Search Results (18)

Background: Hyperlipidaemia is common and most patients can be managed with established oral therapies and lifestyle modifications. However, patients with complex high-risk lipid disorders require specialist input and access to novel therapies to achieve treatment targets. While new agents are progressing through late phase trials, the eligibility criteria of these studies may limit their applicability to real-world settings. Aim: Assessing the generalisability of novel lipid-lowering therapy (LLT) trials by mapping their eligibility criteria to a cohort of patients attending a specialist lipid clinic. Methods: An ethically approved study was conducted at a specialist clinic in St James’s Hospital, Dublin over 6 months, enrolling 370 patients. Demographics, clinical characteristics, lipid profiles, genetic testing results and LLT use were collected. A structured search of clinicaltrials.gov and euclinicaltrials.eu identified phase 3 pharmacological trials registered since 2018. Patient data were then mapped against trial eligibility criteria to estimate the proportion of clinic patients that would have been eligible for each study. Results: In total, 38 trials were identified, including 15 different novel LLTs. It was found that the percentage of the cohort (n = 370) that would have been eligible for these LLT trials ranged from 0% to 62.4%, with an average eligibility of 19% across the 38 trials. Further analysis of specific patient subgroups and corresponding trial categories was performed. Conclusions: The included novel LLTs trials are reasonably applicable to a specialist lipid clinic cohort, suggesting generalisability to a wider group of real-world patients seen in clinics. This study can help guide future trial design by aligning eligibility criteria more closely with real-world patient populations, ensuring safe and effective clinical practice. Full article

Aligning information technology (IT) workforce demands with educational assessments is essential for bridging skills gaps; yet, no prior corpus maps IT task reasoning to Programme for International Student Assessment (PISA) proficiency levels. This paper introduces a large language model (LLM)-powered framework aligning IT competencies with PISA 2022 and the OECD (Organisation for Economic Co-operation and Development) Learning Compass 2030, drawing on O*NET v30.2 (Occupational Information Network), ESCO (European Skills, Competences, Qualifications, and Occupations) v1.2.1, PISA descriptors and OECD definitions. The framework operates in two stages: Stage 1 aligns 562 IT task statements with minimum PISA 2022 proficiency levels via LLM annotation and cross-model validation; and Stage 2 extends this mapping to the OECD Learning Compass 2030 through the semantic clustering of task embeddings and a bidirectional gap analysis of 95 ESCO transversal skills. Using Gemini 2.5 Flash, 562 tasks are annotated with minimum PISA levels across Mathematical, Reading, and Science literacy (first stage). Annotation reliability is assessed through a five-model cross-validation against a blind human domain expert (treated as a reference benchmark, not a gold standard) on a stratified 100-task sample (17.8% of the corpus), with agreement ranging from fair (Gemini 2.5 Flash, κ = 0.29) to moderate (Claude Haiku 4.5, κ = 0.50; LLaMA 3.3 70B, κ = 0.44). A bias-correction sensitivity analysis confirms that distributional findings remain stable after accounting for the primary annotator’s systematic overestimation, and OLS-calibrated alignment against O*NET ability ratings provides directional plausibility support. Validated tasks are embedded and clustered into 25 technical profiles via K-Means, each classified against OECD dimensions. The framework is extended to 95 ESCO transversal skills in 24 clusters. Bidirectional analysis reveals that, while every PISA proficiency level is engaged by at least one transversal cluster, 33% of these clusters, covering creative, ethical, social–emotional, and dispositional competencies, fall entirely outside PISA’s cognitive scope. This boundary mapping identifies where the PISA-based alignment is valid and where complementary tools are required for a full readiness assessment. Full article

Recent advancements in AI have enabled autonomous agents to interact within complex environments, with deliberative BDI (Belief–Desire–Intention) agents standing out for their human-inspired reasoning capabilities. However, defining the initial beliefs that constitute an agent’s cognitive profile remains a significant challenge. This process often relies on manual approaches that limit scalability and validation. This study proposes the Personality–Role–Belief (P–R–B) Model for BDI agents, introducing a novel architecture for generating cognitive profiles applicable to domains such as social simulation and non-player characters (NPCs). The model translates Five-Factor Model (FFM) scores into specific social roles, assigning base beliefs to each. A key contribution is a weighting mechanism designed to resolve conflicts between beliefs when multiple roles coexist. Inspired by Cohen’s effect size conventions, this mechanism establishes an influence hierarchy that quantifies belief strength based on social roles. Consequently, this approach not only enables agents to exhibit coherent behavior consistent with their personality but also establishes a foundation for modeling ethical decision-making through role–trait alignment, thereby facilitating the creation of agents capable of navigating morally complex social contexts. Full article

