bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multivariate Analyses Reveal Biological Components Related to Neuronal Signaling and Immunity Mediating Electroencephalograms Abnormalities in Alcohol‐Dependent Individuals from the Collaborative Study on the Genetics of Alcoholism Cohort
Authors: Meda Shashwath A. , Narayanan Balaji , Chorlian David , Meyers Jacquelyn L. , Gelernter Joel , Hesselbrock Victor , Bauer Lance , Calhoun Vince D. , Porjesz Bernice , Pearlson Godfrey D. 
Published: April 2019

BackgroundThe underlying molecular mechanisms associated with alcohol use disorder (AUD) risk have only been partially revealed using traditional approaches such as univariate genomewide association and linkage‐based analyses. We therefore aimed to identify gene clusters related to Electroencephalograms (EEG) neurobiological phenotypes distinctive to individuals withAUDusing a multivariate approach.MethodsThe current project adopted a bimultivariate data‐driven approach, parallel independent component analysis (para‐ICA), to derive and explore significant genotype–phenotype associations in a case–control subset of the Collaborative Study on the Genetics of Alcoholism (COGA) dataset. Para‐ICAsubjects comprisedN = 799 self‐reported European Americans (367 controls and 432AUDcases), recruited fromCOGA, who had undergone restingEEGand genotyping. BothEEGand genomewide single nucleotide polymorphism (SNP) data were preprocessed prior to being subjected to para‐ICA in order to derive genotype–phenotype relationships.ResultsFrom the data, 4EEGfrequency and 4SNPcomponents were estimated, with 2 significantly correlatedEEG–genetic relationship pairs. The first such pair primarily represented theta activity, negatively correlated with a genetic cluster enriched for (but not limited to) ontologies/disease processes representing cell signaling, neurogenesis, transmembrane drug transportation, alcoholism, and lipid/cholesterol metabolism. The second component pair represented mainly alpha activity, positively correlated with a genetic cluster with ontologies similarly enriched as the first component. Disease‐related enrichments for this component revealed heart and autoimmune disorders as top hits. Loading coefficients for both the alpha and theta components were significantly reduced in cases compared to controls.ConclusionsOur data suggest plausible multifactorial genetic components, primarily enriched for neuronal/synaptic signaling/transmission, immunity, and neurogenesis, mediating low‐frequency alpha and theta abnormalities in alcohol addiction.
Novel Role of Macrophage Migration Inhibitory Factor in Upstream Control of the Unfolded Protein Response After Ethanol Feeding in Mice
Authors: Poulsen Kyle Lauren , McMullen Megan R. , Huang Emily , Kibler Christopher D. , Sheehan Megan M. , Leng Lin , Bucala Richard , Nagy Laura E. 
Published: April 2019

BackgroundMacrophage migration inhibitory factor (MIF), a pluripotent immune regulator, is an emerging mediator in alcohol‐related liver disease (ALD).MIFis associated withALDprogression through its chemokine‐ and cytokine‐like activities.MethodsMechanistic studies into the role ofMIFin ethanol (EtOH)‐induced liver injury were performed inMif−/−mice and in C57BL/6J mice treated with a small‐moleculeMIFantagonist,MIF098, after Gao‐Binge (acute‐on‐chronic) EtOH feeding, an EtOH feeding protocol associated with hepatic neutrophilia and induction of the unfolded protein response (UPR).ResultsTheMIFaxis, for example,MIFandMIFreceptors invariant polypeptide of major histocompatibility complex, class II antigen‐associated (CD74),CXCR2,CXCR4, andCXCR7, was enhanced in the livers of alcoholic hepatitis (AH) patients as compared to healthy controls.Mif−/−mice were protected from hepatocellular injury after Gao‐Binge feeding, independent of neutrophilia and inflammation, but were associated with theUPR. Interestingly, theUPRsignature inAHpatients and in mice following Gao‐Binge feeding was biased toward cell death with increased expression of pro‐cell death CCAAT–enhancer‐binding protein homologous protein (CHOP) and decreased prosurvivalGRP78. TheUPRand liver injury 6 hours after binge were prevented both inMif−/−mice and inMIF098‐treated mice. However, bothMIFinterventions led to increased liver injury and exacerbated the hepaticUPR9 hours after binge. Induction of upstreamUPRsignaling and expression ofCHOPprotein by thapsigargin in alpha mouse liver 12 hepatocytes were blunted by coexposure toMIF098, directly connectingMIFtoUPRin hepatocytes.ConclusionsThe current study revealed that, in addition to its cytokine/chemokine functions,MIFis an upstream regulator ofUPRin response to EtOH feeding in mice. Importantly, bothMIFandUPRcan either protect or contribute to liver injury, dependent upon the stage or severity of EtOH‐induced liver injury.
Effect of feeding rice whole crop silage on growth rate, levels of vitamin A, β‐carotene, vitamin E and IGF‐1 in plasma and skeletal muscle protein degradation in Japanese black calves
Authors: Tsuruoka Katsuhiko , Kurahara Takami , Kanamaru Hidenobu , Takahashi Hideyuki , Gotoh Takafumi 
Published: April 2019

