bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of a priori-identified addiction and smoking gene sets in smoking behaviors
Authors: Evans Luke M. , Johnson Emma C. , Melroy-Grief Whitney E. , Hewitt John K. , Hoeffer Charles A. , Keller Matthew C. , Saba Laura M. , Stitzel Jerry A. , Ehringer Marissa A. 
Published: August 2019

ABSTRACTIntroductionSmoking is a leading cause of death, and genetic variation contributes to smoking behaviors. Identifying genes and sets of genes that contribute to risk for addiction is necessary to prioritize targets for functional characterization and for personalized medicine.MethodsWe performed a gene set-based association and heritable enrichment study of two addiction-related gene sets, those on the Smokescreen Genotyping Array and the nicotinic acetylcholine receptors, using the largest available GWAS summary statistics. We assessed smoking initiation, cigarettes per day, smoking cessation, and age of smoking initiation.ResultsIndividual genes within each gene set were significantly associated with smoking behaviors. Both sets of genes were significantly associated with cigarettes per day, smoking initiation, and smoking cessation. Age of initiation was only associated with the Smokescreen gene set. While both sets of genes were enriched for trait heritability, each accounts for only a small proportion of the SNP-based heritability (2-12%).ConclusionsThese two gene sets are associated with smoking behaviors, but collectively account for a limited amount of the genetic and phenotypic variation of these complex traits, consistent with high polygenicity.ImplicationsWe evaluated evidence for association and heritable contribution of expert-curated and bioinformatically identified sets of genes related to smoking. Although they impact smoking behaviors, these specifically targeted genes do not account for much of the heritability in smoking and will be of limited use for predictive purposes. Advanced genome-wide approaches and integration of other ‘omics data will be needed to fully account for the genetic variation in smoking phenotypes.
Reversible Mitochondrial Fragmentation in iPSC-Derived Cardiomyocytes from Children with DCMA, a Mitochondrial Cardiomyopathy
Authors: Rohani Leili , Machiraju Pranav , Sabouny Rasha , Meng Guoliang , Liu Shiying , Zhao Tian , Iqbal Fatima , Ravandi Amir , Wu Joseph C. , Khan Aneal , Shutt Timothy , Rancourt Derrick , Greenway Steven C. 
Published: August 2019

ABSTRACTBackgroundThe dilated cardiomyopathy with ataxia syndrome (DCMA) is an understudied autosomal recessive disease caused by loss-of-function mutations in the poorly characterized gene DNAJC19. Clinically, DCMA is commonly associated with heart failure and early death in affected children through an unknown mechanism. DCMA has been linked to Barth syndrome, a rare but well-studied disorder caused by deficient maturation of cardiolipin (CL), a key mitochondrial membrane phospholipid.MethodsPeripheral blood mononuclear cells from two children with DCMA and severe cardiac dysfunction were reprogrammed into induced pluripotent stem cells (iPSCs). Patient and control iPSCs were differentiated into beating cardiomyocytes (iPSC-CMs) using a metabolic selection strategy and mitochondrial structure and CL content before and after incubation with the mitochondrially-targeted peptide SS-31 were quantified.ResultsPatient iPSCs carry the causative DNAJC19 mutation (rs137854888) found in the Hutterite population and the iPSC-CMs demonstrated highly fragmented and abnormally-shaped mitochondria associated with an imbalanced isoform ratio of the mitochondrial protein OPA1, an important regulator of mitochondrial fusion. These abnormalities were reversible by incubation with SS-31 for 24 hours. Differentiation of iPSCs into iPSC-CMs increased the number of CL species observed but consistent, significant differences in CL content were not seen between patients and control.ConclusionsWe describe a unique and novel cellular model that provides insight into the mitochondrial abnormalities present in DCMA and identifies SS-31 as a potential therapeutic for this devastating disease.
A probabilistic approach to explore signal execution mechanisms with limited experimental data
Authors: Kochen Michael A. , Lopez Carlos F. 
Published: August 2019

AbstractMathematical models of biochemical reaction networks are central to the study of dynamic cellular processes and hypothesis generation that informs experimentation and validation. Unfortunately, model parameters are often not available and sparse experimental data leads to challenges in model calibration and parameter estimation. This can in turn lead to unreliable mechanistic interpretations of experimental data and the generation of poorly conceived hypotheses for experimental validation. To address this challenge, we evaluate whether a Bayesian-inspired probability-based approach, that incorporates available information regarding reaction network topology and parameters, can be used to qualitatively explore hypothetical biochemical network execution mechanisms in the context of limited available data. We test our approach on a model of extrinsic apoptosis execution to identify preferred signal execution modes across varying conditions. Apoptosis signal processing can take place either through a mitochondria independent (Type I) mode or a mitochondria dependent (Type II) mode. We first show that in silico knockouts, represented by model subnetworks, successfully identify the most likely execution mode for specific concentrations of key molecular regulators. We then show that changes in molecular regulator concentrations alter the overall reaction flux through the network by shifting the primary route of signal flow between the direct caspase and mitochondrial pathways. Our work thus demonstrates that probabilistic approaches can be used to explore the qualitative dynamic behavior of model biochemical systems even with missing or sparse data.
A single cell atlas of the developingDrosophilaovary identifies follicle stem cell progenitors
Authors: Slaidina Maija , Banisch Torsten U. , Gupta Selena , Lehmann Ruth 
Published: August 2019