Airport digital transformation is commonly approached through technological integration and data-driven optimization, yet such perspectives provide limited insight into system-level reasoning and governance. This paper introduces the cognitive airport paradigm (CAP) as a mathematically grounded framework that models the airport as a domain-specific cognitive digital twin within a complex aviation ecosystem. Methodologically, the study follows a conceptual–analytical and design-science research approach, combining system analysis, conceptual modeling, ontology engineering, and formal mathematical representation of cognitive transitions and governance constraints. CAP represents airport cognition as an explicit state space characterized by cognitive maturity, governance integrity, and semantic stability. Analytical reasoning, adaptive learning, and orchestration mechanisms are formalized through instrument dominance profiles and cognitive performance functionals, enabling analytical comparison of airport configurations and identification of cognitive regimes. The results include (i) a formalization of airports as cognitive digital twins with measurable cognitive and governance properties; (ii) quantitative indices such as the cognitive readiness index, governance integrity index, and ethical alignment coefficient supporting structured evaluation of airport cognitive maturity; and (iii) illustrative expert-based parameterizations and a geometric interpretation in a cognitive simplex demonstrating that governance-oriented orchestration stabilizes airport cognition under increasing system complexity. Airport development is interpreted as continuous cognitive evolution rather than discrete stages of digitalization. The paper further proposes a cognitive roadmap for guiding airport evolution through structured cognitive rebalancing. The framework contributes to the theoretical foundations of cognitive digital twins and is transferable to other safety-critical and institutionally governed socio-technical systems. Full article

Background: Ethical decision-making in medical care increasingly requires balancing clinical values, professional duties, and organizational reasoning. Understanding how healthcare professionals navigate moral dilemmas necessitates examining the philosophical orientations that shape their ethical judgments. Alongside traditional medical ethics, a business ethics perspective highlights organizational and managerial dimensions of healthcare, offering a more comprehensive understanding of ethical decision-making in modern clinical contexts. Aim: This study aims to examine how healthcare professionals reason about ethical dilemmas by mapping their moral orientations and decision-making patterns across five ethical frameworks-idealism, relativism, objectivism, legalism, and Machiavellianism-integrating both medical and business ethics perspectives. Methods: A cross-sectional study was conducted with 277 participants (medical doctors and students). Two validated instruments were used: the Attitudes Toward Business Ethics Questionnaire (ATBEQ) to assess moral orientations and the Clinical Ethical Dilemmas Questionnaire (Richeux & Duquéroy) to evaluate ethical decision patterns. Data were analyzed using correlation, multiple regression, and k-means cluster analyses. Results: Among the five orientations, Legalism negatively predicted “It depends” responses (i.e., higher Legalism scores were associated with fewer indecisive responses), indicating greater decisiveness in ethically ambiguous situations. Unexpected positive correlations were also found between traditionally opposing constructs-such as Ethical Relativism and Moral Objectivism-suggesting moral pluralism. The overall regression model was not statistically significant (R² = 0.04, p = 0.08). Cluster analysis identified four distinct ethical reasoning profiles: High Machiavellian Idealists, Pragmatic Relativists, Context-Sensitive Objectivists, and Ethical Purists. Conclusions: Abstract philosophical orientations showed limited predictive power for contextual ethical decision-making, highlighting the complex and multidimensional nature of moral reasoning in healthcare. Findings inform the design of context-sensitive ethics education programs that integrate philosophical reflection with case-based learning to strengthen ethical competence among medical professionals. Full article

Unrefined vegetable oils are an important source of bioactive compounds with beneficial effects on health. Therefore, confirming the biological identity of oils is important for ethical and economic reasons. In this study, a method was developed for discriminating vegetable oils based on the phenolic compounds profile obtained by ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS/MS). It was found that extra virgin olive oil has a cinnamic acid content of 2.2 mg/kg (mean value), a much higher value compared to other oils (not detected—0.4 mg/kg), thus being a representative phenolic marker for this oil. From the phenolic compounds profile of different vegetable oils, it can be stated that extra virgin olive oil has a specific phenolic content. However, walnut, sunflower, and corn oils have some similarities regarding the phenolic compounds content (for instance, ellagic acid) and, therefore, these oils can be used as adulterants of extra virgin olive oil. Data analysis, including principal component analysis, hierarchical cluster analysis, and partial least-squares discriminant analysis, demonstrated the discrimination of olive oils from other vegetable oils. Data analysis also allowed the discrimination and classification of olive oil samples adulterated with corn oil when the percentage of adulterant was 1%, with an accuracy of more than 90%. Full article

