bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuropsychiatric, cognitive and brain morphology characteristics of conversion from Mild Cognitive Impairment to Alzheimer’s Disease
Authors: Lucas Ronat , Alexandru Hanganu ,   for the ADNI group
Published: December 2021

AbstractThe impact of neuropsychiatric symptoms (NPS) on cognitive performance has been extensively reported, and this impact was better defined in the aging population. Yet a potential impact of NPS on brain morphology, cognitive performance and interactions between them in a longitudinal setting, as well as the potential of using these values as prediction of conversion – have remained questionable. We studied 156 participants with mild cognitive impairment (MCI) from theAlzheimer’s Disease Neuroimaging Initiativedatabase who maintained the same level of cognitive performance after a 4-year follow-up and compared them to 119 MCI participants who converted to dementia. Additionally, we assessed the same analysis in 170 healthy controls who remained healthy at follow-up. Compared to 15 controls who converted to MCI. Their neuropsychological, neuropsychiatric, and brain morphology data underwent statistical analyses of 1) baseline comparison between the groups; (2) analysis of covariance model controlling for age, sex, education, and MMSE score, to specify the cognitive performance and brain structures that distinguish the two subgroups, and 3) used the significant ANCOVA variables to construct a binary logistic regression model that generates a probability equation for a given individual to convert to a lower cognitive performance state.Results showed that MCI who converted to AD in comparison to those who did not convert, exhibited a higher NPS prevalence, a lower cognitive performance and a higher number of involved brain structures. Furthermore, agitation, memory and the volumes of inferior temporal, hippocampal and amygdala sizes were significant predictors of MCI to AD conversion.
Metabolic phenotyping reveals a potential link between elevated faecal amino acids, diet and symptom severity in individuals with severe mental illness
Authors: Jansma Jack , van Essen Rogier , Haarman Bartholomeus C.M. , Chatziioannou Anastasia Chrysovalantou , Borkent Jenny , Ioannou Magdalini , van Hemert Saskia , Sommer Iris E.C. , Aidy Sahar El 
Published: December 2021

AbstractThe brain-gut axis is increasingly recognized as an important contributing factor in the onset and progression of severe mental illnesses such as schizophrenia spectrum disorders and bipolar disorder. This study investigates associations between levels of faecal metabolites identified using 1H-NMR, clinical parameters, and dietary components of forty-two individuals diagnosed in a transdiagnostic approach to have severe mental illness. Faecal levels of the amino acids; alanine, leucine, and valine showed a significant positive correlation with psychiatric symptom severity as well as with dairy intake. Overall, this study proposes a diet-induced link between the brain-gut axis and the severity of psychiatric symptoms, which could be valuable in the design of novel dietary or therapeutic interventions to improve psychiatric symptoms.
A temporal sequence of thalamic activity unfolds at transitions in behavioral arousal state
Authors: Setzer Beverly , Fultz Nina E. , Gomez Daniel E. P. , Williams Stephanie D. , Bonmassar Giorgio , Polimeni Jonathan R. , Lewis Laura D. 
Published: December 2021

ABSTRACTThe moment of awakening from sleep reflects a profound transformation in neural activity and behavior. The thalamus is a key controller of arousal state, but whether its diverse nuclei exhibit coordinated or distinct activity at transitions in behavioral arousal state is not known. Using fast fMRI at ultra-high field (7 Tesla), we measured sub-second activity across thalamocortical networks and within nine thalamic nuclei to delineate these dynamics during spontaneous transitions in behavioral arousal state. We discovered a stereotyped sequence of activity across thalamic nuclei that preceded behavioral arousal after a period of inactivity, followed by widespread cortical deactivation. These thalamic dynamics were linked to whether participants remained awake or fell back asleep, with unified thalamic activation reflecting subsequent maintenance of awake behavior. These results provide an outline of the complex interactions across thalamocortical circuits that orchestrate arousal state transitions, and additionally, demonstrate that fast fMRI can resolve sub-second subcortical dynamics in the human brain.
Single-cell transcriptome reveals insights into the development and function of the zebrafish ovary
Authors: Liu Yulong , Kossack Michelle E. , McFaul Matthew E. , Christensen Lana , Siebert Stefan , Wyatt Sydney R. , Kamei Caramai , Horst Samuel , Arroyo Nayeli , Drummond Iain , Juliano Celina E. , Draper Bruce W. 
Published: December 2021