AbstractThis study evaluated the effects of rice whole crop silage (RWCS) on growth, plasma levels of vitamin A, β‐carotene, vitamin E and IGF‐1, and expression of genes involved in muscle protein degradation and synthesis in Japanese Black calves. Eleven calves were divided into RWCS (fed RWCS ad libitum and concentrate, n = 5) and control groups (fed hay ad libitum and concentrate, n = 6). Final body weight and dairy gain were significantly larger in the RWCS group compared with the control group. Plasma β‐carotene and vitamin E concentrations were significantly higher in the RWCS group compared with control group. Although plasma vitamin E concentration in the RWCS group significantly increased from 4 to 9 months of age, it did not increase in the control group. At 6 months of age in the RWCS group, ubiquitin B (p < 0.05) and calpain 1 (p = 0.097) mRNA expression were lower than control group, but they were not different between groups at 9 months of age. These results indicate that RWCS increases plasma β‐carotene level and promotes muscle growth because of a decrease in the rate of protein degradation, but the effect is lost with the increase in plasma vitamin E level.
Fast Bayesian Inference in Large Gaussian Graphical Models
Authors: Leday Gwenaël G. R. , Richardson Sylvia 
Published: April 2019

AbstractDespite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a method to infer the marginal and conditional independence structures between variables by multiple testing, which bypasses the exploration of the model space. Specifically, we introduce closed-form Bayes factors under the Gaussian conjugate model to evaluate the null hypotheses of marginal and conditional independence between variables. Their computation for all pairs of variables is shown to be extremely efficient, thereby allowing us to address large problems with thousands of nodes as required by modern applications. Moreover, we derive exact tail probabilities from the null distributions of the Bayes factors. These allow the use of any multiplicity correction procedure to control error rates for incorrect edge inclusion. We demonstrate the proposed approach on various simulated examples as well as on a large gene expression data set from The Cancer Genome Atlas.
Copula-Based Semiparametric Models for Spatiotemporal Data
Authors: Tang Yanlin , Wang Huixia J. , Sun Ying , Hering Amanda S. 
Published: April 2019

Abstract
The joint analysis of spatial and temporal processes poses computational challenges due to the data's high dimensionality. Furthermore, such data are commonly non-Gaussian. In this paper, we introduce a copula-based spatiotemporal model for analyzing spatiotemporal data and propose a semiparametric estimator. The proposed algorithm is computationally simple, since it models the marginal distribution and the spatiotemporal dependence separately. Instead of assuming a parametric distribution, the proposed method models the marginal distributions nonparametrically and thus offers more flexibility. The method also provides a convenient way to construct both point and interval predictions at new times and locations, based on the estimated conditional quantiles. Through a simulation study and an analysis of wind speeds observed along the border between Oregon and Washington, we show that our method produces more accurate point and interval predictions for skewed data than those based on normality assumptions.
Using a Surrogate Marker for Early Testing of a Treatment Effect
Authors: Parast Layla , Cai Tianxi , Tian Lu 
Published: April 2019

