bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physics-inspired analysis of the two-class income distribution in the USA in 1983–2018
Authors: Ludwig Danial , Yakovenko Victor M. 
Published: April 2022

The first part of this paper is a brief survey of the approaches to economic inequality based on ideas from statistical physics and kinetic theory. These include the Boltzmann kinetic equation, the time-reversal symmetry, the ergodicity hypothesis, entropy maximization and the Fokker–Planck equation. The origins of the exponential Boltzmann–Gibbs distribution and the Pareto power law are discussed in relation to additive and multiplicative stochastic processes. The second part of the paper analyses income distribution data in the USA for the time period 1983–2018 using a two-class decomposition. We present overwhelming evidence that the lower class (more than 90% of the population) is described by the exponential distribution, whereas the upper class (about 4% of the population in 2018) by the power law. We show that the significant growth of inequality during this time period is due to the sharp increase in the upper-class income share, whereas relative inequality within the lower class remains constant. We speculate that the expansion of the upper-class population and income shares may be due to increasing digitization and non-locality of the economy in the last 40 years.This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.
Characterisation of ethnic differences in DNA methylation between UK resident South Asians and Europeans
Authors: Elliott Hannah R. , Burrows Kimberley , Min Josine L. , Tillin Therese , Mason Dan , Wright John , Santorelli Gillian , Smith George Davey , Lawlor Deborah A. , Hughes Alun D. , Chaturvedi Nishi , Relton Caroline L. 
Published: April 2022

AbstractEthnic differences in non-communicable disease risk have been described between individuals of South Asian and European ethnicity that are only partially explained by genetics and other known risk factors. DNA methylation is one underexplored mechanism that may explain differences in disease risk. Currently there is little knowledge of how DNA methylation varies between South Asian and European ethnicities.This study characterised differences in blood DNA methylation between individuals of self-reported European and South Asian ethnicity from two UK-based cohorts; Southall and Brent Revisited (SABRE) and Born in Bradford (BiB). DNA methylation differences between ethnicities were widespread throughout the genome (n=16,433 CpG sites, 3.4% sites tested). Specifically, 76% of associations were attributable to ethnic differences in cell composition with fewer effects attributable to smoking and genetic variation. Ethnicity associated CpG sites were enriched for EWAS Catalog phenotypes including metabolites. This work highlights the need to consider ethnic diversity in epigenetic research.
Histopathological growth patterns of liver metastasis: updated consensus guidelines for pattern scoring, perspectives, and recent mechanistic insights
Authors: Latacz Emily , Höppener Diederik , Bohlok Ali , Leduc Sophia , Tabariès Sébastien , Moro Carlos Fernández , Lugassy Claire , Nyström Hanna , Bozóky Béla , Floris Giuseppe , Geyer Natalie , Brodt Pnina , Llado Laura , Mileghem Laura Van , Schepper Maxim De , Majeed Ali W. , Lazaris Anthoula , Dirix Piet , Zhang Qianni , Petrillo Stéphanie K. , Vankerckhove Sophie , Joye Ines , Meyer Yannick , Gregorieff Alexander , Roig Nuria Ruiz , Vidal-Vanaclocha Fernando , Denis Larsimont , Oliveira Rui Caetano , Metrakos Peter , Grünhagen Dirk J. , Nagtegaal Iris D. , Mollevi David G. , Jarnagin William R , D’Angelica Michael I , Reynolds Andrew R. , Doukas Michail , Desmedt Christine , Dirix Luc , Donckier Vincent , Siegel Peter M. , Barnhill Raymond , Gerling Marco , Verhoef Cornelis , Vermeulen Peter B. 
Published: April 2022

