Search Results (1,428)

Piezo1 is a mechanosensitive non-selective cation channel. Genetic alterations of the channel result in a hematologic phenotype named Hereditary Xerocytosis. With Yoda1 and, more recently, Yoda2, compounds to increase the activity of Piezo1 have become available. However, their concrete effect depends on the nano environment of the channel and hence on the cell type. Here we compare the potency of Yoda1 and Yoda2 in red blood cells (RBCs). We investigate the effect of the compounds on direct channel activity using automated patch clamp, as well as the secondary effects of channel activation on signalling molecules and cellular response. In terms of signalling, we investigate the temporal response of the second messenger Ca²⁺, and in terms of cellular response, the activity of the Gárdos channel. The opening of the Gárdos channel leads to a hyperpolarisation of the RBCs, which is measured by the Macey–Bennekou–Egée (MBE) method. Although the interpretation of the data is not straightforward, we discuss the results in a physiological context and provide recommendations for the use of Yoda1 and Yoda2 to investigate RBCs. Full article

This article introduces the Index of Distributive and Developmental Outlook (IDDO), a composite indicator designed to jointly assess economic performance and income inequality across EU-27 Member States. While GDP per capita is widely used to evaluate national prosperity, and the Gini coefficient captures income distribution, their separate use often obscures the interaction between growth and equity—an essential dimension of sustainable development. To address this gap, the IDDO integrates normalized values of both indicators using arithmetic and geometric means. The study applies the IDDO to a longitudinal dataset covering the years 2005, 2014, and 2024, allowing for comparative and temporal analysis. Based on IDDO scores, countries are classified into four development types: balanced development, growth with inequality, equity with stagnation, and dual vulnerability. Results show that while some Member States, such as Luxembourg, Czechia, and Slovenia, maintain consistently high IDDO levels, others—including Bulgaria, Romania, and Latvia—exhibit persistent challenges in aligning growth with equitable outcomes. The findings underscore the need for cohesion policies that prioritize not only economic convergence but also distributive fairness. The IDDO provides a practical and adaptable tool for diagnosing development patterns, benchmarking performance, and informing policy design within the EU framework. Full article

Prescriptive Maintenance (PsM) transforms industrial asset management by enabling autonomous decisions through simultaneous failure anticipation and optimal maintenance recommendations. Yet, despite increasing research interest, the conceptual clarity, technological maturity, and practical deployment of PsM remains fragmented. Here, we conduct a comprehensive and application-oriented Systematic Literature Review of studies published between 2013–2024. We identify key enablers—artificial intelligence and machine learning, horizontal and vertical integration, and deep reinforcement learning—that map the functional space of PsM across industrial sectors. The results from our multivariate meta-synthesis uncover three main thematic research clusters, ranging from decision-automation of technical (multi)component-level systems to strategic and organisational-support strategies. Notably, while predictive models are widely adopted, the translation of these capabilities to PsM remains limited. Primary reasons include semantic interoperability, real-time optimisation, and deployment scalability. As a response, a structured research agenda is proposed to emphasise hybrid architectures, context-aware prescription mechanisms, and alignment with Industry 5.0 principles of human-centricity, resilience, and sustainability. The review establishes a critical foundation for future advances in intelligent, explainable, and action-oriented maintenance systems. Full article

