ABSTRACT To encourage a more critical, evidence-based use of neuromarketing, this study conducts a systematic conceptual and empirical examination of neuromarketing myths. We propose an operational definition of neuromarketing myths and use a mixed-methods approach to identify 21 myths through a literature review and interviews with 13 experts. These myths are organised into four conceptual categories and examined in a large-scale quantitative survey (N = 639). The results reveal a high overall prevalence of neuromarketing myths in all stakeholder groups, with academics showing comparatively lower myth endorsement levels. Distinct patterns emerge across myth categories indicating that even experienced professionals remain susceptible to certain methodological and ethical misconceptions. The implications highlight the need for targeted myth-debunking and neuro-literacy interventions in marketing education and professional practice.

Background/Objectives: Growing evidence indicates that melatonin contributes to kidney development and function, while disruptions of fetal circadian signaling have been linked to congenital anomalies of the kidney and urinary tract (CAKUT). This study aimed to characterize the developmental and spatial expression patterns of melatonin receptors MTNR1A and MTNR1B in normal human fetal kidneys and in CAKUT phenotypes. Methods: This study analyzed 40 human fetal kidney specimens, including healthy controls and CAKUT cases (horseshoe kidneys, duplex kidneys, and dysplastic kidneys), obtained from spontaneous abortions and pregnancy terminations. Samples were classified into developmental phases Ph2–Ph4 according to established morphological criteria. Immunofluorescence staining was used to visualize MTNR1A and MTNR1B expression. Quantitative analysis was performed using ImageJ, measuring the fluorescence area percentage. Statistical comparisons were conducted using a two-way ANOVA. Results: In control kidneys, MTNR1A expression was predominantly observed in glomeruli and interstitial cells and showed a descending trend across developmental stages, whereas MTNR1B was localized to glomeruli and strongly to the apical membranes of tubules, particularly distal tubules, without substantial developmental variation. CAKUT phenotypes exhibited higher expression of both receptors compared to controls. Significant phase-dependent differences in MTNR1A expression were observed in horseshoe, duplex, and dysplastic kidneys. MTNR1B expression decreased across developmental stages in dysplastic kidneys and differed significantly between Ph3 and Ph4 in duplex kidneys. At Ph3, duplex kidneys showed the highest MTNR1B expression. Conclusions: Altered developmental expression patterns of MTNR1A and MTNR1B in CAKUT suggest an association between melatonin signaling and abnormal human kidney development.

Background: The clinical course of COVID-19 is highly variable, ranging from asymptomatic infection to critical illness with hyperinflammation and multiorgan failure. Oxidative stress plays a central role in COVID-19 pathogenesis, and genetic polymorphisms in glutathione S-transferase (GST) enzymes, particularly GSTM1 and GSTT1 null genotypes, may impair antioxidant defense and exacerbate inflammatory responses. This study aimed to investigate the association of GSTM1 and GSTT1 null genotypes with both disease severity and serum cytokine levels in hospitalized COVID-19 patients. Methods: This cross-sectional study enrolled 137 COVID-19 patients hospitalized during the second pandemic wave (July–September 2020). Patients were stratified into mild (n = 67) and severe (n = 70) groups based on clinical criteria. GSTM1 and GSTT1 polymorphisms were determined by multiplex polymerase chain reaction. Serum levels of 13 cytokines were measured using flow cytometry. Logistic regression analyzed genotype associations with disease severity, and multivariate linear regression assessed relationships between null genotypes and pro-inflammatory cytokine levels (IL-6, TNF-α, IL-17A, IFN-γ), adjusted for age, sex, hypertension, and diabetes. Results: The GSTT1 null genotype was significantly associated with severe COVID-19 (adjusted OR = 2.56, 95% CI: 1.08–6.07, p = 0.032). Severe patients exhibited significantly elevated levels of IL-6 (75.6% increase, p = 0.008), TNF-α (69.4% increase, p = 0.005), IL-17A (54.4% increase, p = 0.016), and IFN-γ (10.1% increase, p = 0.021). Both GSTM1 and GSTT1 null genotypes were associated with higher levels of these cytokines, with stronger effects observed for GSTT1 null. In multivariate analysis, GSTT1 null independently predicted elevated IL-6 (β = 52.6, p = 0.003), TNF-α (β = 13.8, p = 0.002), IL-17A (β = 2.4, p = 0.001), and IFN-γ (β = 56.4, p = 0.012). The combined both null genotype showed the strongest associations but was limited by small sample size (n = 10) and should be interpreted with caution. Conclusions: The GSTT1 null genotype is associated with severe COVID-19 and appears to be associated with heightened pro-inflammatory cytokine responses, particularly IL-6, TNF-α, IL-17A, and IFN-γ. These findings suggest a potential role for genetic impairment of antioxidant defense may contribute to hyperinflammation in COVID-19 hyperinflammation, although validation in larger cohorts is needed.

