bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of protein-carbohydrate binding sites from protein primary sequence
Authors: Nawar Quazi Farah , Nafi Md Muhaiminul Islam , Islam Tasnim Nishat , Rahman M Saifur
Published: February 2024

A protein is a large complex macromolecule that has a crucial role in performing most of the work in cells and tissues. It is made up of one or more long chains of amino acid residues. Another important biomolecule, after DNA and protein, is carbohydrate. Carbohydrates interact with proteins to run various biological processes. Several biochemical experiments exist to learn the protein-carbohydrate interactions, but they are expensive, time consuming and challenging. Therefore developing computational techniques for effectively predicting protein-carbohydrate binding interactions from protein primary sequence has given rise to a prominent new field of research. In this study, we proposeStackCBEmbed, an ensemble machine learning model to effectively classify protein-carbohydrate binding interactions at residue level. StackCBEmbed combines traditional sequence-based features along with features derived from a pre-trained transformer-based protein language model. To the best of our knowledge, ours is the first attempt to apply protein language model in predicting protein-carbohydrate binding interactions. StackCBEmbed achieved sensitivity, specificity and balanced accuracy scores of 0.730, 0.821, 0.776 and 0.666, 0.818, 0.742 in two separate independent test sets. This performance is superior compared to the earlier prediction models benchmarked in the same datasets. We thus hope that StackCBEmbed will discover novel protein-carbohydrate interactions and help advance the related fields of research. StackCBEmbed is freely available as python scripts athttps://github.com/nafiislam/StackCBEmbed.
Global diversity and evolution of Salmonella Panama, an understudied serovar causing gastrointestinal and invasive disease worldwide: a genomic epidemiology study
Authors: Pulford Caisey Victoria , Perez-Sepulveda Blanca M , Ingle Danielle J , Bengtsson Rebecca J , Bennet Rebecca J , Rodwell Ella V , Pardos de la Gandara Maria , Chong Charlotte , De Silva P. Malaka , Ravel Magali , Guibert Veronique , Njamkepo Elisabeth , Hall Neil , Chattaway Marie A , Howden Benjamin , Williamson Deborah A , Hinton Jay C. D. , Weill Francois-Xavier , Baker Kate S
Published: February 2024

Background Nontyphoidal Salmonella (NTS) is a globally important bacterial pathogen, typically associated with foodborne gastrointestinal infection. Some NTS serovars can also colonise normally sterile sites in humans to cause invasive NTS (iNTS) disease. One understudied Salmonella enterica serovar which is responsible for a significant number of cases of iNTS disease is Panama. Despite global dissemination, numerous outbreaks, and a reported association with iNTS disease, S. enterica serovar Panama (S. Panama) has not been investigated in detail. Methods Using combined epidemiological and whole genome sequencing data we analysed 836 S. Panama genomes derived from historical collections, national surveillance datasets, and publicly available data. The collection represents all inhabited continents and includes isolates collected between 1931 and 2019. Maximum likelihood and Bayesian phylodynamic approaches were used to determine population structure & evolutionary history, and to infer geo-temporal dissemination. A combination of different bioinformatic approaches utilising short-read and long-read data were used to characterise geographic and clade-specific trends in antimicrobial resistance (AMR), and genetic markers for invasiveness. Findings We identified the presence of multiple geographically linked S. Panama clades, and regional trends in antimicrobial resistance profiles. Most isolates were pan-susceptible to antibiotics and belonged to clades circulating in the United States of America, Latin America, and the Caribbean. Multidrug resistant (MDR) isolates in our collection belonged to two phylogenetic clades circulating in Europe and Asia/Oceania, which exhibited the highest invasiveness indices based on the conservation of 196 extra-intestinal predictor genes. Interpretation This first large-scale phylogenetic analysis of S. Panama revealed important information about population structure, AMR, global ecology, and genetic markers of invasiveness of the identified genomic subtypes. Our findings provide an important baseline for understanding S. Panama infection in the future. The presence of MDR clades with an elevated invasiveness index should be monitored by ongoing surveillance as such clades may pose an increased public health risk.
Federated Learning for Predicting Compound Mechanism of Action Based on Image-data from Cell Painting
Authors: Ju Li , Hellander Andreas , Spjuth Ola
Published: February 2024