Multiple Sclerosis (MS) is a chronic neurological disorder affecting the central nervous system that significantly impairs postural control and functional abilities. Robotic-assisted gait training mitigates this functional deterioration. This preliminary study aims to investigate the effects of a four-week gait training with the ExoAtlet II exoskeleton on static balance control and functional mobility in five individuals with MS (Expanded Disability Status Scale ≤ 2.5). Before and after the training, they were assessed in quiet standing under Eyes Open (EO) and Eyes Closed (EC) conditions and with the Timed Up and Go (TUG) test. Center of Pressure (CoP) Sway Area, Antero–Posterior (AP) and Medio–Lateral (ML) CoP displacement, Stay Time, and Total Instability Duration were computed. TUG test Total Duration, sit-to-stand, stand-to-sit, and linear walking phase duration were analyzed. To establish target reference values for rehabilitation advancement, the same evaluations were performed on a matched healthy cohort. After the training, an improvement in static balance with EO was observed towards HS values (reduced Sway Area, AP and ML CoP displacement, and Total Instability Duration and increased Stay Time). Enhancements under EC condition were less marked. TUG test performance improved, particularly in the stand-to-sit phase. These preliminary findings suggest functional benefits of exoskeleton gait training for individuals with MS. Full article

Pyridoxine-dependent epilepsy (PDE) represents a group of rare developmental and epileptic encephalopathies. The most common PDE is caused by biallelic pathogenic variants in ALDH7A1 (PDE-ALDH7A1; OMIM #266100), which encodes α-aminoadipate semialdehyde (α-AASA) dehydrogenase, a key enzyme in lysine catabolism. Affected individuals present with seizures unresponsive to conventional anticonvulsant medications but responsive to high-dose of pyridoxine (vitamin B6). Adjunctive lysine restriction and arginine supplementation have also shown potential in improving neurodevelopmental outcomes. Given the significant benefit of early intervention, PDE-ALDH7A1 is a strong candidate for newborn screening (NBS). However, traditional biomarkers are biochemically unstable at room temperature (α-AASA and piperideine-6-carboxylate) or lack sufficient specificity (pipecolate), limiting their utility for biomarker-based NBS. The recent identification of two novel and stable biomarkers, 2S,6S-/2S,6R-oxopropylpiperidine-2-carboxylate (2-OPP) and 6-oxo-pipecolate (oxo-PIP), offers renewed potential for biochemical NBS. We evaluated the feasibility of incorporating 2-OPP, oxo-PIP, and pipecolate into routine butylated FIA-MS/MS workflows used for biochemical NBS. A total of 9402 dried blood spots (DBS), including nine confirmed PDE-ALDH7A1 patients and 9393 anonymized controls were analyzed using a single multiplex assay. 2-OPP emerged as the most sensitive biomarker, identifying all PDE-ALDH7A1 patients with 100% sensitivity and a positive predictive value (PPV) of 18.4% using a threshold above the 99.5th percentile. Combining elevated 2-OPP (above the 99.5th percentile) with either pipecolate or oxo-PIP (above the 85.0th percentile) as secondary marker detected within the same multiplex FIA-MS/MS assay further improved the PPVs to 60% and 45%, respectively, while maintaining compatibility with butanol-derivatized method. Notably, increasing the 2-OPP threshold above the 99.89th percentile, in combination with either pipecolate or oxo-PIP above the 85.0th percentile resulted in both 100% sensitivity and 100% PPV. This study supports the strong potential of 2-OPP-based neonatal screening for PDE-ALDH7A1 within existing NBS infrastructures. The ability to multiplex 2-OPP, pipecolate and oxo-PIP within a single assay offers a robust, practical, high-throughput and cost-effective approach. These results support the inclusion of PDE-ALDH7A1 in existing biochemical NBS panels. Further prospective studies in larger cohorts are needed to refine cutoffs and confirm clinical performance. Full article

Additive manufacturing (AM) has emerged as a transformative technology in dentistry, enabling the production of patient-specific dental applications with reduced costs and fabrication times. Despite the growth of applications, a consolidated understanding of current 3D printing technologies, materials, and performance in dental settings remains fragmented. Here, we perform a Systematic Literature Review (SLR) using the PRISMA protocol, retrieving 19 closely related primary studies. The evidence is synthesized across three axes: application domain, AM technology, and critical quality parameters. Dental restorations, prosthetics, crowns, and implants are the most common applications, while fused deposition modeling, stereolithography, digital light processing, selective laser sintering, and laser-directed energy deposition are the most used technologies. AM materials include polymers, metals, and emerging biomaterials. Key quality determinants include dimensional accuracy, wear and corrosion resistance, and photosensitivity. Notably, biocompatibility and cytotoxicity remain underexplored yet critical factors for ensuring long-term clinical safety. The evidence also suggests a lack of in vivo studies, insufficient tribological and microbiological testing, including limited data degradation pathways of AM materials under oral conditions. Understanding that there are disconnects between the realization of the clinical and the economic benefits of 3D printing in dentistry, future research requires standardized testing frameworks and long-term biocompatibility validation. Full article