Abstract
The development of methods to identify, validate, and use surrogate markers to test for a treatment effect has been an area of intense research interest given the potential for valid surrogate markers to reduce the required costs and follow-up times of future studies. Several quantities and procedures have been proposed to assess the utility of a surrogate marker. However, few methods have been proposed to address how one might use the surrogate marker information to test for a treatment effect at an earlier time point, especially in settings where the primary outcome and the surrogate marker are subject to censoring. In this paper, we propose a novel test statistic to test for a treatment effect using surrogate marker information measured prior to the end of the study in a time-to-event outcome setting. We propose a robust nonparametric estimation procedure and propose inference procedures. In addition, we evaluate the power for the design of a future study based on surrogate marker information. We illustrate the proposed procedure and relative power of the proposed test compared to a test performed at the end of the study using simulation studies and an application to data from the Diabetes Prevention Program.
Integrative Analysis of Genetical Genomics Data Incorporating Network Structures
Authors: Gao Bin , Liu Xu , Li Hongzhe , Cui Yuehua 
Published: April 2019

Abstract
In a living organism, tens of thousands of genes are expressed and interact with each other to achieve necessary cellular functions. Gene regulatory networks contain information on regulatory mechanisms and the functions of gene expressions. Thus, incorporating network structures, discerned either through biological experiments or statistical estimations, could potentially increase the selection and estimation accuracy of genes associated with a phenotype of interest. Here, we considered a gene selection problem using gene expression data and the graphical structures found in gene networks. Because gene expression measurements are intermediate phenotypes between a trait and its associated genes, we adopted an instrumental variable regression approach. We treated genetic variants as instrumental variables to address the endogeneity issue. We proposed a two-step estimation procedure. In the first step, we applied the LASSO algorithm to estimate the effects of genetic variants on gene expression measurements. In the second step, the projected expression measurements obtained from the first step were treated as input variables. A graph-constrained regularization method was adopted to improve the efficiency of gene selection and estimation. We theoretically showed the selection consistency of the estimation method and derived the bound of the estimates. Simulation and real data analyses were conducted to demonstrate the effectiveness of our method and to compare it with its counterparts.
Detection of Differentially Expressed Genes in Discrete Single-Cell RNA Sequencing Data Using a Hurdle Model With Correlated Random Effects
Authors: Sekula Michael , Gaskins Jeremy , Datta Susmita 
Published: April 2019

Abstract
Single-cell RNA sequencing (scRNA-seq) technologies are revolutionary tools allowing researchers to examine gene expression at the level of a single cell. Traditionally, transcriptomic data have been analyzed from bulk samples, masking the heterogeneity now seen across individual cells. Even within the same cellular population, genes can be highly expressed in some cells but not expressed (or lowly expressed) in others. Therefore, the computational approaches used to analyze bulk RNA sequencing data are not appropriate for the analysis of scRNA-seq data. Here, we present a novel statistical model for high dimensional and zero-inflated scRNA-seq count data to identify differentially expressed (DE) genes across cell types. Correlated random effects are employed based on an initial clustering of cells to capture the cell-to-cell variability within treatment groups. Moreover, this model is flexible and can be easily adapted to an independent random effect structure if needed. We apply our proposed methodology to both simulated and real data and compare results to other popular methods designed for detecting DE genes. Due to the hurdle model's ability to detect differences in the proportion of cells expressed and the average expression level (among the expressed cells), our methods naturally identify some genes as DE that other methods do not, and we demonstrate with real data that these uniquely detected genes are associated with similar biological processes and functions.
Experience, represent, apply (ERA): A heuristic for digital engagement in the early years
Authors: Lowrie Tom , Larkin Kevin 
Published: April 2019

