Search Results (53,452)

Thoracic aortopathies, including aneurysm and dissection, are complex vascular disorders characterized by structural alterations of the aortic wall that disrupt normal haemodynamics. Altered shear stress, turbulent flow, and endothelial dysfunction promote thrombus formation and modulate systemic hemostasis via platelet activation and the von Willebrand factor–ADAMTS13 axis. The Total Thrombus-Formation Analysis System (T-TAS) is a microfluidic, flow-dependent assay that quantitatively evaluates thrombus formation under physiological shear conditions. Although studied in various cardiovascular contexts, its application in aortopathies remains largely unexplored, and no prospective studies have validated its clinical utility. Integrating T-TAS with computational haemodynamic approaches, such as two-way fluid–structure interaction simulations, enables assessment of the interplay between blood flow, vessel wall mechanics, pulse wave propagation, and local shear patterns. Patient-specific modelling, including individualized flow profiles, pressure distributions, and wall properties, may enhance mechanistic insights. Genetic variants in Fibrillin-1 gene (FBN1), Transforming Growth Factor Beta Receptor 1/2 (TGFBR1/2), Actin Alpha 2 (ACTA 2), and Myosin Heavy Chain 11 (MYH11) further contribute to structural vascular heterogeneity and diverse systemic haemostatic phenotypes, highlighting the need for personalized assessment. T-TAS should currently be considered an exploratory research tool rather than a validated diagnostic or prognostic method. This narrative review proposes a hypothesis-generating framework integrating structural, haemodynamic, molecular, and functional perspectives. Combining flow-based thrombosis assays with advanced modelling may inform future translational studies, improve mechanistic understanding of thrombus formation, and support personalized risk stratification and management in patients with thoracic aortopathies. Full article

Introduction: Oral squamous cell carcinoma (OSCC) is a frequent head and neck malignancy with high morbidity and mortality. Locoregional recurrence is the main determinant of long-term prognosis, yet reliable predictive models remain limited. This study aimed to identify clinicopathological predictors of recurrence and to develop a nomogram-based recurrence risk score (RRS) for patient stratification. Materials and Methods: A retrospective study was conducted including 332 patients with histologically confirmed OSCC treated surgically between 2012 and 2022. Clinical and pathological variables were analyzed. Statistical analyses included Chi-squared tests, Cox regression, Kaplan–Meier survival analysis, and multivariate modeling to construct a predictive nomogram and derive the RRS. Results: Close or involved surgical margins were observed in 33.4% of patients, and 66.9% presented moderately or poorly differentiated tumors. Locoregional recurrence occurred in 34.6% of cases, mainly within 24 months. Close margins and poor differentiation were independent predictors of recurrence (p < 0.005). The RRS effectively stratified patients into low-, intermediate-, and high-risk groups, with recurrence rates of 21.6%, 50.6%, and 82.1%, respectively (p < 0.001). Conclusions: The RRS is a practical tool for predicting OSCC recurrence and may support personalized follow-up and adjuvant treatment strategies. Prospective validation is warranted. Full article

Sustaining employees’ work engagement remains a critical challenge for contemporary organizations, particularly in contexts marked by increasing complexity and changing job demands. Despite extensive attention to engagement, less is known about how leadership behaviors contribute to engagement through employees’ perceptions of it with their organization. Drawing on fit theory, the present study examines the relationship between leadership behaviors and work engagement, focusing on the role of person–organization fit. To this end, the current paper presents a theoretical model positing value congruence (a core element of person–organization fit) as a key factor in mediating the positive relationship between the perceptions of leadership behaviors and work engagement. To test this assertion, a two-wave study using a final sample of 143 employees from a food industry company was designed. Results from structural equation modelling (SEM) supported the hypothesized model, such that, over time, the perceptions of leadership behaviors were associated with higher value congruence, which, in turn, was associated with higher work engagement. In addition, value congruence fully mediated the relationship between the perceptions of leadership behaviors and work engagement, even after controlling for the effect of gender, age, and organizational tenure. Practical implications, limitations, and directions for future research are discussed. Full article