Having access to sufficient data is essential in order to train accurate machine learning models, but much data is not publicly available. In drug discovery this is particularly evident, as much data is withheld at pharmaceutical companies for various reasons. Federated Learning (FL) aims at training a joint model between multiple parties but without disclosing data between the parties. In this work, we leverage Federated Learning to predict compound Mechanism of Action (MoA) using fluorescence image data from cell painting. Our study evaluates the effectiveness and efficiency of FL, comparing to non-collaborative and data-sharing collaborative learning in diverse scenarios. Specifically, we investigate the impact of data heterogeneity across participants on MoA prediction, an essential concern in real-life applications of FL, and demonstrate the benefits for all involved parties. This work highlights the potential of federated learning in multi-institutional collaborative machine learning for drug discovery and assessment of chemicals, offering a promising avenue to overcome data-sharing constraints.
TheivorylncRNA regulates seasonal color patterns in buckeye butterflies
Authors: Fandino Richard A. , Brady Noah K. , Chatterjee Martik , McDonald Jeanne M. C. , Livraghi Luca , van der Burg Karin R. L. , Mazo-Vargas Anyi , Markenscoff-Papadimitriou Eirene , Reed Robert D.
Published: February 2024

Long non-coding RNAs (lncRNAs) are transcribed elements increasingly recognized for their roles in regulating gene expression. Thus far, however, we have little understanding of how lncRNAs contribute to evolution and adaptation. Here we show that a conserved lncRNA,ivory, is an important color patterning gene in the buckeye butterflyJunonia coenia.ivoryoverlaps withcortex, a locus linked to multiple cases of crypsis and mimicry in Lepidoptera. Along with a companion paper by Livraghi et. al., we argue thativory, notcortex, is the color pattern gene of interest at this locus. InJ. coeniaa cluster ofcis-regulatory elements (CREs) in the first intron ofivoryare genetically associated with natural variation in seasonal color pattern plasticity, and targeted deletions of these CREs phenocopy seasonal phenotypes. Deletions of differentivoryCREs produce other distinct phenotypes as well, including loss of melanic eyespot rings, and positive and negative changes in overall wing pigmentation. We show that the color pattern transcription factors Spineless, Bric-a-brac, and Ftz-f1 bind to theivorypromoter during wing pattern development, suggesting that they directly regulateivory. This case study demonstrates howcis-regulation of a single non-coding RNA can exert diverse and nuanced effects on the evolution and development of color patterns, including modulating seasonally plastic color patterns.

Significance

The genomic locus hosting thecortexgene has been linked to numerous cases of color pattern adaptation in moths and butterflies, including crypsis, mimicry, and seasonal polyphenism. Here we show in buckeye butterflies that the actual color pattern gene at thecortexlocus is an evolutionarily conserved long non-coding RNA (lncRNA), dubbedivory, that overlaps withcortex. Compared with other wing pattern genes,ivorystands out because of the highly nuanced, quantitative changes in pigmentation that can be achieved by manipulating adjacentcis-regulatory sequences. This study highlights how lncRNAs can be important factors underlying morphological evolution, and emphasizes the importance of considering non-coding transcripts in comparative genomics.
Reovirus infection induces transcriptome-wide unique A-to-I editing changes in the murine fibroblasts
Authors: Tariq Ayesha , Piontkivska Helen
Published: February 2024

The conversion of Adenosine (A) to Inosine (I), by Adenosine Deaminases Acting on RNA or ADARs, is an essential post-transcriptional modification that contributes to proteome diversity and regulation in metazoans including humans. In addition to its transcriptome-regulating role, ADARs also play a major part in immune response to viral infection, where an interferon response activates interferon-stimulated genes, such as ADARp150, in turn dynamically regulating host-virus interactions. A previous report has shown that infection from reoviruses, despite strong activation of ADARp150, does not influence the editing of some of the major known editing targets, while likely editing others, suggesting a potentially nuanced editing pattern that may depend on different factors. However, the results were based on a handful of selected editing sites and did not cover the entire transcriptome. Thus, to determine whether and how reovirus infection specifically affects host ADAR editing patterns, we analyzed a publicly available deep-sequenced RNA-seq dataset, from murine fibroblasts infected with wild-type and mutant reovirus strains that allowed us to examine changes in editing patterns on a transcriptome-wide scale. To the best of our knowledge, this is the first transcriptome-wide report on host editing changes after reovirus infection. Our results demonstrate that reovirus infection induces unique nuanced editing changes in the host, including introducing sites uniquely edited in infected samples. Genes with edited sites are overrepresented in pathways related to immune regulation, cellular signaling, metabolism, and growth. Moreover, a shift in editing targets has also been observed, where the same genes are edited in infection and control conditions but at different sites, or where the editing rate is increased for some and decreased for other differential targets, supporting the hypothesis of dynamic and condition-specific editing by ADARs.
The Cas10 nuclease activity relieves host dormancy to facilitate spacer acquisition and retention during type III-A CRISPR immunity
Authors: Aviram Naama , Shilton Amanda K. , Lyn Nia G. , Reis Bernardo S. , Brivanlou Amir , Marraffini Luciano A.
Published: February 2024

