bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Psychological and Physiological Part of Emotions: Multimodal Approximation for Valence Classification
Authors: Sorinas Jennifer , Ferrández Jose Manuel , Fernandez Eduardo 
Published: May 2019

AbstractIn order to develop more precise and functional affective applications, it is necessary to achieve a balance between the psychology and the engineering applied to emotions. Signals from the central and peripheral nervous systems have been used for emotion recognition purposes, however, their operation and the relationship between them remains unknown. In this context, in the present work we have tried to approach the study of the psychobiology of both systems in order to generate a computational model for the recognition of emotions in the dimension of valence. To this end, the electroencephalography (EEG) signal, electrocardiography (ECG) signal and skin temperature of 24 subjects have been studied. Each methodology has been evaluated individually, finding characteristic patterns of positive and negative emotions in each of them. After feature selection of each methodology, the results of the classification showed that, although the classification of emotions is possible at both central and peripheral levels, the multimodal approach did not improve the results obtained through the EEG alone. In addition, differences have been observed between cerebral and physiological responses in the processing emotions by separating the sample by sex; though, the differences between men and women were only notable at the physiological level.
Male sex chromosomal complement exacerbates the pathogenicity of Th17 cells in a chronic model of CNS autoimmunity
Authors: Arokia Doss Prenitha Mercy Ignatius , Baillargeon Joanie , Yeola Asmita Pradeep , Williams John B. , Leclercq Mickael , Joly-Beauparlant Charles , Alpaugh Melanie , Anderson Ana C. , Droit Arnaud , Lassmann Hans , Moore Craig S. , Rangachari Manu 
Published: May 2019

SummarySex differences in the incidence and severity of multiple sclerosis (MS) have long been recognized. However, the underlying cellular and molecular mechanisms for why male sex is associated with more aggressive and debilitating disease remain poorly defined. Using an T cell adoptive transfer model of chronic EAE, we find that male Th17 cells induced disease of increased severity relative to female Th17 cells, irrespective of whether transferred to male or female recipients. Throughout the disease course, a greater frequency of male Th17 cells produced the heterodox cytokine IFNγ, a hallmark of pathogenic Th17 responses. Intriguingly, sex chromosomal complement, and not hormones, were responsible for the increased pathogenicity of male Th17 cells and an X-linked immune regulator,Jarid1c, was downregulated in both pathogenic male Th17 and CD4+T cells from men with MS. Together, our data indicate that male sex critical regulates Th17 cell plasticity and pathogenicity via sex chromosomal complement.
Accuracy of robotic coil positioning during transcranial magnetic stimulation
Authors: Goetz Stefan M. , Kozyrkov I. Cassie , Luber Bruce , Lisanby Sarah H. , Murphy David L. K. , Grill Warren M. , Peterchev Angel V. 
Published: May 2019

AbstractObjectiveRobotic positioning systems for transcranial magnetic stimulation (TMS) promise improved accuracy and stability of coil placement, but there is limited data on their performance. This text investigates the usability, accuracy, and limitations of robotic coil placement with a commercial system, ANT Neuro, in a TMS study.Approach21 subjects underwent a total of 79 TMS sessions corresponding to 160 hours under robotic coil control. Coil position and orientation were monitored concurrently through an additional neuronavigation system.Main ResultsRobot setup took on average 14.5 min. The robot achieved low position and orientation error with median 1.34 mm and 3.48°. The error increased over time at a rate of 0.4%/minute for both position and orientation.SignificanceAfter the elimination of several limitations, robotic TMS systems promise to substantially improve the accuracy and stability of manual coil position and orientation. Lack of pressure feedback and of manual adjustment of all coil degrees of freedom were limitations of this robotic system.
Spring Model – chromatin modeling tool based on OpenMM
Authors: Kadlof Michal , Rozycka Julia , Plewczynski Dariusz 
Published: May 2019

AbstractChromatin structures modelling is a rapidly developing field. Parallel to the enormous growth of available experimental data, there is a growing need of building and visualizing 3D structures of nuclei, chromosomes, chromatin domains, and single loops associated with particular genes locus. Here we present a tool for chromatin domain modeling. It is available as a webserver and standalone python script. Our tool is based on molecular mechanics. It uses OpenMM engine for building models. In this method, the user has to provide contacts and will obtain 3D structure that satisfies these contacts. Additional extra parameters allow controlling fibre stiffness, type of initial structure, resolution. There are also options for structure refinement, and modelling in a spherical container. A user may provide contacts using beads indices, or paste interactions in genome coordinates from BEDPE file. After modelling user is able to download the structure in Protein Data Bank (PDB) file format for further analysis.We dedicate this tool for all who are interested in chromatin structures. It is suitable for quick visualization of datasets, studying the impact of structural variants (SVs), inspecting the effects of adding and removing particular contacts, measuring features like maximum distances between certain sites (e.g. promotor-enhancer) or local density of chromatin.
SAFEPPP: a Simple And Fast method to Find and analyze Extreme Points of a metabolic Phenotypic Phase Plane
Authors: Moteallehi-Ardakani Mohammad Hossein , Marashi Sayed-Amir 
Published: May 2019