Background: Recurrent pregnancy loss (RPL) and recurrent implantation failure (RIF) are significant challenges in reproductive medicine. For both, embryonic aneuploidy is the leading etiological factor. Preimplantation genetic testing for aneuploidy (PGT-A) via trophectoderm biopsy is the current standard for embryo selection. However, it is limited by its invasiveness, potential for embryo damage, and diagnostic errors due to mosaicism. Rationale/Objectives: This review critically evaluates the emerging role of noninvasive PGT (niPGT). NiPGT analyzes cell-free DNA from spent blastocyst culture media, thus, it is a potential alternative for managing RPL and RIF. Hence, the primary objective is to determine whether current evidence supports niPGT as a reliable replacement for conventional biopsy-based PGT-A in these high-risk populations. Outcomes: The analysis reveals that niPGT offers significant theoretical advantages. These include complete non-invasiveness, enhanced embryo preservation, and high patient acceptability. However, its clinical application is hampered by substantial limitations. Key amongst them is the inconsistent and often suboptimal diagnostic accuracy (sensitivity 70–85%, specificity 88–92%) compared to biopsy. Other significant factors include the high rates of amplification failure (10–50%), vulnerability to maternal DNA contamination, as well as low DNA yield. Crucially, there is a definitive lack of robust, prospective randomized controlled trial (RCT) data demonstrating improved live birth rates or reduced miscarriage rates specifically in RPL and RIF cohorts. As such, niPGT is not yet ready to be a standalone clinical adoption in RPL and RIF cases. However, it may serve as a valuable adjunct for rescue scenarios following biopsy failure or for ethical reasons. Wider Implications: The integration of niPGT with artificial intelligence, time-lapse imaging, and multi-omics profiling underlies a promising future. However, its transition from a predominantly research tool to a clinical standard necessitates various critical undertakings. These include rigorous multicenter RCTs, standardizing international protocol, and tailoring validation for the RPL and RIF subgroups. This review highlights the need for cautious optimism, positing that evidence-based integration, rather than premature adoption, is essential to realizing niPGT’s full potential without compromising patient care in these complex fertility scenarios. Full article

This study examines the relationship between attitudes toward artificial intelligence (AI) and AI dependency among Ecuadorian university students. A cross-sectional design was used, applying two validated instruments: the Artificial Intelligence Dependence Scale (DAI) and the General Attitudes Toward Artificial Intelligence Scale (GAAIS), with a sample of 540 students. Structural equation modeling (SEM) assessed how both positive and negative attitudes predict dependency levels. Results indicate a moderate level of AI dependency and an ambivalent attitudinal profile. Both attitudinal dimensions significantly predicted dependency, suggesting dual-use behaviors shaped by perceived utility and ethical concerns. Urban students reported higher dependency and greater sensitivity to AI-related risks, highlighting digital inequalities. Although the SEM model showed adequate comparative fit (CFI = 0.976; TLI = 0.973), residual indicators (RMSEA = 0.075) suggest further refinement is needed. This study contributes to underexplored Latin American contexts and emphasizes the need for equity-driven digital literacy strategies in higher education. Findings support pedagogical frameworks promoting critical thinking, ethical reasoning, and responsible AI use. The study aligns with Sustainable Development Goals 4 (Quality Education) and 10 (Reduced Inequalities), reinforcing the importance of inclusive, learner-centered approaches to AI integration. Full article

Scientific dispute and scholarly debate have traditionally served as mechanisms for arbitrating between competing scientific categorizations. However, current AI technologies lack both the ethical framework and technical capabilities to handle the adversarial reasoning inherent in scientific discourse effectively. This creates a ‘categorization conundrum’ where new knowledge emerges from opaque black-box systems while simultaneously introducing unresolved vulnerabilities to errors and adversarial attacks. Our research addresses this challenge by examining how to preserve and enhance human dispute’s vital role in the creation, development, and resolution of knowledge categorization, supported by traceable AI assistance. Building on our previous work, which introduced GRAPHYP—a multiverse hypergraph representation of adversarial opinion profiles derived from multimodal web-based documentary traces—we present three key findings. First, we demonstrate that standardizing concepts and methods through ‘Dispute Learning’ not only expands the range of adversarial pathways in scientific categorization but also enables the identification of GRAPHYP model extensions. These extensions accommodate additional forms of human reasoning in adversarial contexts, guided by novel philosophical and methodological frameworks. Second, GRAPHYP’s support for human reasoning through graph-based visualization provides access to a broad spectrum of practical applications in decidable challenging categorizations, which we illustrate through selected case studies. Third, we introduce a hybrid analytical approach combining probabilistic and possibilistic methods, applicable to diverse classical research data types. We identify analytical by-products of GRAPHYP and examine their epistemological implications. Our discussion of standardized representations of documented adversarial uses highlights the enhanced value that structured dispute brings to elicit differential categorizations in the scientific discourse. Full article

