bluuebunny/crossref_metadata_2025 huggingface dataset:
Glucose, insulin, and brain health in the UK Biobank: A Mendelian randomisation study
Authors: Garfield Victoria , Fatih Nasri , Rentsch Christopher T. , Smeeth Liam , Bhaskaran Krishnan , Chaturvedi Nish
Published: February 2025

Previous research suggests that HbA1cand diabetes are unlikely to be causally related to brain health and dementia outcomes. With the availability of better genetic instruments for additional glycaemic-related markers (i.e., insulin resistance (IR), fasting glucose (FPG), fasting insulin (FI) and 2hr post-glucose (2hPG), there is scope to more thoroughly examine how diabetes-related mechanisms are causally related to specific neuroimaging brain health outcomes, and/or all-cause dementia and/or Alzheimer’s dementia (AD). Data were from the UK Biobank (maxn= 349,288) with our sample consisting of an average age of 56 years (54% women). We constructed genetic instruments for 2hPG (15 variants), FPG (109 variants), FI (48 variants) and examined their relationships with neuroimaging outcomes such as total brain volume (TBV), hippocampal volume (HV), white matter hyperintensity volume (WMHV), Alzheimer’s dementia (AD) and all-cause dementia. We ran a two-sample MR and used conventional inverse-variance–weighted (IVW), weighted median estimator (WME), as well as MR-Egger intercept for horizontal pleiotropy. We found an association between 2hPG and higher risk of AD in both the IWV (OR: 1.49 [1.17, 1.90]) and WME (OR: 1.54 [1.12, 2.10]) models. However, we did not find that this association replicated in the International Genomics of Alzheimer’s Project (IGAP) data. We also observed an association between higher FI and higher TBV (β 15.25 (3.43, 27.07) in the IVW model. MR analyses of FPG and 2hPG with volumetric brain measures showed no evidence of a causal relationship with TBV, WMHV or hippocampal volume. These findings provide interesting results in how diabetes-related markers are causally related to brain health albeit the precise mechanisms through which postprandial hyperglycaemia increases AD risk and higher insulin preserves brain volumes warrant further research.
Self-reported and tracker-estimated physical activity outcomes in women with chronic pelvic pain disorders: A longitudinal evaluation of construct validity
Authors: Nagaldinne Tanisee , Shahnawaz Samia , Bakken Suzanne R , Elhadad Noemie , Horan Emma N , Ewing-Garber Carol , Rodrigues Jovita , Danieletto Matteo , Landell Kyle , Ensari Ipek
Published: February 2025

Objective

This study aims to evaluate the short form International Physical Activity Questionnaire (IPAQ) for use in women with chronic pelvic pain disorders (CPPDs) by comparing its scores against objectively-estimated physical activity (PA) outcomes. We investigated IPAQ components that are most consistently predictive of habitual PA behavior.

Method

The study sample included 966 weeks of data from 112 women with CPPDs who enrolled in a 14-week mHealth-based self-tracking study. Participants wore Fitbit devices and completed the IPAQ every week. We compared the IPAQ-reported minutes of walking, total activity, sitting, light-, moderate-, and vigorous intensity PA for concordance and divergence against their corresponding Fitbit estimates. We used linear mixed-effects regression models (MLMs) for all analyses and quantified the between-participant variance in the magnitude of agreement between the two methods via random slope terms. We further evaluated temporal consistency in scores using intraclass correlation coefficients (ICCs).

Results

IPAQ-reported walking minutes were strongly associated with Fitbit step counts (B = 3952.36; p = 0.006), minutes of moderate PA (B = 15.498; p = 0.0113), and moderate-to-vigorous PA (MVPA; B = 28.973; p = 0.007). IPAQ total activity minutes were associated with Fitbit minutes of vigorous PA (B = 15.183; p = 0.007) and MVPA (B = 25.658; p = 0.010). IPAQ moderate activity minutes were predictive of Fitbit vigorous PA minutes (B = 9.060; SE = 3.719; p = 0.0151). There was substantial between-individual variance in these point estimates based on the significant random-effect terms, and average weekly PA level was a significant moderator of the association between IPAQ-reported and Fitbit-estimated scores for these variables. IPAQ-reported sitting minutes were inversely associated with Fitbit step counts (B = - 3125.61; p = 0.004), and minutes of MVPA (B = -21.848; p = 0.007), vigorous AP (B = -10.854; p = 0.042), and moderate PA (B = -10.985; p = 0.004).