Growing consumer awareness of environmental issues has led to heightened interest in environmentally responsible personal care products, with notable growth in the green beauty market. Despite this trend, consumer evaluations and purchasing decisions are shaped by numerous elements, particularly the trustworthiness of environmental information provided by brands. While elements such as eco-labels, environmentally friendly packaging, and individual concern for the environment are generally associated with favourable views of green marketing, they can also trigger doubt among consumers. This study investigates how eco-labeling, green packaging, and environmental concern influence consumer attitudes toward green beauty products and how these attitudes affect purchase intentions for them. The study included 500 South African consumer participants, and data were collected through an accredited research organization. The results indicate that eco-labeling, green packaging, and environmental concern each have a significant positive effect on consumer attitudes toward green beauty products. In addition, consumer attitudes were found to strongly influence purchase intentions among South African consumers. The study contributes to the literature by emphasizing the complex role of informational cues and potential perceptual barriers in sustainable consumption of green beauty products. It also provides practical insights for marketers, highlighting the importance of enhancing the credibility of eco-labels and reducing consumer doubt through clear, transparent communication strategies in the South African context. Full article

Background: Vitamin D plays an important role in overall health. This study aimed to conduct a pilot screening of serum vitamin D levels in a Malagasy cohort and to compare vitamin D status groups with selected health indicators. Methods: A cross-sectional observational pilot study was performed in two geographically distinct regions of Madagascar—a coastal area and an inland area. In total, 150 individuals underwent a single health screening, including semi-quantitative assessment of serum 25-hydroxyvitamin D, as well as evaluation of glycemic and cholesterol levels, blood pressure, anthropometric parameters, and a brief personal and lifestyle questionnaire. Results: A total of 148 participants (aged 18–88 years) were analyzed. 45.9% of participants had low serum vitamin D levels (<75 nmol/L). Lower vitamin D levels and higher total cholesterol were observed in the coastal group compared to the inland group (p < 0.05). No significant differences were found for most other examined health indicators. In multivariable analysis, age was identified as an important determinant of several outcomes. Vitamin D status did not remain an independent predictor; however, a trend toward an independent association with hypercholesterolemia was observed (p = 0.07), while the association with hyperglycemia was less pronounced (p = 0.11). Conclusions: A substantial proportion of participants exhibited low vitamin D levels despite favorable geographic conditions. The results suggest a potential relationship between vitamin D status and lipid metabolism, although this association did not reach statistical significance after adjustment. These findings provide initial insight into vitamin D status and its potential associations in this setting and may inform future research and public health monitoring. Full article

Background: Dental professionals are routinely exposed to occupational noise from high-speed handpieces and ultrasonic scalers, with levels that can reach up to 90 dB(A). While such exposure is suspected to affect cochlear function, objective assessments in this population remain limited. This study investigated short-term changes in distortion product otoacoustic emissions (DPOAEs) as a biomarker of outer hair cell (OHC) function following routine clinical dental procedures. Methods: DPOAEs were recorded at frequencies from 1000 to 6000 Hz in young dental professionals with clinically normal hearing. Measurements were obtained at three time points: prior to dental procedures (baseline), immediately after exposure (3–5 min post-procedure), and at a 48-h (follow-up). Participants were stratified into two groups based on exposure profile: those exposed to occupational dental noise alone (Group 1) and those with concurrent use of personal listening devices (PLDs) in addition to occupational exposure (Group 2). Results: A significant reduction in DPOAE amplitudes was observed immediately following dental procedures in both groups, indicating an acute effect on OHC function. This reduction was more pronounced in Group 1 (PLD users) compared to Group 2 (occupational noise only). Amplitudes returned to baseline levels at the 48-h follow-up in both groups, confirming the transient nature of the effect. The absence of significant Frequency × Time interactions indicates that the observed amplitude reductions were broadly distributed across the tested frequency range rather than confined to a specific spectral region. Conclusions: Routine clinical dental procedures can induce transient, measurable changes in cochlear outer hair cell function, detectable by DPOAEs in young professionals with normal audiometric thresholds. Although these changes appear reversible within 48 h, the greater acute response observed in individuals with concurrent personal listening device use suggests that cumulative acoustic exposure may increase cochlear susceptibility. These findings support the integration of objective cochlear monitoring into occupational health surveillance for dental personnel. Full article