We sought to investigate the inter- and intra-country variation in paediatric heart transplantation (HTx) and mechanical circulatory support (MCS) availability and practice in Europe. Data was obtained through a survey circulated to paediatric transplant cardiologists identified through the Association of European Paediatric and Congenital Cardiology between November 2022 and March 2023. Twenty-eight respondents from twenty-eight European countries completed the survey. Twenty-four (86%) had paediatric and 25 (89%) had adult congenital HTx services. National paediatric HTx centre density ranged from 0.00 to 5.35 per 10 million inhabitants. Eighteen (64%) countries followed either Eurotransplant or Scandiatransplant protocols for organ allocation and 59% of the surveyed countries had low HTx volumes (< 4 paediatric HTx annually), based on the self-reported numbers. A ventricular assist device (VAD) programme was operational in 22 (79%) countries. In only 9 countries (38%), there were dedicated resources for HTx as part of the hospital budget; however, a vast majority (77%) reported that families suffered no cost when a VAD was utilised. Twenty-one countries (78%) reported limited intensive care unit beds and 14 (54%) reported that HTx impacted on congenital heart surgery cases. Only 12 of 27 countries (44%) had a standardised national protocol for post-HTx care. There was no correlation between paediatric HTx centre density, population or GDP per capita. Conclusion: There is a high degree of variation both within and between the surveyed European countries with regard to paediatric HTx centre density, VAD availability, listing protocols, and post-HTx management. Multiple factors contribute to this heterogeneity, which makes standardisation of HTx listing and VAD criteria challenging. Increased cross-national collaborative efforts between European countries may strengthen both HTx and MCS availability and outcomes, especially in regions with several smaller neighbouring countries. What is Known: • The care of paediatric heart transplant (HTx) and mechanical support (MCS) patients varies across Europe. What is New: • This paper elucidates the differences in transplant service organisation and the care of transplant and MCS patients in twenty-eight European countries. • These findings could potentially encourage broader open dialogue and facilitate collaboration across European paediatric HTx centres with development of standardised listing criteria, improved collective European registry data and creation of standards for screening post-HTx patients. What is Known: • The care of paediatric heart transplant (HTx) and mechanical support (MCS) patients varies across Europe. What is New: • This paper elucidates the differences in transplant service organisation and the care of transplant and MCS patients in twenty-eight European countries. • These findings could potentially encourage broader open dialogue and facilitate collaboration across European paediatric HTx centres with development of standardised listing criteria, improved collective European registry data and creation of standards for screening post-HTx patients.

Digital transformation (DT) is widely recognised as a strategic imperative for organisations seeking to sustain competitiveness in increasingly digitalised environments. Despite extensive research, empirical evidence on how digital transformation translates into financial and non-financial performance remains inconclusive. This study addresses this gap by proposing and empirically testing a model that links digital maturity to organisational performance through internal process efficiency as a process-based mediating mechanism. The study draws on survey data from 300 managers in Croatian enterprises across multiple industries and tests the proposed model using structural equation modelling (SEM) to examine both direct and mediated relationships. The results show that both managerial and technological dimensions of digital maturity are positively associated with internal process efficiency, which in turn enhances financial and non-financial performance. The mediating role of internal process efficiency has been confirmed, particularly in contexts where strategic readiness alone does not translate into operational outcomes. The findings indicate that digital maturity should not be approached only as a technological upgrade, but as an organisational transformation that requires integrating strategic intent, technological capabilities, and internal process redesign. The proposed model helps decision-makers align digital investments with process optimisation to improve organisational performance. This study advances the literature by introducing a two-dimensional operationalisation of digital maturity and empirically validating the mediating role of internal process efficiency in a transitional economy context. The findings provide novel empirical evidence on this mechanism within a European transitional economy.