AbstractZebrafish are an established research organism that has made many contributions to our understanding of vertebrate tissue and organ development, yet there are still significant gaps in our understanding of the genes that regulate gonad development, sex, and reproduction. Unlike the development of many organs, such as the brain and heart that form during the first few days of development, zebrafish gonads do not begin to form until the larval stage (≥5 dpf). Thus, forward genetic screens have identified very few genes required for gonad development. In addition, bulk RNA sequencing studies which identify genes expressed in the gonads do not have the resolution necessary to define minor cell populations that may play significant roles in development and function of these organs. To overcome these limitations, we have used single-cell RNA sequencing to determine the transcriptomes of cells isolated from juvenile zebrafish ovaries. This resulted in the profiles of 10,658 germ cells and 14,431 somatic cells. Our germ cell data represents all developmental stages from germline stem cells to early meiotic oocytes. Our somatic cell data represents all known somatic cell types, including follicle cells, theca cells and interstitial stromal cells. Further analysis revealed an unexpected number of cell subpopulations within these broadly defined cell types. To further define their functional significance, we determined the location of these cell subpopulations within the ovary. Finally, for select examples, we used gene knockout experiments to determine the role of newly identified genes. Our results reveal novel insights into ovarian development and function and the sequencing information will provide a valuable resource for future studies.
Characterising genome architectures using Genome Decomposition Analysis
Authors: Aunin Eerik , Berriman Matthew , Reid Adam James 
Published: December 2021

AbstractGenome architecture describes how genes and other features are arranged in genomes. These arrangements reflect the evolutionary pressures on genomes and underlie biological processes such as chromosomal segregation and the regulation of gene expression. We present a new tool called Genome Decomposition Analysis (GDA) that characterises genome architectures and acts as an accessible approach for discovering hidden features of a genome assembly. With the imminent deluge of high quality genome assemblies from projects such as the Darwin Tree of Life and the Earth BioGenome Project, GDA has been designed to facilitate their exploration and the discovery of novel genome biology. We highlight the effectiveness of our approach in characterising the genome architectures of single-celled eukaryotic parasites from the phylumApicomplexaand show that it scales well to large genomes.SignificanceGenome sequencing has revealed that there are functionally important arrangements of genes, repetitive elements and regulatory sequences within chromosomes. Identifying these arrangements requires extensive computation and analysis. Furthermore, improvements in genome sequencing technology and the establishment of consortia aiming to sequence all species of eukaryotes mean that there is a need for high throughput methods for discovering new genome biology. Here we present a software pipeline, named GDA, which determines the patterns of genomic features across chromosomes and uses these to characterise genome architecture. We show that it recapitulates the known genome architecture of several Apicomplexan parasites and use it to identify features in a recently sequenced, less well-characterised genome. GDA scales well to large genomes and is freely available.
Regulation of dctA and DctA by cAMP-CRP and EIIAGlc at the transcriptional and post-translational levels in E. coli: Consequences for aerobic uptake and metabolism of C4-dicarboxylates
Authors: Schubert Christopher , Unden Gottfried 
Published: December 2021

AbstractThe expression of dctA, encoding the aerobic C4-dicarboxylate (C4-DC) transporter DctA of Escherichia coli, and its use in the presence of alternative carbon sources was characterized. dctA is regulated by cAMP-CRP and substrates that control cAMP levels, either through the phosphotransferase system (PTS), or through their metabolic link to PEP synthesis. The data indicates that phosphorylation of the regulator EIIAGlc of the glucose-specific PTS represents the mediator for regulation. The dctA promotor region contains a class I CRP-binding site (position -81.5) and a DcuR-binding site (position -105.5). The response regulator DcuR of the C4-DC-activated DcuS-DcuR two-component system is known to stimulate expression of dctA, and cAMP-CRP is known to stimulate expression of dcuS-dcuR. Thus, activation of dctA expression by cAMP-CRP and DcuR is organized in a coherent feed-forward loop (FFL) where cAMP-CRP positively regulates the expression of dctA by direct stimulation and by stimulating the expression of dcuR. Stimulation by DcuR is presumed to require DNA bending by cAMP-CRP. In this way, CRP-FFL integrates carbon catabolite control and C4-DC-specific regulation. Moreover, EIIAGlc of the glucose-specific PTS strongly interacts with DctA, which could lead to substrate exclusion of C4-DCs when preferred carbon substrates such as sugars are present. Since C4-DCs are perceived in the periplasmic space by the sensor DcuS, the substrate exclusion is not linked to inducer exclusion, contrasting classical inducer exclusion known for the lactose permease LacY. Thus, aerobic C4-DC metabolism is tightly regulated at the transcriptional and post-translational levels, whereas uptake of L-aspartate by DcuA is essentially unaffected. Overall, transcriptional and post-translational regulation of dctA expression and DctA function efficiently fine-tunes C4-DC catabolism in response to other preferred carbon sources.
Investor sentiment and stock return volatility: evidence from the Indian Stock Exchange
Authors: N Sreenu , Naik Suresh 
Published: December 2021