AbstractThere are many algorithms that help us understand how genome-scale metabolic networks work and what are their capabilities. But unfortunately, the majority of these methods are based on integer linear programming suffer from long run times and high instrumental demand. Optimal solutions in any constraint-based modeling as genome-scale metabolic networks models are on the extreme points of the solution space. We introduce a fast and simple toolbox that reveals extreme characters of metabolic networks in desired situations which can unmask the hidden potentials of metabolic networks. Determining the possibility of coupling between two desired reaction and the capability of synergic substrate consuming are examples of the applications of this method. Fast enumeration of elementary flux modes that exist in extreme points of phase plane of any two reactions is another achievement of this study.
Selective integration during sequential sampling in posterior neural signals
Authors: Luyckx Fabrice , Spitzer Bernhard , Blangero Annabelle , Tsetsos Konstantinos , Summerfield Christopher 
Published: May 2019

AbstractDecisions are typically made after integrating information about multiple attributes of alternatives in a choice set. The computational mechanisms by which this integration occurs have been a focus of extensive research in humans and other animals. Where observers are obliged to consider attributes in turn, a framework known as “selective integration” can capture salient biases in human choices. The model proposes that successive attributes compete for processing resources and integration is biased towards the alternative with the locally preferred attribute. Quantitative analysis shows that this model, although it discards choice-relevant information, is optimal when the observers’ decisions are corrupted by noise that occurs beyond the sensory stage. Here, we used scalp electroencephalographic (EEG) recordings to test a neural prediction of the model: that locally preferred attributes should be encoded with higher gain in neural signals over posterior cortex. Over two sessions, human observers (of either sex) judged which of two simultaneous streams of bars had the higher (or lower) average height. The selective integration model fit the data better than a rival model without bias. Single-trial analysis showed that neural signals contralateral to the preferred attribute covaried more steeply with the decision information conferred by locally preferred attributes. These findings provide neural evidence in support of selective integration, complementing existing behavioural work.Significance StatementWe often make choices about stimuli with multiple attributes, such as when deciding which car to buy on the basis of price, performance and fuel economy. A model of the choice process, known as selective integration, proposes that rather than taking all of the decision-relevant information equally into account when making choices, we discard or overlook a portion of it. Although information is discarded, this strategy can lead to better decisions when memory is limited. Here, we test and confirm predictions of the model about the brain signals that occur when different stimulus attributes of stimulus are being evaluated. Our work provides the first neural support for the selective integration model.
Oligonucleotide Length Determines Intracellular Stability of DNA-Wrapped Carbon Nanotubes
Authors: Gravely Mitchell , Safaee Mohammad Moein , Roxbury Daniel 
Published: May 2019

AbstractNon-covalent hybrids of single-stranded DNA and single-walled carbon nanotubes (SWCNTs) have demonstrated applications in biomedical imaging and sensing due to their enhanced biocompatibility and photostable, environmentally-responsive near-infrared (NIR) fluorescence. The fundamental properties of such DNA-SWCNTs have been studied to determine the correlative relationships between oligonucleotide sequence and length, SWCNT species, and the physical attributes of the resultant hybrids. However, intracellular environments introduce harsh conditions that can change the physical identities of the hybrid nanomaterials, thus altering their intrinsic optical properties. Here, through visible and NIR fluorescence imaging in addition to confocal Raman microscopy, we show that the oligonucleotide length determines the relative uptake, intracellular optical stability, and expulsion of DNA-SWCNTs in mammalian cells. While the absolute NIR fluorescence intensity of DNA-SWCNTs in murine macrophages increases with increasing oligonucleotide length (from 12 to 60 nucleotides), we found that shorter oligonucleotide DNA-SWCNTs undergo a greater magnitude of spectral shift and are more rapidly internalized and expelled from the cell after 24 hours. Furthermore, by labeling the DNA with a fluorophore that dequenches upon removal from the SWCNT surface, we found that shorter oligonucleotide strands are displaced from the SWCNT within the cell, altering the physical identity and changing the fate of the internalized nanomaterial. These findings provide fundamental understanding of the interactions between SWCNTs and live cells which can be applied towards development of robustly engineered carbon nanotube sensors while mitigating associated nanotoxicity.
TOC Graphic
To Tweet or Not to Tweet, That is the Question: A Randomized Trial of Twitter Effects on Article Engagement in Medical Education
Authors: Maggio Lauren A. , Leroux Todd C. , Artino Anthony R. 
Published: May 2019

