bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generation of human iPSC-derived pancreatic organoids to study pancreas development and disease
Authors: Darrigrand Jean-Francois , Isaacson Abigail , Spagnoli Francesca M. 
Published: October 2024

AbstractThe pancreas has vital endocrine and exocrine functions that can be affected by life-threatening diseases such as diabetes and pancreatic cancer. While animal models have been essential for understanding pancreatic development and disease, they are limited by their low-throughput and major species-specific molecular and physiological differences. Generating 3D in vitro models, such as organoids, that are physiologically relevant is thus primordial for investigating pancreatic development and disease in the human context. However, producing human stem cell-derived pancreatic organoids with proper branched architecture and correct patterning of cell domains has remained challenging. Here, we successfully developed a protocol that efficiently and reproducibly generates such organoids from human induced pluripotent stem cells (hiPSCs) by optimising organoid culture format and media. Our differentiation protocol promotes acinar cell differentiation and generates organoids with branches patterned into central trunk and peripheral tip domains, without relying on animal-derived matrices for organoid culture. This platform opens the door to high-throughput investigations of human pancreas development in a system recapitulating the most important aspects of pancreatic tissue architecture. Lastly, we anticipate that this system will contribute to the partial replacement of animal models used to investigate diseases such as pancreatic cancer.
Fragmentation and Multithreading of Experience in the Default-Mode Network
Authors: Yazin Fahd , Majumdar Gargi , Bramley Neil , Hoffman Paul 
Published: October 2024

AbstractReliance on internal predictive models of the world is central to many theories of human cognition. Yet it is unknown whether humans acquired multiple separate internal models, each evolved for a specific domain, or maintain a globally unified representation. Using fMRI, we show that during naturalistic experiences (during movie watching or narrative listening), adult participants selectively engage three topographically distinct midline prefrontal cortical regions, for different forms of predictions. Regions responded selectively to abstract spatial, referential (social), and temporal domains during model updates implying separate representations for each. Prediction-error-driven neural transitions in these regions, indicative of model updates, preceded subjective belief changes in a domain-specific manner. We find these parallel top-down predictions are unified and selectively integrated with sensory streams in the Precuneus, shaping participants’ ongoing experience. Results generalized across sensory modalities and content, suggesting humans recruit abstract, modular predictive models for both vision and language. Our results highlight a key feature of human world modeling: fragmenting information into abstract domains before global integration.
The deubiquitinase Rpn11 functions as an allosteric ubiquitin sensor to promote substrate engagement by the 26S proteasome
Authors: Htet Zaw Min , Dong Ken C. , Martin Andreas 
Published: October 2024

SummaryThe 26S proteasome is the major compartmental protease in eukaryotic cells, responsible for the ATP-dependent turnover of obsolete, damaged, or misfolded proteins that are delivered for degradation through attached ubiquitin modifications. In addition to targeting substrates to the proteasome, ubiquitin was recently shown to promote degradation initiation by directly modulating the conformational switching of the proteasome, yet the underlying mechanisms are unknown. Here, we used biochemical, mutational, and single-molecule FRET-based approaches to show that the proteasomal deubiquitinase Rpn11 functions as an allosteric sensor and facilitates the early steps of degradation. After substrate recruitment to the proteasome, ubiquitin binding to Rpn11 interferes with conformation-specific interactions of the ubiquitin-receptor subunit Rpn10, thereby stabilizing the engagement-competent state of the proteasome and expediting substrate insertion into the ATPase motor for mechanical translocation, unfolding, and Rpn11-mediated deubiquitination. These findings explain how modifications with poly-ubiquitin chains or multiple mono-ubiquitins allosterically promote substrate degradation and allow up to four-fold faster turnover by the proteasome.
Mitochondrial ETF insufficiency drives neoplastic growth by selectively optimizing cancer bioenergetics
Authors: Papadopoli David , Palia Ranveer , Jovanovic Predrag , Tabariès Sébastien , Ciccolini Emma , Sabourin Valerie , Igelmann Sebastian , McLaughlan Shannon , Zhan Lesley , Kim HaEun , Chekkal Nabila , Szkop Krzysztof J. , Bertomeu Thierry , Zeng Jibin , Vassalakis Julia , Afzali Farzaneh , Mzoughi Slim , Guccione Ernesto , Tyers Mike , Avizonis Daina , Larsson Ola , Postovit Lynne-Marie , Djuranovic Sergej , Ursini-Siegel Josie , Siegel Peter M. , Pollak Michael , Topisirovic Ivan 
Published: October 2024