A hallmark of CRISPR immunity is the acquisition of short viral DNA sequences, known as spacers, that are transcribed into guide RNAs to recognize complementary sequences. The staphylococcal type III-A CRISPR-Cas system uses guide RNAs to locate viral transcripts and start a response that displays two mechanisms of immunity. When immunity is triggered by an early-expressed phage RNA, degradation of viral ssDNA can cure the host from infection. In contrast, when the RNA guide targets a late-expressed transcript, defense requires the activity of Csm6, a non-specific RNase. Here we show that Csm6 triggers a growth arrest of the host that provides immunity at the population level which hinders viral propagation to allow the replication of non-infected cells. We demonstrate that this mechanism leads to defense against not only the target phage but also other viruses present in the population that fail to replicate in the arrested cells. On the other hand, dormancy limits the acquisition and retention of spacers that trigger it. We found that the ssDNase activity of type III-A systems is required for the re-growth of a subset of the arrested cells, presumably through the degradation of the phage DNA, ending target transcription and inactivating the immune response. Altogether, our work reveals a built-in mechanism within type III-A CRISPR-Cas systems that allows the exit from dormancy needed for the subsistence of spacers that provide broad-spectrum immunity.
Nanoscale interaction of endonuclease APE-1 with DNA characterized by atomic force microscopy
Authors: Vemulapalli Sridhar , Hashemi Mohtadin , Chen Yinglink , Pramanik Suravi , Bhakat Kishor K. , Lyubchenko Yuri L.
Published: February 2024

Apurinic/apyrimidinic endonuclease 1 (APE1) is involved in DNA replication, repair, and transcriptional regulation mechanisms. This multifunctional activity of APE1 should be supported by specific structural properties of APE1 that have not yet been elucidated. Here we applied atomic force microscopy (AFM) to characterize the interactions of APE1 with DNA. Complexes of APE1 with DNA containing G-rich segments were visualized, and analysis of the complexes revealed the affinity of APE1 to G-rich DNA sequences. Furthermore, loops in the DNA-APE1 complexes were visualized, and their yield was as high as 53 %. However, the loops were non-specific, with quantitative analysis revealing the yield of loops bridging two G-rich DNA segments to be 41%. Analysis of protein size in various complexes was performed, and these data showed that loops are formed by APE1 monomer, suggesting that APE1 has two DNA binding sites. The data lead us to a model for the interaction of APE1 with DNA that describes its molecular site search mechanism. The new properties of APE1 in organizing DNA, by bringing two distant sites together, may be important for facilitating the scanning for damage and coordinating repair and transcription.
Classification of LTR Retrotransposons via Interaction Prediction
Authors: Cardoso Silvana C. S. , Domingues Douglas S. , Paschoal Alexandre R. , Fischer Carlos N. , Cerri Ricardo
Published: February 2024

Transposable Elements (TEs) are genetic sequences that can relocate within the genome, thus promoting genetic diversity. Classifying TEs in eukaryotes involves a hierarchy formed by classes, subclasses, orders, superfamilies, families, and subfamilies. According to this taxonomy, LTR retrotransposons (LTR-RT) constitute an order. The primary objective of this study is to explore the classification of LTR retrotransposons at the superfamily level. This was achieved by predicting interactions between LTR-RT sequences and conserved protein domains using Predictive Bi-Clustering Trees (PBCTs). Two datasets were used to investigate the relationships among different superfamilies. The first one comprised LTR retrotransposon sequences assigned to Copia, Gypsy, and Bel-Pao superfamilies, whereas the second dataset included consensus sequences of the conserved domains for each superfamily. Therefore, the PBCT decision tree tests could relate to both sequence and class attributes. In the classification process, interaction is interpreted as either the presence or absence of a domain in a given LTR-RT sequence. Subsequently, this sequence is classified into the superfamily with the highest number of predicted domains. Precision-recall curves were adopted as evaluation metrics for the method, and its performance was compared to some of the most commonly used models in the task of transposable element classification. Experiments onD. melanogasterandA. thalianashowed that PBCTs are promising and comparable to other methods, especially in the classification of the Gypsy superfamily.
Contrastive Fitness Learning: Reprogramming Protein Language Models for Low-NLearning of Protein Fitness Landscape
Authors: Zhao Junming , Zhang Chao , Luo Yunan
Published: February 2024