Cyber threat intelligence (CTI) analysts must answer complex questions over large collections of narrative security reports. Retrieval-augmented generation (RAG) systems help language models access external knowledge, but traditional vector retrieval often struggles with queries that require reasoning over relationships between entities such as threat actors, malware, and vulnerabilities. This limitation arises because relevant evidence is often distributed across multiple text fragments and documents. Knowledge graphs address this challenge by enabling structured multi-hop reasoning through explicit representations of entities and relationships. However, multiple retrieval paradigms, including graph-based, agentic, and hybrid approaches, have emerged with different assumptions and failure modes. It remains unclear how these approaches compare in realistic CTI settings and when graph grounding improves performance. We present a systematic evaluation of four RAG architectures for CTI analysis: standard vector retrieval, graph-based retrieval over a CTI knowledge graph, an agentic variant that repairs failed graph queries, and a hybrid approach combining graph queries with text retrieval. We evaluate these systems on 3,300 CTI question-answer pairs spanning factual lookups, multi-hop relational queries, analyst-style synthesis questions, and unanswerable cases. Results show that graph grounding improves performance on structured factual queries. The hybrid graph-text approach improves answer quality by up to 35 percent on multi-hop questions compared to vector RAG, while maintaining more reliable performance than graph-only systems.

Electric power systems require accurate, scalable, distributed, and near real-time state estimation (SE) to support reliable monitoring and control under increasingly complex operating conditions. Limited monitoring capabilities can lead to inefficient operation and, in extreme cases, large-scale disturbances such as blackouts. To address these challenges, this paper proposes a vectorized Gaussian belief propagation (GBP) framework for phasor measurement unit-based SE, formulated over factor graphs and specifically designed to support distributed and near real-time monitoring. The proposed framework includes multivariate and fusion-based GBP formulations. The multivariate formulation jointly models related state variables and their measurement relationships, while the fusion-based formulation reduces factor graph complexity by combining multiple measurements associated with the same set of variables, resulting in a structure that more closely reflects the underlying electrical coupling of the power system. The resulting algorithms operate in a fully distributed manner at the bus level and achieve fast convergence and high estimation accuracy, often within a few iterations, as demonstrated by numerical results on systems ranging from 60 to 13659 buses, where the fusion-based formulation achieves single-digit millisecond iteration times on the largest test case.

Audio media – radio, podcasts, audiobooks – structures everyday life: we keep up, wind down, and share moments through long-form listening. Yet for people living with aphasia – a communication disability that affects audio comprehension – unsupported audio often means losing the thread and marring the experience. While accessibility advances have focused on print, web, and audiovisual content, audio-only remains unconsidered; oftentimes optimised for marketisation rather than sustained understanding. We report a three-week in-situ deployment of Re-Connect app, an audio media player which meets the people at the moment of comprehension difficulty. With ten adults living with aphasia, we show how people assemble personal repertoires of small, co-present communication cues that repair in the moment and support recall. Grounded in lived experience, we argue for personal, source-proximate scaffolds that help make long-form audio more understandable and enjoyable.

Advances in generative AI have given rise to a growing industry centred on interactive representations of deceased individuals. Within this emerging “digital afterlife industry”, interactive deadbots (IDBs) are presented as hyper-realistic avatars that use a person’s likeness, voice, and personal data to simulate conversational interactions with them. Rapidly moving from a niche experiment to a mainstream phenomenon, IDBs are poised to reshape the ethical, social, legal, and governance landscapes surrounding death, mourning, and digital legacy. This paper examines the disruptive nature of IDB technology through a multidisciplinary lens, using the concept of indeterminacy as its guiding analytical framework and a novel way to conceptualise the unstable field. Rather than advancing a unified understanding of indeterminacy, we introduce a structured analytical map and provisional taxonomy that distinguishes technological, social, philosophical, legal, and regulatory manifestations of indeterminacy in IDBs. By offering a tentative and necessarily selective map of this fluid and nascent field, we explore how indeterminacy and IDBs intersect. The paper examines how IDBs amplify existing forms of indeterminacy and how indeterminacy itself shapes the development and use of these systems across five domains: technological, social, philosophical, legal, and regulatory.

This response to the letter expands the discussion on the evolving demands of peer review for systematic reviews and meta-analyses. We emphasize that the main concern surrounding artificial intelligence is not its limited and disclosed use for language support, but undisclosed application and insufficient human verification, which may compromise citation accuracy, interpretation, and overall trustworthiness. We also argue that similarity reports should be interpreted contextually, particularly in evidence syntheses where standardized methodological language is unavoidable, and that low similarity does not necessarily exclude manuscript manipulation. Finally, we highlight reference verification as a central research-integrity challenge that should not rest on peer reviewers alone. Preserving the credibility of evidence synthesis requires shared responsibility across authors, reviewers, editors, and publishers.

