bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cell type-specific enhancer-promoter connectivity maps in the human brain and disease risk association
Authors: Nott Alexi , Holtman Inge R. , Coufal Nicole G. , Schlachetzki Johannes C.M. , Yu Miao , Hu Rong , Han Claudia Z. , Pena Monique , Xiao Jiayang , Wu Yin , Keuelen Zahara , Pasillas Martina P. , O’Connor Carolyn , Schafer Simon T. , Shen Zeyang , Rissman Robert A. , Brewer James B. , Gosselin David , Gonda David D. , Levy Michael L. , Rosenfeld Michael G. , McVicker Graham , Gage Fred H. , Ren Bing , Glass Christopher K. 
Published: September 2019

AbstractUnique cell type-specific patterns of activated enhancers can be leveraged to interpret non-coding genetic variation associated with complex traits and diseases such as neurological and psychiatric disorders. Here, we have defined active promoters and enhancers for major cell types of the human brain. Whereas psychiatric disorders were primarily associated with regulatory regions in neurons, idiopathic Alzheimer’s disease (AD) variants were largely confined to microglia enhancers. Interactome maps connecting GWAS variants in cell type-specific enhancers to gene promoters revealed an extended microglia gene network in AD. Deletion of a microglia-specific enhancer harboring AD-risk variants ablated BIN1 expression in microglia but not in neurons or astrocytes. These findings revise and expand the genes likely to be influenced by non-coding variants in AD and suggest the probable brain cell types in which they function.One Sentence SummaryIdentification of cell type-specific regulatory elements in the human brain enables interpretation of non-coding GWAS risk variants.
Neurobehavioural characterisation and stratification of reinforcement-related behaviour
Authors: Jia Tianye , Ing Alex , Quinlan Erin Burke , Tay Nicole , Luo Qiang , Francesca Biondo , Banaschewski Tobias , Barker Gareth J. , Bokde Arun L.W. , Bromberg Uli , Büchel Christian , Desrivières Sylvane , Feng Jianfeng , Flor Herta , Grigis Antoine , Garavan Hugh , Gowland Penny , Heinz Andreas , Ittermann Bernd , Martinot Jean-Luc , Martinot Marie-Laure Paillère , Nees Frauke , Orfanos Dimitri Papadopoulos , Paus Tomáš , Poustka Luise , Fröhner Juliane H. , Smolka Michael N. , Walter Henrik , Whelan Robert , Schumann Gunter ,   IMAGEN Consortium
Published: September 2019

Abstract:Reinforcement-related cognitive processes, such as reward processing, impulsiveness and emotional processing are critical components of externalising and internalising behaviours. It is unclear to what extent each of these processes contributes to individual behavioural symptoms, how their neural substrates give rise to distinct behavioural outcomes, and if neural profiles across different reinforcement-related processes might differentiate individual behaviours. We created a statistical framework that enabled us to directly compare functional brain activation during reward anticipation, motor inhibition and viewing of emotional faces in the European IMAGEN cohort of 2000 14-year-old adolescents. We observe significant correlations and modulation of reward anticipation and motor inhibition networks in hyperactivity, impulsivity, inattention and conduct symptoms, and describe neural signatures across neuroimaging tasks that differentiate these behaviours. We thus characterise shared and distinct functional brain activation patterns that underlie different externalising symptoms and identify neural stratification markers, while accounting for clinically observed co-morbidity.
Characterizing neural coding performance for populations of sensory neurons: comparing a weighted spike distance metrics to other analytical methods
Authors: Marsat G. , Daly K.C. , Drew J.A. 
Published: September 2019

