bluuebunny/crossref_metadata_2025_split huggingface dataset:
Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations
Authors: Gangavarapu Karthik , Latif Alaa Abdel , Mullen Julia L. , Alkuzweny Manar , Hufbauer Emory , Tsueng Ginger , Haag Emily , Zeller Mark , Aceves Christine M. , Zaiets Karina , Cano Marco , Zhou Jerry , Qian Zhongchao , Sattler Rachel , Matteson Nathaniel L , Levy Joshua I. , Lee Raphael TC , Freitas Lucas , Maurer-Stroh Sebastian ,   GISAID core and curation team, Suchard Marc A. , Wu Chunlei , Su Andrew I. , Andersen Kristian G. , Hughes Laura D. 
Published: January 2022

AbstractThe emergence of SARS-CoV-2 variants of concern has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced and shared over 10 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the interpretable and opinionated visualizations in the variant and location focussed reports available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data, and the server infrastructure that enables widespread data dissemination via a high performance API that can be accessed using an R package. We present a case study that illustrates how outbreak.info can be used for genomic surveillance and as a hypothesis generation tool to understand the ongoing pandemic at varying geographic and temporal scales. With an emphasis on scalability, interactivity, interpretability, and reusability, outbreak.info provides a template to enable genomic surveillance at a global and localized scale.
A Machine Learning Approach to Differentiate Between COVID-19 and Influenza Infection Using Synthetic Infection and Immune Response Data
Authors: Farhang-Sardroodi Suzan , Ghaemi Mohammad Sajjad , Craig Morgan , Ooi Hsu Kiang , Heffernan Jane M 
Published: January 2022

AbstractData analysis is widely used to generate new insights into human disease mechanisms and provide better treatment methods. In this work, we used the mechanistic models of viral infection to generate synthetic data of influenza and COVID-19 patients. We then developed and validated a supervised machine learning model that can distinguish between the two infections. Influenza and COVID-19 are contagious respiratory illnesses that are caused by different pathogenic viruses but appeared with similar initial presentations. While having the same primary signs COVID-19 can produce more severe symptoms, illnesses, and higher mortality. The predictive model performance was externally evaluated by the ROC AUC metric (area under the receiver operating characteristic curve) on 100 virtual patients from each cohort and was able to achieve at least AUC=91% using our multiclass classifier. The current investigation highlighted the ability of machine learning models to accurately identify two different diseases based on major components of viral infection and immune response. The model predicted a dominant role for viral load and productively infected cells through the feature selection process.
Widespread alterations in microRNA biogenesis in human Huntington’s disease putamen
Authors: Petry Serena , Keraudren Rémi , Nateghi Behnaz , Loiselle Andréanne , Pircs Karolina , Jakobsson Johan , Sephton Chantelle , Langlois Mélanie , St-Amour Isabelle , Hébert Sébastien S. 
Published: January 2022

AbstractAltered microRNA (miRNA) expression is a common feature of Huntington’s disease (HD) and could participate in disease onset and progression. However, little is known about the underlying causes of miRNA disruption in HD. We and others have previously shown that mutant Huntingtin (mHTT) binds to Ago2, a central component of miRNA biogenesis, and disrupts mature miRNA levels. In this study, we sought to determine if miRNA maturation per se was compromised in HD. Towards this end, we characterized t major miRNA biogenesis pathway components and miRNA maturation products (pri-miRNA, pre-miRNA, and mature) in human HD (N=41, Vonsattel grades HD2-4) and healthy control (N=25) subjects. Notably, the striatum (putamen) and cortex (BA39) from the same individuals were analyzed in parallel. We show that Ago2, Drosha, and Dicer were strongly downregulated in human HD at early stages of disease. Using a panel of HD-related miRNAs (miR-10b, miR-196b, miR-132, miR-212, miR-127, miR-128), we uncovered various types of maturation defects in HD brain, the most prominent occurring at the pre-miRNA to mature miRNA maturation step. Consistent with earlier findings, we provide evidence that alterations in autophagy could participate in miRNA maturation defects. Notably, most changes occurred in the striatum, which is more prone to HTT aggregation and neurodegeneration. Likewise, we observed no significant alterations in miRNA biogenesis in human HD cortex and blood, strengthening tissue-specific effects. Overall, these data provide important clues into the underlying mechanisms behind miRNA alterations in HD-susceptible tissues. Further investigations are now required to understand the biological, diagnostic, and therapeutic implications of miRNA/RNAi biogenesis defects in HD and related neurodegenerative disorders.
Decoding the temporal dynamics of affective scene processing
Authors: Bo Ke , Cui Lihan , Yin Siyang , Hu Zhenhong , Hong Xiangfei , Kim Sungkean , Keil Andreas , Ding Mingzhou 
Published: January 2022

