bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 inequalities in England: a mathematical modelling study of transmission risk and clinical vulnerability by socioeconomic status
Authors: Goodfellow Lucy , van Leeuwen Edwin , Eggo Rosalind M 
Published: January 2024

AbstractBackgroundThe COVID-19 pandemic resulted in major inequalities in infection burden between areas of varying socioeconomic deprivation in many countries, including England. Areas of higher deprivation tend to have a different population structure - generally younger - which can increase viral transmission due to higher contact rates in school-going children and working-age adults. Higher deprivation is also associated with higher presence of chronic comorbidities, which were convincingly demonstrated to be risk factors for severe COVID-19 disease. These two major factors need to be combined to better understand and quantify their relative importance in the observed COVID-19 inequalities.MethodsWe used UK Census data on health status and demography stratified by decile of the Index of Multiple Deprivation (IMD), which is a measure of socioeconomic deprivation. We calculated epidemiological impact using an age-stratified COVID-19 transmission model, which incorporated different contact patterns and clinical health profile by decile. To separate the contribution of each factor, we also considered a scenario where the clinical health profile of all deciles was at the level of the least deprived. We also considered the effectiveness of school closures in each decile.ResultsIn the modelled epidemics in urban areas, the most deprived decile experienced 9% more infections, 13% more clinical cases, and a 97% larger peak clinical size than the least deprived; we found similar inequalities in rural areas. 21% of clinical cases and 16% of deaths in England observed under the model assumptions would not occur if all deciles experienced the clinical health profile of the least deprived decile. We found that more deaths were prevented in more affluent areas during school closures.ConclusionsThis study demonstrates that both clinical and demographic factors synergise to generate health inequalities in COVID-19, that improving the clinical health profile of populations would increase health equity, and that some interventions can increase health inequalities.
Quantifying morphological changes in middle trapezius with ultrasound scanning and a novel histogram-matching algorithm for adults with and without Facioscapulohumeral dystrophy (FSHD)
Authors: Philp Fraser , Meilak Erik , Seyres Martin , Willis Tracey , Winn Naomi , Pandyan Anand 
Published: January 2024

AbstractBackground and ObjectivesFacioscapulohumeral dystrophy (FSHD) is a neuromuscular disease causing changes in muscle structure that can negatively affect upper-limb function. Echogenicity, measured using quantified muscle ultrasound, is a potential biomarker that could be used for informing decision making. Histogram-matching allows for image normalisation, which could enable comparison of echogenicity between different machine capture settings which is a current limitation. This study aimed to investigate if ultrasonography and histogram-matching can measure trapezius muscle echogenicity and morphology for differentiating between people with and without FSHD, and different levels of arm function.MethodsSingle measurement timepoint case control study of adults with FSHD and age- and sex-matched controls. Main outcomes were trapezius echogenicity and muscle thickness measured using 2D-ultrasound, and maximum thoracohumeral elevation angle, measured using 3D-movement analysis. A sensitivity analysis evaluating the effect of histogram-matching and different reference images was conducted. Between group differences for echogenicity were evaluated using an unpaired student t-test. Echogenicity, muscle thickness and range of movement were plotted to evaluate the explained variance between variables.ResultsData was collected for 14 participants (10M:4F), seven with FSHD and seven controls with a mean (SD) age of 41.6 (15.7). Normalisation was necessary and echogenicity values for the FSHD group were higher than the controls (118.2 (34.0) vs 42.3 (14.0) respectively, with statistically significant differences (p=0.002). An overall variance of 6.2 (LLOA −2.9 to ULOA 15.4) was identified between reference images. Echogenicity accounted for the largest explained variance in muscle thickness (R2=0.81) and range of movement (R2=0.74), whilst muscle thickness and range of movement was the lowest (R2=0.61).DiscussionPeople with FSHD demonstrated higher echogenicity, smaller muscle thicknesses and less range of movement. Histogram-matching for comparison of echogenicity values is necessary and can provide quantifiable differences. Different reference images affect echogenicity values but the variability is less than between group differences. Further work is needed to evaluate the longitudinal variability associated with this method on a larger sample of people with varying levels of arm function. Ultrasound scanning and post-histogram matching may be used to quantify and compare differences in muscle structure and function people with and without FSHD.
Aspergillus-mediated allergic airway inflammation is triggered by dendritic cell recognition of a defined spore morphotype, a process that can be targeted via antifungal therapeutics
Authors: Houlder EL , Gago S , Vere G , Conn D , Khan S , Thomson D , Shepherd MW , Lebedinec R , Brown GD , Bromley M , MacDonald AS , Cook PC 
Published: January 2024