Care home staff are routinely exposed to stressful and traumatic events, increasing risks of psychological distress, burnout, and reduced workforce resilience. Psychological First Aid (PFA), recommended by the World Health Organization, provides an evidence-based framework for delivering immediate emotional and practical support; however, its adaptation for care home contexts is limited. This study aimed to co-produce and adapt an existing PFA training resource for care home staff using a person-based approach (PBA) to enhance contextual relevance, acceptability, and feasibility. A two-phase qualitative design guided by PBA principles was used. Phase 1 integrated stakeholder workshops, semi-structured interviews, and literature review to generate guiding principles, a logic model, and preliminary training content. We adapted the WHO PFA “Look–Listen–Link” framework alongside existing open-access materials. Phase 2 used think aloud interviews to optimize usability and contextual fit. Thematic and sentiment analysis identified key needs: high exposure to traumatic events, inconsistent organisational support, desire for measurable skill development, the importance of transferable competencies, and motivational factors. Participants emphasized the need for flexibility, inclusivity, and realistic care-home-specific examples. Adaptations included bite-sized interactive modules, blended delivery options, and reflective exercises. The final co-produced intervention aligns with trauma-informed principles and organisational realities. Further work is needed to access feasibility, acceptability, and fidelity in real-world settings, offering a transferable model for adapting psychological interventions in other high-stress care environments internationally. Full article

This work explores how deep learning models, with different numbers of parameters, can be effectively applied to detect personal data within unstructured text using Named Entity Recognition (NER) techniques. We evaluate the performance of various architectures by leveraging a plethora of language models (LMs) consisting of Distilbert-base-uncased, Distilbert-base-cased, Bert-base-uncased, Bert-base-cased, Bert-large-uncased, Bert-large-cased, ModernBERT-base, ModernBERT-large, nomic-BERT-2048, RoBERTa-base, DistilRoBERTa-base, RoBERTa-large, Deberta-v3-xsmall, Deberta-v3-small, and Deberta-v3-base, which are evaluated using the performance indices of accuracy, precision, recall, and F1-score. Our experiments show that some Small Language Models (SLMs) compete equally with some corresponding LLMs (Large Language Models), based on the specific PII (Personally Identifiable Information) dataset, thus enhancing personal data detection, which is of paramount importance in financial applications. Moreover, we proposed a novel architecture based on an optimized transformer fine-tuning strategy to improve PII recognition across diverse contexts and conducted an extensive comparative analysis to evaluate the performance of our proposed architecture in relation to all relevant existing approaches reported in the literature. This evaluation, performed on the AI4Privacy PII 43 K dataset, encompasses every publicly available work we identified and provides a thorough benchmarking of our methods within the current research field. The results highlight both the strengths and limitations of existing solutions and demonstrate the effectiveness of SLMs in addressing the challenges of privacy-preserving information extraction. Full article