ABSTRACTNatural images containing affective scenes are used extensively to investigate the neural mechanisms of visual emotion processing. Functional fMRI studies have shown that these images activate a large-scale distributed brain network that encompasses areas in visual, temporal, and frontal cortices. The underlying spatial and temporal dynamics among these network structures, however, remain to be characterized. We recorded simultaneous EEG-fMRI data while participants passively viewed affective images from the International Affective Picture System (IAPS). Applying multivariate pattern analysis to decode EEG data, and representational similarity analysis to fuse EEG data with simultaneously recorded fMRI data, we found that: (1) ~100 ms after picture onset, perceptual processing of complex visual scenes began in early visual cortex, proceeding to ventral visual cortex at ~160 ms, (2) between ~200 and ~300 ms (pleasant pictures: ~200 ms; unpleasant pictures: ~260 ms), affect-specific neural representations began to form, supported mainly by areas in occipital and temporal cortices, and (3) affect-specific neural representations, lasting up to ~2 s, were stable and exhibited temporally generalizable activity patterns. These results suggest that affective scene representations in the brain are formed in a valence-dependent manner and are sustained by recurrent neural interactions among distributed brain areas.
Factors associated with secondhand smoke exposure among non-smoking employees in the workplace: A cross-sectional study in Qingdao, China
Authors: Jia Xiaocen , Wang Rui , Qiu Xiaofei , Huang Yiqing , Wang Yani , Jia Xiaorong , Li Shanpeng , Wu Yibo , Qi Fei 
Published: January 2022

AbstractObjectiveThe study was designed to describe secondhand smoke (SHS) exposure among non-smoking employees in the workplace and identify factors that related exposure in Qingdao.MethodsThe study subjects covered the key non-smoking places stipulated in the “Qingdao City Smoking Control Regulations”. Airborne nicotine concentration in the workplace and saliva cotinine concentration of employees were measured. Questionnaire included employees’ demographics factors, smoke-free measures in the workplace, the employer’s tobacco hazard knowledge and attitudes towards smoke-free policy.ResultsA total of 222 non-smoking employees and 46 employees were included in the study. The median concentrations of airborne nicotine and salivary cotinine were 0.389 μg/m3 and 0.575 ng/ml. Educational status, average number of smokers per day and exposure time of SHS in the workplace, whether to divide smoking and non-smoking areas were related to the airborne nicotine concentration significantly. Age, educational status, exposure time of SHS in the workplace, tobacco control training and publicity and whether the employers support the “Qingdao Tobacco Control Regulation” were related to the salivary cotinine concentration significantly.ConclusionsExposure to SHS is highly prevalent among non-smoking employees in the workplace. Interventions to reduce SHS exposure in the workplace are urgently needed.
Haplotype-aware modeling of cis-regulatory effects highlights the gaps remaining in eQTL data
Authors: Ehsan Nava , Kotis Bence M. , Castel Stephane E. , Song Eric J. , Mancuso Nicholas , Mohammadi Pejman 
Published: January 2022

AbstractExpression Quantitative Trait Loci (eQTLs) are critical to understanding the mechanisms underlying disease-associated genomic loci. Nearly all protein-coding genes in the human genome have been associated with one or more eQTLs. Here we introduce a multi-variant generalization of allelic Fold Change (aFC), aFC-n, to enable accurate quantification of the cis-regulatory effects in genes with multiple conditionally independent eQTLs. Applying aFC-n to 458,465 eQTLs in the Genotype-Tissue Expression (GTEx) project data, we demonstrate significant improvement in accuracy over the current tools for estimating the eQTL effect size and predicting genetically regulated gene expression. We characterize some of the empirical properties of the eQTL data and use this framework to assess the current state of eQTL data in terms of characterizing cis-regulatory landscape in individual genomes. Notably, we show that 77.4% of the genes with an allelic imbalance in a sample show 0.5 log2 fold or more of residual imbalance after accounting for the eQTL data underlining the remaining gap in characterizing regulatory landscape in individual genomes. We further contrast this gap across tissue types, and ancestry backgrounds to identify its correlates and guide future studies.
A single nucleotide polymorphism determines constitutive versus inducible type VI secretion in Vibrio cholerae
Authors: Drebes Dörr Natália C. , Proutière Alexis , Jaskólska Milena , Stutzmann Sandrine , Bader Loriane , Blokesch Melanie 
Published: January 2022