Conclusion

These findings provide support for using IPAQ-reported walking and total activity minutes to monitor several PA domains in women with CPPDs, given their concordance with several tracker-estimated PA outcomes. However, the item on “sitting time” may not be a suitable for assessing sedentary time.
Data-Driven Early Prediction of Cerebral Palsy Using AutoML and interpretable kinematic features
Authors: Segado Melanie , Prosser Laura , Duncan Andrea F. , Johnson Michelle J. , Kording Konrad P.
Published: February 2025

Early identification of cerebral palsy (CP) remains a major challenge due to the reliance on expert assessments that are time-intensive and not scalable. Consequently, a range of studies have aimed at using machine learning to predict CP scores based on motion tracking,e.g. from video data. These studies generally predict clinical scores which are a proxy for CP risk. However, clinicians do not REALLY want to estimate scores, they want to estimate the patients’ risk of developing clinical symptoms. Here we present a data-driven machine-learning (ML) pipeline that extracts movement features from infant video based motion tracking and estimates CP risk using AutoML. Using AutoSklearn, our framework minimizes risk of overfitting by abstracting away researcher-driver hyperparameter optimization. Trained on movement data from 3- to 4-month-old infants, our classifier predicts a highly indicative clinical score (General Movements Assessment [GMA]) with an ROC-AUC of 0.78 on a held-out test set, indicating that kinematic movement features capture clinically relevant variability. Without retraining, the same model predicts the risk of cerebral palsy outcomes at later clinical follow-ups with an ROC-AUC of 0.74, demonstrating that early motor representations generalize to long-term neurodevelopmental risk. We employ pre-registered lock-box validation to ensure rig-orous performance evaluation. This study highlights the potential of AutoML-powered movement analytics for neurodevelopmental screening, demonstrating that data-driven feature extraction from movement trajectories can provide an interpretable and scalable approach to early risk assessment. By integrating pre-trained vision transformers, AutoML-driven model selection, and rigorous validation protocols, this work advances the use of video-derived movement features for scalable, data-driven clinical assessment, demonstrating how computational methods based on readily available data like infant videos can enhance early risk detection in neurodevelopmental disorders.

CCS Concepts

Computing methodologies→Machine learning approaches;

Applied computing→Health informatics.

ACM Reference Format

Melanie Segado, Laura Prosser, Andrea F. Duncan, Michelle J. Johnson, and Konrad P. Kording.. Data-Driven Early Prediction of Cerebral Palsy Using AutoML and interpretable kinematic features. In. ACM, New York, NY, USA, 8 pages.
Unique neural signatures of childhood sexual abuse revisited
Authors: Brosch Katharina , Hammes Vincent , Usemann Paula , Stein Frederike , Zika Stephanie , Schrott Franziska , Thomas-Odenthal Florian , Teutenberg Lea , Meinert Susanne , Thiel Katharina , Flinkenflügel Kira , Schürmeyer Navid , Goltermann Janik , Leehr Elisabeth J. , Bonnekoh Linda M. , Grotegerd Dominik , Winter Nils , Hahn Tim , Straube Benjamin , Jamalabadi Hamidreza , Jansen Andreas , Krug Axel , Dannlowski Udo , Nenadić Igor , Dhamala Elvisha , Kircher Tilo , Alexander Nina
Published: February 2025

Childhood sexual abuse (CSA) constitutes a detrimental subtype of childhood maltreatment (CM) associated with high trauma load and adverse health outcomes. Previous studies indicate CSA-specific reductions in gray matter volume (GMV) and cortical thickness. It remains challenging to disentangle brain alterations associated with CSA from those related to trauma intensity or psychopathology. Here, we apply a novel approach, comparing individuals with CSA, non-sexual maltreatment, and a non-maltreated control group, to identify CSA-specific findings.

Drawing from a cohort ofn=2039 depressed and healthy men and women allowed us to match groups 1:1 for age, sex, depression diagnosis, and, for maltreated groups, trauma load. The Childhood Trauma Questionnaire was used to assess childhood maltreatment. Applying threshold-free cluster enhancement, we investigated GMV and cortical thickness inn=195 adults with CSA compared to non-sexually maltreated (nCSA,n=195) and non-maltreated (nCM,n=195) individuals.

CSAshowed larger GMV in the right cerebellum compared tonCSAbut not compared tonCM.CSAdisplayed larger cortical thickness encompassing the bilateral superior frontal gyri, pre- and postcentral gyri, supramarginal gyri, superior parietal cortices, precunei, and insulae, compared to bothnCSAandnCM.

This is the largest study to investigate CSA-specific effects on brain morphometry, applying matched group comparisons. These findings highlight distinct neural signatures of CSA, characterized by preserved cortical thickness in regions also affected by major depression, and larger cerebellar GMV compared to non-sexual types of maltreatment. These results underscore the importance of distinguishing between types of childhood maltreatment and considering confounding factors when assessing their neurobiological impacts.
Automatic Classification of EEG Signals, Based on Image Interpretation of Spatio-Temporal Information
Authors: Oxenberg Or , Fire Michael , Alpert Galit Fuhrmann
Published: February 2025