AbstractThe first consensus guidelines for scoring the histopathological growth patterns (HGPs) of liver metastases were established in 2017. Since then, numerous studies have applied these guidelines, have further substantiated the potential clinical value of the HGPs in patients with liver metastases from various tumour types and are starting to shed light on the biology of the distinct HGPs. In the present guidelines, we give an overview of these studies, discuss novel strategies for predicting the HGPs of liver metastases, such as deep learning algorithms for whole slide histopathology images and medical imaging, and highlight liver metastasis animal models that exhibit features of the different HGPs. Based on a pooled analysis of large cohorts of patients with liver-metastatic colorectal cancer, we propose a new cut-off to categorize patients according to the HGPs. An up-to-date standard method for HGP assessment within liver metastases is also presented with the aim of incorporating HGPs into the decision-making processes surrounding the treatment of patients with liver metastatic cancer. Finally, we propose hypotheses on the cellular and molecular mechanisms that drive the biology of the different HGPs, opening some exciting pre-clinical and clinical research perspectives.
Comorbidity clusters associated with newly treated Type 2 diabetes mellitus: a Bayesian nonparametric analysis
Authors: la Torre Adrian Martinez-De , Perez-Cruz Fernando , Weiler Stefan , Burden Andrea M. 
Published: April 2022

AbstractBackgroundType 2 Diabetes Mellitus (T2DM) is associated with the development of chronic comorbidities over time, which can lead to high drug utilization and adverse events. Understanding the patterns of disease progression is needed.ObjectivesTo identify common comorbidity clusters and explore the progression over time in newly treated T2DM patients.MethodsThe IQVIA Medical Research Data incorporating data from THIN, a Cegedim database of anonymized electronic health records, was used to identify all patients with a first-ever prescription for a non-insulin antidiabetic drug (NIAD) between January 2006 and December 2019. We selected 58 chronic comorbidities of interest and used Bayesian nonparametric latent models (BNLM) to identify disease clusters and model their progression over time.ResultsAmong the 175,383 eligible T2DM patients, we identified the 20 most frequent comorbidity clusters, which were comprised of 14 latent features (LFs). Each LF was associated with a main disease (e.g., 98% of patients in cluster 2, characterized by LF2, had congestive heart failure [CHF]). The presence of certain LFs increased the probability of having another LF active. For example, LF2 (CHF) frequently appeared with LFs related to chronic kidney disease (CKD). Over time, the clusters associated with cardiovascular diseases, such as CHF, progressed rapidly. Moreover, the onset of certain diseases led to the appearance of further complications (e.g., CHF onset was associated with an increasing prevalence of CKD).ConclusionsOur models identified established T2DM complications and previously unknown connections, thus, highlighting the potential for BNLMs t to characterize complex comorbidity patterns.
Droplet array-based platform for parallel optical analysis of dynamic extracellular vesicle secretion from single cells
Authors: Hattori Kazuki , Goda Yuki , Yamashita Minato , Yoshioka Yusuke , Kojima Ryosuke , Ota Sadao 
Published: April 2022

ABSTRACTExtracellular vesicles (EVs) are essential intercellular communication tools, but the regulatory mechanisms governing heterogeneous EV secretion are still unclear due to the lack of methods for precise analysis. Monitoring the dynamics of secretion from individually isolated cells is crucial because, in bulk analysis, secretion activity can be perturbed by cell–cell interactions, and a cell population rarely performs secretion in a magnitude- or duration-synchronized manner. Although various microfluidic techniques have been adopted to evaluate the abundance of single-cell-derived EVs, none can track their secretion dynamics continually for extended periods. Here, we have developed a droplet array-based method that allowed us to optically quantify the EV secretion dynamics of >300 single cells every 2 hours for 36 hours, which covers the cell doubling time of many cell types. The experimental results clearly show the highly heterogeneous nature of single-cell EV secretion and suggest that cell division facilitates EV secretion, showing the usefulness of this platform for discovering EV regulation machinery.
A spiking neural network model for the control of oscillatory phase differences between multiple brain areas
Authors: Canolty Ryan T. , Stimberg Marcel 
Published: April 2022