Machine learning (ML) is revolutionizing our ability to model the fitness landscape of protein sequences, which is critical to answering fundamental life science questions and addressing important protein engineering applications, such as quantifying the pathogenicity of disease variants, forecasting viral evolution in a pandemic, and engineering new antibodies. Recently, the protein language model (pLM) has emerged as an effective ML tool in deciphering the intrinsic semantics of protein sequences and become the foundation of state-of-the-art ML solutions for many problems in protein biology. However, significant challenges remain in leveraging pLMs for protein fitness prediction, in part due to the disparity between the scarce number of sequences functionally characterized by high-throughput assays and the massive data samples required for training large pLMs. To bridge this gap, we introduce Contrastive Fitness Learning (ConFit), a pLM-based ML method for learning the protein fitness landscape with limited experimental fitness measurements as training data. We propose a novel contrastive learning strategy to fine-tune the pre-trained pLM, tailoring it to achieve protein-specific fitness prediction while avoiding overfitting, even when using a small number (low-N) of functionally assayed mutant sequences for supervised fine-tuning. Evaluated across over 30 benchmark datasets of protein fitness, ConFit consistently provided accurate fitness predictions and outperformed several competitive baseline methods. Further analysis revealed that ConFit’s capability of low-Nlearning enabled sample-efficient active learning for identifying high-fitness protein variants. Collectively, our work represents a novel strategy to harness the potential of pLMs to elucidate the protein sequence-function relationship. The source code of ConFit is available athttps://github.com/luo-group/ConFit.
Gaussian boson sampling with click-counting detectors
Authors: Bressanini Gabriele , Kwon Hyukjoon , Kim M. S.
Published: February 2024

Gaussian boson sampling constitutes a prime candidate for an experimental demonstration of quantum advantage within reach with current technological capabilities. The original proposal employs photon-number-resolving detectors, however, these are not widely available. Nevertheless, inexpensive threshold detectors can be combined into a single click-counting detector to achieve approximate photon-number resolution. We investigate the problem of sampling from a general multimode Gaussian state using click-counting detectors and show that the probability of obtaining a given outcome is related to a matrix function which is dubbed as the Kensingtonian. We show how the Kensingtonian relates to the Torontonian and the Hafnian, thus bridging the gap between known Gaussian boson sampling variants. We then prove that, under standard complexity-theoretical conjectures, the model cannot be simulated efficiently.

Published by the American Physical Society
2024
Materials adopted for particle beam windows in relevant experimental facilities
Authors: Notari Lorenzo , Pasquali Michele , Carra Federico , Losasso Marcello , Tomut Marilena
Published: February 2024

A beam vacuum window is a thin interface of separation between a volume under vacuum and a volume at a higher pressure traversed by particle beams. Their application is not only limited to particle accelerators, where they are typically installed inside the beamline to separate vacuum sectors, but also extends to other fields of nuclear research and to high-power hadron beam applications, such as spallation neutron sources and accelerator-driven systems. The main issue concerning the beam window technology resides intrinsically in the dual role of these components: the thickness of the window is supposed to be as thin as possible to allow the passage of the particles through matter with minimal interaction but, at the same time, enough resistant to maintain the required differential pressure between the two environments.

Published by the American Physical Society
2024
Thermal effect in hot QCD matter in strong magnetic fields
Authors: Wen Xin-Jian , Zhang Jia
Published: February 2024

The quasiparticle model is improved by the free magnetic contribution to investigate the QCD matter in a strong magnetic field. The temperature-dependent bag function is determined by the thermodynamic consistency to represent the difference in energy density between physical vacuum and the lowest state of QCD. It is found that the positive bag function vanishes at high temperature, indicating the deconfinement. The rapid decrease of the bag function in stronger magnetic fields reveals the so-called inverse magnetic catalysis. The interaction measure at high temperature remains so large that the usual Stefan-Boltzmann limit cannot be reached. We suggest a limit |qiBm|T2/4 for each Landau level pressure. Finally, it is demonstrated that the positive magnetization modified by the bag function and free magnetic contribution indicates the paramagnetic characteristic of QCD matter.