Abstract

Brain-Computer Interface (BCI) applications provide a direct way to map human brain activity onto the control of external devices, without a need for physical movements. These systems, crucial for medical applications and also useful for non-medical applications, predominantly use EEG signals recorded non-invasively, for system control, and require algorithms to translate signals into commands. Traditional BCI applications heavily depend on algorithms tailored to specific behavioral paradigms and on data collection using EEG systems with multiple channels. This complicates usability, comfort, and affordability. Moreover, the limited availability of extensive training datasets limits the development of robust models for classifiying collected data into behavioral intents. To address these challenges, we introduce an end-to-end EEG classification framework that employs a pre-trained Convolutional Neural Network (CNN) and a Transformer, initially designed for image processing, applied here for spatiotemporal representation of EEG data, and combined with a custom developed automated EEG channel selection algorithm to identify the most informative electrodes for the process, thus reducing data dimensionality, and easing subject comfort, along with improved classification performance of EEG data onto subject’s intent. We evaluated our model using two benchmark datasets, the EEGmmidb and the OpenMIIR. We achieved superior performance compared to existing state-of-the-art EEG classification methods, including the commonly used EEGnet. Our results indicate a classification accuracy improvement of 7% on OpenMIIR and 1% on EEGmmidb, reaching averages of 81% and 75%, respectively. Importantly, these improvements were obtained with fewer recording channels and less training data, demonstrating a framework that can support a more efficient approach to BCI tasks in terms of the amount of training data and the simplicity of the required hardware system needed for brain signals. This study not only advances the field of BCI but also suggests a scalable and more affordable framework for BCI applications.
A Bayesian Re-analysis of the Steroids to Reduce Systemic Inflammation after Infant Heart Surgery (STRESS) Trial
Authors: Hill Kevin D. , Koerner Jake , Hong Hwanhee , Li Jennifer S. , Hornik Christoph , Kannankeril Prince J. , Jacobs Jeffrey P. , Baldwin H. Scott , Jacobs Marshall L. , Graham Eric M. , Blasiole Brian , Vener David F. , Husain Adil S. , Kumar S. Ram , Benscoter Alexis , Wald Eric , Karamlou Tara , Van Bergen Andrew H , Overman David , Eghtesady Pirooz , Butts Ryan , Kim John S. , Scott John P. , Anderson Brett R. , Swartz Michael F. , O’Brien Sean M.
Published: February 2025

Background

Prophylactic steroids are often used to reduce the systemic inflammatory response to cardiopulmonary bypass in infants undergoing heart surgery. The STRESS trial found that the likelihood of a worse outcome did not differ between infants randomized to methylprednisolone (n=599) versus placebo (n=601) in a risk-adjusted primary analysis (adjusted odds ratio [OR], 0.86; 95% CI, 0.71 to 1.05; P=0.14). However, secondary analyses showed possible benefits with methylprednisolone. To ensure that a potentially efficacious therapy is not unnecessarily avoided, we re-analyzed the STRESS trial using Bayesian analytics to assess the probability of benefit.

Methods

Our Bayesian analysis used the original STRESS trial primary outcome measure, a hierarchically ranked composite of death, transplant, major complications and post-operative length of stay. We evaluated probability of benefit (OR<1) versus harm (OR>1) by comparing the posterior distribution of the OR assuming a neutral probability of benefit versus harm with weak prior belief strength (nearly non-informative prior distribution). Reference results were calculated under the vague prior distribution. To convey magnitude of effect we used model parameters to calculate a predicted risk of death, transplant or major complications for methylprednisolone and placebo. Analyses consisted of 10 Markov Chain Monte Carlo simulations, each consisting of 2000 iterations with a 1000 iteration burn-in to ensure proper posterior convergence. Sensitivity analyses evaluated pessimistic (5%-30% prior likelihood of benefit), neutral and optimistic (70%-95%) prior beliefs, and controlled strength of prior belief as weak (30% variance), moderate (15%) and strong (5%).

Results

In primary analysis, the posterior probability of benefit from methylprednisolone was 91% and probability of harm was 9%. Composite death or major complication occurred in 18.8% of trial subjects with an absolute risk difference of -2% (95% CI -3%, +1%) associated with methylprednisolone. Each of 9 sensitivity analyses demonstrated greater probability of benefit than harm in the methylprednisolone group with 8 of 9 demonstrating >80% probability of benefit and ≥1% absolute difference in risk of death, transplant or major complications.

Conclusion

Probability of benefit with prophylactic methylprednisolone is high and harm is unlikely. This more in-depth analysis of the data expands the initial clinical evaluation of methylprednisolone provided by the STRESS trial.
Expression ofmecAreduces the daptomycin susceptibility ofStaphylococcus aureus
Authors: Ledger Elizabeth V. K. , Recker Mario , Massey Ruth C.
Published: February 2025