AbstractThe causal mechanisms which underlie rapid, transient, and dynamic coordination of large-scale functional brain networks remain unknown. Neuronal oscillations have been hypothesized to play a critical role influencing long-range communication between brain areas, with oscillatory phase differences influencing the effective connectivity between areas (Fries, 2005). However, it remains unclear how networks of spiking neurons could causally and mechanistically control the relative phase difference between cortical regions. Here we describe a simple model of spiking neurons that can dynamically control the relative phase differences between multiple brain areas. The model applies to any inhibition-based rhythm, and has four essential elements: a) tonic excitation of local recurrent networks of excitatory and inhibitory cells produces oscillations (Börgers et al., 2012); b) winner-take-all (WTA) dynamics permit only a small fraction of cells to fire on any given cycle (de Almeida et al., 2009); c) di-synaptic feed-forward inhibition leads to oscillatory phase resetting in a target area (Traub et al., 1996); and d) the range of conduction delays for inter-regional axonal projections span the duration of one oscillatory cycle (Swadlow, 1998). The key assumption of our model is to link WTA dynamics to conduction delays, such that only axons with a narrow range of delays are active at one time and are selected via local activity. Phase resetting in the target area converts this conduction delay into a specific phase difference. Thus, the model converts local differences in cellular excitation into inter-areal phase differences via WTA dynamics and feed-forward inhibition, where excitatory cells act as phase difference effectors or detectors. Including several WTA modules within a given area allows it to serve as a coordinating hub, controlling the relative phase differences of multiple distributed brain regions. Finally, we show how this model can help explains recent empirical results showing that individual neurons are sensitive to the relative phase difference between areas (Canolty et al., 2010).
Protocol for mixed-method study by LOng COvid Multidisciplinary consortium: Optimising Treatments and servIces acrOss the NHS (LOCOMOTION)
Authors: Sivan Manoj , Greenhalgh Trisha , Darbyshire Julie L. , Mir Ghazala , O’Connor Rory J. , Dawes Helen , Greenwood Darren C. , O’Connor Daryl B. , Horton Mike , Petrou Stavros , de Lusignan Simon , Curcin Vasa , Mayer Erik , Casson Alexander , Milne Ruairidh , Rayner Clare , Smith Nikki , Parkin Amy , Preston Nick , Delaney Brendan 
Published: April 2022

AbstractIntroductionLong COVID, a new condition whose origins and natural history are not yet fully established, currently affects 1.5 million people in the UK. Most do not have access to specialist long COVID services. We seek to optimise long COVID care both within and outside specialist clinics, including improving access, reducing inequalities, helping patients manage their symptoms effectively at home, and providing guidance and decision support for primary care. We aim to establish a ‘gold standard’ of care by systematically analysing symptom clusters and current practices, iteratively improving pathways and systems of care, and working to disseminate better practices.Methods and analysisThis mixed-method, multi-site study is informed by the principles of applied health services research, quality improvement, co-design, and learning health systems. It was developed in close partnership with patients (whose stated priorities are prompt clinical assessment; evidence-based advice and treatment; and help with returning to work and other roles) and with front-line clinicians. Workstreams and tasks to optimise assessment, treatment and monitoring are based in three contrasting settings: [1] specialist management in 10 long COVID clinics across the UK, via a quality improvement collaborative, experience-based co-design and targeted efforts to reduce inequalities of access; [2] patient self-management at home, with technology-supported monitoring; and [3] generalist management in primary care, harnessing electronic record data to study population phenotypes and develop evidence-based decision support, referral pathways and prioritisation criteria across the primary-secondary care interface, along with analysis of costs. Study governance includes an active patient advisory group.Ethics and disseminationLOCOMOTION is sponsored by the University of Leeds and approved by Yorkshire & The Humber - Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers to influence service specifications and targeted funding streams.Study registrationClinicalTrials.gov: NCT05057260; ISRCTN15022307.
Sequence Analysis of WRKY Transcription Factor Family in Dendrobium officinale
Authors: Pan Haoyu , Feng Yeyuan , Wei Liangwen , Sun Xinxin , Tao Shili , Song Cheng 
Published: April 2022