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants that continue to raise concern owing to their ability to accumulate in living organisms. In recent years, a growing body of research has shown that PFAS can exert their toxicity through disruption of both DNA integrity and epigenetic regulation. This includes changes in DNA methylation patterns, histone modifications, chromatin remodeling, and interference with DNA repair mechanisms. These molecular-level alterations can impair transcriptional regulation and cellular homeostasis, contributing to genomic instability and long-term biological dysfunction. In neural systems, PFAS exposure appears particularly concerning. It affects key regulators of neurodevelopment, such as BDNF, synaptic plasticity genes, and inflammatory mediators. Importantly, epigenetic dysregulation extends to non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), which mediate post-transcriptional silencing and chromatin remodeling. Although direct evidence of transgenerational neurotoxicity is still emerging, animal studies provide compelling hints. Persistent changes in germline epigenetic profiles and transcriptomic alterations suggest that developmental reprogramming might be heritable by future generations. Additionally, PFAS modulate nuclear receptor signaling (e.g., PPARγ), further linking environmental cues to chromatin-level gene regulation. Altogether, these findings underscore a mechanistic framework in which PFAS disrupt neural development and cognitive function via conserved epigenetic and genotoxic mechanisms. Understanding how these upstream alterations affect long-term neurodevelopmental and neurobehavioral outcomes is critical for improving risk assessment and guiding future interventions. This review underscores the need for integrative research on PFAS-induced chromatin disruptions, particularly across developmental stages, and their potential to impact future generations. Full article

Introduction: Limited access to pulmonary rehabilitation (PR) has contributed to the rise of telerehabilitation (TPR) for COPD patients. Positive comparable effects are observed in exercise tolerance, quality of life (QoL), and dyspnoea with TPR. However, patient adherence to TPR is an outcome that has not been sufficiently analysed. Objective: To analyse adherence, satisfaction, and quality-of-life improvements in COPD patients following the TPR program to determine whether telerehabilitation is comparable to conventional therapy or usual care. Methods: A systematic search was conducted using four electronic databases, retrieving 392 articles. Two independent researchers selected and evaluated these articles based on predefined eligibility criteria. A third researcher was consulted in the event of disagreements. Results: Primary outcomes: Adherence to PR and/or usual care showed a minimum reported value of 62% and a maximum reported value of 91%, while TPR adherence had the lowest reported value of 21% and the highest reported value of 93.5%. Five articles compared TPR to PR and/or usual care, showing that TPR adherence is higher or similar to other interventions, whereas only one article found lower TPR adherence compared to PR. Secondary outcomes: A higher number of dropouts were reported for PR and usual care compared to TPR. Three publications analysed satisfaction and demonstrated that patients are satisfied across groups. Tertiary outcomes: Comparable improvements in QoL were found for TPR and PR, both being superior to usual care. Conclusions: This systematic review reveals heterogeneity in classifying adherence for pulmonary rehabilitation and telerehabilitation. Adherence classification may be standardised in future studies for consistent analysis. Full article