Published by the American Physical Society
2024
Emergence of directed motion in a crowded suspension of overdamped particles with different effective temperatures
Authors: Schwarcz Deborah , Burov Stanislav
Published: February 2024

In this work, we focus on the behavior of a single passive Brownian particle in a suspension of passive particles with short-range repulsive interactions and higher effective temperature. While the forces affecting the single particle are thermal-like fluctuations and repulsion, due to other particles in the suspension, our numerical simulations show that on intermediate timescales directed motion on a single-particle level emerges. This emergent directional motion leads to a breakdown of the Einstein relation and nonmonotonic augmentation of the measured diffusion coefficient. Directional tendency increases with the density of the suspension and leads to growth of the diffusivity with the density of the suspension, a phenomenon recently observed for a system of hard spheres by Ilker, Castellana, and Joanny. Counterintuitively, the directional flow originates from the tendency of different particles to push each other out of their way. Due to such strictly repulsive interactions, nearby particles form into temporally correlated pairs and move cooperatively, thus creating a preferred direction of motion on intermediate timescales. We show that directional motion emerges when the ratio of the effective temperatures of the tracked particle and suspension constituents is below a critical value.

Published by the American Physical Society
2024
Universal parameters of bulk-solvent masks
Authors: Urzhumtsev Alexandre , Adams Paul , Afonine Pavel
Published: February 2024

The bulk solvent is a major component of biomacromolecular crystals that contributes significantly to the observed diffraction intensities. Accurate modelling of the bulk solvent has been recognized as important for many crystallographic calculations. Owing to its simplicity and modelling power, the flat (mask-based) bulk-solvent model is used by most modern crystallographic software packages to account for disordered solvent. In this model, the bulk-solvent contribution is defined by a binary mask and a scale (scattering) function. The mask is calculated on a regular grid using the atomic model coordinates and their chemical types. The grid step and two radii, solvent and shrinkage, are the three parameters that govern the mask calculation. They are highly correlated and their choice is a compromise between the computer time needed to calculate the mask and the accuracy of the mask. It is demonstrated here that this choice can be optimized using a unique value of 0.6 Å for the grid step irrespective of the data resolution, and the radii values adjusted correspondingly. The improved values were tested on a large sample of Protein Data Bank entries derived from X-ray diffraction data and are now used in the computational crystallography toolbox (CCTBX) and in Phenix as the default choice.
The curious case of Hotel King’s Cross
Authors: Satpute Pratik , Bapat Gautam Surendra
Published: February 2024

Learning outcomes

The learning outcomes of this study are to recall the fundamental concept of revenue management in the hotel industry (remembering); explain the various performance measures used to evaluate room revenue in hotels (understanding); use revenue management strategies to improve room revenue in hotel operations (applying); and examine and evaluate the optimal solution for revenue enhancement, considering factors such as capacity management, duration control and differential pricing (analyzing).

Case overview/synopsis

This case study delves into the challenges faced by Hotel King’s Cross, a business hotel located in Pune, Maharashtra, in the year 2022. A week before Christmas Eve, Soham Dande, the hotel’s revenue manager, sought a meeting with Rohan Chopra, the director of sales and marketing, to discuss “revenue optimization for the hotel.”

During their meeting, Dande mentioned that the hotel had fallen behind its budgeted room sales targets for 2022 across various metrics, such as room booking nights, occupancy percentage, average room rate and revenue per available room. Furthermore, the hotel was trailing behind its competitors. The situation was compounded by the management’s decision to raise the targets for 2023 by 5%–7%, factoring in upcoming events, competitive performance and pandemic-related losses over the past two years. Chopra faced the dilemma of formulating an action plan to achieve the ambitious 2023 targets and establish Hotel King’s Cross as a market leader.

Complexity academic level

Students undertaking executive development programs and graduate-level courses in non-profit hospitality and tourism management, as well as revenue management courses in the executive MBA, management development and graduate MBA programs, may all benefit from this case study.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS12: Tourism and hospitality.
Exploratory search in information systems: a systematic review
Authors: Liu Yaxi , Qin Chunxiu , Wang Yulong , Ma XuBu
Published: February 2024

Purpose

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Design/methodology/approach

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

Findings

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

Originality/value

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.
Point and interval forecasting for wine prices: an approach based on artificial intelligence
Authors: Cui Huiyu , Guo Honggang , Wang Jianzhou , Wang Yong
Published: February 2024

Purpose

With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.

Design/methodology/approach

The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.

Findings

The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.

Originality/value

This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.
A study on factors affecting Japanese consumer’s behavior toward 5G smartphone purchase
Authors: Fukui Mikihiro , Tan Caroline S.L.
Published: February 2024

Purpose

The purpose of this study is to analyze the determinants influencing Japanese consumers’ behavior toward the purchase of 5G smartphones.

