bluuebunny/crossref_metadata_2025_split huggingface dataset:
RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data
Authors: Ge Changhao , Hu Xiaowen , Zhang Lin , Li Hongzhe 
Published: November 2024

ABSTRACTTranscriptome sequencing (RNA-seq) is widely used in cancer research to study the transcriptome and its role in disease progression. Somatic copy number aberrations (SCNAs) are key drivers of cancer development, and inferring SCNAs from RNA-seq data can provide critical insights for disease classification and treatment prediction. We introduce RCANE, a deep learning-based method designed to predict genome-wide SCNAs across various cancer types using RNA-seq data. RCANE is trained on data from The Cancer Genome Atlas (TCGA) and DepMap cancer cell lines, demonstrating superior performance compared to existing methods. This scalable approach offers a robust solution for improving SCNA prediction in cancer diagnostics and treatment.
The role of dormant propagule banks in shaping eco-evolutionary dynamics of community assembly
Authors: Lin Jian-Hao , Han Bo-Ping , Urban Mark C. , De Meester Luc 
Published: November 2024

AbstractThe metacommunity framework provides a theoretical framework for understanding how dispersal alters species distribution patterns at different spatial scales. Dormancy is a strategy that decreases the extinction risk and can be viewed as dispersal over time, shaping the assembly dynamics of populations and communities. However, dormancy has only recently been recognized as a potentially important mediator of metacommunity-level processes. Here, we extend an individual-based model of metacommunity dynamics by adding propagule banks that store dormant propagules that can hatch in subsequent growing seasons. By systematically varying the propagule bank size in the model, we investigated how dormant propagule bank size influenced the eco-evolutionary dynamics of community assembly in populations of both asexual and sexual species at three dispersal levels (isolated communities and weakly and strongly connected communities). Our simulations show that as the propagule bank size increases, 1) the rate of evolution decreases in asexual species, whereas the rate of evolution increases in sexual species; 2) species sorting becomes less important while evolution-mediated zpriority effects (monopolization) make a more significant contribution; and 3) α-diversity decreases and β-diversity increases. We also found that patches with well-established propagule banks contributed more to the regional species pool than patches with less well-developed propagule banks. Dispersal asymmetries also emerge as patches with a well-established bank tend to reduce the invasion success of new arrivals while also providing more emigrants with diverse genetic variation to the other patches, fostering regional monopolization. To this end, we regard the banks in a metacommunity as a hidden state of a local community, a potential gene pool, and a latent part of a regional species pool.
A single-gene-based AI model to identify core and context-specific essential genes by biological interpretation from pooled genome-wide CRISPR and omics data
Authors: Chou Chih-Yuan , Lee Jung-Yu , Lee Chia-Hwa , Yang Jinn-Moon 
Published: November 2024

AbstractGenome-wide Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a powerful tool for screening essential genes (EGs) and studying gene function by systematically knocking out individual genes. EGs are essential for the survival of organisms and can be divided into core EGs (CEGs) and context-specific EGs, which are crucial for the development of drugs. Although a variety of CEGs have been identified using knockout technology, the concordance among these CEG sets is extremely low; there is a lack of studies on the EG mechanisms. Therefore, developing systematic methods to identify CEGs and reveal corresponding mechanisms are important biological issues.To address these issues, we propose a comprehensive ensembled-based model utilizing gene community-regulated pathways to decipher pan-cancer CEGs and context-specific EGs across 29 cancer types and provide insights into their regulatory abilities for each pathway. The project aims include developing a model with Systematic Identification of Essential Gene (SIEG) scores for CEGs and Context-Specific Enrichment (CSE) scores for context-specific EGs. Subsequently, we assess the regulated pathways and mechanisms of these identified EGs by integrating diverse data sources such as genome-wide CRISPR/Cas9 knockout screens, multiple omics data, KEGG pathways, and Gene Ontology. Ultimately, we aim to establish a user-friendly web service.In our preliminary results, we gathered 1,845 genome-wide CRISPR datasets and various omics datasets, including 8,941 clinical samples and 1,346 cell lines, leading to the identification of 3,213 CEGs. By employing the SIEG score, we found that 1,178 of these pan-cancer CEGs overlapped with previously defined CEGs, reflecting a 60% similarity rate. These 3,213 CEGs play crucial roles in regulating pathways associated with cell viability, expansion, and proliferation. Additionally, they exhibit characteristics typical of CEGs, showing less favorable as therapeutic targets and centralizing within protein-protein interaction networks. Moreover, we delineated six pathway signatures of pan-cancer CEGs, encompassing transcription, translation, protein folding, replication and repair, cell growth and death, as well as energy. We anticipate that these signatures will contribute to the future redefinition of CEGs.
Inhibition of Yes-Associated Protein (YAP) with Verteporfin Enhances Radiosensitivity in Chordoma by Inducing G2M Arrest and Inhibiting the DNA Damage Response
Authors: Akinduro Oluwaseun O. , Suarez-Meade Paola , Schiapparelli Paula , Whitehead Rachel , Tzeng Stephany Y. , Rosenfeld Steven S. , Kim Sungjune , Palena Claudia , Gokaslan Ziya L. , Green Jordan J. , Quinones-Hinojosa Alfredo 
Published: November 2024