Staphylococcus aureusis a leading cause of bacteraemia and infections caused by methicillin-resistant strains (MRSA) are especially challenging to treat. MRSA strains are resistant to front-line beta-lactams due to PBP2a, a low-affinity penicillin-binding protein encoded bymecA. Daptomycin is used to treat MRSA infections but is not always effective and is associated with high rates of morbidity and mortality. Understanding why daptomycin fails is crucial to devising strategies to improve treatment outcomes. Here, using a panel of clinical bacteraemia isolates, we show that MRSA strains are less susceptible to daptomycin than methicillin-susceptible (MSSA) strains. This difference in susceptibility was due tomecAand was independent of any changes in surface properties previously associated with altered daptomycin susceptibility. Instead, using amecAtransposon mutant, we found that a lack of this gene led to higher activity of the Agr quorum sensing system, resulting in an increased release of the phenol-soluble modulin toxins. Increased levels of these surfactant-like toxins prevented daptomycin from being inactivated by lipids released by the bacteria, leading to enhanced susceptibility to the antibiotic. Additionally, the clinical MRSA strains tested produced lower levels of toxins than the MSSA strains and inactivated daptomycin to a greater extent, explaining their reduced susceptibility. Expression ofmecAin clinical MSSA strains reduced toxin production, increasing daptomycin inactivation and thereby enhancing survival. Together, these results demonstrate thatmecAdoes not only affect beta-lactam susceptibility but also compromises the efficacy of the last resort antibiotic daptomycin.
TMEM145 is a key component in stereociliary link structures of outer hair cells
Authors: Roh Jae Won , Oh Kyung Seok , Lee Jiahn , Choi Yujin , Kim Soomin , Hong Ji Won , Kim Yelim , Lew Hogun , Jang Seung Hyun , Shin Hae-Sol , Ohk Jiyeon , Jung Hosung , Seo Kyoung Yul , Bok Jinwoong , Kim Chul Hoon , Gee Heon Yung
Published: February 2025

Outer hair cells (OHCs) in the cochlea contain specialized stereociliary structures essential for auditory function. These include horizontal top connectors (HTCs), linking adjacent stereocilia and tectorial membrane-attachment crowns (TM-ACs), anchoring the tallest stereocilia to the tectorial membrane. The known molecular components of these structures, such as stereocilin, otogelin, otogelin-like, and tubby, lack transmembrane domains, suggesting the existence of anchoring proteins. This study identified TMEM145, a transmembrane protein with a Golgi dynamics (GOLD) domain, as a crucial OHC stereocilia component. TMEM145 was expressed in both OHCs and spiral ganglion neurons, with specific localization to TM-ACs and HTCs in OHCs.Tmem145knockout (KO) mice exhibited profound hearing impairment at three weeks of age, with complete loss of distortion product otoacoustic emissions, indicating OHC dysfunction. Immunostaining and scanning electron microscopy revealed the absence of TM-ACs and HTCs inTmem145KO mice. In heterologous cell systems, TMEM145 interacted with stereocilin and tubby, facilitating their extracellular secretion. TMEM145 was undetectable instereocilinKO and tubby mutant mice, indicating interdependence among these proteins. These findings establish TMEM145 as an essential membrane protein for the structural integrity of OHC stereocilia, providing insights into the molecular architecture of cochlear hair cells and their role in auditory function.
Connectome architecture favours within-module diffusion and between-module routing
Authors: Seguin Caio , Puxeddu Maria Grazia , Faskowitz Joshua , Betzel Richard F. , Sporns Olaf
Published: February 2025

Connectomes are the structural scaffold for signalling within nervous systems. While many network models have been proposed to describe connectome communication, current approaches assume that every pair of neural elements communicates according to the same principle. Connectomes, however, are heterogeneous networks, comprising elements with varied topological and neurobiological makeups. In this paper, we investigate how connectome architecture may facilitate different signalling regimes depending on the topological embedding of communicating neural elements. Specifically, we test the hypothesis that the modular structure of brain networks fosters a dual mode of communication balancing diffusion—passive signal broadcasting—and routing—selective transmission via efficient paths. To this end, we introduce the relative diffusion score (RDS), a measure to quantify the proportional capacity for network communication via diffusion versus routing. We examined the interplay between RDS and connectome architecture in 6 organisms spanning a wide range of spatial resolutions and connectivity mapping techniques—from the complete nervous system of the larval fly to the inter-areal human connectome. Our analyses establish multiple lines of evidence suggesting that connectomes may be universally organised to support within-module diffusion and between-module routing. Using a series of rewiring null models, we untangle the contributions of connectome topology and geometry to the relationship between routing, diffusion and modular architecture. In conclusion, our work puts forth a hybrid conceptualisation of neural communication, in which diffusion contributes to functional segregation by concentrating information within localised clusters, while specialised signal routes enable fast, long-range and cross-system functional integration.
Dynamic nanoscale architecture of synaptic vesicle fusion in mouse hippocampal neurons
Authors: Kroll Jana , Kravčenko Uljana , Sadeghi Mohsen , Diebolder Christoph A. , Ivanov Lia , Lubas Małgorzata , Sprink Thiemo , Schacherl Magdalena , Kudryashev Mikhail , Rosenmund Christian
Published: February 2025