The performance of the pitcher is the cornerstone of baseball, often determining the flow and ultimate outcome of a game. Given this centrality, understanding the mechanics of an elite pitcher and decoding their strategies are paramount for both internal optimization and competitive scouting. This study proposes an end-to-end deep learning pipeline for automatically classifying five distinct pitch types from raw broadcast footage of MLB pitcher Max Scherzer between 2015 and 2020. By formulating pitch delivery as a time-series classification problem tailored to the unique biomechanics of an elite athlete, the proposed CNN–LSTM framework integrates per-frame spatial feature extraction using an advanced CNN backbone (YOLOv8s-cls) with a two-layer long short-term memory (LSTM) network to capture subtle biomechanical cues across a standardized 20-frame delivery sequence. While skeletal pose estimation primarily focuses on tracking major joints to analyze standard pitching mechanics, the proposed pixel-based method preserves fine-grained visual cues—such as finger grip and wrist rotation—that are critical for distinguishing pitch variations. The proposed framework achieved an accuracy of 91.8% under a standard Random Split and, importantly, 84.5% under a strict Chronological Split across different seasons, validating the feasibility of automated pitch “tell” detection from broadcast video. The resulting system provides coaches and analysts with an objective, data-driven tool for generating personalized scouting reports, identifying mechanical inconsistencies, and refining pitching strategies. Full article

This study explores the digital competence of foreign language teachers in Bulgarian secondary education by focusing on the institutional context of which they are a part, the strengths and gaps of their competence, and their levels of competence. It draws upon empirical data that were collected and analyzed within an integrated, dual-instrument framework, combining the SELFIE (Self-reflection on Effective Learning by Fostering the Use of Innovative Educational Technologies) and SELFIE for TEACHERS (Self-reflection on Effective Learning by Fostering the Use of Innovative Educational Technologies for Teachers) EU-aligned assessment tools. The results from the questionnaire data show that the foreign language teachers state that they work in a relatively good technological environment and evaluate the usage of digital technologies for teaching and communication purposes within the school context as a salient aspect of their digital competence. The results also reveal three areas in the study participants’ digital competence that are in need of improvement: (1) empowering learners/personalizing the educational process, (2) assessment and (3) facilitating learners’ digital competence. In addition, the findings indicate that the foreign language educators rate their digital competence at a low to medium level. By blending institutional and teacher-oriented perspectives into a single integrated study of Bulgarian secondary school foreign language teachers, this investigation extends the existing research and makes evidence-based recommendations for institutional capacity building, teacher education policy and targeted professional development aimed at improving the educators’ digital competence. Full article

The neonatal development period from the time of birth can be considered the period of greatest physiological changes throughout the human lifespan. These changes are partly due to dietary or environmental factors and are also modulated by genetic, neuronal, and humoral influences. The focus of research is increasingly on the microbial colonization of the neonatal intestine, since the establishment of a healthy, symbiotic newborn microbiota not only corresponds closely with nutrient metabolism, immune functions, and growth, but also with the brain as part of the so-called “gut–brain axis”. At the same time, a critical time window of opportunity opens up for the early infant microbiota, which is accessible to modulating approaches in favor of normal infant development. Although the definition of “normal” microbiota in infants still remains challenging, the microbiota of infants delivered at term can be discussed as the gold standard—provided they were exclusively breastfed and have not been exposed to antibiotics. Advances in sequencing technologies now also allow us to identify and characterize the microbiota at the strain level and to provide the scientific rationale for new approaches to modulate the early-life microbiome in a more targeted and personalized way—applicable also for formula-fed children who cannot be supplied with human milk. This review addresses the challenges associated with the “healthy” development of a newborn during the first weeks and months of life and discusses potentially modifiable external factors in light of the requirements for the establishment of a functional gut microbiota, gastrointestinal system, and gut–brain axis. Full article

Background/Objectives: Obesity has a huge impact on global healthcare and economy. Consequently, the pharmaceutical industry has recently introduced novel anti-obesity drugs such as semaglutide and tirzepatide, which can yield remarkable weight reduction in patients, while also having significant cardiovascular benefits. Methods: Other weight-lowering medications are currently under investigation, and this narrative review provides an overview of the main novel drugs that are being tested. Results: These novel agents have different mechanisms of action, e.g., calorie intake reduction, increase in basal metabolism, and increase in muscle mass. Conclusions: In the future, obesity treatment is likely to become increasingly personalized, and further cardiovascular benefits could be expected. The combined use of different molecules could minimize their side effects, for instance, by minimizing muscle wasting observed during glucagon-like peptide 1 receptor agonists (GLP1-RAs) therapy. In our opinion, these highly effective drugs could represent a valuable addition to healthy lifestyle, as the evidence linking increases in muscle mass and basal metabolic rate to improved cardiovascular health is strongest when these changes are achieved through diet and regular physical activity. Full article

