bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of Specialized tRNA Expression in Early Human Brain Development
Authors: Bagi Alex L. , Lowe Todd M. , Salama Sofie R. 
Published: January 2025

AbstractTransfer RNAs (tRNAs) are traditionally known for their role in protein translation, yet recent discoveries highlight their broader functions in gene regulation, particularly through tRNA-derived small RNAs (tDRs). Studies have shown the singular importance of one unique ArgUCU tRNA isodecoder in mouse neural development, yet potential function(s) of tDRs derived from this and all other tRNAs remain largely unexplored in early human brain development. In this study, we employed cerebral cortical organoid models and AlkB-facilitated RNA methylation sequencing (ARM-seq) to profile tDRs across distinct stages of early human cerebral cortex development. Our analysis reveals dynamic expression patterns of diverse tDR groups derived from a wide range of isodecoders, with several distinct groups showing neural-specific expression. Computational analyses of these tDRs shows biased sequence motifs in over-represented tRNAs that are enriched with particular RNA modifications, giving initial clues to traits that change within the pool of tDRs during neural development. This expanded catalog of tDRs provides a framework for future studies on tRNA function in brain development and offers a deeper understanding of the complexity of tDR dynamics in neural differentiation.
Large Animal Epilepsy Model Platform: Kainic Acid Porcine Model of Mesial Temporal Lobe Epilepsy
Authors: Mivalt Filip , Maltais Daniela , Kim Inyong , Kim Jiwon , Began Patrik , Duque Lopez Andrea , Krakorova Veronika , Winter Bailey , Gregg Nick , Montonye Dan , Gow Christopher , Miller Kai , Van Gompel Jamie , Leyde Kent , Kremen Vaclav , Chang Su-youne , Worrell Gregory A. 
Published: January 2025

AbstractObjectiveTranslational animal models are essential for advancing neuromodulation therapies for drug-resistant epilepsy. Large animal epilepsy models that accommodate implantable neuromodulation devices designed for humans are needed to advance electrical brain stimulation and sensing applicaitons. We establish a kainic acid (KA) porcine model of mesial temporal lobe epilepsy (mTLE) for pre-clinical research and development of novel stimulating therapies.MethodsWe developed a platform integrating MRI-guided stereotactic electrode and chemotoxin delivery with intraoperative and long-term electrophysiology monitoring. Six domestic pigs underwent MRI-guided stereotactic implantation of bilateral hippocampal (HPC) and anterior nucleus of the thalamus (ANT) electrodes, followed by KA infusion into the right HPC. Local field potential (LFP) monitoring was conducted intraoperatively with a bedside workstation and chronically with an implantable neural sensing and recording (INSR) device designed for human use. Cresyl violet staining, commonly used to visualize neurons, was used to assess the neuropathophysiological effect of the KA infusion.ResultsKA infusion led to the emergence of interictal epileptiform discharges (IEDs), acute status epilepticus (SE), and spontaneous seizure activity. Acute IEDs and electrographic SE was observed in all cases, with two pigs euthanized due to uncontrolled seizures. Of the surviving four pigs, spontaneous IEDs were detected in all, and spontaneous seizures within 2 weeks were observed in three. Seizures in freely behaving animals varied from subclinical events to focal and generalized tonic-clonic seizures. Single pulse evoked response potentials (SPEP) measured in two pigs demonstrated functional connectivity between ANT and HPC circuits. Neuronal disorganization and loss, both major components of mTLE neuropathology were observed.SignificanceThe KA-induced porcine mTLE model supports the feasibility of testing human neuromodulation devices and provides a translational platform for studying therapeutic electrical sensing and stimulation. In particular, the model should be useful for advancing automated seizure diaries, closed-loop and adaptive therapies targeting Papez circuit nodes.
The Binary Cellular Biology of Human Growth: II. Calculating the Size of the Human Fetus from the Size of its Parts
Authors: Gu Zifan , Gupta Rashi , Cantonwine David E , McElrath Thomas F , Tiemeier Henning , Michaelson James Selib 
Published: January 2025

ABSTRACTAssessing and understanding theSizeof the human fetus provides essential information for the management of the health of the newborn and its mother, a quality that is commonly measured byFetal Ultrasound. Many equations for making such calculations have been considered, none of which have been entirely satisfactory. As we have shown in the previous paper in this series, a consideration of the formation of the body, in units of numbers of cells,N, an approach we callBinary Cellular Analysis, provides new quantitative tools for estimating theSizeandAgeof the fetus. These tools include a new mathematical basis for creating useful expressions,Binary Cellular Estimated Fetal Weight Equations, for calculating humanFetal WeightfromUltrasound Measurements. As we show here, the most promising of these expressions, theAbdominal Circumference Binary Cellular Estimated Fetal Weight Equation, performs better than other currently usedFetal Weight Equations, while also yielding up new methods for improving ultrasound size assessment. Web-based calculators (https://kidzgrowth.com) make these mathematical manipulations available for obstetric care.
Specification of a smart-analysis system of sound events for smart environments
Authors: Santiago Gabriela , Aguilar Jose 
Published: January 2025