ABSTRACTThe identity of sensory stimuli is encoded in the spatio-temporal patterns of responses of the encoding neural population. For stimuli to be discriminated reliably, differences in population responses must be accurately decoded by downstream networks. Several methods to compare patterns of responses have been used by neurophysiologists to characterize the accuracy of the sensory responses studied. Among the most widely used analysis, we note methods based on Euclidean distances or on spike metric distances. Methods based on artificial neural networks and machine learning that recognize and/or classify specific input patterns have also gained popularity. Here, we first compare these three strategies using datasets from three different model systems: the moth olfactory system, the electrosensory system of gymnotids, and leaky-integrate- and-fire (LIF) model responses. We show that the input-weighting procedure inherent to artificial neural networks allows the efficient extraction of information relevant to stimulus discrimination. To combine the convenience of methods such as spike metric distances but leverage the advantages of weighting the inputs, we propose a measure based on geometric distances where each dimension is weighted proportionally to how informative it is. We show that the result of this Weighted Euclidian Distance (WED) analysis performs as well or better than the artificial neural network we tested and outperforms the more traditional spike distance metrics. We applied information theoretic analysis to LIF responses and compare their encoding accuracy with the discrimination accuracy quantified through this WED analysis. We show a high degree of correlation between discrimination accuracy and information content and that our weighting procedure allowed the efficient use of information present to perform the discrimination task. We argue that our proposed measure provides the flexibility and ease of use sought by neurophysiologists while providing a more powerful way to extract relevant information than more traditional methods.
CSAG1 Maintains the Integrity of the Mitotic Centrosome in Cells with Defective P53
Authors: Sapkota Hem , Wren Jonathan D. , Gorbsky Gary J. 
Published: September 2019

AbstractCentrosomes focus microtubules to promote mitotic spindle bipolarity, a critical requirement for balanced chromosome segregation. Comprehensive understanding of centrosome function and regulation requires a complete inventory of components. While many centrosome components have been identified, others may yet remain undiscovered. We have used a bioinformatics approach, based on “guilt by association” expression to identify novel mitotic components among the large group of predicted human proteins that have yet to be functionally characterized. Here we identify Chondrosarcoma-Associated Gene 1 (CSAG1) in maintaining centrosome integrity during mitosis. Depletion of CSAG1 disrupts centrosomes and leads to multipolar spindles more effectively in cells with compromised p53 function. Thus, CSAG1 may reflect a class of “mitotic addiction” genes whose expression is more essential in transformed cells.
Modeling Cell-Specific Dynamics and Regulation of the Common Gamma Chain Cytokines
Authors: Farhat Ali M. , Weiner Adam C. , Posner Cori , Kim Zoe S. , Orcutt-Jahns Brian , Carlson Scott M. , Meyer Aaron S. 
Published: September 2019

AbstractMany receptor families exhibit both pleiotropy and redundancy in their regulation, with multiple ligands, receptors, and responding cell populations. Any intervention, therefore, has multiple effects, confounding intuition about how to precisely manipulate signaling for therapeutic purposes. The common γ-chain cytokine receptor dimerizes with complexes of the cytokines interleukin (IL)-2, IL-4, IL-7, IL-9, IL-15, and IL-21 and their corresponding “private” receptors. These cytokines have existing uses and future potential as immune therapies due to their ability to regulate the abundance and function of specific immune cell populations. However, engineering cell specificity into a therapy is confounded by the complexity of the family across responsive cell types. Here, we build a binding-reaction model for the ligand-receptor interactions of common γ-chain cytokines enabling quantitative predictions of response. We show that accounting for receptor-ligand trafficking is essential to accurately model cell response. This model accurately predicts ligand response across a wide panel of cell types under diverse experimental designs. Further, we can predict the effect and specificity of natural or engineered ligands across cell types. We then show that tensor factorization is a uniquely powerful tool to visualize changes in the input-output behavior of the family across time, cell types, ligands, and concentration. In total, these results present a more accurate model of ligand response validated across a panel of immune cell types, and demonstrate an approach for generating interpretable guidelines to manipulate the cell type-specific targeting of engineered ligands. These techniques will in turn help to study and therapeutically manipulate many other complex receptor-ligand families.Summary pointsA dynamical model of the γ-chain cytokines accurately models responses to IL-2, IL-15, IL-4, and IL-7.Receptor trafficking is necessary for capturing ligand response.Tensor factorization maps responses across cell populations, receptors, cytokines, and dynamics to visualize cytokine specificity.An activation model coupled with tensor factorization provides design specifications for engineering cell-specific responses.
Kv1 potassium channels control action potential firing of putative GABAergic deep cerebellar nuclear neurons
Authors: Feria Pliego Jessica Abigail , Pedroarena Christine M. 
Published: September 2019