AbstractMitochondrial electron transport flavoprotein (ETF) insufficiency causes metabolic diseases known as a multiple acyl-CoA dehydrogenase deficiency (MADD). Although essential in muscle, we identified ETF dehydrogenase (ETFDH) as one of the most dispensable metabolic genes in neoplasia, and its expression is reduced across human cancers. ETF insufficiency caused by decreased ETFDH expression limits flexibility of OXPHOS fuel utilization but paradoxically increases cancer cell bioenergetics and accelerates neoplastic growth by retrograde activation of the mTORC1/BCL-6/4E-BP1 axis. Collectively, these findings reveal that while ETF insufficiency is rare and has detrimental effects in non-malignant tissues, it is common in neoplasia, where ETFDH downregulation leads to bioenergetic and signaling reprogramming that accelerate neoplastic growth.
ESG rating disagreements and stock price crash risk: can distraction, regional digital economy and corporate intelligence maturity play important roles?
Authors: Li Yiyuan 
Published: October 2024

PurposeESG issues are gaining increasing attention from investors, but the environmental, social and governance (ESG) rating disagreement caused by different standards of rating agencies misleads investors' investment decisions. This can lead to an increased risk of stock price crashes, causing turbulence in the financial markets and reducing investors' confidence. The paper investigates whether ESG rating disagreement of the current period increases stock price crash risk and the mechanism to mitigate this impact.Design/methodology/approachWith the sample of the listed companies of Shanghai and Shenzhen Stock Exchanges from 2010 to 2022 this paper examines the impact of ESG rating disagreement itself on stock price crash risk. Moreover, this paper examines the mechanisms by analyzing the moderating effect of distraction of investors; digital economy and corporate intelligence maturity.FindingsThis paper finds that ESG rating disagreement itself would amplify the stock price crash risk. When exploring the moderating effect of institutional investors' distraction, digital economic development level and corporate intelligence, the paper found that they would mitigate the impact of ESG rating disagreement on stock price crash risk. The relationship between ESG rating disagreement and stock price crash risk is more pronounced in the context of heavily-polluted, state-owned enterprises (SOEs) and enterprises with star analysts.Originality/valueCurrently, few articles discuss ESG rating disagreement, especially the impact of current ESG rating disagreement on stock price crash risk. This paper focuses on this topic and provides strategies to mitigate the impact of current ESG rating divergence on stock price crash risk.
Exploring market-wide herding behavior in the major stock markets of Latin America
Authors: Lobão Júlio , Almeida Benedita 
Published: October 2024

PurposeThis paper investigates market-wide herding behavior among investors in the stock markets of Brazil, Chile, Colombia and Mexico from January 2013 to December 2022.Design/methodology/approachWe analyze a survivor-bias-free dataset of daily stock returns, employing a measure reflecting the cross-sectional deviation of stock returns relative to market consensus.FindingsSignificant anti-herding is observed in Brazil and Mexico, while Chile and Colombia show results consistent with rational asset pricing models. The COVID-19 pandemic generally intensifies anti-herding trends. Additionally, significant asymmetries in herding/anti-herding effects are noted during different market trends and volatility levels. Furthermore, we identify the drivers of this phenomenon, revealing that extreme crude oil price movements are associated with more pronounced anti-herding, and herding/anti-herding effects appear synchronized across all four markets.Practical implicationsOur findings regarding synchronization in herding dynamics suggest challenges in realizing the desired benefits of international diversification in the region.Social implicationsThe significant cross-country effects indicate that herding dynamics may play a crucial role in precipitating regional financial crises.Originality/valueFor the first time, we examine various features of herding behavior in the sample markets, including the impact of the COVID-19 pandemic, psychological and economic drivers of the phenomenon and synchronization in herding dynamics among the four markets.
Exploring Savico’s journey: dynamic capabilities and Industry 4.0 integration in organisation–industry actor relationships
Authors: Nguyen Ngan Mai , Duarte Alonso Abel , Vu Oanh Thi Kim , Nguyen Trung Thanh , Akbari Mohammadreza 
Published: October 2024