Design/methodology/approach

Empirical data was collected through an online survey of 320 Japanese respondents from ages 20 to 59. Data was analyzed by exploratory factor analysis, confirmatory factor analysis and multiple regression analysis.

Findings

The results indicate that hedonic value, user interface and price value (PV) positively influence attitude toward 5G smartphone purchase, while utilitarian value does not. In addition, the mediation effect of social influence (SI) is found to increase those positive effects. Male and female consumers displayed differences in the determinants, showcasing the effect of gender on attitude and behavior.

Originality/value

To the best of the authors’ knowledge, this study is the first research to analyze Japanese consumers’ behaviors’ toward 5G smartphone purchase. Past research for 3G/4G smartphones supported that usefulness positively influenced consumers’ behavior toward smartphones, so usefulness of 5G (e.g. high speed) was expected to be a factor to influence consumer behaviors’ toward 5G smartphones. However, this research reveals that a simple tagline emphasizing such usefulness may not be convincing enough to promote the 5G smartphones to Japanese consumers. Alternatively, the research indicates that introducing the concepts of joyfulness, improved HV and greater PV of the 5G smartphone could attract more consumers in Japan. In addition, SI could enhance the perception of the various benefits of 5G smartphones.
Strategic leadership and transactional leadership: the mediating effect of digital leadership in the world of Industry 4.0
Authors: Avwokeni Arthur Joseph
Published: February 2024

Purpose

The dearth of leadership competencies to transform traditional industries to Industry 4.0 is a barrier to global production. This study explains the deficiencies in leadership competencies that hinder the transformation of traditional industries to Industry 4.0.

Design/methodology/approach

Leadership was explained into transactional leadership, digital leadership and Leadership 4.0. Then, the network of relationships between these leadership constructs was plotted in a path diagram to learn the mediating effect of digital leadership.

Findings

The results indicate that a lack of digital competencies to coordinate tasks, share information and solve problems in a digitalized environment is the barrier to the transformation.

Practical implications

The findings can be used in human resources (HR) management. In addition, the findings provide evidence to present the contingency theory as a universal theory of leadership.

Originality/value

The study is the first to assess the mediating effect of digital leadership on transactional leadership to explain the changes to strategic leadership due to the emergence of Leadership 4.0.
Knowledge management and career readiness: a review and synthesis
Authors: Raut Sachin Kumar , Alon Ilan , Rana Sudhir , Kathuria Sakshi
Published: February 2024

Purpose

This study aims to examine the relationship between knowledge management and career development in an era characterized by high levels of youth unemployment and a demand for specialized skills. Despite the increasing transition to a knowledge-based economy, there is a significant gap between young people’s skills and career readiness, necessitating an in-depth analysis of the role of knowledge management at the individual, organizational and national levels.

Design/methodology/approach

The authors conducted a qualitative study using the theory-context-characteristics-methodology approach based on a systematic literature review. The authors created an ecological framework for reflecting on knowledge management and career development, arguing for a multidisciplinary approach that invites collaboration across sectors to generate innovative and reliable solutions.

Findings

This study presents a comprehensive review of the existing literature and trends, noting the need for more focus on the interplay between knowledge management and career development. It emphasizes the need for businesses to promote the acquisition, storage, diffusion and application of knowledge and its circulation and exchange to create international business human capital.

Practical implications

The findings may help multinational corporations develop managerial training programs and recruitment strategies, given the demand for advanced knowledge-based skills in the modern workspace. The study also discusses the influences of education, experience and job skills on business managers’ performance, guiding the future recruitment of talents.

Originality/value

To the best of the authors’ knowledge, this review is among the first to assess the triadic relationship between knowledge management, career development and the global unemployment crisis. The proposed multidisciplinary approach seeks to break down existing silos, thus fostering a more comprehensive understanding of how to address these ongoing global concerns.
The impact of climate change news on the US stock market
Authors: Fedorova Elena , Iasakova Polina
Published: February 2024

Purpose

This paper aims to investigate the impact of climate change news on the dynamics of US stock indices.

Design/methodology/approach

The empirical basis of the study was 3,209 news articles. Sentiment analysis was performed by a pre-trained bidirectional FinBERT neural network. Thematic modeling is based on the neural network, BERTopic.

Findings

The results show that news sentiment can influence the dynamics of stock indices. In addition, five main news topics (finance and politics natural disasters and consequences industrial sector and Innovations activism and culture coronavirus pandemic) were identified, which showed a significant impact on the financial market.