AbstractMany medical education journals use Twitter to garner attention for their articles. The purpose of this study was to test the effects of tweeting on article page views and downloads.The authors conducted a randomized trial usingAcademic Medicinearticles published in 2015. Beginning in February through May 2018, one article per day was randomly assigned to a Twitter (case) or control group. Daily, an individual tweet was generated for each article in the Twitter group that included the title, #MedEd, and a link to the article. The link delivered users to the article’s landing page, which included immediate access to the HTML full text and a PDF link. The authors extracted HTML page views and PDF downloads from the publisher. To assess differences in page views and downloads between cases and controls, a time-centered approach was used, with outcomes measured at 1, 7, and 30 days.In total, 189 articles (94 cases, 95 controls) were analyzed. After days 1 and 7, there were no statistically significant differences between cases and controls on any metric. On day 30, HTML page views exhibited a 63% increase for cases (M=14.72, SD=63.68) when compared to controls (M=9.01, SD=14.34; incident rate ratio=1.63, p=0.01). There were no differences between cases and controls for PDF downloads on day 30.Contrary to the authors’ hypothesis, only one statistically significant difference in page views between the Twitter and control groups was found. These findings provide preliminary evidence that after 30 days a tweet can have a small positive effect on article page views.
Estimating MIC distributions and cutoffs through mixture models: an application to establish M. Tuberculosis resistance
Authors: Grazian Clara 
Published: May 2019

AbstractAntimicrobial resistance is becoming a major threat to public health throughout the world. Researchers from around the world are attempting to contrast it by developing both new antibiotics and patient-specific treatments. It is, therefore, necessary to study these treatments, via phenotypic tests, and it is essential to have robust methods available to analyze the resistance patterns to medication, which could be applied to both new treatments and to new phenotypic tests. A general method is here proposed to study minimal inhibitory concentration (MIC) distributions and fixed breakpoints in order to separate sensible from resistant strains. The method has been applied to a new 96-well microtiter plate.
A theoretical and econometric evaluation of corporate governance and capital structure in JSE-listed companies
Authors: Sewpersadh Navitha Singh 
Published: May 2019

PurposeA vital resource for attracting investments and boosting economic growth is compliance with corporate-governance practices. To achieve firm growth, businesses often rely on leverage as a source of finance, which has tax-saving benefits but could attract financial distress costs. In this context, this study aims to examine the relationship between corporate governance and the use of debt financing in Johannesburg Stock Exchange (JSE)-listed companies.Design/methodology/approachThis study used a six-year period to examine 713 annual reports in an unbalanced panel of 130 JSE-listed companies from 2011 to 2016. The empirical econometric methodology used was the two-step difference generalised method of moments estimation model, which is robust in controlling endogeneity and potential bi-directional causality between leverage and corporate governance.FindingsThis study illustrated that corporate governance practices and firm-specific variables such as profitability, firm size and firm age have a significant influence on the capital structure decisions of JSE-listed firms. This study found support for four out of the six hypotheses. CEO duality and director ownership are positively correlated with leverage, whereas audit committee independence and board size are negatively correlated with leverage. This study also found contraventions of board independence, audit committee independence and CEO duality. The technology sector was the least compliant, with only 40 per cent of their boards being independent. The consumer-services sector had the maximum presence of CEO duality (7 per cent). The industrial sector had the highest average director ownership (18 per cent). The heath-care sector had 28 per cent of their audit committees in contravention of the independence rule.Practical implicationsA useful analysis of the theoretical frameworks used by academic writers are provided. This study revealed the governance practices contravened by the relevant sectors, as well as the associations between corporate governance and leverage.Originality/valueThe study contributes to the literature on capital structure and corporate governance by an emerging economy such as South Africa (SA) which has not been explored. This study’s results have key implications for policy-makers, practitioners, investors and regulatory authorities. This study informs these constituencies about a set of governance attributes that are catalysts and/or inhibitors of leverage.
Locating, Identifying, and Comparing Sub‐visible Paint Particles
Authors: Palenik Christopher S. , Groves Ethan , Insana Joseph , Palenik Skip 
Published: May 2019