During neurotransmission, presynaptic action potentials trigger synaptic vesicle fusion with the plasma membrane within milliseconds. To visualize membrane dynamics before, during, and right after vesicle fusion at central synapses under near-native conditions, we developed an experimental strategy for time-resolvedin situcryo-electron tomography with millisecond temporal resolution. We coupled optogenetic stimulation with cryofixation and confirmed the stimulation-induced release of neurotransmitters via cryo-confocal microscopy of a fluorescent glutamate sensor. Our morphometric analysis of tomograms from stimulated and control synapses allowed us to characterize five states of vesicle fusion intermediates ranging from stalk formation to the formation, opening, and collapsing of a fusion pore. Based on these measurements, we generated a coarse-grained simulation of a synaptic vesicle approaching the active zone membrane. Both, our morphofunctional and computational analyses, support a model in which calcium-triggered fusion is initiated from synaptic vesicles in close proximity to the active zone membrane, whereby neither tight docking nor an induction of membrane curvature at the active zone are favorable. Numbers of filamentous tethers closely correlated to the distance between vesicle and membrane, but not to their respective fusion readiness, indicating that the formation of multiple tethers is required for synaptic vesicle recruitment preceding fusion.
Tissue damage-induced axon injury-associated responses in sensory neurons – requirements, prevention, and potential role in persistent post-surgical pain
Authors: Rau Kristofer K. , Harrison Benjamin J. , Venkat Gayathri , Petruska Sara E. , Taylor Bradley K. , Hill Caitlin E. , Petruska Jeffrey C.
Published: February 2025

Pain resulting from tissue damage, including surgical incision, is often only partially responsive to standard treatments focusing on inflammation, suggesting additional mechanisms are involved. Tissue damage leads to expression in dorsal root ganglion (DRG) sensory neurons of genes associated with axonal injury and regeneration, most notably activating transcription factor 3 (ATF3) and GAP-43. ATF3 expression is associated with sensitization of cellular physiology and enhanced amplitude/duration of a nociceptive reflex. It is unclear how tissue damage leads to these changes in the sensory neurons, but it could include direct damage to the tissue-innervating axons and inflammation-associated retrograde biochemical signalling. Using the CTM reflex to map innervation fields, we examined the necessity and sufficiency of incision, inflammation, and axonal conduction for induction of ATF3 in response to skin incision. Incision outside the innervation field, but close enough to induce inflammation inside the innervation field, was not sufficient to induce ATF3 expression in the field-innervating DRG. Incision inside the innervation field led to strong expression of ATF3. Anti-inflammatory treatments did not prevent this induction of ATF3. In rodent models of repeated injury - a major etiological factor for chronic pain - ATF3 expression was synergistically-increased and the threshold for paw-withdrawal to mechanical stimulation was significantly decreased for an extended duration. Together, these results suggest that actual damage to axons innervating the skin is both necessary and sufficient for induction of ATF3, expression of which appears additionally increased by repeated injury. Further, pre-treatment of the nerves innervating the incised skin with bupivacaine, a local anesthetic commonly used to reduce surgical pain, did not prevent induction of ATF3, indicating that conduction of action potentials is not necessary for induction of ATF3. We also determined that closure of incision with surgical glue significantly reduced incision-induced expression of GAP-43. Intriguingly, treatment with polyethylene glycol (PEG), known to enhance membrane integrity after injury among other effects, reduced incision-associated ATF3 expression and electrophysiological changes. These results suggest that pain resulting from tissue damage may arise from a mix of ATF3-/axonal-damage-associated mechanism as well as ATF3-independent inflammation-related mechanisms and therefore require a mix of approaches to achieve more complete control.
An artificial metal-free peroxidase designed using a ferritin cage
Authors: Tian Jiaxin , Maity Basudev , Furuta Tadaomi , Pan Tiezheng , Ueno Takafumi
Published: February 2025

Developing artificial enzymes is challenging because it requires precise design of active sites with well-arranged amino acid residues. Histidine-rich oligopeptides have been recently shown to exhibit peroxidase-mimetic activities, but their catalytic function relies on maintaining unique supramolecular structures. This work demonstrates the design of a specific array of histidine residues on the internal surface of the ferritin cage to function as an active center for catalysis. The crystal structures of the ferritin mutants revealed histidine-histidine interactions, forming well-defined histidine clusters (His-clusters). These mutants exhibit peroxidase-mimetic activities by oxidizing 3,3’,5, 5’-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide. Molecular dynamics simulations further highlight the co-localization of TMB and hydrogen peroxide at the histidine-rich clusters, indicating that the confined environment of the ferritin cage enhances their interactions. This study presents a simple yet effective approach to design cofactor-free artificial enzymes, paving the way for innovations in bioinspired catalysis.
Between facilitation and hindrance: linking CEO Machiavellianism, top management team collective organizational engagement and new ventures performance
Authors: Song Shanghao , Chen Xiaoxuan , Xu Xinfeng , Jiang Wendi , Wang Wenzhou , Shi Yunsheng
Published: February 2025

Purpose

Based on upper echelons theory, this paper aims to explore the mixed impacts of chief executive officer (CEO) Machiavellianism on new venture performance. At the same time, this paper tests the mediating and suppression effect of top management team (TMT) collective organizational engagement, and the moderating effect of entrepreneurial orientation.

