bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antibiotic resistance detection is essential for gonorrhoea point-of-care testing: A mathematical modelling study
Authors: Fingerhuth Stephanie M. , Low Nicola , Bonhoeffer Sebastian , Althaus Christian L. 
Published: April 2017

AbstractAntibiotic resistance is threatening to make gonorrhoea untreatable. Point-of-care (POC) tests that detect resistance promise individually tailored treatment, but might lead to more treatment and higher levels of resistance. We investigate the impact of POC tests on antibiotic-resistant gonorrhoea. We used data about the prevalence and incidence of gonorrhoea in men who have sex with men (MSM) and heterosexual men and women (HMW) to calibrate a mathematical gonorrhoea transmission model. With this model, we simulated four clinical pathways for the diagnosis and treatment of gonorrhoea: POC test with (POC + R) and without (POC − R) resistance detection, culture, and nucleic acid amplification tests (NAATs). We calculated the proportion of resistant infections, cases averted after 5 years, and compared how fast resistant infections spread in the populations. The proportion of resistant infections after 30 years is lowest for POC + R (median MSM: 0.18%, HMW: 0.12%), and increases for culture (MSM: 1.19%, HWM: 0.13%), NAAT (MSM: 100%, HMW: 99.27%), and POC − R (MSM: 100%, HMW: 99.73%). NAAT leads to 36 366 (median MSM) and 1 228 (median HMW) observed cases after 5 years. When compared with NAAT, POC + R results in most cases averted after 5 years (median MSM: 3 353, HMW: 118 per 100 000 persons). POC tests that detect resistance with intermediate sensitivity slow down resistance spread more than NAAT. POC tests with very high sensitivity for the detection of resistance are needed to slow down resistance spread more than using culture. POC with high sensitivity to detect antibiotic resistance can keep gonorrhoea treatable longer than culture or NAAT. POC tests without reliable resistance detection should not be introduced because they can accelerate the spread of antibiotic-resistant gonorrhoea.
Association between genetically elevated levels of inflammatory biomarkers and risk of schizophrenia: a two-sample Mendelian randomisation study
Authors: Hartwig Fernando Pires , Borges Maria Carolina , Horta Bernardo Lessa , Bowden Jack , Smith George Davey 
Published: April 2017

AbstractBackgroundPositive associations between inflammatory biomarkers and risk of psychiatric disorders, including schizophrenia, have been reported in observational studies. However, conventional observational studies are prone to bias such as reverse causation and residual confounding.MethodsIn this study, we used summary data to evaluate the association of genetically elevated C reactive protein (CRP), interleukin-1 receptor antagonist (IL-1Ra) and soluble interleukin-6 receptor (IL-6R) levels with schizophrenia in a two-sample Mendelian randomisation design.ResultsThe pooled odds ratio estimate using 18 CRP genetic instruments was 0.90 (95% CI: 0.84; 0.97) per two-fold increment in CRP levels; consistent results were obtained using different Mendelian randomisation methods and a more conservative set of instruments. The odds ratio for soluble IL-6R was 1.06 (95% CI: 1.01; 1.12) per two-fold increment. Estimates for IL-1Ra were inconsistent among instruments and pooled estimates were imprecise and centred on the null.ConclusionUnder Mendelian randomisation assumptions, our findings suggest a protective causal effect of CRP and a risk-increasing causal effect of soluble IL-6R (potentially mediated at least in part by CRP) on schizophrenia risk.
From neural network to psychophysics of time: Exploring emergent properties of RNNs using novel Hamiltonian formalism
Authors: Sengupta Rakesh , Pattanayak Anindya , Bapi Raju Surampudi 
Published: April 2017

AbstractThe stability analysis of dynamical neural network systems generally follows the route of finding a suitable Liapunov function after the fashion Hopfield’s famous paper on content addressable memory network or by finding conditions that make divergent solutions impossible. For the current work we focused on biological recurrent neural networks (bRNNs) that require transient external inputs (Cohen-Grossberg networks). In the current work we have proposed a general method to construct Liapunov functions for recurrent neural network with the help of a physically meaningful Hamiltonian function. This construct allows us to explore the emergent properties of the recurrent network (e.g., parameter configuration needed for winner-take-all competition in a leaky accumulator design) beyond that available in standard stability analysis, while also comparing well with standard stability analysis (ordinary differential equation approach) as a special case of the general stability constraint derived from the Hamiltonian formulation. We also show that the Cohen-Grossberg Liapunov function can be derived naturally from the Hamiltonian formalism. A strength of the construct comes from its usability as a predictor for behavior in psychophysical experiments involving numerosity and temporal duration judgements.
QuickRNASeq: Guide for Pipeline Implementation and for Interactive Results Visualization
Authors: He Wen , Zhao Shanrong , Zhang Chi , Vincent Michael S. , Zhang Baohong 
Published: April 2017