ABSTRACTChordomas are locally invasive cancers that are highly resistant to radiotherapy. The Brachyury and Yes-Associated Protein (YAP) regulatory axis has been implicated as the primary driver of tumorigenicity in chordoma. Here, we aimed to enhance chordoma radiosensitivity by repurposing the FDA-approved YAP inhibitor, Verteporfin. We used five patient-derived chordoma cell lines and generated two YAP1 knockdown cell lines to validate the YAP-targeting phenotype in chordoma. Verteporfin treatment reduced the expression of DNA damage repair proteins and genes. YAP inhibition with either verteporfin or YAP knockdown resulted in enhanced DNA double-stranded breaks after radiation via inhibition of the DNA damage repair pathway and accumulation of cells in the G2M phase. Verteporfin inhibited chordoma tumor growth alone and in combination with radiation in a xenograft mouse model treated with verteporfin loaded microparticles, resulting in sensitization of chordoma tumors to radiation. YAP inhibition with verteporfin renders chordoma more sensitive to radiation via inhibition of the DNA damage repair cascade and accumulation of cells in G2M when they are most susceptible to radiation damage.
Learning interpretable representations of single-cell multi-omics data with multi-output Gaussian Processes
Authors: Moslehi Zahra , Buettner Florian 
Published: November 2024

AbstractLearning representations of single-cell genomics data is challenging due to the non-linear and often multi-modal nature of the data on one hand and the need for interpretable representations on the other hand. Existing approaches tend to either focus on interpretability aspects via linear matrix factorisation or on maximising expressive power via neural-network based embeddings using black-box variational autoencoders or graph embedding approaches. We address this trade-off between expressive power and interpretability by introducing a novel approach that combines highly expressive representation learning via an embedding layer with an interpretable multi-output Gaussian processes within a unified framework. In our model, we learn distinct representations for samples (cells) and features (genes) from multi-modal single-cell data. We demonstrate that even a few interpretable latent dimensions can effectively capture the underlying structure of the data. Our model yields interpretable relationships between groups of cells and their associated marker genes: leveraging a gene relevance map, we establish connections between cell clusters (e.g. specific cell types) and feature clusters (e.g., marker genes for those specific cell types) within the learnt latent spaces of cells and features.
High-throughput Generation of Collagen Microbeads for 3D Cell Culture and Extracellular Vesicle Production
Authors: Ali Samantha , Mastantuono Fabiana , Orozco-Torres Andrea , Barua Niloy , Zhou Xin , Wu Lizi , He Mei 
Published: November 2024

ABSTRACTCollagen type I, a fundamental component of natural extracellular matrices across species, is an attractive material for the development of tissue engineering constructs. Nevertheless, the poor mechanical properties and thermal instability hinder its use for specific construction of 3D cultures and 3D printing. In this study, we present a microfluidic high-throughput approach for producing high-quality and uniform collagen microbeads without introducing any chemical modification. We achieved rapid and uniform collagen droplet fabrication with sizes spanning from 50 µm to 1200 µm in a production rate of up to 10000 droplets per minute. The resulting collagen microbeads can serve as numerous microbioreactors which are suspended in the culture medium without precipitation and are ideal for 3D cell growth. We demonstrated excellent cell compatibility, facilitating cell attachment and proliferation, as well as promoting extracellular vesicle secretion from collagen microbeads. This technology is facile and versatile for high throughput 3D cell culture, heterogeneous tissue modeling, and extracellular vesicle production, which is essential in drug delivery and drug screening.
Tetraquarks made of sufficiently unequal-mass heavy quarks are bound in QCD
Authors: Assi Benoît , Wagman Michael L. 
Published: November 2024

Tetraquarks, bound states composed of two quarks and two antiquarks, have been the subject of intense study but are challenging to understand from first principles. We apply variational and Green’s function Monte Carlo methods to compute tetraquark ground-state energies in potential nonrelativistic QCD using a wide range of color and spatial wave functions. We find no evidence for bound tetraquarks composed of equal-mass quarks and antiquarks. Conversely, we find clear evidence for the existence of bound tetraquarks for sufficiently unequal quark/antiquark mass ratios at all overall mass scales where our effective theory results are applicable. We predict the critical mass ratios for bound state formation and study tetraquark bound states’ spatial and color structure at leading order and next-to-leading order in potential nonrelativistic QCD.