Design/methodology/approach

The authors conducted a three-wave survey of a sample of 1,550 enterprises established within three years, finally retained the full sample of 216 companies (216 CEOs, 733 vice presidents) with complete responses in all surveys. By using SPSS 26.0 and Amos 26.0 software to conduct data analysis, the authors empirically tested the hypothesized relationships.

Findings

Regression results show that CEO Machiavellianism negatively affects new venture performance through TMT collective organizational engagement, whereas there is a direct positive relationship between CEO Machiavellianism and new venture performance when TMT collective organizational engagement is controlled for. In addition, entrepreneurial orientation plays a boundary role in this mechanism, which can weaken the negative effect of CEO Machiavellianism on TMT collective organizational engagement.

Originality/value

By expanding the application contexts of the upper echelons theory, this paper enriches the research on Machiavellianism in the organizational research and further clarified the simultaneous positive and negative effects of CEO Machiavellianism on new venture performance.
The influence of digital voice of customer on the resilience of supply chains in the renewable energy industry
Authors: Zaman Syed Imran , Gunasekaran Angappa , Khan Sharfuddin Ahmed , Dawood Hamza Muhammad
Published: February 2025

Purpose

This research examines the influence of the digital voice of consumers (DVoC) on the resilience of supply chains (SCR) within the renewable energy sector. The main goal is to identify and highlight the crucial aspects that enable the examination of this impact.

Design/methodology/approach

A comprehensive literature analysis was performed utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach to ascertain pertinent factors. This research utilizes a comprehensive methodology that merges interpretive structural modeling (ISM) with Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis to assess the discovered variables.

Findings

The study identified 16 factors that contribute to both DVoC and SCR. Key influential factors include top management support, collaboration, feedback influence and flexibility. These factors play a significant role in enhancing SCR by facilitating better adaptation and response to disruptions.

Research limitations/implications

The study is confined to the renewable energy sector and may lack generalizability to other businesses without additional validation. Subsequent studies ought to investigate the implementation of these findings across various industrial contexts to enhance comprehension of DVoC’s influence on SCR.

Originality/value

This study presents a new integrated framework for comprehending the function of DVoC in improving SCR. It presents significant practical consequences for stakeholders in the renewable energy sector, such as researchers, regulators, manufacturers and consumers, highlighting the necessity for a resilient and flexible supply chain.
A tailored framework for heritage and values identification in historic Alexandria: Cultural Mapping through Historic Urban Landscape conceptualisation
Authors: Teba Tarek , Hawash Hadir , Moustafa Ahmed H. , Gharib Nevin
Published: February 2025

Purpose

Heritage identification has been a challenging process in terms of capturing the holistic significance of a place, including its tangible, intangible and sociocultural dimensions. This problem is more evident in cities that face challenges of densification, housing demand and economically driven developments. The city of Alexandria in Egypt demonstrates an exemplary case in which societal and intangible values have not been adequately addressed as part of a broader marginalisation of heritage by societal, economic and political challenges. Acknowledging that participatory Cultural Mapping can inform heritage decision-making and encourage communities to create and re-create legacy through regenerative processes, this research investigates how to employ Cultural Mapping methodology in valuing local heritage in Alexandria.

Design/methodology/approach

Based on “Historic Urban Landscape” theorisation and a multi-method qualitative approach (i.e. desk review, literature analysis and semi-structured interviews), the article aims to build a tailored framework, utilising community-based mapping techniques for heritage identification in historic Alexandria. At later stages of this research, a framework is developed to inform the design of a localised toolkit for recognising social values.

Findings

This work is a beneficial starting point to inform and guide further mapping exercises that aim to elicit values from the local community and understand how residents value their heritage landscapes beyond the conventional approach. The study addresses critical challenges in the local context by utilising the Cultural Mapping methodology in conjunction with the Historic Urban Landscape lens. It frees heritage academic and public discourse from the prevalent perception concerned only with heritage's monumental dimensions.

Originality/value

The developed framework fills the gaps in the formal valuation process by (1) emphasising intangible values and the statement of significance as a critical step and negotiation milestone, (2) demonstrating inclusivity in terms of stakeholders’ perceptions and values and (3) providing a complementary valuation approach that addresses the multiplicity of values at different scales.
360 VR adoption intention in tourism: approach of protection motivation theory
Authors: Rahehagh Atena , Nazarova Dildora , Pallathadka Harikumar , Joshi Meeta , Aulakh Damanjeet , Prasad K.D.V.
Published: February 2025

Purpose

This study endeavors to comprehend the impact of perceived risks and coping strategies on tourists' inclination to participate in virtual tourism.