AbstractBackgroundExposure to fungi, especiallyAspergillus fumigatus (A.f.), can elicit potent allergic inflammation that triggers and worsens asthmatic disease. Dendritic cells (DCs), initiate allergic inflammatory responses to allergic stimuli. However, it is unclear ifA.f.spores during isotropic growth (early spore swelling) can activate DCs to initiate allergic responses or if germination is required. This lack of basic understanding of howA.f.causes disease is a barrier to the development of new treatments.ObjectiveTo show that a preciseA.f. morphotype stage during spore swelling can trigger DCs to mediate allergic inflammatory responses and ascertain if antifungal therapeutics can be effective at suppressing this process.MethodsWe employed anA.f.strain deficient in pyrimidine biosynthesis (ΔpyrG) to generate populations ofA.f.spores arrested at different stages of isotropic growth (swelling) via temporal removal of uracil and uridine from growth media. These arrested spore stages were cultured with bone marrow derived DCs (BMDCs), and their activation measured via flow cytometry and ELISA to interrogate which growth stage was able to activate BMDCs. These BMDCs were then adoptively transferred into the airways, to assess if they were able to mediate allergic inflammation in naive recipient mice. Allergic airway inflammationin vivowas determined via flow cytometry, ELISA and qPCR. This system was also used to determine if antifungal drug (itraconazole) treatment could alter early stages of spore swelling and therefore BMDC activation andin vivoallergic inflammation upon adoptive transfer.ResultsWe found thatA.f. isotropic growth is essential to trigger BMDC activation and mediate allergic airway inflammation. Furthermore, using time arrestedA.f.stages, we found that least 3h in growth media enabled spores to swell sufficiently to activate BMDCs to elicit allergic airway inflammationin vivo. Incubation of germinatingA.f.with itraconazole reduced spore swelling and partially reduced their ability to activate BMDCs to elicitin vivoallergic airway inflammation.ConclusionIn summary, our results have pinpointed the precise stage ofA.f. development when germinating spores are able to activate DCs to mediate downstream allergic airway inflammation. Furthermore, we have identified that antifungal therapeutics can be effective in reducing the potential ofA.f.spores to stimulate allergic responses, highlighting a potential mechanism by which antifungal treatment might help to prevent the development of fungal allergy.
Epigenetic priming of embryonic lineages in the mammalian epiblast
Authors: Sendra Miquel , McDole Katie , Jimenez-Carretero Daniel , Hourcade Juan de Dios , Temiño Susana , Raiola Morena , Guignard Léo , Keller Philipp J , Sánchez-Cabo Fátima , Domínguez Jorge N. , Torres Miguel 
Published: January 2024

SummaryUnderstanding the diversification of mammalian cell lineages is an essential to embryonic development, organ regeneration and tissue engineering. Shortly after implantation in the uterus, the pluripotent cells of the mammalian epiblast generate the three germ layers: ectoderm, mesoderm and endoderm1. Although clonal analyses suggest early specification of epiblast cells towards particular cell lineages2–4, single-cell transcriptomes do not identify lineage-specific markers in the epiblast5–11and thus, the molecular regulation of such specification remains unknow. Here, we studied the epigenetic landscape of single epiblast cells, which revealed lineage priming towards endoderm, ectoderm or mesoderm. Unexpectedly, epiblast cells with mesodermal priming show a strong signature for the endothelial/endocardial fate, suggesting early specification of this lineage aside from other mesoderm. Through clonal analysis and live imaging, we show that endothelial precursors show early lineage divergence from the rest of mesodermal derivatives. In particular, cardiomyocytes and endocardial cells show limited lineage relationship, despite being temporally and spatially co-recruited during gastrulation. Furthermore, analysing the live tracks of single cells through unsupervised classification of cell migratory activity, we found early behavioral divergence of endothelial precursors shortly after the onset of mesoderm migration towards the cardiogenic area. These results provide a new model for the phenotypically silent specification of mammalian cell lineages in pluripotent cells of the epiblast and modify current knowledge on the sequence and timing of cardiovascular lineages diversification12,13.
SAX-7/L1CAM acts with the adherens junction proteins MAGI-1, HMR-1/Cadherin, and AFD-1/Afadin to promote glial-mediated dendrite extension
Authors: Cebul Elizabeth R. , Marivin Arthur , Wexler Leland R. , Perrat Paola N. , Bénard Claire Y. , Garcia-Marcos Mikel , Heiman Maxwell G. 
Published: January 2024