Published by the American Physical Society
2024
Mapping the global regulatory terrain in digital banking: a longitudinal study across countries
Authors: Seyedjafarrangraz Fariba , De Fuentes Claudia , Zhang Michael 
Published: November 2024

Purpose
This study aims to comprehensively understand the regulatory landscape and digital transformation (DT) within the banking sector, anchored in the theory of national innovation systems.

Design/methodology/approach
Using insights from a comprehensive literature review, an innovative framework is introduced to categorize regulators and digital banking attributes across 88 countries. The study uses k-means clustering to analyze the digital banking and regulatory status of 88 countries, tracing their evolution over two distinct timeframes.

Findings
The cross-country analysis spanning 2014 and 2022 reveals compelling trends in regulatory rankings and digital banking across diverse nations. These findings shed light on the dynamic interplay between regulatory environments and technological innovation.

Originality/value
This research contributes to knowledge by establishing a robust framework for understanding regulator dynamics in digital banking across a wide spectrum of countries. It offers valuable insights for academia, practitioners and policymakers by elucidating the complex relationship between the regulatory landscape and DT, shaping discourse and implications in this field, and informing strategic decision-making and policy formulation in the global financial landscape.
Optimized design of energy absorption of aluminum foam filled CFRP thin-walled square tube based on agent model
Authors: Xiao Yong , Hu Honglin , Li Zhao , Long Hai , Wu Qianwen , Liu Yu 
Published: November 2024

PurposeAluminum foam-filled thin-walled unit structures have received much attention for their excellent energy absorption properties. To improve the energy absorption effect of car energy absorption box under axial compression, this paper optimizes the fiber lay-up sequence, fiber angle and aluminum foam density of aluminum foam filled carbon fiber reinforced plastic (CFRP) thin-walled square tubes.Design/methodology/approachDesign of sample points required to construct the proxy model using design of experiments (DOE) method, and the data sample points of different models are obtained through Abaqus simulation and test. A double high-precision proxy model with the maximum specific energy absorption (SEA) and the minimum initial peak crash force (PCF) as the evaluation index is constructed based on the response surface function method. The NSGA-II multi-objective genetic algorithm was used to optimize the design parameters and obtain the optimal solution for the Pareto front, and the results were verified by using the multi-objective optimization toolbox in design-expert.FindingsThe results show that the optimal solution to the multi-objective optimization problem with the inclusion of the lay-up sequence is ρ = 0.5g/cm3 for a fiber lay-up angle varying in the range ±15–90° and an aluminum foam density varying in the range 0.2g/cm3-0.5g/cm3, with a lay-up method of [±87°/±16°/±15°/±89°]. The two optimization methods correspond to SEA and PCF errors of 2.109% and 4.1828%, respectively. The optimized SEA value is 18.2 J/g and the PCF value is 18,230 N. The optimized design reduces the peak impact force and increases the specific energy absorption, which improves the energy absorption effect of thin-walled energy-absorbing boxes for automobiles.Originality/valueIn this paper, the impact resistance of CFRP thin-walled square tubes filled with aluminum foam is optimized. Based on numerical simulations and experiments to obtain the sample point data for constructing the dual-agent model, we investigate the effect of filling with different densities of aluminum foam under the simultaneous change of fiber lay-up angle and order on its mechanical properties in this process, and carry out the multi-objective optimization design with NSGA-II algorithm.
Exploring employable profiles of elite student athletes through fsQCA: unleashing the power of their soft skills
Authors: Vidal-Vilaplana Alberto , González-Serrano María Huertas , Calabuig-Moreno Ferran 
Published: November 2024

PurposeTo analyse the degree to which elite student athletes acquire different soft skills (resilience, creativity, proactivity and problem solving) and the role they play in their perceived employability.Design/methodology/approachThe study assessed 163 elite Spanish student athletes. A validated survey to measure perceived employability and the degree of acquisition of soft skills was employed. Fuzzy-set qualitative comparative analysis (fsQCA) was used to analyse the data.FindingsStudents and athletes perceived a high degree of development of these skills and employability. Six solutions accounting for 64% of the cases were identified for achieving high employability levels. Three profiles emphasised combinations of elevated resilience with either creativity or problem-solving skills. Education and competition levels differed depending on the skill combination. Identifying and promoting the transferability of student athletes’ sports skills to the labour market was important for enhancing their employability. Collaboration with academic institutions and increased awareness of social media can facilitate the successful integration of elite athletes into the labour market.Originality/valueThe development and analysis of soft skills in the context of sports provide a foundation for future research in the field of athlete employability. This paper provides important information for academic institutions, through a novel method in the field, on the development and transfer of student-athlete soft skills from sports to the labour market.
Flow, job performance and psychological wellbeing: the role of psychological ownership and trust in the ICT work place
Authors: Nguyen Duyen Le , Nguyen Thuy-Nhu Thi , Nguyen Tuan Manh 
Published: November 2024

Purpose
This paper, drawing on self-enhancement theory and from employee perspective, aims to develop and validate an integrative theoretical model that centers on the trust–psychological ownership (PO) link to investigate information and communications technology (ICT) employee work outcomes.