The demand for land monitoring information continues to increase, but the range and diversity of the available products to date have made their integrated use challenging and, at times, counterproductive. There has therefore been a growing need to enhance and harmonise the practice of land monitoring on a pan-European level with the formulation of a more consistent and standardised set of modelling criteria. The outcome has been a paradigm shift away from a “paper map”-based world where features are given a single, fixed label to one where features have a rich characterisation which is more informative, flexible and powerful. The approach allows the characteristics to be dynamic so that, over time, a feature may only change part of its description (i.e., a forest can be felled, but it may remain as forestry if replanted) or it can have multiple descriptors (i.e., a forest may be used for both timber production and recreation). The concept proposed by the authors has evolved since 2008 from first drafts to a comprehensive and powerful tool adopted by the European Union’s Copernicus programme. It provides for the semantic decomposition of existing nomenclatures, as well as supports a descriptive approach to the mapping of all landscape features in a flexible and object-oriented manner. In this way, the key move away from classification towards the characterisation of the Earth’s surface represents a novel and innovate approach to handling complex land surface information more suited to the age of distributed databases, cloud computing and object-oriented data modelling. In this paper, the motivation for and technical approach of the EAGLE concept with its matrix and UML model implementation are explained. This is followed by an update of the latest developments and the presentation of a number of experimental and operational use cases at national and European levels, and it then concludes with thoughts on the future outlook. Full article

This paper addresses the problem of optimal stabilization for stochastic dynamical systems characterized by Markov switches and concentration points of jumps, which is a scenario not adequately covered by classical stability conditions. Unlike traditional approaches requiring a strictly positive minimal interval between jumps, we allow jump moments to accumulate at a finite point. Utilizing Lyapunov function methods, we derive sufficient conditions for exponential stability in the mean square and asymptotic stability in probability. We provide explicit constructions of Lyapunov functions adapted to scenarios with jump concentration points and develop conditions under which these functions ensure system stability. For linear stochastic differential equations, the stabilization problem is further simplified to solving a system of Riccati-type matrix equations. This work provides essential theoretical foundations and practical methodologies for stabilizing complex stochastic systems that feature concentration points, expanding the applicability of optimal control theory. Full article

Autogenous tooth transplantation offers a biologically favorable approach to tooth replacement, preserving the periodontal ligament, promoting alveolar development, and maintaining proprioception. Background/Objectives: Its broader clinical applicability is limited by variability in techniques and outcome definitions. This systematic review and meta-analysis evaluated the clinical success of autogenous tooth transplantation across donor tooth types, developmental stages, surgical techniques, and fixation methods. Methods: Following PRISMA 2020 guidelines and a PROSPERO-registered protocol (CRD42024625550), five databases and the gray literature were searched through July 2025. Eligible studies reported clinical outcomes for autogenous tooth transplantation. Risk of bias was assessed using the Newcastle–Ottawa Scale. A random-effects meta-analysis of logit-transformed proportions was conducted, with subgroup and sensitivity analyses by tooth type, root development stage, surgical technique, and fixation method. Results: Twenty studies involving 1366 transplanted teeth were included. The pooled success rate was 94.0% (95% CI: 22.5–99.9%) across follow-up periods ranging from one month to twenty-nine years. However, interpretation is limited by distinct heterogeneity (I² = 99.8%) and the wide confidence interval. Subgroup analyses by tooth type, root maturity, surgical technique, and fixation method are, therefore, emphasized to support clinical interpretation. Conclusions: Autogenous tooth transplantation achieves consistently high success across clinical contexts when biologic handling is respected. These findings support its broader use in dental and orthodontic practice and underscore the need for standardized outcome reporting and prospective research. Interpretation is limited by heterogeneity and variation in reporting standards. Full article