Background: Due to environmental, health, and ethical concerns, more consumers are reducing their meat consumption or giving it up entirely. Plant protein is most often chosen as a sustainable source of protein. Still, recently, edible insects have been gaining popularity as a source of alternative protein with a better nutritional profile. However, there is no information on whether vegetarians can accept insects. Methods: An online survey was conducted with a sample of 790 vegetarians to address this gap. The findings of this survey are crucial in understanding the potential acceptance of insects in vegetarian diets. Results: We found that 13% of the respondents approve of using processed insect protein in vegetarian dishes. Moreover, 9% of the respondents declared that they had knowingly consumed insects before; of these, 42% of them found the taste of the insects to be neutral, 16% found it to be very good, and 25% found it to be good. The level of insect acceptance was influenced by the type of vegetarian diet and its duration of use. Furthermore, pesca-vegetarians and flexi-vegetarians were the most likely to eat insects for ecological reasons ($\overline{x}$ = 3.54 ± 0.74; $\overline{x}$ = 3.00 ± 0.67, respectively). Conclusions: These findings do not eliminate the possibility of using edible insects in vegetarian diets but support their partial acceptance. Full article

Fermented nut-based products, obtained after soaking and fermentation, are gaining increasing interest as animal food substitutes because of ethical, environmental and health reasons. In these products, Lactic Acid Bacteria (LAB) perform the fermentation, leading to matrix acidification and contributing to controlling spoilage and pathogenic microbiota. In this work, LAB strains isolated from an artisanal product and combined with a commercial strain were added as starter cultures during nut soaking to produce a cheese-like fermented plant-based product. Three different LAB consortia were used in challenge tests at laboratory scale against Listeria monocytogenes, Escherichia coli or Salmonella Enteritidis, inoculated in nuts at 5 log CFU/g, and monitored for pathogen survival and matrix acidification. The combination of Lactiplantibacillus plantarum 82 and Leuc. carnosum 4010 resulted in faster acidification (pH value < 4.4 after 18 h instead of 48 h) and the reduction of target pathogens; L. monocytogenes was already absent after seven days from production, and the counts of E. coli or S. Enteritidis were lower with respect to other samples. Thus, this microbial consortium was used for a pilot-scale production in which, beyond safety, the fermented plant-based product was also characterized for aroma profile and phenolic compounds, parameters that are known to be affected by LAB fermentation. The results showed an enhancement of the aroma profile, with an accumulation of molecules able to confer cheese-like notes (i.e., acetoin and diacetyl) and higher phenolic content, as well as the presence of compounds (i.e., phenyllactic acid and hydroxyphenyllactic acid) that could exert antimicrobial activity. This study allowed us to set up a guided fermentation for a cheese-like vegan product, guaranteeing safety and improving aromatic and functional features. Full article

Food authentication significantly impacts consumer health and the credibility of Food Business Operators (FBOs). As European regulations mandate the verification of food authenticity and supply chain integrity, competent authorities require access to innovative analytical methods to identify and prevent food fraud. This study utilizes the DNA metabarcoding approach on meat preparations, sampled during an official control activity. It assesses animal and plant composition by amplifying DNA fragments of the 12S rRNA and trnL (UAA) genes, respectively. The results not only confirmed the declared species but also revealed undeclared and unexpected taxa in products labelled as containing a single animal species and various unspecified plant species. Notable findings such as the presence of Murinae, Sus scrofa, Ovis aries, and Pisum sativum could raise public health concerns, compromise consumer choices made for ethical or religious reasons, and reflect the hygienic conditions of the processing plant. This study demonstrates that the DNA metabarcoding approach looks to be a promising support tool for official control authorities to ensure food authenticity and safety, and to develop risk profiles along the supply chain. Full article