Triple-negative breast cancer represents one of the most aggressive and therapeutically challenging subtypes of breast malignancies, characterized by marked biological heterogeneity, rapid progression, and limited targeted treatment options. Conventional therapies are frequently constrained by drug resistance, systemic toxicity, and high rates of recurrence. In this context, natural products have gained increasing attention as multifunctional agents capable of modulating several hallmarks of triple-negative breast cancer. Bioactive compounds, including polyphenols, terpenoids, alkaloids, and marine-derived molecules, exhibit pleiotropic antitumor effects by interfering with key oncogenic pathways. Importantly, these compounds have demonstrated the ability to counteract major mechanisms of therapeutic resistance, modulate the tumor immune microenvironment, and enhance the efficacy of standard chemotherapy and immunotherapy. Advances in drug delivery strategies, such as nanoparticle-based systems and tumor-targeted formulations, together with patient-specific molecular profiling, further expand the potential of these agents within personalized treatment approaches. This narrative review critically examines the role of natural compounds in targeting the hallmarks of triple-negative breast cancer and their potential synergistic use to improve therapeutic efficacy while reducing treatment-related toxicity. Overall, the integration of natural product-based strategies into precision oncology frameworks may offer more effective, less toxic, and individualized therapeutic options for this aggressive breast cancer subtype. Full article

We developed a Python-integrated closed-loop industrial safety system that bridges real-time helmet-compliance detection with immediate machine control. The custom Python application serves as critical middleware, orchestrating the complete pipeline from You Only Look Once Version 8 computer vision inference to industrial automation by trans-lating AI detection results into Object Linking and Embedding for Process Control Unified Architecture communications with a Mitsubishi programmable logic controller (PLC). The Python framework implements configurable safety policies through polygonal zones with authorized helmet colors, incorporates persistence filtering to prevent nuisance trips, and ensures deterministic translation from probabilistic AI outputs to Boolean PLC con-trol signals. Validation demonstrates reliable, low-latency safety actuation with clear ar-chitectural separation between vision processing, Python-mediated policy enforcement, and PLC-based deterministic control. Full article

Background/Objectives: Performing presurgical functional magnetic resonance imaging (fMRI) mapping in young patients is considered a challenge for clinicians, as fMRI maps are the sole source of information about the functional organization of cognitive functions/areas, especially when an awake craniotomy is not possible, as is often the case for pediatric populations. The literature on the fMRI tasks used in pediatric populations with brain injuries shows a certain heterogeneity in the approaches (task-based or resting states) and tasks, with a preference for motor/language mapping: tasks assessing extra-language functions are lacking. Methods: We have designed fMRI tasks focused on language and extra-language functions, which can be easily be applied when clinicians need to perform presurgical mapping. We present a retrospective case series of 17 patients. Results: Seventeen young patients (13.4 ± 2.8 years; range 7–16) were included in the study, for whom fMRI was performed. All underwent successful fMRI mapping by completing fMRI tasks selected based on their lesion site. The number of tasks performed by each patient significantly correlated with their age (r(17) = 0.561, p = 0.019). The patients tolerated the assessment and had good motion control: their movement parameters were minimal (range of rotation of −0.015–0.01 degrees; range of translation of −0.8–0.2 mm). The most administered fMRI tasks were tongue motor localizer (60%) and object naming (70%), with some patients performing extra-language function mapping involving visuo-spatial processing, selective attention, memory, and inhibition. Conclusions: This is an exploratory study given the sample size. fMRI measurements were considered feasible, as patients were able to complete the tasks under clinically realistic conditions. We discuss the clinical implication/usefulness of administering tasks for a personalized functional assessment of the young patient before surgery. Full article