AbstractThis paper presents an heuristic that underpinned the development of a range of early years applications (apps) as part of the Early Learning Science, Technology, Engineering and Mathematics (STEM) Australia (ELSA) project (2016–19). The heuristic was developed to address a range of challenges that accompany the use of digital technologies in the year before formal schooling. These include the role of digital technologies in play‐based learning environments, screen time and the importance of agency when young children are using digital technologies. In an increasingly digital world, the issue of screen time looms large as a particularly contested aspect of technology use by young children. The ELSA project responded to this challenge by developing a pedagogical framework that embedded digital technologies into context‐rich, play‐based STEM learning. The Experience, Represent, Apply (ERA) heuristic discussed in this paper is a component of the project's overall pedagogical framework and provides early years educators with the opportunity, and the know‐how, to integrate digital technologies into STEM activities through intentional teaching and play‐based engagement. It was evident from educator feedback at the four days of workshops we delivered, and in other comments throughout the year long trial, that the educators were able to embrace the cyclic nature of the ERA heuristic and ensure that the time spent on the tablet (Represent) was connected to contextualised learning opportunities (Experience and Apply). Importantly, the tablets provided affordances for the children to utilise User Generated Content (UGC) to support active engagement when using the tablets.
Biological responses of human bone mesenchymal stem cells to Ti and TiZr implant materials
Authors: Yin Lihua , Chang Yaoren , You Yuanhe , Liu Chun , Li Jie , Lai Hong‐Chang 
Published: April 2019

AbstractBackgroundTitanium‐zirconium alloy (TiZr1317) is a new material used for biological implants. There are several studies on the effects of TiZr implants on the biological characteristics of human bone mesenchymal stem cells (hBMSCs).PurposeThe purpose of this study was to investigate the biological responses of hBMSCs to implant holes affected by the physicochemical properties of oral implants (TiSLA, TiSLActive, TiZrSLA, and TiZrSLActive).Materials and MethodsGrade 4 Ti and TiZr (13‐17% Zr) substrates were modified by sand‐blasted large‐grit acid‐etched (SLA) or hydrophilic sand‐blasted large‐grit acid‐etched (SLActive), resulting in four types of surface with complex microstructures corresponding to the commercially‐available implants SLA, RoxolidSLA, SLActive, and RoxolidSLActive (Institute Straumann AG, Basel, Switzerland). Physicochemical properties were detected and the biological responses of hBMSCs were observed.ResultsSurface morphology characterization by scanning electron microscopy and atomic force microscopy revealed differences between the four groups. SLActive had higher surface energy/wettability than SLA, indicating that increased surface energy/wettability can promote the absorption of osteogenic proteins and enhance osseointegration. hBMSCs seeded on SLActive substrates exhibited better performance in terms of cell attachment, proliferation and osteoblastic differentiation than cells seeded on SLA.ConclusionBecause of their more suitable physicochemical properties, TiSLActive and TiZrSLActive materials demonstrated more pronounced effects on the biological responses of hBMSCs compared with TiSLA and TiZrSLA.
Phase transformation and fracture load of stock and CAD/CAM‐customized zirconia abutments after 1 year of clinical function
Authors: Schepke Ulf , Gresnigt Marco M. M. , Browne Wesley R. , Abdolahzadeh Shaghayegh , Nijkamp Joey , Cune Marco S. 
Published: April 2019