AbstractForensic paint comparisons are generally conducted on samples which, while small relative to their source, are still visible to the unaided eye and are thus located and analyzed without great difficulty. Here we demonstrate that a more detailed examination of candidate transfer surfaces can capture materials (questioned samples), even when such traces are invisible to the unaided eye. While certain analytical details (such as layer sequence or a pure FTIR spectrum) may not be obtainable from such traces due to their size and condition, a detailed analysis of the sample characteristics that are analytically accessible may still provide sufficient analytical data to arrive at a probative result. Here we present the application of this approach to a suspected paint transfer case, involving particles of paint as small as 40 μm in size. Using a combination of stereomicroscopy, polarized light microscopy, infrared microspectroscopy, Raman microspectroscopy, and SEM/EDS, all performed on a single, subsample of the original minute particle, it was possible to demonstrate evidence of a two‐way transfer between the suspected sources. Furthermore, the transferred paint particle in one direction could be classified as automotive in nature based on a combination of polymer composition, microscopic texture, and pigment package (which included three specifically identified pigments). This work demonstrates (i) the potential for improving detection limits when searching for a questioned sample, (ii) the potential benefits of higher resolution analyses on samples that would be traditionally labeled as “sample‐size limited,” and (iii) the value of case‐specific interpretation over standardized, one‐size fits all report templates.
Medical marijuana laws are associated with increases in substance use treatment admissions by pregnant women
Authors: Meinhofer Angélica , Witman Allison , Murphy Sean M. , Bao Yuhua 
Published: May 2019

AbstractBackground and AimsBetween 2002 and 2014, past‐month marijuana use among pregnant women in the United States increased 62%, nearly twice the growth of the general population. This growth coincides with the proliferation of state medical marijuana laws (MMLs) authorizing physicians to recommend marijuana for approved conditions. We estimated the association between MMLs and substance use treatment utilization among pregnant and non‐pregnant women of reproductive age. We also examined whether the association varied across MML provisions, age groups and treatment referral sources to clarify potential pathways.DesignNation‐wide administrative data from the 2002–14 Treatment Episodes Data Set Admissions, and a difference‐in‐differences design that exploited the staggered implementation of MMLs to compare changes in outcomes before and after implementation between MML and non‐MML states.SettingTwenty‐one MML and 27 non‐MML US states.ParticipantsPregnant and non‐pregnant women aged 12–49 admitted to publicly funded specialty substance use treatment facilities.MeasurementsThe primary outcome variable was the number of treatment admissions per 100 000 women aged 12–49, aggregated at the state‐year level (n = 606). Admissions for marijuana, alcohol, cocaine and opioids were considered. The primary independent variable was an indicator of MML implementation in a state.FindingsAmong pregnant women, the rate of marijuana treatment admissions increased by 4.69 [95% confidence interval (CI) = 1.32, 8.06] in MML states relative to non‐MML states. This growth was accompanied by increases in treatment admissions involving alcohol (β = 3.19; 95% CI = 0.97, 5.410 and cocaine (β = 2.56; 95% CI = 0.34, 4.79), was specific to adults (β = 5.50; 95% CI = 1.52, 9.47) and was largest in states granting legal protection for marijuana dispensaries (β = 6.37; 95% CI = –0.97, 13.70). There was no statistically significant association between MMLs and treatment admissions by non‐pregnant women.ConclusionsMedical marijuana law implementation in US states has been associated with greater substance use treatment utilization by pregnant adult women, especially in states with legally protected dispensaries.
Saliva cotinine concentrations in pregnant women who smoke and use nicotine patches
Authors: Claire Ravinder , Coleman Tim , Leonardi‐Bee Jo , Berlin Ivan 
Published: May 2019

AbstractBackground and AimsDue to concerns about increased exposure to nicotine, pregnant women using nicotine replacement therapy (NRT) to stop smoking are usually advised to stop using NRT if they relapse to smoking. This study investigated whether this is justified. We compared changes in saliva cotinine from baseline to 2 weeks post‐target quit date pregnant smokers who relapsed to smoking and continued to use their patches having been assigned to use nicotine patches or placebo.Design and SettingControlled pre–post design stratified by intervention condition from the ‘Study of Nicotine Patch in Pregnancy’, a randomized, placebo‐controlled trial.ParticipantsA sample of 268 pregnant women, assigned placebo (n = 122) or nicotine (n = 146) patches, who returned for further supplies of patches and who reported any smoking in the week prior to a visit at 2 weeks after their target quit date.MeasurementsSaliva cotinine concentrations were measured at baseline and 2 weeks after participants’ target quit dates. Any smoking in the previous week was assessed by self‐report, validated by expired air carbon monoxide (CO).FindingsThere was no change in saliva cotinine concentrations between baseline and 2 weeks post‐target quit date in saliva cotinine concentration in the nicotine patch group [ratio of geometric means = 0.94, 95% confidence interval (CI) = 0.83 to 1.07; P = 0.37, Bayes factor = 0.15]. However, there was a reduction in reported number of cigarettes smoked/day (mean difference −6, 95% CIs −7 to −5, P < 0.001) and in CO concentrations (mean difference −3.0 parts per million, 95% CIs −4.2 to −1.9, P < 0.001). These changes were not significantly different from changes in the placebo group except for cigarette consumption, which reduced more in the nicotine group (P = 0.046).ConclusionsIn women trying to stop smoking with the aid of a nicotine patch but having smoked at 2 weeks post‐target quit, their nicotine concentration did not change from baseline, but they reported smoking fewer cigarettes and had lower carbon monoxide concentrations.