PurposeIn any stock market, volatility is a significant factor in strengthening their asset pricing. The upsurge in volatility in the stock market can activate and bring changes in the financial risk. According to financial conventional theory, the stakeholders (investors) are selected to be balanced and variations in pertinent risk are also to be anticipated due to the outcome of the drive-in basic factors in Indian stock markets. The hypothesis shows that there are actions in systematic and unsystematic risks that are determined by volatility. It is allied to sentiment-driven in the trader movement.Design/methodology/approachThe paper used the methodology of generalized autoregressive conditional heteroskedasticity-in mean GARCH-M and exponential GARCH-M (E-GARCH-M) methods on the Indian stock market. The data have been covered from 2000 to 2019.FindingsFinally, the study suggests that due to the unfitness of the capital asset pricing model (CAPM), the selection has enhanced with sentiment is an important risk factor.Practical implicationsThe investor sentiment and stock return volatility statement are established by using the investor sentiment amalgamated stock market index built.Originality/valueThe outcome of the study shows that there is an important association between stakeholder (investor) sentiment and stock return, in case of volatility behavioural finance can significantly explain the behaviour of stock returns on the Indian Stock Exchange.
Defining risk reduction strategies for tourists with specific food needs: a qualitative approach
Authors: Fuentes-Moraleda Laura , Muñoz-Mazón Ana , Santiago-Rincón Coral , Orea-Giner Alicia 
Published: December 2021

PurposeThis exploratory study aims to identify the main risk reduction strategies when individuals suffer from coeliac disease (CD) or non-coeliac gluten sensitivity (NCGS) travel. Based on Yeung and Yee's (2013; 2019) model, the paper offers a new framework for analysing the main travel risk reduction strategies for people with specific food needs. The empirical work focuses on the perspectives of different stakeholders (CD and NCGS community, restaurant managers/service providers and nutritionists).Design/methodology/approachA qualitative approach based on thematic analysis is adopted. The results of 32 semi-structured in-depth interviews reveal different stakeholders' perspectives in order to understand the various strategies.FindingsThe findings confirm the high level of consensus that the main food risk reducers are: travel information, staff training in safety assurance, legislation and risk prevention protocols. The findings also show significant limitations in the information offered by restaurants, organisations and tourist destinations and the negative repercussions on the tourist experience and the reputation on a particular destination.Practical implicationsThe results will help hospitality business managers and destination management organisations develop food risk reduction strategies to solve some of the most important food-related problems when people in this market segment travel.Originality/valueThis work contributes to the literature by providing a new framework on travel risk reduction strategies for people with specific food needs. The novelty of this research is mainly found in the study of risk reduction strategies related to the travel decision-making process for those with CD and NCGS from different perspectives.
Burnt to a crisp? Understanding drivers of burnout amongst New Zealand workers
Authors: Haar Jarrod 
Published: December 2021

PurposeJob burnout is a popular topic for researchers and a pressing issue for employees and employers. However, the most popular measure has become widely critiqued, and a new construct – the Burnout Assessment Tool (BAT) – has been offered as a better way to assess burnout.Design/methodology/approachThe study uses data from 1,022 employees across a wide range of occupations, sectors and industries. Confirmatory factor analysis (CFA) and odds ratio calculations are explored.FindingsThe present psychometric properties of the BAT construct are supported. Overall, 11.1% of employees met the high burnt-out risk threshold. Determinants of burnt-out risk were explored, with significant findings from high perceptions of organizational support, large firm-size, young age and long work hours found. No gender differences. The odds ratio provides greater insights into the risks associated with factors, especially working 55+ hours/week, which resulted in 580% higher risk of burnt-out risk.Research limitations/implicationsThe findings highlight the danger of burnt-out risk and provide a useful benchmark for those exploring the burnt-out risk rate.Originality/valueThe BAT has not been tested in New Zealand across a sample of employees. Given the large size and breadth of employees, this provides useful generalizability to the BAT-NZ. The determinants tested here are all unique to the literature and provide new insights.
Developing a risk assessment model for banking software development projects based on rough-grey set theory
Authors: Karimi Tooraj , Yahyazade Yalda 
Published: December 2021