i.Summary/AbstractSequencing of transcribed RNA molecules (RNA-seq) has been used wildly for studying cell transcriptomes in bulk or at the single-cell level (1, 2, 3) and is becoming thede factotechnology for investigating gene expression level changes in various biological conditions, on the time course, and under drug treatments. Furthermore, RNA-Seq data helped identify fusion genes that are related to certain cancers (4). Differential gene expression before and after drug treatments provides insights to mechanism of action, pharmacodynamics of the drugs, and safety concerns (5). Because each RNA-seq run generates tens to hundreds of millions of short reads with size ranging from 50bp-200bp, a tool that deciphers these short reads to an integrated and digestible analysis report is in high demand. QuickRNASeq (6) is an application for large-scale RNA-seq data analysis and real-time interactive visualization of complex data sets. This application automates the use of several of the best open-source tools to efficiently generate user friendly, easy to share, and ready to publish report. Figure 1 illustrates some of the interactive plots produced by QuickRNASeq. The visualization features of the application have been further improved since its first publication in early 2016. The original QuickRNASeq publication (6) provided details of background, software selection, and implementation. Here, we outline the steps required to implement QuickRNASeq in user’s own environment, as well as demonstrate some basic yet powerful utilities of the advanced interactive visualization modules in the report.
High cooperativity in negative feedback can amplify noisy gene expression
Authors: Bokes Pavol , Ting Lin Yen , Singh Abhyudai 
Published: April 2017

AbstractBurst-like synthesis of protein is a significant source of cell-to-cell variability in protein levels. Negative feedback is a common example of a regulatory mechanism by which such stochasticity can be controlled. Here we consider a specific kind of negative feedback, which makes bursts smaller in the excess of protein. Increasing the strength of the feedback may lead to dramatically different outcomes depending on a key parameter, the noise load, which is defined as the squared coefficient of variation the protein exhibits in the absence of feedback. Combining stochastic simulation with asymptotic analysis, we identify a critical value of noise load: for noise loads smaller than critical, the coefficient of variation remains bounded with increasing feedback strength; contrastingly, if the noise load is larger than critical, the coefficient of variation diverges to infinity in the limit of ever greater feedback strengths. Interestingly, high-cooperativity feedbacks have lower critical noise loads, implying that low-cooperativity feedbacks in burst size can be preferable for noisy proteins. Finally, we discuss our findings in the context of previous results on the impact of negative feedback in burst size and burst frequency on gene-expression noise.
Neural overlap in item representations across episodes impairs context memory
Authors: Kim Ghootae , Norman Kenneth A. , Turk-Browne Nicholas B. 
Published: April 2017

AbstractWe frequently encounter the same item in different contexts, and when that happens, memories of earlier encounters can get reactivated in the brain. Here we examined how these existing memories are changed as a result of such reactivation. We hypothesized that when an item’s initial and subsequent neural representations overlap, this allows the initial item to become associated with novel contextual information, interfering with later retrieval of the initial context. That is, we predicted a negative relationship between representational similarity across repeated experiences of an item and subsequent source memory for the initial context. We tested this hypothesis in an fMRI study, in which objects were presented multiple times during different tasks. We measured the similarity of the neural patterns in lateral occipital cortex that were elicited by the first and second presentations of objects, and related this neural overlap score to source memory in a subsequent test. Consistent with our hypothesis, greater item-specific pattern similarity was linked to worse source memory for the initial task. Our findings suggest that the influence of novel experiences on an existing context memory depends on how reliably a shared component (i.e., same item) is represented across these episodes.
Morphogen And Community Effects Determine Cell Fates In Response To BMP4 Signaling In Human Embryonic Stem Cells
Authors: Nemashkalo Anastasiia , Ruzo Albert , Heemskerk Idse , Warmflash Aryeh 
Published: April 2017