AbstractVibrio cholerae is a well-studied human pathogen that is also a common inhabitant of marine habitats. In both environments, the bacterium is subject to interbacterial competition. A molecular nanomachine that is often involved in such competitive behavior is the type VI secretion system (T6SS). Interestingly and in contrast to non-pandemic or environmental isolates, the T6SS of the O1 El Tor clade of V. cholerae, which is responsible for the ongoing 7th pandemic, is largely silent under standard conditions. Instead, these strains induce their full T6SS capacity only under specific conditions such as growth on chitinous surfaces (signaled through TfoX and QstR) or when the cells encounter low intracellular c-di-GMP levels (TfoY-driven). In this study, we identified a single nucleotide polymorphism (SNP) within an intergenic region of the major T6SS gene cluster of V. cholerae that determines the T6SS status of the cell. We show that SNP conversion is sufficient to induce T6SS production in numerous pandemic strains, while the converse approach renders non-pandemic/environmental V. cholerae strains T6SS-silent. We further demonstrate that SNP-dependent T6SS production occurs independently of the known T6SS regulators TfoX, QstR, and TfoY. Finally, we identify a putative promoter region adjacent to the identified SNP that is required for all forms of T6SS regulation.
Identification of 121 variants of honey bee Vitellogenin protein sequences with structural differences at functional sites
Authors: Leipart Vilde , Ludvigsen Jane , Kent Matthew , Sandve Simen , To Thu-Hien , Árnyasi Mariann , Kreibich Claus D , Dahle Bjørn , Amdam Gro V. 
Published: January 2022

AbstractProteins are under selection to maintain central functions and to accommodate needs that arise in ever-changing environments. The positive selection and neutral drift that preserve functions result in a diversity of protein variants. The amount of diversity differs between proteins: multifunctional or disease-related proteins tend to have fewer variants than proteins involved in some aspects of immunity. Our work focuses on the extensively studied protein Vitellogenin (Vg), which in honey bees(Apis mellifera)is multifunctional and highly expressed and plays roles in immunity. Yet, almost nothing is known about the natural variation in the coding sequences of this protein or how amino acid-altering variants might impact structure–function relationships. Here, we map out allelic variation in honey bee Vg using biological samples from 15 countries. The successful barcoded amplicon Nanopore sequencing of 543 bees revealed 121 protein variants, indicating a high level of diversity in Vg. We find that the distribution of non-synonymous single nucleotide polymorphisms (nsSNPs) differs between protein regions with different functions; domains involved in DNA and protein–protein interactions contain fewer nsSNPs than the protein’s lipid binding cavities. We outline how the central functions of the protein can be maintained in different variants and how the variation pattern may inform about selection from pathogens and nutrition.
Molecular hydrogen is an overlooked energy source for marine bacteria
Authors: Lappan Rachael , Shelley Guy , Islam Zahra F. , Leung Pok Man , Lockwood Scott , Nauer Philipp A. , Jirapanjawat Thanavit , Chen Ya-Jou , Kessler Adam J. , Williams Timothy J. , Cavicchioli Ricardo , Baltar Federico , Cook Perran L.M. , Morales Sergio E. , Greening Chris 
Published: January 2022

AbstractMolecular hydrogen (H2) and carbon monoxide (CO) are supersaturated in seawater relative to the atmosphere and hence are readily accessible energy sources for marine microbial communities. Yet while marine CO oxidation is well-described, it is unknown whether seawater communities consume H2. Here we integrated genome-resolved metagenomics, biogeochemistry, thermodynamic modelling, and culture-based analysis to profile H2and CO oxidation by marine bacteria. Based on analysis of 14 surface water samples, collected from three locations spanning tropical to subantarctic fronts, three uptake hydrogenase classes are prevalent in seawater and encoded by major marine families such as Rhodobacteraceae, Flavobacteriaceae, and Sphingomonadaceae. However, they are less abundant and widespread than carbon monoxide dehydrogenases. Consistently, microbial communities in surface waters slowly consumed H2and rapidly consumed CO at environmentally relevant concentrations, with H2oxidation most active in subantarctic waters. The cell-specific power from these processes exceed bacterial maintenance requirements and, for H2, can likely sustain growth of bacteria with low energy requirements. Concordantly, we show that the polar ultramicrobacteriumSphingopyxis alaskensisgrows mixotrophically on H2by expressing a group 2a [NiFe]-hydrogenase, providing the first demonstration of atmospheric H2oxidation by a marine bacterium. Based on TARA Oceans metagenomes, genes for trace gas oxidation are globally distributed and are fourfold more abundant in deep compared to surface waters, highlighting that trace gases are important energy sources especially in energy-limited waters. Altogether, these findings show H2is a significant energy source for marine communities and suggest that trace gases influence the ecology and biogeochemistry of oceans globally.
Structural equation modeling of the critical driving forces of offsite construction in Ghana
Authors: Guribie Francis Lanme , Kheni Nongiba Alkanam , Sule Mohammed 
Published: January 2022