AbstractObjectivesFunctional loading and low‐temperature degradation may give rise to impaired clinical long‐term service of zirconia implant abutments. The aim of this study was to compare the fracture strength (primary outcome measure) and the volume percentage of monoclinic surface zirconia (m‐ZrO2) of stock and CAD/CAM‐customized zirconia implant abutments that functioned clinically for 1 year with geometrically identical pristine controls in an ex vivo experiment.Material and methodsTwenty‐three stock (ZirDesign™) and 23 CAD/CAM‐customized (Atlantis™) zirconia implant abutments were retrieved after 1 year of clinical service. They were compared with pristine copies with respect to the volume fraction of the monoclinic phase using Raman spectroscopy and their fracture load by means of a single load‐to‐fracture test. Failure analysis was performed using optical and SEM microscopy. After verification of normal distribution, paired t tests were used for comparison of fracture loads between pristine and clinically aged specimen. All statistical tests employed a level of significance of α = 0.05.ResultsThe fracture loads of the stock zirconia abutments were significantly (p < 0.05) reduced to 78.8% (SD 29.5%) after one year of clinical function. For the CAD/CAM abutments, no reduction in fracture load was found. No m‐ZrO2 volume percentages beyond the detection threshold of 5% were observed in any of the samples.ConclusionsAfter 1 year of clinical service, no difference in fracture strength of the CAD/CAM‐customized zirconia implant abutments could be demonstrated, whereas the stock zirconia abutments decreased considerably in fracture strength. No substantial tetragonal‐to‐monoclinic transformation was observed.
Voluntary, permanent land protection reduces forest loss and development in a rural‐urban landscape
Authors: Nolte Christoph , Meyer Spencer R. , Sims Katharine R. E. , Thompson Jonathan R. 
Published: April 2019

AbstractVoluntary, permanent land protection is a key conservation process in many countries. Concerns with the effectiveness of such decentralized processes exist due to the potential for (1) selection bias, that is, the protection of parcels whose land cover would have been conserved in the absence of protection, and (2) local spillover effects, that is, protection increasing the likelihood that adjacent parcels lose land cover due to additional conversion. We examine the validity of both concerns using a quasi‐experimental approach and a dataset of 220,187 parcels and 26 years of protection and land‐cover change in Massachusetts. We find that land acquisitions and conservation restrictions implemented by state, local, and nongovernmental actors reduced forest loss and conversion to developed uses without increasing either type of land‐cover change on adjacent parcels. Our results suggest that voluntary, permanent land protection can make significant contributions in protecting land cover in landscapes dominated by private ownership.
Oral intramuscular hemangioma: Report of three cases
Authors: Lescura Carlos M. , de Andrade Bruno A. B. , Bezerra Kelly T. , Agostini Michelle , Ankha Milagros V. A. , de Castro Felix , Carvalho Yasmin R. , Romañach Mário J. , Anbinder Ana Lia 
Published: April 2019

AbstractIntramuscular hemangioma (IMH) represents less than 1% of all hemangiomas. In the head and neck region, it occurs mostly in the masseter, temporalis and sternocleidomastoid muscles. Despite its infiltrative growth pattern and several worrisome histological features, such as increased mitotic activity, plumpness of the nuclei, intraluminal papillary projections or perineural infiltration, the lesion is benign, and complete surgical excision is the preferred treatment for such oral lesions. Herein, we report three rare cases of IMH in the tongue and lip, discuss the clinical and histological aspects, and review the literature regarding this lesion.
Water contaminant levels interact with parenting environment to predict development of depressive symptoms in adolescents
Authors: Manczak Erika M. , Miller Jonas G. , Gotlib Ian H. 
Published: April 2019

AbstractContaminants in drinking water, such as lead, nitrate, and arsenic, have been linked to negative physical health outcomes. We know less, however, about whether such pollutants also predict mental health problems and, if so, the conditions under which such effects are strongest. In this longitudinal study, we examined whether drinking water contaminants interact with negative family environments (parental psychological control) to predict changes in depressive symptoms in 110 adolescents—a developmental period when symptoms often first emerge. We found that for adolescents in psychologically controlling families, levels of drinking water contaminants prospectively predicted depressive symptoms 2 years later; this effect was not present in adolescents in non‐controlling families. Importantly, these associations were not accounted for by family‐ or community‐level socioeconomic resources, demographic features, or by the adolescents’ stress exposure. These findings highlight the interplay of physical and psychological environments in influencing depressive symptoms in adolescents. A video abstract of this article can be viewed at https://youtu.be/thBV-DwnGcY