AbstractAddressing the complexity of organogenesis at a system-wide level requires a complete understanding of adult cell types, their origin and precursor relationships. TheDrosophilaovary has been a model to study how coordinated stem cell units, germline and somatic follicle stem cells, maintain and renew an organ. However, lack of cell-type specific tools have limited our ability to study the origin of individual cell types and stem cell units. Here, we use a single cell RNA sequencing approach to uncover all known cell types of the developing ovary, reveal transcriptional signatures, and identify cell type specific markers for lineage tracing. Our study identifies a novel cell type corresponding to the elusive follicle stem cell precursors and predicts sub-types of known cell types. Altogether, we reveal a previously unanticipated complexity of the developing ovary, and provide a comprehensive resource for the systematic analysis of ovary morphogenesis.
Individualized ctDNA Fingerprints to Monitor Treatment Response and Recurrence in Multiple Cancer Types
Authors: Li Jiaping , Jiang Wei , Wei Jinwang , Zhang Jianwei , Cai Linbo , Luo Minjie , Wang Zhan , Sun Wending , Wang Chen , Dai Chun , Wang Guan , Xu Qiang , Deng Yanhong 
Published: August 2019

AbstractCirculating tumor DNA (ctDNA) panels hold high promise of accurately predicting the therapeutic response of tumors while being minimally invasive and cost-efficient. However, their use has been limited to a small number of tumor types and patients. Here, we developed individualized ctDNA fingerprints suitable for most patients with multiple cancer types. The panels were designed based on individual whole-exome sequencing data in 521 Chinese patients and targeting high clonal population clusters of somatic mutations. Together, these patients represent 12 types of cancers and seven different treatments. The customized ctDNA panels have a median somatic mutation number of 19, most of which are patient-specific rather than cancer hotspot mutations; 66.8% of the patients were ctDNA-positive. We further evaluated the ctDNA content fraction (CCF) of the mutations, and analyzed the association between the change of ctDNA concentration and therapeutic response. We followed up 106 patients for clinical evaluation, demonstrating a significant correlation of changes in ctDNA with clinical outcomes, with a consistency rate of 93.4%. In particular, the median CCF increased by 204.6% in patients with progressive disease, decreased by 82.5% in patients with remission, and was relatively stable in patients with stable disease. Overall, 85% of the patients with a ctDNA-positive status experienced metastasis or relapse long before imaging detection, except for two patients who developed recurrence and metastasis almost simultaneously. The average lead time between the first ctDNA-positive finding and radiological diagnosis was 76 days in three patients that changed from a ctDNA-negative to -positive status. Our individualized ctDNA analysis can effectively monitor the treatment response, metastasis, and recurrence in multiple cancer types in patients with multiple treatment options, therefore offering great clinical applicability for improving personalized treatment in cancer.One Sentence SummaryctDNA fingerprint panels were customized to predict the treatment response for multiple cancer types from individual whole-exome sequencing data.
Comparing the utility of in vivo transposon mutagenesis approaches in yeast species to infer gene essentiality
Authors: Levitan Anton , Gale Andrew N. , Dallon Emma K. , Kozan Darby W. , Cunningham Kyle W. , Sharan Roded , Berman Judith 
Published: August 2019

ABSTRACTIn vivo transposon mutagenesis, coupled with deep sequencing, enables large-scale genome-wide mutant screens for genes essential in different growth conditions. We analyzed six large-scale studies performed on haploid strains of three yeast species (Saccharomyces cerevisiae, Schizosaccaromyces pombe, and Candida albicans), each mutagenized with two of three different heterologous transposons (AcDs, Hermes, and PiggyBac). Using a machine-learning approach, we evaluated the ability of the data to predict gene essentiality. Important data features included sufficient numbers and distribution of independent insertion events. All transposons showed some bias in insertion site preference because of jackpot events, and preferences for specific insertion sequences and short-distance vs long-distance insertions. For PiggyBac, a stringent target sequence limited the ability to predict essentiality in genes with few or no target sequences. The machine learning approach also robustly predicted gene function in less well-studied species by leveraging cross-species orthologs. Finally, comparisons of isogenic diploid versus haploid S. cerevisiae isolates identified several genes that are haplo-insufficient, while most essential genes, as expected, were recessive. We provide recommendations for the choice of transposons and the inference of gene essentiality in genome-wide studies of eukaryotic haploid microbes such as yeasts, including species that have been less amenable to classical genetic studies.
Null results from a dimensional study of error-related negativity (ERN) and self-reported psychiatric symptoms
Authors: Seow T. X.F. , Benoit E. , Dempsey C. , Jennings M. , Maxwell A. , McDonough M. , Gillan C. M. 
Published: August 2019