Design/methodology/approach
A cross-sectional survey with PLS-SEM analysis of 424 employees in ICT industry in Ho Chi Minh City, Vietnam, reports that all of 10 hypotheses are empirically supported.

Findings
PO is found to be an important driver of employee flow, job performance and psychological wellbeing. Moreover, it is posited that trust acts a moderator of the relationship between flow experience and job performance, and between job performance and psychological wellbeing.

Originality/value
To the best of the authors’ knowledge, this paper is among the first to affirm that trust in work environment serves as both an enabler for PO and a moderator for the relationship between flow experience–job performance as well as between job performance–psychological wellbeing path. The study also affirms that flow state plays a mediating role in the PO–job performance path, and that job performance acts as a mediator in the flow experience–psychological wellbeing sequence. Finally, new evidence expectedly highlights the positive impact of job performance, a short-term work outcome, on psychological wellbeing, a long-term work outcome.
Gender diversity in top management team and corporate social responsibility performance: examining the moderating nature of TMT international experience
Authors: Chiao Yu-Ching , Chang Yu-Chen , Hsu Yi-Jung , Lu Chang Hong , Chang Man-Ling 
Published: November 2024

Purpose
This study is based on the role congruity theory that examines the association between top management team (TMT) gender diversity and corporate social responsibility (CSR) performance.

Design/methodology/approach
This study uses data from the Taiwan Economic Journal database and the Market Observation Post System provided by the Taiwan Stock Exchange. The sample consists of 4,140 annual observations of Taiwanese-listed companies in the electronics industry from 2016–2020.

Findings
The results revealed that TMT gender diversity is positively associated with CSR performance, and TMT international experience strengthens the positive association between TMT gender diversity and CSR performance.

Practical implications
CSR is imperative. The TMT’s gender diversity aligns with current environmental trends and social expectations, driven for CSR implementation essential. This diverse configuration enables the TMTs to address corporate adaptability and maintain global competitiveness.

Originality/value
The findings contribute significantly to the literature on TMT gender diversity by extending the application of role congruity theory beyond individual to team-level contexts and across gender boundaries. By incorporating diverse capabilities such as international experience within TMTs, the authors identify key boundary conditions that foster CSR. This expansion not only aligns with practical realities but also opens new avenues for research into the dynamics of diverse management teams.
Circular economy adoption in MSMEs: unveiling enablers and barriers
Authors: Mishra Sarmistha , Sahoo Dukhabandhu , Mohapatra Souryabrata 
Published: November 2024

Purpose
The study aims to explore the enablers and barriers to the adoption of circular economy (CE) practices in micro, small and medium enterprises (MSMEs) and examine how these factors differ between developed and developing countries.

Design/methodology/approach
The research uses a systematic literature review (SLR) methodology to identify key enablers and barriers to CE adoption in MSMEs. The SLR process involved a detailed search and analysis of relevant academic articles from the Scopus and Web of Science databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure transparency.

Findings
The study identifies 19 enablers and 16 barriers to CE adoption in MSMEs. Technological upgrades are the key factor helping MSMEs successfully implement CE practices, while financial constraints are the main challenge they face, according to studies from both developed and developing countries.

Originality/value
This research contributes to the existing body of literature by not only identifying the primary factors that either support or impede the implementation of CE by MSMEs but also by classifying them according to developed and developing countries to provide policymakers and MSME stakeholders with valuable insights on enhancing the implementation of CE in both countries by taking into account the particular barriers and enablers faced by each group individually.
Driving circular economy adoption through top management commitment and organisational motivation: a quantitative study on small- and medium-sized enterprises
Authors: Al Rawashdeh Salam , Nasaj Mohamed , Ahmad Syed Zamberi 
Published: November 2024

Purpose
This paper aims to influence top management commitment and organisational motivation on small- and medium-sized enterprises’ (SMEs) adoption of circular economy practices in the United Arab Emirates.

Design/methodology/approach
Data were collected from 438 middle- and higher-level managers, owners, directors and chief executive officers of SMEs through an online survey. The theoretical model was tested using structural equation modelling.

Findings
The results reveal positive relationships between top management commitment, organisational motivation and circular economy adoption. Furthermore, organisational motivation partially mediates the impact of top management commitment on adoption, highlighting the importance of both direct and indirect influences of leadership.

Originality/value
This study contributes to the emerging discourse on circular economy adoption in emerging markets by offering insights for policymakers, industry stakeholders and SMEs aiming for sustainable growth amidst resource constraints.