Cellular traction forces are conventionally measured by tracking the displacement of beads or micropillars and converting them to force via mechanical models. Although widely used, these displacement-based methods primarily report translational motion and, when based on the linear Euler-Bernoulli beam assumption, can suffer from geometric-nonlinearity errors under non-negligible deformation. Here we introduce an alternative approach: quantifying force by directly measuring pillar rotation angle rather than displacement, using fluorescent nanodiamonds (FNDs) as embedded 3D orientation markers. Specifically, by integrating optically detected magnetic resonance (ODMR) with laser polarization modulation (LPM), we determine the complete three‑dimensional orientation of FNDs attached to polydimethylsiloxane (PDMS) micropillars with sub‑degree precision (∼0.5°). This angle‑based measurement framework enables force reconstruction from pillar rotation and provides a robust analytical readout for stocky beams and large deformations. Finite‑element simulations demonstrate that our method reduces force estimation errors by at least 10% compared to linear displacement‑based approaches. Moreover, we successfully capture three-dimensional pillar deformations, including bending and in-plane rotation, that are inaccessible to the conventional displacement‑only method. Taken together, our work establishes diamond‑based angular force microscopy as a high‑precision platform for mechanobiology.
Neurological disorders affect more than 3.4 billion people worldwide and are now the leading cause of disability globally. Despite remarkable advances in neuroscience, substantial inequities remain in access to prevention, diagnosis, treatment, and rehabilitation. World Brain Day 2026 adopts the theme "Brain Health: Access for All", calling for coordinated global action to reduce these disparities. The campaign recognises that equitable access to brain healthcare is essential to achieving healthier individuals, stronger communities, and more resilient health systems. It emphasises prevention across the life course, earlier diagnosis, community-based care, workforce development, and advocacy to improve neurological outcomes worldwide. Built around five core pillars and five strategic priorities, World Brain Day 2026 provides a practical framework for governments, healthcare professionals, researchers, patient organisations, and communities to work together towards equitable access to brain health. The campaign reinforces a simple but urgent message: access delayed is potentially access, and brain health, denied.
The brain is uniquely vulnerable to mitochondrial dysfunction, a primary hallmark of neurodegenerative diseases. While mitochondria are universally recognized as cellular powerhouses, their organ-specific functional architectures remain poorly defined. In this study, we present a high-resolution transcriptomic analysis compared across cerebellar tissue (used as the neural reference) and peripheral tissues (heart, kidney, and ovary) to map the coordination of transport, signaling, and detoxification. Using ovarian tissue as a stable physiological baseline, our findings demonstrate that neural mitochondria are fundamentally architected for metabolic surveillance and repair rather than sheer bioenergetic throughput. To safely meet the extreme metabolic demands of synaptic transmission, the brain exhibits reduced transcriptional emphasis on bulk bioenergetic exchange pathways relative to signaling and repair modules in favor of three highly specialized functional pillars: tightly regulated transport (e.g., SFXN4, SLC25A14, and SLC25A22, SLC25A25), highly responsive metabolic signaling (anchored by EFHD1 and retrograde communication), and targeted detoxification and protein repair (e.g., MSRA and MSRB2). Furthermore, phylogenetic conservation analysis comparing the bovine lineage to the human transcriptomic reference data across 90 million years of mammalian evolution confirms that these neural-specific adaptations exhibit highly conserved expression hierarchies. This evolutionary rigidity proves that this specific neurochemical architecture is a deeply conserved, essential requirement for protecting the central nervous system. Consequently, defining this baseline establishes a critical molecular framework for identifying precise therapeutic targets to combat oxidative stress, excitotoxicity, and age-related neurodegeneration.
