J.‐C. , Mège J.‐L. , Vitte J. 
Published: May 2017

AbstractA wide spectrum of pathological conditions may result from the interaction of Aspergillus fumigatus and the immune system of its human host. Allergic bronchopulmonary aspergillosis is one of the most severe A. fumigatus‐related diseases due to possible evolution toward pleuropulmonary fibrosis and respiratory failure. Allergic bronchopulmonary aspergillosis occurs almost exclusively in cystic fibrosis or asthmatic patients. An estimated 8%‐10% of patients with cystic fibrosis experience this condition. The diagnosis of allergic bronchopulmonary aspergillosis relies on criteria first established in 1977. Progress in the understanding of host‐pathogen interactions in A. fumigatus and patients with cystic fibrosis and the ongoing validation of novel laboratory tools concur to update and improve the diagnosis of allergic bronchopulmonary aspergillosis.
Systematic review with meta‐analysis: endoscopic dilation is highly effective and safe in children and adults with eosinophilic oesophagitis
Authors: Moawad F. J. , Molina‐Infante J. , Lucendo A. J. , Cantrell S. E. , Tmanova L. , Douglas K. M. 
Published: May 2017

SummaryBackgroundOesophageal dilation is frequently used as an adjunct treatment to alleviate symptoms that develop from fibrostenotic remodelling in eosinophilic oesophagitis (EoE). Earlier reports described an increased risk of complications associated with dilation.AimPerform a systematic review and meta‐analysis to assess the efficacy and safety of endoscopic dilation in children and adults with EoE.MethodsProfessional librarians searched MEDLINE, EMBASE, the Cochrane library, Scopus, and Web of Science for articles in any language describing studies of dilation in EoE through December 2016. Studies were selected and data were abstracted independently and in duplicate. Random effects modelling was used to generate summary estimates for clinical improvement and complications (haemorrhage, perforation, hospitalisation, and death).ResultsThe search resulted in 3495 references, of which 27 studies were included in the final analysis. The studies described 845 EoE patients, including 87 paediatric patients, who underwent a total of 1820 oesophageal dilations. The median number of dilations was 3 (range: 1‐35). Clinical improvement occurred in 95% of patients (95% CI: 90%‐98%, I2: 10%, 17 studies). Perforation occurred in 0.38% (95% CI: 0.18%‐0.85%, I2: 0%, 27 studies), haemorrhage in 0.05% (95% CI: 0%‐0.3%, I2: 0%, 18 studies), and hospitalisation in 0.67% (95% CI: 0.3%‐1.1%, I2: 44%, 24 studies). No deaths occurred (95% CI: 0%‐0.2% I2: 0%, 25 studies).ConclusionsEndoscopic dilation is consistently effective in children and adults with EoE, resulting in improvement in 95% of patients with very low rates (<1%) of major complications.
Trade Destruction and Trade Diversion: Evidence from China
Authors: Chandra Piyush 
Published: May 2017

AbstractOver the past three decades, we have seen a dramatic increase in the incidence of temporary trade barriers such as antidumping duties and countervailing duties. China has been at the receiving end of a large number of such measures. In this paper, we study how China's exports to its major trade partners have been affected when its major trade partners have used these measures either against China or against other countries. We find that Chinese exports to the country that imposed an antidumping duty decreased by approximately 35 percent. At the same time, an antidumping duty used by the importing country that was directed towards other countries but not against China led to an approximate 30‐percent increase in China's exports to the policy‐imposing country. These results remain robust across various specifications. Our findings have important policy implications. In particular, the magnitude of these effects highlights why it is important to curb the recent widespread use of these barriers.