Design/methodology/approach

Employing a quantitative methodology and the protection motivation theory (PMT), an online survey was administered to 215 foreign tourists with an awareness of security concerns in Iran. The collected questionnaire data underwent statistical analysis using SPSS and structural equation modeling analysis via SmartPLS software.

Findings

The findings reveal that perceived severity and vulnerability exert a significant positive influence on the likelihood of embracing 360 VR. Additionally, the positive effect of perceived response efficacy in using 360 VR on adoption intention was confirmed. Notably, perceived self-efficacy in using 360 VR does not significantly affect adoption intention. Finally, the results showed that negative media coverage, unlike the mental image of the destination, has a positive effect on 360 VR adoption intention.

Practical implications

Extending PMT with 360 VR in tourism risk management allows for more effective risk communication. By immersing tourists in VR simulations, stakeholders can educate them about potential threats, empowering them to navigate risks confidently. This reduces anxiety and enhances travel satisfaction. Moreover, VR integration across sectors promotes a collaborative and proactive approach to risk mitigation within the tourism industry.

Originality/value

This research extends PMT to understand 360 VR adoption in tourism. It investigates how perceived security risks (severity and vulnerability), coping strategies (response efficacy and self-efficacy), negative media and destination image influence tourists' intention to use 360 VR experiences. The findings offer valuable insights for destination marketers in addressing perceived security risks and promoting 360 VR adoption.
Tourist experiences: a systematic literature review of computer vision technologies in smart destination visits
Authors: Panigrahy Abhijeet , Verma Anil
Published: February 2025

Purpose

This study investigates the applications of computer vision (CV) technology in the tourism sector to predict visitors' facial and emotion detection, augmented reality (AR) visitor engagements, destination crowd management and sustainable tourism practices.

Design/methodology/approach

This study employed a systematic literature review, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses methodology and bibliometric study on research articles related to the tourism sector. In total, 407 articles from the year, 2013 to 2024, all indexed in Scopus, were screened. However, only 150 relevant ones on CV in Tourism were selected based on the following criteria: academic journal publication, English language, empirical evidence provision and publication up to 2024.

Findings

The findings reveal a burgeoning interest in utilizing CV in tourism, highlighting its potential for crowd management and personalized experience. However, ethical concerns surrounding facial recognition and integration challenges need addressing. AR enhances engagement, but ethical and accessibility issues persist. Image processing aids sustainability efforts but requires precision and integration for effectiveness.

Originality/value

The study’s originality lies in its thorough examination of CV’s role in tourism, covering facial recognition, crowd insights, AR and image processing for sustainability. It addresses ethical concerns and proposes advancements for a more responsible and sustainable tourist experience, offering novel insights for industry development.
Carbon emission disclosure and earnings management: ethical behaviour or opportunism motivation?
Authors: Mayapada Arung Gihna , Lyu Junxiu
Published: February 2025

Purpose

This study aims to investigate the relationship between carbon emission disclosure and earnings management within Indonesian firms. The authors use the stakeholder theory and agency theory frameworks to explain this relationship.

Design/methodology/approach

Panel data of Indonesian listed firms between 2016 and 2021 are used in this study. Data are analysed using fixed effects with robust standard errors.

Findings

Firms disclosing carbon emission-related information exhibit less absolute discretionary accruals. This finding implies that these firms are less likely to engage in unethical financial reporting practices, such as earnings management. This finding is also confirmed through the robustness check and endogeneity tests.

Practical implications

The findings of this study can be used when formulating policy initiatives and regulations to promote carbon emission disclosure practices within Indonesian firms.

Originality/value

To the best of the authors’ knowledge, this study is the first to examine the effect of carbon emission disclosure in sustainability reports on earnings management amid the sustainability reporting requirement period. It provides empirical evidence that carbon emission disclosure is considered an ethical practice in an emerging country.
Material and energy co-optimization for additive manufacturing of scale-up prototypes based on multiple layers prediction
Authors: Gao Mingyu , Xu Jinghua , Liu Kunqian , Zhang Shuyou , Tan Jianrong
Published: February 2025

Purpose

The purpose of this paper is to verify the performance and function of the scale-up prototypes by predicting the material and energy consumption on the basis of dimension-reduced prototypes. Additive manufacturing (AM) costs determine carbon emissions in total life cycle, among which material and energy consumption are major components. Predicting material and energy consumption is fundamental to reducing costs.

Design/methodology/approach

This paper presents a material and energy co-optimization method for AM via multiple layers prediction (MLP). Material and energy consumption are predicted to reduce the AM costs. In particular, scalable, complex curved surface component is used to improve forecasting efficiency. Subsequently, the back pressure distribution is obtained by scale-up specimens, which can lay the foundation for the ergonomic conceptual design.

Findings

Taking evolutionary ergonomic product as an example, the relative gravity direction of backrest is calculated. The material and energy consumption are predicted with low deviation. Physical experiments were carried out to validate information. Digital and physical tests have revealed that material and energy co-optimization improves manufacturing efficiency.