AbstractWRKY transcription factors are a key class of plant regulators that regulate Dendrobium growth, development, and stress tolerance. In this work, 74 Dendrobium WRKY genes were found in the Dendrobium whole genome file using tbtools software, hmmer3.0 software, pfam website, mega6.0 software, genedoc software, meme online analysis website, and other tools, and tbtools software was utilized after amino acid alignment. A phylogenetic tree of the Dendrobium and Arabidopsis WRKY transcription factors’ sequence alignment was built, as well as the chromosomal location, gene structure analysis, conserved domain analysis, and cis-acting element analysis of the Dendrobium WRKY gene. The phylogenetic tree comparison analysis revealed that Dendrobium WRKY transcription factors were classified into three groups: I, II, and III, with Group II subdivided into five subgroups: II-a, II-b, II-c, II-d, and II-e. According to amino acid alignment research, the Dendrobium WRKY transcription factor contains a highly conserved WRKYGQK sequence. According to gene chromosomal mapping, the Dendrobium WRKY gene was found to be irregularly distributed across many chromosomes of Dendrobium officinale. Introns vary greatly in terms of quantity and starting place. According to conserved domain analysis, the Dendrobium WRKY gene comprised diverse patterns in number and species, but all had the conserved domain WRKYGQK, and there were certain distinguishing motifs amongst subfamilies. Elements with a cis-action It was found that the Dendrobium WRKY gene has a lot of cis-acting elements, like light response, low temperature stress response, drought response, hormone response, growth differentiation responses.
Digital transformation and accountants as advisors
Authors: Yigitbasioglu Ogan , Green Peter , Cheung May-Yin Decca 
Published: April 2022

PurposeThe purpose of this study is to explore the role of accountants as advisors in professional services firms (PSFs), and it examines the impact of digital transformation on the work, knowledge and skills of accountants in their role as advisors in PSFs.Design/methodology/approachData were collected using semi-structured interviews predominantly with partners in Australian PSFs, including the Big4 and directors of professional accounting bodies.FindingsThe findings show that accountants as advisors fill a critical role in PSFs as they represent substantial human capital for such firms. Accountants as advisors are a valuable strategic resource because of their unique capabilities in combining generic human capital with digital human capital and social capital resources. Some differences between the Big4 and non-Big4 were found in terms of services offered that were attributable to the respective industry foci and resource availability.Practical implicationsThe findings have broader implications for both the accounting profession and the education sector in terms of providing a better, and more overt, understanding of what the future holds for the accounting profession and the relevant knowledge and skills required. Also, recruiters and managers at PSFs are likely to benefit from the findings.Originality/valueEvidence from PSFs provides insights into an evolutionary path for the accounting profession, and the knowledge and skills accountants need to work in that increasingly competitive domain, due to digital transformation.
A spatio-temporal emotional framework for knowledge extraction and mining in digital humanities
Authors: Deng Jun , Zhong Chuyi , Sun Shaodan , Wang Ruan 
Published: April 2022