As digital transformation accelerates across Europe, cloud computing plays an increasingly central role in modernizing public services and private enterprises. Yet adoption rates vary markedly among EU member states, reflecting deeper structural differences in digital capacity. This study employs explainable machine learning to uncover the drivers of national cloud adoption across 27 EU countries using harmonized panel datasets spanning 2014–2021 and 2014–2024. A methodological pipeline combining Random Forests (RF), XGBoost, Support Vector Machines (SVM), and Elastic Net regression is implemented, with model tuning conducted via nested cross-validation. Among individual models, Elastic Net and SVM delivered superior predictive performance, while a stacked ensemble achieved the best overall accuracy (MAE = 0.214, R² = 0.948). The most interpretable model, a standardized RF with country fixed effects, attained MAE = 0.321, and R² = 0.864, making it well-suited for policy analysis. Variable importance analysis reveals that the density of ICT specialists is the strongest predictor of adoption, followed by broadband access and higher education. Fixed-effect modeling confirms significant national heterogeneity, with countries like Finland and Luxembourg consistently leading adoption, while Bulgaria and Romania exhibit structural barriers. Partial dependence and SHAP analyses reveal nonlinear complementarities between digital skills and infrastructure. A hierarchical clustering of countries reveals three distinct digital maturity profiles, offering tailored policy pathways. These results directly support the EU Digital Decade’s strategic targets and provide actionable insights for advancing inclusive and resilient digital transformation across the Union. Full article

Background/Objectives: Childhood cancer leads to significant physical, cognitive, and psychosocial consequences that adversely affect the development and quality of life. Occupational Therapy (OT) has the potential to mitigate these effects. However, its integration into pediatric oncology care in Spain remains limited and underexplored. This study aims to examine the availability, characteristics, and perceived impact of OT services within pediatric oncology units across Spain and to identify key barriers to their implementation. Methods: A descriptive, cross-sectional study using a mixed-methods approach was conducted. An online questionnaire was distributed to healthcare professionals working in pediatric oncology units nationwide. Quantitative data were analyzed using descriptive statistics, Fisher’s exact test, and odds ratios with 95% confidence intervals to explore associations. Effect sizes were calculated using Cramér’s V where applicable. Qualitative responses underwent inductive thematic analysis. Results: A total of 42 hospital centers from 12 autonomous communities participated. Only 16 reported having OT services in pediatric oncology, with notable regional disparities. A significant proportion of respondents were unaware of the integration of OT in their institutions. Identified barriers included lack of resources, insufficient specialized training, and limited institutional recognition of OT. Nonetheless, professionals familiar with OT interventions reported positive outcomes, particularly in improving patients’ functional autonomy, emotional well-being, and social participation. Conclusions: OT remains insufficiently integrated into pediatric oncology care in Spain. To optimize the quality of care, it is essential to address educational, structural, and institutional challenges and promote OT as a key component of multidisciplinary teams. Full article

This study investigates the robustness of steel moment-resisting frames (MRFs) under column loss scenarios, both in undamaged and post-seismic conditions. In this context, robustness is defined as the ability of a damaged structure to prevent progressive collapse following an earthquake. A parametric investigation was conducted on 48 three-dimensional MRF configurations, varying key design and geometric parameters such as the number of storeys, span length, and design load combinations. Nonlinear dynamic analyses were performed using realistic ground motions and column loss scenarios defined by UFC guidelines. The effects of pre-existing seismic damage, façade claddings, and joint typologies were explicitly accounted for using validated component-based modelling approaches. The results indicate that long-span, low-rise frames are more vulnerable to collapse initiation due to higher plastic demands, while higher-rise frames benefit from load redistribution through their increased redundancy. In detail, long-span, low-rise frames experience roughly ten times higher displacement demands than their short-span counterparts, and post-seismic damage has limited influence, yielding rotational demands within 5–10% of the undamaged case. The Reserve Displacement Ductility (RDR) ranges from approximately 6.3 for low-rise, long-span frames to 21.5 for high-rise frames, highlighting the significant role of geometry in post-seismic robustness. The post-seismic damage was found to have a limited influence on the dynamic displacement and rotational demands, suggesting that the robustness of steel MRFs after a moderate earthquake is largely comparable to that of the initially undamaged structure. These findings support the development of more accurate design and retrofit provisions for seismic and multi-hazard scenarios. Full article