Originality/value

The innovatively proposed MLP method predicts material and energy consumption of scale-up prototypes to reduce the costs. It is propitious to improve the carbon emission efficiency in life cycle of AM. The originality may be widely adopted alongside increasing environmental awareness.
A textometric analysis of Quality 4.0 research
Authors: El Manzani Younès , Belahouaoui Rida , Tajouri Oumayma
Published: February 2025

Purpose

This study aims to provide a comprehensive, textometric analysis of the evolving Quality 4.0 (Q4.0) research, identifying key themes, emerging trends and critical research gaps in the field.

Design/methodology/approach

A total of 129 peer-reviewed articles on Q4.0 were analyzed using IRAMUTEQ software. The textometric approach employed includes lexicographic analysis, descending hierarchical classification, factorial correspondence analysis and similarity analysis to uncover underlying patterns in the literature.

Findings

Three major clusters emerged from the analysis of Q4.0 research: (1) the digital transformation of quality management practices, (2) technological enablers of Q4.0 and (3) organizational implications of Q4.0 adoption. Key themes identified include the integration of Industry 4.0 technologies (e.g. IoT, AI and big data) into traditional quality management systems, the role of artificial intelligence in quality control and the challenges organizations face during Q4.0 implementation. This research also conceptualizes a comprehensive framework that outlines a strategic roadmap for Q4.0 adoption and integration, including the identification of antecedents and consequences of Q4.0 implementation. Additionally, the study proposes a measurement scale for assessing the dimensions of Q4.0.

Practical implications

The research proposes valuable implications for practitioners and organizations seeking to implement Q4.0 strategies as well as for researchers in the field of digital transformation and quality management. The proposed conceptual framework serves as a practical guide for effectively navigating Q4.0 implementation in diverse organizational contexts.

Originality/value

This study presents an innovative approach by applying textometric analysis to the field of Q4.0, offering an objective, data-driven perspective on the existing literature. It identifies significant gaps in research and proposes future avenues for investigation. As one of the first studies to develop a conceptual framework for Q4.0, including its antecedents, consequences and a measurement scale, this research provides a foundational contribution to the growing body of knowledge on Q4.0.
Artificial intelligence driven adaptive learning methods in sustainable tourism education
Authors: Neophytou Raphaela , Liasidou Sotiroula , Pipyros Kosmas , Christofi Anastasia
Published: February 2025

Purpose

The research’s purpose is to examine the incorporation of Artificial Intelligence (AI) within the context of sustainable tourism education, emphasizing its capacity to augment educational achievements and provide future practitioners with vital competencies.

Design/methodology/approach

Semi-structured interviews targeting academics in the tourism field were conducted.

Findings

The study results are indicative and suggest a compatible relationship between the benefits of integrating educational content on sustainable tourism and AI. Specifically, AI can equip students with a more analytical understanding of sustainability.

Originality/value

The study’s originality exists in the integration of AI as an innovative tool into the educational context of sustainable tourism, thereby providing students with valuable knowledge.
Global warming affects foraging efficiency of fish by influencing mutual interference
Authors: Augustyniak Mateusz , Preiszner Bálint , Kobak Jarosław , Czeglédi István , Kakareko Tomasz , Erős Tibor , Cuthbert Ross N. , Jermacz Łukasz
Published: February 2025

Predator–prey interactions underpin ecological dynamics from population to ecosystem scales, affecting population growth and influencing community stability. One of the classic methods to study these relationships is the functional response (FR) approach, measuring resource use across resource densities.

Global warming is known to strongly mediate consumer–resource interactions, but the relevance of prey and predator densities remains largely unknown. Elevated temperature could increase consumer energy expenditure, which needs to be compensated by greater foraging activity. However, such greater activity may concurrently result in a higher encounter rate with other consumers, which potentially affects their total pressure on resource populations because of synergistic or antagonistic effects among multiple predators.

We performed a laboratory experiment using three densities of a fish predator (pumpkinseed, Lepomis gibbosus) (one, two and four specimens), two temperatures (25 and 28°C) and six prey densities. Using the FR approach, we investigated the combined effects of elevated temperature and predator and prey density on the consumer's foraging efficiency.

We observed a reduced maximum feeding rate at the higher temperature for single predators. However, the foraging efficiency of predators in groups was negatively affected by antagonistic interactions between individuals and further mediated by the temperature. Specifically, we observed a general decrease in antagonistic interactions at elevated compared to the ambient water temperature for multiple predator groupings. Irrespective of temperature, antagonistic multiple predator effects increased with predator density and peaked unimodally at intermediate prey densities, indicating multiple dimensions of density‐dependence that interact to supersede the effects of warming.

This study shows that conspecific presence negatively affects the per capita performance of predators, but that this effect is dampened with increasing temperature. Their adaptive response to temperature consists of limited food intake and further reduced intraspecific interactions. Including intraspecific competition in study design may thus offer more realistic outcomes compared to widely used experiments with only single predator individuals, which could overestimate the effect of increasing temperature.