PurposeIn this work, we proposed a smart-analysis system of sound events for smart/intelligent environments based on an autonomic cycle of data analysis tasks.Design/methodology/approachWe propose an autonomic cycle of data analysis tasks. An autonomic cycle of data analysis tasks is a set of data analysis tasks that supervise and control a process anonymously, which are based on knowledge models (of prediction, recognition, etc.), interacting with each other to reach a common goal. Each task has a different function in the cycle: observation of the process, or its analysis, or decision-making.FindingsThis work presents the autonomic cycle. With its components, this autonomic cycle detects sound information using a taxonomic model of the sound events to analyze them and give a recommendation about the context. The taxonomic model is a hierarchical pattern that considers different aspects to recognize the sound events. This work defines the architecture of this autonomic cycle, specifies its machine-learning-based analysis tasks and evaluates its capabilities of reasoning, adaptation and communication in case studies.Research limitations/implicationsIt is important to work in the future on the improvement of the accuracy of the system by implementing neural networks or more sophisticated techniques. To take the implemented autonomic cycle to a higher level, it could use parallel function management. The automation also needs improvement. In addition to that, future works are going to be directed not only to sound events but also to include emotion recognition and its relation with sound events happening simultaneously.Originality/valueThe main contributions of this paper are as follows: the detailed description of the intelligent sound analysis (ISA) autonomic cycle for the smart sound analysis of sound events (SAS-SE) in an intelligent environment (IE); the specification of the machine-learning-based analysis tasks of ISA for the smart sound analysis and the development of a case study that settles the use of the system in different IEs.
Linking paternalistic leadership and service behaviours through perceived support from supervisor and organisation: empirical evidence from the Pakistani healthcare sector
Authors: Hussain Muzammil , Luu Trong Tuan , Marjoribanks Timothy 
Published: January 2025

PurposeDrawing upon social exchange theory, this study aims to assess whether paternalistic leadership style (authoritarianism, benevolence and morality) influences employee in-role service behaviour and extra-role service behaviour, particularly patient-oriented organisational citizenship behaviour via a dual mediation mechanism, i.e. perceived supervisor support and perceived organisational support.Design/methodology/approachThe data were gathered from doctors and nurses working in Pakistan’s public, private and semi-government hospitals. We used SPSS and AMOS 27 to run structural equation modelling.FindingsResults revealed that authoritarianism was negatively associated with in-role service behaviour and patient-oriented organisational citizenship behaviour through perceived supervisor support and perceived organisational support. In contrast, benevolent and moral behaviours of leaders were positively associated with in-role service behaviour via perceived supervisor support and perceived organisational support. However, perceived supervisor support did not mediate the relations between paternalistic leadership dimensions and patient-oriented organisational citizenship behaviour.Originality/valueOur research advances the paternalistic leadership literature concerning paternalistic leadership and employees’ service behaviours through dual mediation mechanisms and in a relatively understudied sector and national context.
Developing a probabilistic model for evaluating the organisational safety climate factors in offsite manufacturing
Authors: Vithanage Sadith Chinthaka , Sing Michael C.P. , Davis Peter Rex , Newaz Tanvi 
Published: January 2025

PurposeOffsite manufacturing (OSM) is a modern construction technique that offers several advantages over traditional construction, including using less material to produce a similar product, lowering costs, increasing quality and enhancing environmental sustainability of the final product in several ways. However, there is evidence of increased safety related incidents at an OSM facility due to the varying nature of its organisational safety climate. Therefore, this study aims to ascertain the relationships between organisational safety climate factors and safety performance in an OSM context, with a view to developing better safety outcomes.Design/methodology/approachA Bayesian Network (BN) approach was adopted to uncover the probabilistic relationships among organisational safety climate factors. First, a literature review was conducted to develop a conceptual model, which was validated by industry experts. Second, a questionnaire survey with Australian OSM professionals was employed to quantify the BN model. Finally, a sensitivity analysis was performed to validate the BN model and identify critical factors.FindingsOwing to the influence of organisational safety climate dimensions, there is a 79% probability that Australian OSM facilities obtain “high” safety performance. Despite this result, improvements in management safety response, the balance between safety and production, supervisor safety expectations, credibility in training and accessibility to safety rules and procedures are critical to maintaining and improving this current outcome.Originality/valueThis study develops a probabilistic model determining relationships between organisational safety climate factors and safety performance, particularly in an OSM context. The proposed model facilitates safety managers’ comprehension of safety climate issues and provides decision-making support when implementing safety management strategies.
Big-data AI analytics in value-chain innovation and international marketing strategy: insights from SMEs in cultural and creative industries
Authors: Zong Zupan , Anwar Muhammad Azfar , Khan Sana , Asmi Fahad , Hussain Nazim 
Published: January 2025