AbstractParacrine signals maintain developmental states and create cell-fate patterns in vivo, and influence differentiation outcomes in human embryonic stem cells (hESCs) in vitro. Systematic investigation of morphogen signaling is hampered by the difficulty of disentangling endogenous signaling from experimentally applied ligands. Here, we grow hESCs in micropatterned colonies of 1-8 cells (“μColonies”) to quantitatively investigate paracrine signaling and the response to external stimuli. We examine BMP4-mediated differentiation in μColonies and standard culture conditions and find that in μColonies, above a threshold concentration, BMP4 gives rise to only a single cell fate, contrary to its role as a morphogen in other developmental systems. Under standard culture conditions, BMP4 acts as morphogen, but this effect requires secondary signals and particular cell densities. We further find that a “community effect” enforces a common fate within μColonies both in the state of pluripotency and when cells are differentiated, and that this effect allows more precise response to external signals. Using live cell imaging to correlate signaling histories with cell fates, we demonstrate that interactions between neighbors result in sustained, homogenous signaling necessary for differentiation.Summary StatementWe quantitatively examined signaling and differentiation in hESC colonies of varying size treated with BMP4. We show that secondary signals result in morphogen and community effects that determine cell fates.
Systematic Identification of Correlates of HIV-1 Infection: An X-Wide Association Study in Zambia
Authors: Patel Chirag J. , Bhattacharya Jay , Ioannidis John P.A. , Bendavid Eran 
Published: April 2017

AbstractBackgroundHIV-1 remains the leading cause of death among adults in Sub-Saharan Africa, and over 1 million people are infected annually. Better identification of at-risk groups could benefit prevention and treatment programmes. We systematically identified factors related to HIV-1 infection in two nationally representative cohorts of women that participated in Zambia’s Demographic and Health Surveys (DHS).MethodsWe conducted a comprehensive analysis to identify and replicate the association of 1,415 social, economic, environmental, and behavioral indicators with HIV-1 status. We used the 2007 and 2013-2014 DHS surveys conducted among 5,715 and 15,433 Zambian women, respectively (727 indicators in 2007; 688 in 2013-2014; 688 in both). We used false discovery rate criteria to identify indicators that are strongly associated with HIV-1 in univariate and multivariate models in the entire population, as well as in subgroups stratified by wealth, residence, age, and history of HIV-1 testing.FindingsIn the univariate analysis we identified 102 and 182 variables that are associated with HIV-1 in the 2007 and 2013-2014 surveys, respectively, among which 79 were associated in both. Variables that were associated with HIV-1 status in all full-sample models (unadjusted and adjusted) as well as in at least 17 out of 18 subgroups include being formerly in a union (adjusted OR 2007 2.8, p<10−16; 2013-2014 2.8, p<10−29), widowhood (adjusted OR 2007 3.7, p<10−12; 2013-2014 4.2, p<10−30), history of genital ulcers in the last 12 months (adjusted 2007 OR 2.4, p<10−5; 2013-2014 2.2, p<10−6), and having a woman for the head of the household (2007 OR 1.7, p<10−7; 2013-2014 OR 2.1, p<10−26), while owning a bicycle (adjusted 2007 OR 0.6, p<10−6; 2013-2014 0.6, p<10−8) and currently breastfeeding (adjusted 2007 OR 0.5, p<10−9; 2013-2014 0.4, p<10−26) were associated with decreased risk. Using the identified variables, area under the curve for HIV-1 positivity ranged from 0.76 to 0.82.InterpretationOur X-wide association study in Zambian women identifies multiple under-recognized factors correlated with HIV-1 infection in 2007 and 2013-2014, including widowhood, breastfeeding, and being the head of the household. These variables could be used to improve HIV-1 testing and identification programs.
Robust inference in summary data Mendelian randomisation via the zero modal pleiotropy assumption
Authors: Hartwig Fernando Pires , Smith George Davey , Bowden Jack 
Published: April 2017