AbstractAlterations in error processing are implicated in a range of DSM-defined psychiatric disorders. For instance, obsessive-compulsive disorder (OCD) and generalised anxiety disorder show enhanced electrophysiological responses to errors – i.e. error-related negativity (ERN) – while others like schizophrenia have an attenuated ERN. However, as diagnostic categories in psychiatry are heterogeneous and also highly intercorrelated, the precise mapping of ERN enhancements and impairments is unclear. To address this, we recorded electroencephalograms (EEG) from 196 participants who performed the Flanker task and collected scores on 9 questionnaires assessing psychiatric symptoms to test if a dimensional framework could reveal specific transdiagnostic clinical manifestations of error processing dysfunctions. Contrary to our hypothesis, we found no association between ERN amplitude and symptom severity of OCD, trait anxiety, depression, social anxiety, impulsivity, eating disorders, alcohol addiction, schizotypy or apathy. A transdiagnostic approach did nothing to improve signal; there was no association between three transdiagnostic dimensions (anxious-depression, compulsive behaviour and intrusive thought and social withdrawal) and ERN magnitude. In these same individuals, we replicated a previously published transdiagnostic association between goal-directed learning and compulsive behaviour and intrusive thought. Associations between the ERN and psychopathology might be smaller than previously assumed and/or dependent on a greater level of symptom severity than other transdiagnostic cognitive biomarkers.
Cellular metabolic activity marker via selective turn-ON detection of serum albumin using an NBD-based fluoroprobe
Authors: Dutta Tanoy , Pal Kaushik , Koner Apurba Lal 
Published: August 2019

AbstractA nitrobenzoxadiazole-based fluoroprobe (NBD-Bu) is designed to probe cellular metabolic activity in cancer and normal cells. NBD-Bu shows a significant fluorescence enhancement upon selective binding to serum albumin. The site specificity of NBD-Bu has been explored through a competitive displacement assay in the presence of site-specific markers such as warfarin and ibuprofen. Subsequently, high-resolution fluorescence microscopy results consolidated the potential of NBD-Bu for cellular imaging and detection of abnormal cellular metabolic activity.
BayICE: A hierarchical Bayesian deconvolution model with stochastic search variable selection
Authors: Tai An-Shun , Tseng George C. , Hsieh Wen-Ping 
Published: August 2019

AbstractGene expression deconvolution is a powerful tool for exploring the microenvironment of complex tissues comprised of multiple cell groups using transcriptomic data. Characterizing cell activities for a particular condition has been regarded as a primary mission against diseases. For example, cancer immunology aims to clarify the role of the immune system in the progression and development of cancer through analyzing the immune cell components of tumors. To that end, many deconvolution methods have been proposed for inferring cell subpopulations within tissues. Nevertheless, two problems limit the practicality of current approaches. First, all approaches use external purified data to preselect cell type-specific genes that contribute to deconvolution. However, some types of cells cannot be found in purified profiles and the genes specifically over- or under-expressed in them cannot be identified. This is particularly a problem in cancer studies. Hence, a preselection strategy that is independent from deconvolution is inappropriate. The second problem is that existing approaches do not recover the expression profiles of unknown cells present in bulk tissues, which results in biased estimation of unknown cell proportions. Furthermore, it causes the shift-invariant property of deconvolution to fail, which then affects the estimation performance. To address these two problems, we propose a novel deconvolution approach, BayICE, which employs hierarchical Bayesian modeling with stochastic search variable selection. We develop a comprehensive Markov chain Monte Carlo procedure through Gibbs sampling to estimate cell proportions, gene expression profiles, and signature genes. Simulation and validation studies illustrate that BayICE outperforms existing deconvolution approaches in estimating cell proportions. Subsequently, we demonstrate an application of BayICE in the RNA sequencing of patients with non-small cell lung cancer. The model is implemented in the R package “BayICE” and the algorithm is available for download.
Distinct microbial communities alter litter decomposition rates in a fertilized coastal plain wetland
Authors: Koceja Megan E. , Bledsoe Regina B. , Goodwillie Carol , Peralta Ariane L. 
Published: August 2019