Purpose Despite great consensus on the positive impact of big-data-driven artificial intelligence (AI) analytics (BDAI) on a firm’s performance, it still appears to be a black box mechanism through which small and medium-sized enterprises (SMEs) strengthen their dynamic competencies to innovate and expand their global footprint. To fill this theoretical and empirical gap we examine the relationship between BDAI affordances, digital marketing capabilities (DMCs), value-chain innovation and international market goals.Design/methodology/approach The study incorporates the dynamic capability view an extension of the resource-based view and the knowledge-based view to empirically examine the primary data collected from marketing managers and executives of SMEs in cultural and creative industries utilizing Structural Equation Modeling (SEM) analysis.Findings The study highlights the significant role of BDAI affordances such as intelligent process recommendations, customer intelligence and market intelligence on DMCs, where DMCs significantly affect value-chain innovation and international market strategy both directly and indirectly.Research limitations/implications The study minimizes the gap in identifying the BDAI affordances to drive innovation and international market strategy in the context of SMEs in cultural and creative industries. Marketing managers can incorporate these findings to enhance their digital capabilities for competitive advantages in international markets.Originality/value The study proposes a holistic framework of BDAI affordances for the strategic use of digital resources and knowledge to transform digital capabilities into new forms of value to expand in the international market. These insights are robust and grounded in findings provided by marketing practitioners.
Sentiments and sustainability: stakeholder perceptions of sustainable fashion on social media
Authors: Blazkova Tereza , Pedersen Esben Rahbek Gjerdrum , Andersen Kirsti Reitan Reitan 
Published: January 2025

PurposeThis study aims to deepen the understanding of what stakeholders talk about when it comes to sustainable fashion on social media and how. Sustainable fashion is a broad umbrella term, which can distract attention from the differences between the individual subtopics and the sentiments ascribed to them. However, little systematic research exists on how the stakeholder activity and dominant sentiments vary across different sustainable fashion topics.Design/methodology/approachThis study is based on a social media analysis of 19,179 tweets authored by 1,819 distinct stakeholders on Twitter (now “X”) from 2007 to 2022. A large language model, a type of artificial intelligence (AI) that focuses on understanding and generating human language, is used to conduct a sentiment analysis of six stakeholder groups and 81 keywords linked to sustainable fashion. Two case examples are used to highlight the differences in stakeholder perceptions of sustainable fashion.FindingsThe social media analysis demonstrates how subcategories of sustainable fashion significantly differ in terms of stakeholder interest, activity and sentiments. For instance, tweets on circular economy and relevant subcategories (closed loop, recycling, upcycling, etc.) are popular, whereas issues linked to environmental, social and governance (ESG) and due diligence receive little attention on social media. While sentiments toward sustainable fashion are in general positive, discussions on topics such as labor rights issues are consistently associated with negative sentiments across most stakeholder groups.Originality/valueThis study contributes to the literature by demonstrating how stakeholders and sentiments vary across different topics linked to sustainable fashion on social media, which has become one of the main channels for communicating sustainability content. The findings thereby shed new light on dominant stakeholder positions regarding a wide variety of sustainable fashion topics.
Carrying the load: a moderated mediation study exploring the link between perceived organizational support and burnout amongst management consultants
Authors: Bernard Dominik , McGuire David , Harte Patrick , Müller Patrick 
Published: January 2025

PurposeThis study investigates the relationship between perceived organizational support (POS), employee resilience and workload on burnout in the consulting sector, which is characterized by long working hours and high pressure.Design/methodology/approachThe proposed hypotheses were tested using data collected from a sample of 169 management consultants. The key constructs were examined using the PROCESS statistical package.FindingsThe findings indicate that POS has a positive effect on exhaustion, cynicism and professional inefficacy. This effect is partially mediated by employee resilience for all three dimensions. A significant moderation between workload and POS has been found for the cynicism dimension of burnout, suggesting that the positive effect of high POS is especially useful for consultants with high workloads (exceeding 60 working hours per week).Practical implicationsThese findings highlight the importance of making employees feel supported in high-pressure work environments, as this has both a direct effect on employees' mental health and an indirect effect by increasing resilience, which in turn reduces the risk of burnout.Originality/valueThe study addresses the paucity of research on the workloads of management consultants and how they navigate burnout. The findings show that both personal resources (in this case, resilience) and organizational resources (POS) have a favorable impact on preventing burnout.
ChatGPT in class: motivation, schadenfreude and student usage intentions
Authors: Hickman Thomas M. , Stoica Michael 
Published: January 2025

Purpose
Integrating social comparison and social identity theories, this study aims to examine students’ emotional and behavioral responses to the use of ChatGPT in academic settings, focusing on intrinsic motivation, dissonance, envy, schadenfreude and artificial intelligence (AI) usage intentions.