ABSTRACTThe Kv1 voltage-gated potassium channels (kv1.1-1.8) display characteristic low-threshold activation ranges what enables their role in regulating diverse aspects of neuronal function, such as the action potential (AP) threshold and waveform, and thereby influence neuronal excitability or synaptic transmission. Kv1 channels are highly expressed in the cerebellar cortex and nuclei and mutations of human Kv1 genes are associated to episodic forms of ataxia (EAT-1). Besides the well-established role of Kv1 channels in regulating the basket-Purkinje cells inhibitory synapses of cerebellar cortex, cerebellar Kv1 channels regulate the principal deep cerebellar nuclear neurons activity (DCNs). DCNs however, include as well different groups of GABAergic cells that project locally to target principal DCNs, or to the inferior-olive or recurrently to the cerebellar cortex, but whether their function is controlled by Kv1 channels remains unclear. Here, using cerebellar slices from the GAD67-GFP line mice to identify putative GABAergic-DCNs and specific Kv1 channel blockers (dendrotoxins-alpha/I/K (DTXs)) we provide evidence that putative GABAergic-DCNs spontaneous and evoked activity is controlled by Kv1 currents. DTXs shifted in the hyperpolarizing direction the voltage threshold of spontaneous APs in GABAergic-DCNs, increased GABAergic-DCNs spontaneous firing rate and decreased these neurons ability to fire repetitively action potentials at high frequency. Moreover, in spontaneously silent putative nucleo-cortical DCNs, DTXs application induced depolarization and tonic firing. These results strongly suggest that Kv1 channels regulate GABAergic-DCNs activity and thereby can control previously unrecognized aspects of cerebellar function.
An inducible genome editing system for plants
Authors: Wang Xin , Ye Lingling , Ursache Robertas , Mähönen Ari Pekka 
Published: September 2019

ABSTRACTConditional manipulation of gene expression is a key approach to investigating the primary function of a gene in a biological process. While conditional and cell-type specific overexpression systems exist for plants, there are currently no systems available to disable a gene completely and conditionally. Here, we present a novel tool with which target genes can be efficiently conditionally knocked out at any developmental stage. The target gene is manipulated using the CRISPR-Cas9 genome editing technology, and conditionality is achieved with the well-established estrogen-inducible XVE system. Target genes can also be knocked-out in a cell-type specific manner. Our tool is easy to construct and will be particularly useful for studying genes which have null-alleles that are non-viable or show strong developmental defects.
Novel regulators of nitric oxide signaling triggered by host perception in a plant pathogen
Authors: Ding Yi , Gardiner Donald M. , Xiao Di , Kazan Kemal 
Published: September 2019

AbstractThe rhizosphere interaction between plant roots or pathogenic microbes is initiated by mutual exchange of signals. However, how soil pathogens sense host signals is largely unknown. Here, we studied early molecular events associated with host recognition in Fusarium graminearum, an economically important fungal pathogen that can infect both roots and heads of cereal crops. We found that host-sensing prior to physical contact with plant roots radically alters the transcriptome and triggers nitric oxide (NO) production in F. graminearum. We identified an ankyrin-repeat domain containing protein (FgANK1) required for host-mediated NO production and virulence in F. graminearum. In the absence of host plant, FgANK1 resides in the cytoplasm. In response to host signals, FgANK1 translocates to the nucleus and interacts with a zinc finger transcription factor (FgZC1), also required for NO production and virulence in F. graminearum. Our results reveal new mechanistic insights into host-recognition strategies employed by soil pathogens.
Automation of (Macro)molecular Properties Using a Bootstrapping Swarm Artificial Neural Network Method: Databases for Machine Learning
Authors: Rahmani Blerta , Kamberaj Hiqmet 
Published: September 2019