Originality/value

First, we extend the theoretical concepts. This study applies signaling theory and overreaction theory to the US stock market in the context of climate change. Second, in addition to the news sentiment, the impact of major news topics on US stock market returns is examined. Third, we examine the impact of sentimental and thematic news variables on US stock market indicators of economic sectors. Previous works reveal the impact of climate change news on specific sectors of the economy. This paper includes stock indices of the economic sectors most related to the topic of climate change. Fourth, the research methodology consists of modern algorithms. An advanced textual analysis method for sentiment classification is applied: a pre-trained bidirectional FinBERT neural network. Modern thematic modeling is carried out using a model based on the neural network, BERTopic. The most extensive topics are “finance and politics of climate change” and “natural disasters and consequences.”
Integrated care system leadership: a rapid realist review
Authors: Knight Lisa , Neiva Ganga Rafaela , Tucker Matthew
Published: February 2024

Purpose

Given the complex nature of integrated care systems (ICSs), the geographical spread and the large number of organisations involved in partnership delivery, the importance of leadership cannot be overstated. This paper aims to present novel findings from a rapid realist review of ICS leadership in England. The overall review question was: how does leadership in ICSs work, for whom and in what circumstances?

Design/methodology/approach

Development of initial programme theories and associated context–mechanism–outcome configurations (CMOCs) were supported by the theory-gleaning activities of a review of ICS strategies and guidance documents, a scoping review of the literature and interviews with key informants. A refined programme theory was then developed by testing these CMOCs against empirical data published in academic literature. Following screening and testing, six CMOCs were extracted from 18 documents. The study design, conduct and reporting were informed by the Realist And Metanarrative Evidence Syntheses: Evolving Standards (RAMESES) training materials (Wong et al., 2013).

Findings

The review informed four programme theories explaining that leadership in ICSs works when ICS leaders hold themselves and others to account for improving population health, a sense of purpose is fostered through a clear vision, partners across the system are engaged in problem ownership and relationships are built at all levels of the system.

Research limitations/implications

Despite being a rigorous and comprehensive investigation, stakeholder input was limited to one ICS, potentially restricting insights from varied geographical contexts. In addition, the recent establishment of ICSs meant limited literature availability, with few empirical studies conducted. Although this emphasises the importance and originality of the research, this scarcity posed challenges in extracting and applying certain programme theory elements, particularly context.

Originality/value

This review will be of relevance to academics and health-care leaders within ICSs in England, offering critical insights into ICS leadership, integrating diverse evidence to develop new evidence-based recommendations, filling a gap in the current literature and informing leadership practice and health-care systems.
Not your average candidate: overqualified job applicants in the eyes of hiring practitioners
Authors: Rafiei Mohsen , Van Dijk Hans
Published: February 2024

Purpose

Early research on overqualification suggested that overqualification is primarily associated with negative attitudes and behavior. As a consequence, hiring practitioners were advised against hiring overqualified job applicants. However, recent studies have revealed that there are several potential positive consequences of overqualification. Given this change in perspective on overqualification, we examine how hiring practitioners nowadays look at overqualified job applicants, and what their considerations are for hiring an overqualified job applicant or not.

Design/methodology/approach

We have interviewed 33 hiring practitioners to examine their attitudes and considerations toward hiring overqualified job applicants.

Findings

Results show that hiring practitioners are aware of potential positive as well as negative consequences of overqualification and consider a variety of factors to assess how beneficial hiring an overqualified candidate will be. These factors fall under three categories: Individual considerations, interpersonal considerations and contextual considerations.

Originality/value

We show that overqualification is not a stigma anymore and that the decision to hire an overqualified job applicant or not depends on a mixture of factors that are carefully considered. Two of these three considerations transcend the individual level (i.e. the overqualified person), whereas most research and theories on the consequences of overqualification do not go beyond the individual level. As such, our findings call for more theory and research on interpersonal and contextual factors shaping the consequences of overqualification.
A comprehensive review on mango allergy: Clinical relevance, causative allergens, cross‐reactivity, influence of processing techniques, and management strategies
Authors: Zhao Jinlong , Camus‐Ela Mukeshimana , Zhang Lili , Wang Yuxin , Rennie Gardiner Henric , Wang Jin , Raghavan Vijaya
Published: February 2024