Wood finger joints are widely used in both structural timber and high-quality furniture due to their ability to create long, continuous members from shorter pieces. The mechanical performance of these joints depends not only on the wood species but also on the geometry of the interlocking teeth and the quality of the adhesive bond. This study explores how the geometry of finger joints affects the tensile behavior and fracture characteristics of beech (Fagus sylvatica L.) and oak (Quercus robur L.). Specimens with varying tooth dimensions were tested using a 50 kN universal testing machine from Shimadzu. Key metrics such as ultimate tensile load, effective cross-sectional area, cohesive stress, energy required to cause failure, and fracture energy (Gc) at 0.5, 1.0, and 2.0 mm displacements were systematically measured. The results revealed that beech specimens achieved ultimate tensile loads up to 21,320 N and cohesive stress of 204 MPa, while oak reached 21,631 N with a cohesive stress of 239 MPa. Fracture energy (Gc) values ranged from 0.036 N/mm for beech to 0.051 N/mm for oak, depending on joint geometry. Results show that both the type of wood and the tooth design, including width and length, play a decisive role in joint performance. In general, longer teeth and larger bonded areas improved tensile capacity and increased resistance to fracture. These findings offer deeper insights into the fracture mechanics of hardwood finger joints and provide practical guidance for optimizing glued connections in furniture and structural timber. The collected data can also support accurate modeling, quality assurance, and numerical simulations in future studies.

Toxicity and harassment are widespread in the video-gaming context. Especially in competitive online multiplayer scenarios, gamers oftentimes send harmful messages to other players (teammates or opponents) whose consequences span from mild annoyance to withdrawal and depression. Abundant prior work tackled these problems, e.g., pointing out the negative effects of toxic interactions. However, few works proposed countermeasures specifically developed and tested on textual messages sent during a match -- i.e., when the"harassment"actually occurs. We posit that such a scarcity stems from the lack of high-quality datasets that can be used to devise"automated"detectors based on natural-language processing (NLP) and machine learning (ML), and which can -- ideally -- mitigate the harm of toxic comments during a gaming session. This work provides a foundation for addressing the problem of toxicity and harassment in video games. First, through a systematic literature review (n=1,039), we provide evidence that only few works proposed ML/NLP-based detectors of toxicity/harassment during live matches. Then, we partner-up with 8 expert League of Legend (LoL) players and create a fine-grained labelled dataset, L2DTnH, containing 1.4k toxic and 13.8k non-toxic messages exchanged during LoL matches. We use L2DTnH to develop a detector that we then empirically show outperforms general-purpose and state-of-the-art toxicity detectors reliant on NLP. To further demonstrate the practicality of our resources, we test our detector on game-related data beyond that included in L2DTnH; and we develop a Web-browser extension that flags toxic content in Webpages -- without querying third-party servers owned by AI companies. We publicly release all of our resources. Our contributions pave the way for more applied research devoted to fighting the spread of toxicity and harassment in video games.

Introduction: Fear of childbirth (FOC) is a common concern during pregnancy that can negatively affect women’s well-being and childbirth experiences. Understanding how different dimensions of FOC relate to one another before and after prenatal interventions may help optimize supportive care. The aim of this study was to examine correlations among specific domains of childbirth fear before and after participation in a prenatal childbirth preparation program. Methods: This prospective longitudinal study included 97 pregnant women with uncomplicated pregnancies who participated in a one-month prenatal childbirth preparation program between November 2024 and February 2025. The intervention consisted of theoretical education and physical exercise sessions, held twice a week. FOC was assessed before and 7 days after the intervention using the Childbirth Fear Questionnaire (CFQ). Spearman correlation coefficients were used to examine relationships among CFQ subscales. Results: Participants had a mean age of 30.5 ± 3.8 years and a mean gestational age of 32.5 ± 3.0 weeks at the time of study entry. Before the intervention, the total CFQ score was most strongly correlated with fear of medical interventions (p = 0.823). After the intervention, the strongest association shifted to fear of pain during vaginal birth (p = 0.859). Conclusion: Following participation in the prenatal childbirth preparation program, the pattern of associations among childbirth fears changed, with fear of medical interventions becoming less dominant and fear of pain during vaginal delivery emerging as a central concern. These findings suggest that prenatal interventions may influence not only the intensity but also the structure of childbirth-related fears, highlighting the importance of addressing multiple fear dimensions simultaneously.