PurposeRisk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology in all fields and the high failure rate of software development projects, it is essential to predict the risk level of each project effectively before starting. Therefore, the main purpose of this paper is proposing an expert system to infer about the risk of new banking software development project.Design/methodology/approachIn this research, the risk of software developing projects is considered from four dimensions including risk of cost deviation, time deviation, quality deviation and scope deviation, which is examined by rough set theory (RST). The most important variables affecting the cost, time, quality and scope of projects are identified as condition attributes and four initial decision systems are constructed. Grey system theory is used to cluster the condition attributes and after data discretizing, eight rule models for each dimension of risk as a decision attribute are extracted using RST. The most validated model for each decision attribute is selected as an inference engine of the expert system, and finally a simple user interface is designed in order to predict the risk level of any new project by inserting the data of project attributesFindingsIn this paper, a high accuracy expert system is designed based on the combination of the grey clustering method and rough set modeling to predict the risks of each project before starting. Cross-validation of different rule models shows that the best model for determining cost deviation is Manual/Jonson/ORR model, and the most validated models for predicting the risk of time, quality and scope of projects are Entropy/Genetic/ORR, Manual/Genetic/FOR and Entropy/Genetic/ORR models; all of which are more than 90% accurateResearch limitations/implicationsIt is essential to gather data of previous cases to design a validated expert system. Since data documentation in the field of software development projects is not complete enough, grey set theory (GST) and RST are combined to improve the validity of the rule model. The proposed expert system can be used for risk assessment of new banking software projectsOriginality/valueThe risk assessment of software developing projects based on RST is a new approach in the field of risk management. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.
Do negative events really have deteriorating effects on stock performance? A comparative study on Tesla (US) and Nio (China)
Authors: Lim Yi Xuan , Tan Consilz 
Published: December 2021

PurposeBoth investors and the stock markets are believed to behave in a perfectly rational manner, where investors focus on utility maximization and are not subjected to cognitive biases or any information processing errors. However, it has been discovered that the sentiment of the social mood has a significant impact on the stock market. This study aims to analyze how did the protest event of Tesla happened in April 2021 have a significant effect on the company's stock performance as well as its competitors, Nio, under the competitive effect.Design/methodology/approachThe research is based on time series data collected from Tesla and Nio by employing 10 days, 15 days and 20 days anticipation and adjustment period for the event study. This study employed a text sentiment analysis to identify the polarity of the sentiment of the protest event using the Microsoft Azure machine learning tool which utilizes MPQA subjective lexicon.FindingsThe findings provide further evidence to show that a company-specific negative event has deteriorating effects on its stock performance, while having an opposite effect on its competitors.Research limitations/implicationsThe paper argues that negative sentiments through social media word of mouth (SWOM) affect the stock market not just in the short run but potentially in the longer run. Such negative sentiments might create a snowball effect which causes the market to further scrutinize a company's operations and possibly lose confidence in the company.Originality/valueThis study explores how the Tesla's protest event at Shanghai Auto Show 2021 has a significant impact on Tesla's stock performance and prolonged negative impact although Tesla implemented immediate remedial actions. The remedial actions were not accepted positively and induced a wave of negative news which had a more persistent effect.
How increased foreign competition motivates domestic firms to do good: an examination of foreign entry mode and domestic CSR response
Authors: Woo Hyun-Soo , Berns John , Mukherjee Kaushik , Kim Jisun 
Published: December 2021

PurposeWe examine whether domestic firms react differently to foreign direct investment (FDI) entry modes –mergers and acquisitions (M&A) versus greenfield. Specifically, we ascertain whether the entry mode of foreign competition motivates different corporate social responsibility (CSR) responses from domestic firms and when such relationships hold.Design/methodology/approachWe employ fixed-effects models using 1,331 US firm-year observations for 2015–2018. Furthermore, we examine the interactive effects of industry concentration to examine a key boundary condition.FindingsForeign entry via greenfield mode has no effect on domestic firm CSR. Entry through M&A has a significantly positive effect. We attribute these findings to the increased threat to domestic firms from foreign M&A whereas foreign entry through greenfield mode is less threatening as entrants face significantly more challenges in host countries. We identify industry concentration as a boundary condition of our findings. The effect of foreign M&A entries on domestic firms' CSR becomes weaker as industries are more concentrated.Originality/valueThis study offers novel insights on FDI by parsing out different reactions to entry mode by domestic firms. We add to our understanding of CSR as a mechanism to stave off foreign competition, offer insights into a key boundary condition of such actions and demonstrate the robustness of our findings.