PurposeThe purpose of the study is to enhance the extant empirical and conceptual understanding of Industry 4.0 (I4.0) adoption and its repercussions for an organisation operating in an emerging economy, considering the dynamic capabilities framework. The study investigates (1) the potential impact of the I4.0 phenomenon on relationships between organisations and industry actors, (2) the existing effects of I4.0 on these relationships and (3) the necessary measures for organisations to unlock the full potential of I4.0 in order to enhance and reinforce these relationships.Design/methodology/approachA qualitative method was used. Semi-structured, open-ended face-to-face and online interviews were conducted with 18 directors, managers and chief executive officers (CEOs) of Savico, a leading Vietnamese car dealership.FindingsThe analysis revealed various dimensions highlighting impacts on organisation–industry actor relationships. For instance, the “enhancing internal/external operations” dimension highlights the significance of benefitting the company’s close stakeholders through a centralised management system or more advanced functions, while the empowering-nimble outcomes dimension underlines the benefits of I4.0 in enabling performance-based choices and staff empowerment.Practical implicationsTechnological phenomena such as the I4.0 regime require constant adaptive strategies, including knowledge acquisition and talent development. Thus, the study has implications for industry stakeholders, including companies, educational institutions and government agencies.Originality/valueThe study’s key value lies in proposing a model that provides conceptual depth into organisation–industry actor relationships. Furthermore, both the analysis and the model can guide researchers in future attempts to examine dynamic capabilities among firms operating in emerging economies, with important practical and theoretical implications.
Understanding the evolution of engagement with brand posts on social media using agent-based models
Authors: Gurazada Pavankumar , Maity Moutusy 
Published: October 2024

Purpose
This paper aims to delineate the nature of the costs associated with the diffusion of brand posts. Since cost is an essential component of customer lifetime value, this research also aims to identify factors that impact consumer engagement (CE) with brand posts.

Design/methodology/approach
This study conceptualize marginal cost of CE as the ratio of a unit change in cost for a unit change in CE – this ratio is conceptualized for a paid brand post compared to an organic brand post. The authors present a theoretically grounded simulation method that analyzes the relative impact of several factors that influence CE with brand posts. By using an agent-based simulation model, the method presented in this paper helps explain the relative impact of four factors on CE with brand posts on social media.

Findings
The authors explain four factors that influence the diffusion of CE with a brand post – promotion-related (i.e. whether it is paid vs organic), network-related, user-related and active periods. The authors also show that the effectiveness of paid posts vs organic posts attributed to a better audience assembled by the seeding algorithms dissipates after the initial stages of diffusion. These findings indicate that paid posts are effective vs organic posts in large part due to higher exposure than due to the efficiency of the algorithms to assemble nodes that are likely to engage with the post.

Research limitations/implications
An agent-based model details the impact of several factors that influence the effectiveness of paid and organic posts and presents methods to analyze the impact of these factors that have implications for theory.

Practical implications
The authors address the difficulty in ascertaining the effectiveness of paid posts by proposing a metric – marginal cost of engagement, defined as the incremental cost incurred by the marketer in earning one additional unit of CE. Since the costs incurred on paid and organic posts differ only on variable components, the marginal cost of engagement presents a way to benchmark paid posts against organic posts, which is very useful for managers in ascertaining the amount to spend on paid posts on social media.

Originality/value
There is little prior research on the costs involved in the diffusion of brand posts on social media. Identifying specific factors that impact costs is valuable for theory and practice.
Does AI need guardrails?
Authors: Mulahuwaish Aos , El-Khoury Moufid , Qolomany Basheer , Bou Abdo Jacques , Zeadally Sherali 
Published: October 2024

Purpose
As the realm of artificial intelligence (AI) expands, its societal implications soar. Today, society actively debates its rollout – yet such discourse often permeates news articles and social media unobjectively and without rigorous peer review. The purpose of this paper is to discuss the most pressing concerns associated with AI development and deployment.

Design/methodology/approach
This paper proposes a tripartite framework as a strategic guide and guardrail for AI’s evolution.

Findings
This robust framework addresses challenges, mitigates potential risks and harnesses AI opportunities for our shared future.

Originality/value
A policy-techno-legal framework for understanding key AI challenges and foundations for building AI guardrails.
The value of augmented reality: exploring hedonic and utilitarian augmented reality experiences
Authors: tom Dieck M. Claudia , Krey Nina , Cranmer Eleanor 
Published: October 2024

PurposeThe current study explores two distinct augmented reality (AR) experiences (hedonic and utilitarian) to determine the drivers of satisfaction and word-of-mouth (WOM). Specifically, this research investigates how different AR characteristics (person–virtual environment (VE) interaction, novelty) impact reality congruence and immersion, which ultimately lead to satisfaction and WOM.Design/methodology/approachWe tested the proposed model using a US consumer sample (N = 401) by applying partial least squares structural equation modeling (PLS-SEM) to reveal differences across the AR experiences regarding the mediating effects of immersion and reality congruence. Furthermore, we administered PLS-SEM multigroup analysis to identify differences for hedonic and utilitarian AR experiences.FindingsThis study provides important insights into the use of AR to create value-driven consumer experiences and outcome behaviors. Interacting with the virtual environment (VE) enhances immersion for hedonic AR experiences while it leads to higher levels of reality congruence for utilitarian AR experiences. While established relationships such as novelty to immersion continue to be significant, new constructs such as person–VE interaction and reality congruence immerge as stronger influences.Originality/valueTo date, most studies have implemented apps such as IKEA Place and have considered value as one comprehensive construct. However, limited research has examined differences in hedonic and utilitarian AR experiences. The current findings enhance the understanding of utilizing value-driven consumer experiences within the AR context to achieve desirable outcome behaviors.
The future of tourism: interview with Peter Bishop about teaching the future
Authors: Postma Albert , Bishop Peter C. 
Published: October 2024