PurposeThe construction sector suffers significant challenges which are intertwined with processes and products of the traditional onsite construction approach. The quest for a lasting solution to these problems is heralding the change toward offsite construction. Amid the scaling drive, to date there are no official reports and contribution to knowledge on the drivers of offsite construction in Ghana. This study models the structural paths of the critical drivers of offsite construction in Ghana.Design/methodology/approachData were collected through a questionnaire from 95 respondents in the Ghanaian construction industry. Exploratory factor analysis and Partial least squares structural equation modeling were employed to analyze the data.FindingsThe results revealed that industry dynamics are the governing drivers of offsite construction in Ghana. As such, factors such as the rocketing housing deficits, high cost of acquiring land permanently, high cost of cast-in-situ construction, the utilization of prefabricated shipping containers for construction and construction market demand constitute the governing drivers of offsite construction in Ghana. Similarly, concern for higher productivity is a critical driver of offsite construction in the Ghanaian construction industry. On the contrary, findings show that performance-related drivers, government policy and regulation, and technological innovation exert little influence in driving offsite construction in Ghana.Practical implicationsThe appreciation of the drivers may help stakeholders to understand the important mechanisms underlying offsite construction in Ghana, and thereafter help them to make more informed decisions regarding its implementation.Originality/valueThe findings contribute some interesting dimensions to the global debate on offsite construction by discovering and adding two drivers of offsite construction peculiar to developing countries (high cost of acquiring land permanently, and the utilization of shipping containers for construction) to the literature.
Organizing for permanent beta: performance measurement before vs performance monitoring after release of digital services
Authors: van Oorschot Kim E. , Akkermans Henk A. , Van Wassenhove Luk N. , Wang Yan 
Published: January 2022

PurposeDue to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains.Design/methodology/approachThe authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain.FindingsWith increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important.Research limitations/implicationsThe performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes.Originality/valueThe authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.
Direct and indirect influences of supply chain management practices on competitive advantage in fast fashion manufacturing industry
Authors: Jahed Mohammed Abu , Quaddus Mohammed , Suresh Nallan C. , Salam Mohammad Asif , Khan Eijaz Ahmed 
Published: January 2022

PurposeThis study investigates supply chain management (SCM) practices in a specific fast fashion apparel (FFA) industry. The impacts of SCM practices on competitive advantage (CA) are investigated via mediating roles of supply chain agility (SCA) and partnership quality (PQ). Resource advantage (R-A) theory, in addition to resource-based view (RBV) and dynamic capability theories, is used as theoretical underpinning.Design/methodology/approachA mixed-method approach is adopted: a qualitative field study and survey research. Data from 296 apparel manufacturers in Bangladesh are analyzed using the partial least squares structural equation modeling (PLS-SEM) approach, involving reflective and formative, first- and second-order constructs and mediation tests using the Hayes PROCESS macro.FindingsBoth SCM practices and PQ significantly affect SCA. SCM practices are found to directly enhance CA, but, counterintuitively, only marginally. Only through mediations of SCA and PQ do SCM practices enhance CA significantly. This is a departure from past research that has postulated direct effects between SCM practices and CA.Research limitations/implicationsThis research is confined to the FFA industry and one national setting, Bangladesh. The data analyzed is also cross-sectional, with customary limitations on the temporal dimension.Practical implicationsSCM practices contribute to CA, but only through the mediation of PQ and SCA. This is an important directive to practitioners. Also, the second-order reflective measures for each construct indicate the specific SCM practices needed to maximize CA.Originality/valueThis study contributes to the literature on SCM practices in FFA industry, specifically the mediating roles of PQ and SCA, resulting in new, more nuanced findings that are important in dynamic business settings, driven by new theoretical perspectives incorporating R-A theory, which has hardly been utilized before in SCM research.