Design/methodology/approach
The research design consisted of two sequential survey-based studies with undergraduate business students. Study 1, analyzed with SmartPLS, measured students’ intrinsic motivation, cognitive engagement, dispositional envy, emotional dissonance and schadenfreude experienced in response to academic dishonesty related to ChatGPT. Study 2 explored the motivations behind students’ future use of AI tools, examining ethical considerations and emotional responses.

Findings
Study 1 determined that higher levels of cognitive engagement reduce dissonance and envy among highly motivated students. Nevertheless, driven by cognitive engagement, dissonance and envy, it was established that highly motivated students experience schadenfreude when others are caught misusing ChatGPT. In contrast, low-motivated students only feel schadenfreude as a product of dissonance and envy. The focus of Study 2 was on the adoption of ChatGPT. Results indicate that future usage is driven by ethical considerations for highly motivated students, whereas less dissonance is key for low-motivated students.

Originality/value
The study’s originality lies in its exploration of schadenfreude in the context of AI use among students, highlighting how cognitive engagement and motivation influence emotional responses. Drawing on social comparison and social identity theories, it sheds new light on the dynamics of academic integrity and the emotional landscape surrounding AI tools like ChatGPT, thus filling a research gap in understanding student behavior and perceptions in higher education.
The virtues of limits and environmental sustainability in healthcare
Authors: Symons Xavier 
Published: January 2025

AbstractThe spectre of human‐induced climate change has drawn attention to the need to discover new, environmentally sustainable approaches to healthcare. This article draws upon David McPherson's The Virtues of Limits (2021) to develop a virtue ethics for sustainability in healthcare. I explore how a virtuous appreciation of the value of healthcare resources can lead us to exercise stewardship in our use of those resources, whereas a failure to appreciate the value of resources can lead to irresponsible and unsustainable patterns of use. I close with some recommendations of how health systems might go about facilitating the cultivation of the virtues of sustainable health practice.
Association of prostate‐specific antigen density with prostate cancer mortality after a benign systematic prostate biopsy result
Authors: Pylväläinen Juho , Talala Kirsi , Raitanen Jani , Rannikko Antti , Auvinen Anssi 
Published: January 2025

ObjectiveTo assess the association between prostate‐specific antigen (PSA) density (PSAD) and prostate cancer mortality after a benign result on systematic transrectal ultrasonography (TRUS)‐guided prostate biopsy.Patients and MethodsThis retrospective study used data from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC) collected between 1996 and 2020. We identified men aged 55–71 years randomised to the screening arm with PSA ≥4.0 ng/mL and a benign systematic TRUS‐guided biopsy result. The cumulative prostate cancer mortality of men stratified by a PSAD cutoff of 0.15 ng/mL/cm3 was modelled with competing risk functions. The ability of PSAD, PSA, and base variables (age at biopsy, DRE result, socioeconomic status, 5α‐reductase inhibitor usage, family history, and Charlson Comorbidity Index (CCI)) to predict prostate cancer death was compared using c‐statistics and a likelihood ratio test.ResultsAfter excluding 10 men without PSA data within 2 years of the biopsy and 65 without prostate volume data, 2276 men were eligible for inclusion in the study. A total of 50 men died from prostate cancer and 1028 from other causes during a median (interquartile range) follow‐up of 17.4 (13.2–20.9) years. The cumulative prostate cancer mortality of men with PSAD <0.15 ng/mL/cm3 was significantly lower than that of men with PSAD ≥0.15 ng/mL/cm3: 0.5% (95% confidence interval [CI] 0.2%–1.1%) vs 2.0% (95% CI 1.2%–3.1%) at 15 years (Grey's test, P = 0.001). The model consisting of PSAD, PSA and the base variables predicted prostate cancer mortality (c‐statistic 0.781) significantly better than either the base variables alone (c‐statistic 0.737; likelihood‐ratio test, P = 0.003) or the base variables and PSA (c‐statistic 0.765; likelihood‐ratio test, P = 0.039).ConclusionProstate cancer mortality after a benign systematic TRUS‐guided biopsy is low. In these patients, PSAD predicts prostate cancer mortality and provides additional value to other clinical variables. PSAD‐based stratification can be used to guide follow‐up strategy.