PurposeAs the Journal of Tourism Futures celebrates its tenth anniversary, Dr Albert Postma interviews Dr Peter Bishop, an expert on teaching the future. The interview was held on July 25, 2024.Design/methodology/approachA personal interview.FindingsThe interview provides insights into the importance of teaching the future, the evolution in teaching the future, competencies and skills that the teaching focuses on, challenges of teaching the future in the current era and the role of AI.Originality/valueBishop shares his expertise on the development of teaching the future, its key features and its challenges in the current era.
Application of a decision tree approach to predict energy consumption in lightweight buildings under subtropical climate
Authors: Zara Rafaela Benan , Moro Guilherme Natal , Martins Rodrigo dos Santos Veloso , Giglio Thalita Gorban Ferreira 
Published: October 2024

PurposeLightweight building systems have emerged as alternatives to reduce the high environmental impact of conventional masonry. However, in subtropical climates, the low thermal inertia of lightweight envelopes negatively affects energy performance. The purpose of this paper is to investigate the thermophysical parameters that influence heating and cooling energy consumption in lightweight residential buildings under subtropical climates and develop a model to predict these parameters using statistical and machine learning tools.Design/methodology/approachA database was created with computer simulation data on the energy performance of 2048 building conditions generated by factorial combination of 10 parameters. Sensitivity analysis was performed to identify which parameters contribute most to energy performance indicators. Subsequently, decision trees were created using a classification and regression tree (CART) algorithm to visualize parameters and improve energy performance indicators, particularly cooling energy consumption.FindingsLow thermal transmittance and ground contact are interesting strategies for low thermal capacity buildings. Furthermore, the findings showed that relying only on the most influential properties does not ensure good energy performance; rather, it is the adequate combination of envelope properties that leads to good energy efficiency. The tree developed by CART can be used as a guide to assist designers and researchers in the initial selection of building envelopes, demonstrating the impact of each choice on electrical energy consumption for indoor climate control.Originality/valueBy adopting a global approach to assess the thermal performance of lightweight buildings, this study makes a significant contribution to synthesizing the results of a complex and time-consuming methodology into a guide for optimizing envelope design decisions and directing efforts and resources toward efficient strategies.
Investor attention and market activity: evidence from green cryptocurrencies
Authors: Ahmed Mohamed Shaker , Helmi Mohamad Husam , Tiwari Aviral Kumar , Al-Maadid Alanoud 
Published: October 2024

Purpose
This paper aims to investigate the relationship between investor attention and market activity (return, volatility and volume) using a sample of 14 clean energy cryptocurrencies (hereafter green cryptocurrency), namely, Chia, Cardano, Stellar, Tron, Ripple, Nano, IOTA, EOS, Bitcoin Green, Alogrand, Hedara, Polkadot, FLOW and Tezos.

Design/methodology/approach
This paper use 26040 crypto-day observations and a range of econometric techniques, including Dynamic Granger causality, Panel vector autoregression (VAR), Impulse response function and the decomposition of forecast error variance.

Findings
Based on 26040 crypto-day observations, this paper finds a bidirectional Granger causal relationship between investor attention and all measures of market activity, namely, return, absolute volatility, squared volatility and volume. The panel VAR and impulse response function demonstrate that market activity in the green crypto ecosystem, especially volatility and volume, is considerably responsive to changes in investor attention proxied by Google search volume (hereafter Google search volume (GSV)). The findings also demonstrate a significant asymmetric effect of return and volume on investor attention since past negative shocks “or bad news” in return and volume are more likely to grab the investor’s attention. All in all, our study emphasizes the crucial role of investor attention in the green crypto ecosystem.

Originality/value
(i) The research is the first to shed light on investor attention in the green cryptocurrency market. (ii) The paper uses a wide range of green cryptocurrencies to offer a comprehensive picture of the green cryptocurrency ecosystem. (iii) This paper is the first to use the panel Granger causality to investigate investor attention in the cryptocurrency market which provides several advantages over the conventional Granger causality approach. (iv) This paper is the first to provide novel empirical evidence on the prevalent influence of investor attention in the green crypto market.