AbstractHuman activities have led to increased deposition of nitrogen (N) and phosphorus (P) into soils. Nutrient enrichment of soils is known to increase plant biomass and rates of microbial litter decomposition. However, interacting effects of hydrologic position and associated changes to soil moisture can constrain microbial activity and lead to unexpected nutrient feedbacks on microbial community structure-function relationships. Examining how feedbacks of nutrient enrichment on decomposition rates is essential for predicting microbial contributions to carbon (C) cycling as atmospheric deposition of nutrients persists. This study explores how long-term nutrient addition and contrasting litter chemical quality influence soil bacterial community structure and function. We hypothesize that long-term nutrient enrichment of low fertility soils alters bacterial community structure and leads to higher rates of litter decomposition with decreasing C:N ratio of litter; but low nutrient and dry conditions limit constrain microbial decomposition of high C:N ratio litter. We leverage a long-term fertilization experiment to test how nutrient enrichment and hydrologic manipulation (due to ditches) affects decomposition and soil bacterial community structure in a nutrient poor coastal plain wetland. We conducted a litter bag experiment and characterized litter-associated and bulk soil microbiomes using 16S rRNA bacterial sequencing and quantified litter mass losses and soil physicochemical properties. Results revealed that distinct bacterial communities were involved in decomposing higher C:N ratio litter more quickly in fertilized compared to unfertilized especially under drier soil conditions, while decomposition rates of green tea litter (lower C:N ratio) were similar between fertilized and unfertilized plots. Bacterial community structure in part explained litter decomposition rates, and long-term fertilization and drier hydrologic status affected bacterial diversity and increased decomposition rates. However, community composition associated with high C:N litter was similar in wetter plots with available nitrate detected, regardless of fertilization treatment. This study provides insight into long-term fertilization effects on soil bacterial diversity and composition, decomposition, and the increased potential for soil C loss as nutrient enrichment and hydrology interact to affect historically low nutrient ecosystems.
The effects of personality, culture and store stimuli on impulsive buying behavior
Authors: Miao Miao , Jalees Tariq , Qabool Sahar , Zaman Syed Imran 
Published: August 2019

PurposeThe purpose of this paper is to examine the relationship between personality factors (i.e. neuroticism, agreeableness, extroversion, conscientiousness and openness), cultural factors (individualism and collectivism) and store stimuli (window display and sales promotion) on impulsive buying behavior.Design/methodology/approachThe sample size for the study was 350 with a response rate of 96 percent. The questionnaire was adapted from the established scale and measures. SmartPLS was used for statistical analysis. After reliability and validity analysis, the structural model was tested, and it fitted very well.FindingsOf the nine hypotheses, five were accepted, and the other four were rejected. The results suggest that neuroticism, openness, individualism, collectivism and sales promotion significantly affect impulsive buying behavior. Marketers can use these results in developing appropriate marketing strategies.Research limitations/implicationsImplications for managers were drawn from the results. In this study, only two cultural factors were considered. Future studies could use all the cultural factors in their model. Additionally, the developed model can be extended for comparative studies.Originality/valueImpulsive buying behavior, on the one hand, is problematic for consumers, but, on the other hand, is used as a tool by retailers for increasing sales. Comparatively, this study examined the effects of personality factors, cultural factors and store stimuli on impulsive buying behavior. These three factors have rarely been used together in one study.
Symbiotic care between residents in service-integrated housing
Authors: Meyer Desneige , Martin Wanda , Funk Laura M. 
Published: August 2019

Purpose
Sustainable solutions for meeting the physical, emotional and social health care needs of individuals may be realized by shifting the care landscape; for instance, through innovative models of service-integrated housing (SIH). By diversifying populations in these settings, care recipients can choose to engage their skills and abilities toward assisting co-residents, and vice versa as a form of symbiosis. The purpose of this paper is to define attributes of the concept and practice of symbiotic care.

Design/methodology/approach
The authors drew on firsthand field experience and secondary data from a literature review to conduct a conceptual derivation and analysis, using Walker and Avant’s methodology. The term symbiotic mutualism was derived from the field of biology as an analogy for care exchanged between non-peer co-residents. Attributes, antecedents and consequences of symbiotic care were identified and illustrated using model, borderline and contrary case descriptions.

Findings
Four defining attributes of symbiotic care were identified: first, cohabitation: care recipients live closely together in SIH settings. Second, non-peer: co-residents have distinct, complementary needs and abilities. Third, mutualism: co-residents experience mutually significant benefits as a result of the activities of their co-residents. Fourth, agency-sponsored: the professional SIH agency or organization attends to unmet resident needs.

Research limitations/implications
Symbiotic care is a relatively rare phenomenon for which little research exists. This analysis provides a starting point for empirical research, policy and program development and critical evaluation.

Originality/value
This paper fills a wide gap in the research literature and offers important terminology. It is the first to define the attributes of symbiotic care.