Mangoes (Mangifera indica) are widely prized for their abundant nutritional content and variety of beneficial bioactive compounds and are popularly utilized in various foods, pharmaceuticals, and cosmetics industries. However, it is important to note that certain proteins present in mango can trigger various allergic reactions, ranging from mild oral allergy syndrome to severe life‐threatening anaphylaxis. The immunoglobulin E‐mediated hypersensitivity of mango is mainly associated with three major allergenic proteins: Man i 1 (class IV chitinase), Man i 2 (pathogenesis‐related‐10 protein; Bet v 1‐related protein), and Man i 4 (profilin). Food processing techniques can significantly affect the structure of mango allergens, reducing their potential to cause allergies. However, it is worth mentioning that complete elimination of mango allergen immunoreactivity has not been achieved. The protection of individuals sensitized to mango should be carefully managed through an avoidance diet, immediate medical care, and long‐term oral immunotherapy. This review covers various aspects related to mango allergy, including prevalence, pathogenesis, symptoms, and diagnosis. Furthermore, the characterization of mango allergens and their potential cross‐reactivity with other fruits, vegetables, plant pollen, and seeds were discussed. The review also highlights the effects of food processing on mango and emphasizes the available strategies for managing mango allergy.
Template‐specific optimization of NGS genotyping pipelines reveals allele‐specific variation in MHC gene expression
Authors: Efstratiou Artemis , Gaigher Arnaud , Künzel Sven , Teles Ana , Lenz Tobias L.
Published: February 2024

Using high‐throughput sequencing for precise genotyping of multi‐locus gene families, such as the major histocompatibility complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from erroneous variants. Several dedicated genotyping pipelines for data from high‐throughput sequencing, such as next‐generation sequencing (NGS), have been developed to tackle the ensuing risk of artificially inflated diversity. Here, we thoroughly assess three such multi‐locus genotyping pipelines for NGS data, the DOC method, AmpliSAS and ACACIA, using MHC class IIβ data sets of three‐spined stickleback gDNA, cDNA and “artificial” plasmid samples with known allelic diversity. We show that genotyping of gDNA and plasmid samples at optimal pipeline parameters was highly accurate and reproducible across methods. However, for cDNA data, the gDNA‐optimal parameter configuration yielded decreased overall genotyping precision and consistency between pipelines. Further adjustments of key clustering parameters were required tο account for higher error rates and larger variation in sequencing depth per allele, highlighting the importance of template‐specific pipeline optimization for reliable genotyping of multi‐locus gene families. Through accurate paired gDNA‐cDNA typing and MHC‐II haplotype inference, we show that MHC‐II allele‐specific expression levels correlate negatively with allele number across haplotypes. Lastly, sibship‐assisted cDNA‐typing of MHC‐I revealed novel variants linked in haplotype blocks, and a higher‐than‐previously‐reported individual MHC‐I allelic diversity. In conclusion, we provide novel genotyping protocols for the three‐spined stickleback MHC‐I and ‐II genes, and evaluate the performance of popular NGS‐genotyping pipelines. We also show that fine‐tuned genotyping of paired gDNA‐cDNA samples facilitates amplification bias‐corrected MHC allele expression analysis.
Bony proliferations in rheumatoid arthritis, psoriatic arthritis and osteoarthritis using high‐resolution peripheral quantitative computed tomography—A systematic literature review
Authors: Moen Haakon Vilstrup , Hänel Mathias , Therkildsen Josephine , Klose‐Jensen Rasmus , Keller Kresten Krarup , Hauge Ellen Margrethe
Published: February 2024

Purpose

Osteoarthritis (OA), rheumatoid arthritis (RA), and psoriatic arthritis (PsA) can all lead to the formation of bony proliferations (BP). This systematic review aimed to examine the characteristics of BPs in patients with RA, PsA, OA, and healthy controls (HC) using high‐resolution peripheral quantitative computed tomography (HR‐pQCT). Secondarily, we examined any treatment‐related effect on BP number and size.

Methods

A systematic literature search was conducted in PubMed and Embase, and a total of 15 studies were included.

Results

Seven studies demonstrated a disease‐specific variation in BP location. One study showed no difference in the number of BPs between patients with PsA and OA. The number of BPs was greater in patients with PsA compared to RA in one study, and to HC in another study, while one study documented no difference in the number of BPs between patients with RA and HC. Five studies showed larger BPs in patients with PsA compared to HC, and one study larger BPs in patients with PsA compared to RA. One study showed no difference in BP size between patients with PsA and OA. Secukinumab may have a potential effect on arresting BP progression. Otherwise, no other treatment was reported to influence BP size and progression. No standard definitions or measurement techniques for BPs using HR‐pQCT have been identified.

Conclusion

BPs showed disease‐specific variations in location, size, and number. Results regarding treatment‐related effects are sparse. An agreement on the definition and measurement technique for BPs using HR‐pQCT is warranted for diagnostic accuracy, disease comparability, and monitoring potential.