ABSTRACTAdherens junctions (AJs) are a fundamental organizing structure for multicellular life. Although AJs are studied mainly in epithelia, their core function – stabilizing cell contacts by coupling adhesion molecules to the cytoskeleton – is important in diverse tissues. We find that twoC. eleganssensory neurons, URX and BAG, require conserved AJ proteins for dendrite morphogenesis. We previously showed that URX and BAG dendrites attach to the embryonic nose via the adhesion molecule SAX-7/L1CAM, acting both in neurons and glia, and then extend by stretch during embryo elongation. Here, we find that a PDZ-binding motif (PB) in the SAX-7 cytoplasmic tail acts with other interaction motifs to promote dendrite extension. Using pull-down assays, we find that the SAX-7 PB binds the multi-PDZ scaffolding protein MAGI-1, which bridges it to the cadherin-catenin complex protein HMP-2/β-catenin. Using cell-specific rescue and depletion, we find that both MAGI-1 and HMR-1/Cadherin act in glia to non-autonomously promote dendrite extension. Double mutant analysis indicates that each protein can act independently of SAX-7, suggesting a multivalent adhesion complex. The SAX-7 PB motif also binds AFD-1/Afadin, loss of which further enhancessax-7BAG dendrite defects. As MAGI-1, HMR-1, and AFD-1 are all found in epithelial AJs, we propose that an AJ-like complex in glia promotes dendrite extension.
Blockchain technology roles to overcome accounting, accountability and assurance barriers in supply chain finance
Authors: Rijanto Arief 
Published: January 2024

PurposeKnow your customer (KYC), accounting standards, issuance, clearing, and trade settlement became the major barrier to implement accounting, accountability and assurance process in supply chain finance (SCF). Blockchain technology features have the potential to solve accounting problems. This research focuses on exploring how blockchain technology provides solutions to overcome the barriers of accounting process in SCF. The benefits, opportunities, costs and risks related to blockchain adoption are also explored.Design/methodology/approachMulti-case study and qualitative methods are used with a framework based on blockchain role to overcome the accounting process barriers. Ten blockchain projects in SCF and 29 interviews of participants as a unit of analysis are considered.FindingsThe findings indicate that blockchain technology offers solutions to solve accounting, accountability and assurance problems in SCF. Validity, verification, smart contracts, automation and enduring data on trade transactions potentially solve those barriers. However, it is also necessary to consider costs such as implementation, technology, education and integration costs. Then there are possible risks such as regulatory compliance, operational, code development and scalability risk. This finding reflects the current status of blockchain technology roles in SCF.Research limitations/implicationsThis study unveils blockchain's SCF accounting potential, emphasizing multi-case method limitations and future research prospects. Diverse contexts challenge findings' applicability, warranting cross-industry studies for deeper insights. Addressing selection bias and integrating quantitative measures can enhance understanding of blockchain's accounting impact.Practical implicationsAccounting professionals can get an idea of the future direction and impact of blockchain technology on accounting, accountability and assurance processes.Originality/valueThis study provides initial findings on the potential, costs and risks of blockchain that is beneficial for parties involved in SCF, especially for banks and insurance underwriters. In addition, the findings also provide direction for the contribution of blockchain technology to accounting theory in the future.
A mixed-methods investigation of the factors affecting the use of facial recognition as a threatening AI application
Authors: Wu Xiaojun , Zhou Zhongyun , Chen Shouming 
Published: January 2024