AbstractIn this study, we employed a novel method for prediction of (macro)molecular properties using a swarm artificial neural network method as a machine learning approach. In this method, a (macro)molecular structure is represented by a so-calleddescription vector, which then is the input in a so-calledbootstrapping swarm artificial neural network(BSANN) for training the neural network. In this study, we aim to develop an efficient approach for performing the training of an artificial neural network using either experimental or quantum mechanics data. In particular, we aim to create different user-friendly online accessible databases of well-selected experimental (or quantum mechanics) results that can be used as proof of the concepts. Furthermore, with the optimized artificial neural network using the training data served as input for BSANN, we can predict properties and their statistical errors of new molecules using the plugins provided from that web-service. There are four databases accessible using the web-based service. That includes a database of 642 small organic molecules with known experimental hydration free energies, the database of 1475 experimental pKa values of ionizable groups in 192 proteins, the database of 2693 mutants in 14 proteins with given values of experimental values of changes in the Gibbs free energy, and a database of 7101 quantum mechanics heat of formation calculations.All the data are prepared and optimized in advance using the AMBER force field in CHARMM macromolecular computer simulation program. The BSANN is code for performing the optimization and prediction written in Python computer programming language. The descriptor vectors of the small molecules are based on the Coulomb matrix and sum over bonds properties, and for the macromolecular systems, they take into account the chemical-physical fingerprints of the region in the vicinity of each amino acid.Graphical TOC Entry
Accommodation providers’ motives in sharing economy: comparison between Turkey and Lithuania
Authors: Urbonavicius Sigitas , Sezer Adil 
Published: September 2019

Purpose
The purpose of this paper is to empirically assess and compare motivations and moderating factors that influence intention to provide accommodation in two countries, which are different in terms of their culture and IT infrastructure development.

Design/methodology/approach
Empirical analysis on the basis of 396 valid questionnaires from two countries allowed finding two different models that explain intentions to provide accommodation in the analyzed environments. Subsequent multilevel modeling disclosed differences between influences on intention to provide accommodation in Turkey and Lithuania.

Findings
The results disclosed importance of country contexts in causing diversity between country-specific models and in generating differences of the influences, if the same model for two countries is applied. The most important findings include observed differences in influences of monetary and social motives on intention, as well as in moderations of materialism and mavenism.

Originality/value
Using the self-determination theory as the theoretical background, the study adds to the knowledge on intention to participate in sharing economy from the accommodation providers’ position. Additional value is brought by finding the importance of cultural contexts in the models that describe intentions of accommodation providing in sharing economy.
Exploring the customer experience with Airbnb
Authors: Li Jing , Hudson Simon , So Kevin Kam Fung 
Published: September 2019

Purpose
The purpose of this study is to investigate the multi-dimensional structure of the Airbnb customer experience and to examine the influences of this experience on behavioral outcomes.

Design/methodology/approach
A multi-phase methodology was adopted using a survey questionnaire to explore the dimensions. Data were collected from a sample of 561 Airbnb users in the USA. Exploratory factor analysis and confirmed factor analysis were conducted to evaluate the reliability and validity of the scale.

Findings
First, the results support the hypothesis that the Airbnb customer experience comprises four dimensions: home benefits, personalized services, authenticity and social connection. Second, the study demonstrates that these dimensions significantly influence customers’ behavioral intentions.

Research limitations/implications
The use of a US Airbnb users sample may affect the generalizability of the results.

Practical implications
The findings of this study provide insights for Airbnb hosts and hotel managers. More specifically, this study offers suggestions to Airbnb hosts about how to enhance their services to customers based on the four experience dimensions and to hotels about how they can compete with Airbnb on the four experience dimensions.