PurposeThis paper aims to construct a spatio-temporal emotional framework (STEF) for digital humanities from a quantitative perspective, applying knowledge extraction and mining technology to promote innovation of humanities research paradigm and method.Design/methodology/approachThe proposed STEF uses methods of information extraction, sentiment analysis and geographic information system to achieve knowledge extraction and mining. STEF integrates time, space and emotional elements to visualize the spatial and temporal evolution of emotions, which thus enriches the analytical paradigm in digital humanities.FindingsThe case study shows that STEF can effectively extract knowledge from unstructured texts in the field of Chinese Qing Dynasty novels. First, STEF introduces the knowledge extraction tools – MARKUS and DocuSky – to profile character entities and perform plots extraction. Second, STEF extracts the characters' emotional evolutionary trajectory from the temporal and spatial perspective. Finally, the study draws a spatio-temporal emotional path figure of the leading characters and integrates the corresponding plots to analyze the causes of emotion fluctuations.Originality/valueThe STEF is constructed based on the “spatio-temporal narrative theory” and “emotional narrative theory”. It is the first framework to integrate elements of time, space and emotion to analyze the emotional evolution trajectories of characters in novels. The execuability and operability of the framework is also verified with a case novel to suggest a new path for quantitative analysis of other novels.
Process innovation capability in less-structured business processes: a systematic literature review
Authors: Goni Joklan Imelda Camelia , Van Looy Amy 
Published: April 2022

PurposeBuilding process innovation capability (PIC) is becoming increasingly important to keep pace with changing business environments and emerging technological opportunities. However, the literature on process innovation capability (PIC) is still very broad and does not consistently reflect today's reality that is becoming increasingly complicated and knowledge-intensive, leading to more organizational needs for supporting less-structured business processes (LSBP).Design/methodology/approachBased on a systematic literature review (SLR), the authors provide evidence for this under-investigated subject by consolidating organizational capabilities for managing PIC in LSBP. The authors screened 1,083 and identified only 26 peer-reviewed articles that simultaneously encompass process innovation and LSBP.FindingsThe authors explain which LSBP types are typically addressed, and in which sectors. The authors categorize research avenues, best practices and a framework that links PIC to performance outcomes by also considering business environments. Three theories (i.e. resource-based view, dynamic capabilities and sociotechnical theory) help to underpin the six empirically observed capabilities along three pillars (i.e. people, process and technology).Research limitations/implicationsBesides a research agenda, the authors offer a conceptual framework for PIC in LSBP as a reference to guide scholars and practitioners.Practical implicationsThe authors offer best practices, as derived from the literature.Originality/valueThis is the first SLR for PIC in LSBP, consolidating and categorizing the PIC-LSBP characteristics. Due to few studies on the subject, this work contributes to a deeper understanding of the PICs needed for LSBP to obtain the desired performance outcomes.
Predicting collaborative consumption behaviour: a meta-analytic path analysis on the theory of planned behaviour
Authors: Ashaduzzaman Md , Jebarajakirthy Charles , Weaven Scott K. , Maseeh Haroon Iqbal , Das Manish , Pentecost Robin 
Published: April 2022

Purpose
Collaborative consumption (CC), a unique business model, provides several monetary and non-monetary benefits to customers. Several adapted theory of planned behaviour (TPB)-based models were developed and tested to understand this consumption behaviour with the findings inconsistent and fragmented. Thus, this study aims to develop a general and consistent TPB model using a meta-analytic path analysis to better understand customers’ CC adoption behaviour.

Design/methodology/approach
Using 37 studies, a meta-analysis was performed adopting several analytical methods; bivariate analysis, moderation analysis and path analysis.

Findings
The universal TPB model shows that factors, that is, trust, attitude, perceived environmental responsibility and communication facilities, drive both perceived usefulness and CC. However, subjective norms, such as perceived behavioural control and emotional value, drive only perceived usefulness. Moderation analysis shows that the relationships between variables used in the proposed TPB model tends to vary depending on five moderators, that is, countries’ economic development level, type of CC, sample size, sample type and survey administration method.

Research limitations/implications
The consideration of only quantitative papers and papers written in English language in this meta-analysis may bias the study’s findings.

Practical implications
Based on the findings regarding important factors that consumers consider when adopting CC, this study provides insightful recommendations to companies facilitating CC.

Originality/value
By developing the universal TPB model, this study theoretically contributes to the TPB model, and by conducting the moderation test, the study contextually contributes to the TPB literature in the CC context.