PurposeArtificial intelligence (AI) applications pose a potential threat to users' data security and privacy due to their high data-dependence nature. This paper aims to investigate an understudied issue in the literature, namely, how users perceive the threat of and decide to use a threatening AI application. In particular, it examines the influencing factors and the mechanisms that affect an individual’s behavioral intention to use facial recognition, a threatening AI.Design/methodology/approachThe authors develop a research model with trust as the key mediating variable by integrating technology threat avoidance theory, the theory of planned behavior and contextual factors related to facial recognition. Then, it is tested through a sequential mixed-methods investigation, including a qualitative study (for model development) of online comments from various platforms and a quantitative study (for model validation) using field survey data.FindingsPerceived threat (triggered by perceived susceptibility and severity) and perceived avoidability (promoted by perceived effectiveness, perceived cost and self-efficacy) have negative and positive relationships, respectively, with an individual’s attitude toward facial recognition applications; these relationships are partially mediated by trust. In addition, perceived avoidability is positively related to perceived behavioral control, which along with attitude and subjective norm is positively related to individuals' intentions to use facial recognition applications.Originality/valueThis paper is among the first to examine the factors that affect the acceptance of threatening AI applications and how. The research findings extend the current literature by providing rich and novel insights into the important roles of perceived threat, perceived avoidability, and trust in affecting an individual’s attitude and intention regarding using threatening AI applications.
Behavior of Zn5Al hot-dip galvanized steel members under fire exposure
Authors: Pinger Thomas , Firan Mirabela , Mensinger Martin 
Published: January 2024

PurposeBased on the known positive effects of conventional hot-dip galvanizing under fire exposure and indicative results on zinc–aluminum coatings from smallscale tests, a series of tests were conducted on zinc-5% aluminum galvanized test specimens under fire loads to verify the previous positive findings under largescale boundary conditions.Design/methodology/approachThe emissivity of zinc-5% aluminum galvanized surfaces applied to steel specimens was determined experimentally under real fire loads and laboratory thermal loads in accordance with the normative specifications of the standard fire curve. Both large and smallscale specimens were used in this study. The steel grade and surface conditions of the specimens were varied for both test scenarios.FindingsLargescale tests on specimens with typical steel construction dimensions under fire loads showed that the surface emissivity of zinc-5% aluminum galvanized steel was significantly lower than that of the conventionally galvanized steel. Only minor influences from the weathering of the specimens and steel chemistry were observed. These results agree well with those obtained from smallscale tests. The design values of zinc-5% aluminum melt (Zn5Al) required for the structural fire design were proposed based on the obtained results.Originality/valueThe novel tests presented in this study are the first ones to study the behavior of zinc-5% aluminum galvanized largescale steel construction components under the influence of real fire exposure and their positive effect on the emissivity of steel components galvanized by this method. The results provide valuable insights and information on the behavior in the case of fire and the associated savings potential for steel construction.
Digital transformation and corporate restructuring: does corporate governance matter?
Authors: Tran Ngoc Phu , Le Quan Thai-Thuong , Vo Anh The , Vo Duc Hong 
Published: January 2024

PurposeAdopting digital transformation is changing the methods through which companies' function, generating novel possibilities and difficulties that force firms to adjust to remain competitive in the digital era. It is critical for firms to embrace this change and utilize technology to develop a more flexible, proactive and effective approach as digital transformation continues to advance at an accelerating pace. Vietnam has been placed at the forefront of these changes in attracting investments and becoming a hub of international trade. As a result, Vietnamese firms have been implementing restructuring and adopting digital transformation to remain competitive with the flow of foreign investment. This paper aims to examine the effects of digital transformation on corporate restructuring in Vietnam. The authors then investigate the moderating role of corporate governance in the digital transformation – corporate restructuring nexus.Design/methodology/approachThe authors employ content analysis to extract information from the annual reports of 747 Vietnamese listed companies, where the authors focus on specific phrases, such as “digitalization”, “big data”, “cloud computing”, “blockchain” and “information technology” over a period of 11 years, from 2011 to 2021. The frequency count of these keywords is calculated to represent the level of digital transformation for the Vietnamese listed firms. A final sample of 118 Vietnamese listed firms with sufficient data is selected for the analysis using the generalized method of moments (GMM) approach.FindingsThe results indicate that digital transformation and corporate governance negatively impact corporate restructuring when their effect on corporate restructuring is examined independently. However, corporate governance strengthens the effect of digital transformation on corporate restructuring.Originality/valueThis paper is one of the first to investigate the moderating role of corporate governance on the effect of digital transformation on corporate restructuring in Vietnam. The findings inspire listed firms in Vietnam to implement digital transformation during their corporate restructuring to enhance performance.
Big data readiness in the public sector: an assessment model and insights from Indonesian local governments
Authors: Ariansyah Kasmad , Setiawan Ahmad Budi , Hikmaturokhman Alfin , Ardison Ardison , Walujo Djoko 
Published: January 2024

Purpose
This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

Design/methodology/approach
This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

Findings
FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

Originality/value
This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.