AbstractBackgroundMendelian randomisation (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions.MethodsHere, a new method –the mode-based estimate (MBE) – is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk.ResultsThe MBE presented less bias and type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared to the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia.ConclusionsThe MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in a sensitivity analysis.Key MessagesSummary data Mendelian randomisation, typically in a two-sample setting, is being increasingly used due to the availability of summary association results from large genome- wide association studies.Mendelian randomisation analyses using multiple genetic instruments are prone to bias due to horizontal pleiotropy, especially when genetic instruments are selected based solely on statistical criteria.A causal effect estimate robust to horizontal pleiotropy can be obtained using the mode- based estimate (MBE).The MBE requires that the most common causal effect estimate is a consistent estimate of the true causal effect, even if the majority of instruments are invalid (i.e., the ZEro Modal Pleiotropy Assumption, or ZEMPA).Plotting the smoothed empirical density function is useful to explore the distribution of causal effect estimates, and to understand how the MBE is determined.
Marketing implications from a behaviourism perspective of consumption dynamics and socio-demographics of wine consumers
Authors: Bruwer Johan , McCutcheon Emily 
Published: April 2017

Purpose
The purpose of this paper is to facilitate a better understanding of the insights provided by adopting a behaviourism perspective of the socio-demographics, consumption dynamics and retail channel patronage of wine consumers and the potential marketing implications these have.

Design/methodology/approach
Systematic random sampling yielded 811 surveys of wine consumers collected at households across Australia’s three main consumption metropoles. A hierarchical multiple regression model is used to test the predictive ability of the socio-demographical variables, gender and age, on personal wine consumption.

Findings
Specific differences exist in the consumption behaviour and wine type preferences of males and females, and between generational cohorts, specifically Millennial and older consumers. There are gender significant differences in wine type consumption, which in turn is moderated by not only the “classical” socio-demographic variables, but also the retail outlet types preferred for product purchase. Younger Millennial females place more importance on external choice cues in making their buying decision than males. The gender and age generation socio-demographic variables are not strong predictors of personal wine consumption.

Practical implications
Opportunities exist for niche-marketed brands targeted at specific segments such as young females and this study highlighted their specific needs and consumer behaviour dynamics.

Originality/value
This study illustrates through carefully executed wine consumer behaviour research, directed by questioning from the extant literature, how information derived from a behaviourism perspective can intelligently inform marketing strategies. In the process, it also provides “baselines” for future research.
Assessing two consumer behavioural intention models in a service environment
Authors: Parvin Shehely , Wang Paul Z. , Uddin Jashim 
Published: April 2017

Purpose
The purpose of this paper is to examine two alternative consumer behavioural intention models that have been developed from the marketing and information systems disciplines in a service environment. Specifically, it reports an empirical assessment of the two non-nested structural models in the context of Australian restaurant industry.

Design/methodology/approach
This study used a web-based survey by an online research organization and structural equation modelling with AMOS was used to compare the two non-nested behavioural intention models.

Findings
This study found that the second model that incorporates expectation-confirmation theory outperformed the first model in terms of model fit with the empirical data.

Practical implications
The findings of this study provide service managers with important insights into the appropriate design of service delivery systems to increase consumer satisfaction which, in turn, leads to more positive behavioural intentions. Moreover, the restaurant research setting means that marketing managers in the growing tourism and hospitality industry should benefit from the study findings.

Originality/value
This study synthesized two consumer behavioural intention models from different disciplines and provided an approach to the empirical comparison of the non-nested structural models.
Schools, universities and history in the world of twenty-first century skills
Authors: Yates Lyn 
Published: April 2017

Purpose
This paper was originally presented as a keynote presentation to the annual conference of the ANZHES whose theme was “knowledge skills and expertise”. The purpose of this paper is to reflect on history as a field of study in the context of changing conditions and new debates about knowledge in the twenty-first century.

Design/methodology/approach
The paper reviews three important lines of sociological argument about changed conditions for knowledge: the case to “bring knowledge back in” to school curriculum; the contention that knowledge in universities is moving from “mode 1” to “mode 2” forms; and arguments about testing and audit culture effects on the practices of universities and schools. It then draws on interviews with historians and history teachers to show how they think about the form of their field, its value, and the impact of the changing conditions signalled in those arguments.

Findings
The paper argues that some features of the discipline which have been important to history continue to be apparent but are under challenge in the conditions of education institutions today and that there is a disjunction between teachers’ views of the value of history and those evident in the public political arena.

Research limitations/implications
The paper draws on a major Australia Research Council funded study of “knowledge building across schooling and higher education” which focusses on issues of disciplinarity and the fields of physics and history.

Originality/value
The paper is intended as a new reflection on the field of value to those working as historians.