Originality/value
This study provides an important theoretical framework for measuring the Airbnb customer experience through an empirical examination.
The medical perspective on mining incidents
Authors: Karlsson Sofia , Saveman Britt-Inger , Gyllencreutz Lina 
Published: September 2019

Purpose
The purpose of this paper is to examine emergency medical service (EMS) personnel’s perceptions and experiences of managing underground mining injury incidents.

Design/methodology/approach
In total, 13 EMS personnel were interviewed according to a semi-structured interview guide. The interviews were transcribed verbatim and analyzed using qualitative content analysis.

Findings
An underground mining environment was described as unfamiliar and unsafe and, with no guidelines for operational actions in an extreme environment, such as underground mines, the EMS personnel were uncertain of their role. They therefore became passive and relied on the rescue service and mining company during a major incident. However, the medical care was not considered to be different from any other prehospital care, although a mining environment would make the situation more difficult and it would take longer for the mine workers to be placed under definitive care.

Originality/value
This study complements earlier studies by examining the EMS personnel’s perceptions and experiences of major incidents.
Managerial competencies of 3PL providers
Authors: Sangka Bayu Khresna , Rahman Shams , Yadlapalli Aswini , Jie Ferry 
Published: September 2019

PurposeThe purpose of this paper is to identify and prioritise competencies of Indonesian third-party logistics (3PL) managers from the perspective of multinational corporations (MNCs) and local firms.Design/methodology/approachUnderlined by the theory of action and job performance (competency model), the study proposes a framework that consists of management, logistics, business and information and communication technology competency categories, with 15 competencies. Data are collected from five MNCs and five local 3PL firms operating in Indonesia. The analytic hierarchy process method is used to calculate the priority weights and to prioritise the competencies.FindingsResults indicate that both the local and MNC 3PL providers emphasise logistics as the “most important” competency category. In the “moderately important” competency group, MNCs prioritise competencies in the management competency category while local firms prioritise competencies in the business competency category.Research limitations/implicationsResults obtained in this study focus on 3PL firms in Indonesian businesses, which may not be applicable to other nations and other industries.Practical implications3PL firms, industry peak bodies (e.g. Indonesian Logistics Association) and education providers can benefit from incorporating the findings of this study in developing curricula for higher education and training programmes for certification designed to improve managerial competencies.Originality/valueBy including the perceptions of the MNCs and local 3PL providers, this study advances the literature on 3PL managerial competencies by extending such knowledge to the global environment.
Systems thinking and CMM for continuous improvement in the construction industry
Authors: Omotayo Temitope Seun , Boateng Prince , Osobajo Oluyomi , Oke Adekunle , Obi Loveline Ifeoma 
Published: September 2019

PurposeThe purpose of this paper is to present a capability maturity model (CMM) developed to implement continuous improvement in small and medium scale construction companies (SMSCC) in Nigeria.Design/methodology/approachA multi-strategy approach involving qualitative studies of SMSCC in Nigeria was conducted. Semi-structured interviews were conducted with purposively selected construction experts in Nigeria to identify variables essential for continuous improvement in SMSCC. Data collected were thematically analysed using NVIVO. Subsequently, a system thinking approach is employed to design and develop the CMM for implementing continuous improvement SMSCC, by exploring possible relationships between the variables established.FindingsCMM provided a five-level approach for the inclusion of investigated variables such as team performance; culture; structure; post-project reviews, financial risk management, waste management policy and cost control. These variables are factors leading to continuous improvement in SMSCC, implementable within a six to seven and a half years’ timeline.Practical implicationsThe system thinking model revealed cogent archetypes in the form of reinforcing loops that can be applied in developing the performance of SMSCC. Continuous improvement is feasible. However, it takes time to implement. Further longitudinal studies on the cost of implementing continuous improvement through CMM a knowledge transfer project can be initiated.Originality/valueA methodical strategy for enhancing the effectiveness and operations of SMSCC in developing countries can be extracted from the causal loop diagram and the CMM.