For historical reasons, the vast majority of primary schools in the Republic of Ireland are under the patronage of the Catholic church. Patronage involves a number of responsibilities, including the provision of a Patron’s Programme. Traditionally in the form of Religious Education (RE), such programmes should satisfy the curricular requirement for religious/ethical education and act as an expression of school ethos. In order to meet this responsibility, the Irish Episcopal conference in 2015 published its first curriculum in Religious Education, which forms the basis for the Grow in Love programme for pupils from Junior Infants to Sixth Class in all Catholic primary schools. However, effective teaching and learning of RE is dependent on the ‘buy in’ of those teaching it. The religious beliefs, understandings, and practices of those teaching RE are influential in this regard. Drawing from the data of a large-scale, multi-phase study, this paper describes the religious identity and beliefs of first-year students entering an Initial Teacher Education programme in Ireland—in this case, the Bachelor of Education (BEd) degree—to qualify as primary-level teachers. It situates the data in the wider context of religious identity and beliefs in Ireland and goes on to explore how the religious profiles of these students fit with the required understanding, knowledge and ability to teach Religious Education in Catholic schools. Findings indicate that the majority of these students identify as Catholic and believe in God. For most, God is important in their lives. However, there is a complexity to these beliefs, with a significant number who do not know what to think. This paper concludes with a discussion of the implications of these findings for the teaching of Religious Education and for the patrons of Catholic schools. Full article

Personality types are related to trustworthy, reliable, and competent communication, especially when dealing with clients. Therefore, the purpose of this study was to investigate whether the Myers–Briggs (MBTI) indicator could be used to detect differences in the personality preferences of students at the Veterinary Faculty, University of Ljubljana (VS) compared to students at the Faculty of Criminal Justice and Security, University of Maribor (CJS). Our aim was to profile the two cohorts of students in Slovenia, to compare profiles of students from the social and natural sciences with similar personality traits, and to compare them with published results. CJS are considered well-established, well-studied, non-science ombudsman profiles of students in Slovenia for whom care and safety will play important roles in their future work, similar to VS. Views of people’s duties to animals and the implications for animal care, safety, and welfare are also very important, especially for VS. For this reason, we tested the ethical viewpoints of the two cohorts of students using an interactive web-based program. Our results show that both VS and CJS had different MBTI types, with ISTJ (Introversion, Sensing, Thinking, and Judging) preferences predominating, followed by INFJ (Introverted, Intuitive, Feeling, and Judging) in VS and ESTJ (Extraverted, Observant, Thinking, and Judging) in CJS. Between the two cohorts, the ratio between ISFJ and INFJ was statistically different. In the animal ethics study, the utilitarian viewpoint was most prevalent and statistically higher in VS compared to CJS, where the animal rights perspective was most prevalent. Compared to previous profile studies, some differences were found that could be related to the COVID-19 pandemic and/or the different generations of students. Overall, this study highlights the importance of personality traits for better communication, work, and animal research in veterinary science as well as criminal justice. Full article

Cardiovascular diseases remain a global challenge, and lipid-associated biomarkers can predict cardiovascular events. Extensive research on cardiovascular benefits of omega-3 polyunsaturated fatty acids (n3-PUFAs) is geared towards fish oil supplementation and fish-rich diets. Nevertheless, vegetarianism and veganism are becoming more popular across all segments of society, due to reasons as varied as personal, ethical and religious values, individual preferences and environment-related principles, amongst others. Due to the essentiality of PUFAs, plant sources of n3-PUFAs warrant further consideration. In this review, we have critically appraised the efficacy of plant-derived n3-PUFAs from foodstuffs and supplements upon lipid profile and selected cardiometabolic markers. Walnuts and flaxseed are the most common plant sources of n3-PUFAs, mainly alpha-linolenic acid (ALA), and feature the strongest scientific rationale for applicability into clinical practice. Furthermore, walnuts and flaxseed are sources of fibre, potassium, magnesium, and non-essential substances, including polyphenols and sterols, which in conjunction are known to ameliorate cardiovascular metabolism. ALA levels in rapeseed and soybean oils are only slight when compared to flaxseed oil. Spirulina and Chlorella, biomasses of cyanobacteria and green algae, are important sources of n3-PUFAs; however, their benefits upon cardiometabolic markers are plausibly driven by their antioxidant potential combined with their n3-PUFA content. In humans, ALA is not sufficiently bioconverted into eicosapentaenoic and docosahexaenoic acids. However, evidence suggests that plant sources of ALA are associated with favourable cardiometabolic status. ALA supplementation, or increased consumption of ALA-rich foodstuffs, combined with reduced omega-6 (n6) PUFAs intake, could improve the n3/n6 ratio and improve cardiometabolic and lipid profile. Full article