The escalating threat of viral pandemics, dramatically illustrated by the COVID-19 crisis, has exposed the critical shortcomings of conventional reactive virology in addressing rapidly evolving pathogens. This review introduces predictive virology (PV) as an artificial intelligence (AI)-driven discipline within broader epidemic intelligence and public health surveillance that uses advanced computational tools to forecast viral threats and accelerate countermeasure design. The current review systematically examines how AI-driven approaches (e.g., machine learning and deep learning) are reshaping virology by integrating vast genomic datasets, multimodal surveillance signals, and advanced computational models to anticipate viral emergence and evolution before widespread transmission occurs. Core pillars of PV discussed include zero-shot mutational fitness and antigenic escape prediction using large protein language models; multimodal early-warning systems that fuse wastewater monitoring, digital epidemiology, mobility data, and social media; neural differential equation-based transmission modeling; generative AI for de novo design of broad-spectrum antivirals and vaccines; and ecological risk assessment of zoonotic spillovers. In retrospective benchmarks against deep mutational scanning experiments and real-world epidemiological outcomes (SARS-CoV-2 variants, influenza, and other outbreaks), several AI-powered tools have demonstrated performance comparable to or exceeding traditional methods, although prospective validation at scale remains limited. Despite remarkable progress, significant challenges persist, including data bias, overfitting to historical patterns, lack of prospective validation, and limited generalizability across settings. In addition, there are concerns about mechanistic interpretability, equitable global data integration, and responsible deployment. This review also critically addresses the ethical, governance, and equity implications of deploying predictive capabilities at a global scale. By consolidating cutting-edge AI methodologies with virological insights and acknowledging current limitations, this work provides a comprehensive framework for transitioning virology from a reactive to a truly predictive discipline, ultimately strengthening global health security and pandemic preparedness.
Stacked graphene oxide membranes (GOMs) show exceptional capabilities for high-throughput sieving of water, ions and molecules, offering transformative potential in environmental and energy sectors1-5. However, achieving GOMs with subnanometre interlayer spacing and subangstrom tunability while maintaining their structural robustness for rapid and selective ion transport remains a big challenge6-8. Here we present polydopamine-pillared composite GOMs with tunable and stable interlayer spacing, featuring controllable interlayer spacing down to 5.9 Å in the dry state, and capable of sieving hydrated rubidium (Rb+) and potassium (K+) ions differing in size by less than 0.1 Å in aqueous environments, achieving an Rb+/K+ separation factor of 5,320. These composite GOMs were fabricated by using the dopamine assembly and reaction timescale separation method. Specifically, the GOM fabrication capitalizes on the fact that nanoconfined water has a lower freezing temperature than that of bulk water, such that the interlayer spacing is regulated by the rapid assembly of dopamines into nanopillars, driven by nanoconfined liquid water while the surrounding is in bulk ice. The assembly process can be halted anytime by further lowering the temperature to tune and fix the interlayer spacing. Thereafter, the GOM is rigidified through the slower chemical reactions, including polymerization of dopamine molecules and covalent bonding at specific oxygen-containing sites on the graphene oxide surface while retaining ample graphene subnanochannels for high-flux transportation. The GOMs deliver continuous freshwater production for 30 days at a water permeance of 67.9 l m-2 h-1 bar-1, 1-2 orders of magnitude higher than conventional membranes9.
The increase in workplace accidents and the growing complexity of work environments have highlighted the need for more sustainable and adaptive occupational health and safety (OHS) management systems. Traditional approaches often fail to fully capture the variability of workers' responses and the multifactorial nature of occupational risks. To address these challenges, an alternative methodology for the development of a human-centered risk management tool (HURMAT) is proposed. This methodology integrates the core principles of conventional OHS frameworks with a more in-depth, worker-centered evaluation of functional capacity. It is structured across different levels of a traditional OHS approach, allowing flexible implementation without requiring full deployment if detailed analysis is not needed. The approach incorporates occupational psychophysiology and considers work-related risk factors, enabling the diagnosis and management of fatigue. The HURMAT methodology enables a more comprehensive characterization of tasks by integrating workers' physiological characteristics and assessing physical, cardiovascular, and psychosocial loads. This approach supports a more detailed understanding of risk exposure and worker responses, improving the identification and management of occupational hazards. HURMAT contributes to the modernization of OHS practices by promoting safer and more adaptive work environments. It underscores the need for a paradigm shift in how occupational risks are conceptualized and managed, emphasizing personalization, data-driven decision-making, and the recognition of individual differences. These elements represent fundamental pillars for fostering healthier, more inclusive workplaces, particularly in the context of ongoing organizational change.
This study provides a comprehensive bibliometric analysis of global research on wild boar (Sus scrofa) meat quality and related attributes, including carcass traits, fatty acid composition, and nutritional characteristics. A total of 423 articles indexed in the Web of Science Core Collection were retrieved and analyzed using RStudio with the Bibliometrix package, complemented by VOSviewer for network visualization. The results indicate a marked increase in scientific production, reflecting growing interest in both genetic and quality-related aspects of wild boar meat. Leading journals such as Journal of Animal Science and Meat Science dominate the field in terms of productivity and citation impact, highlighting the strong linkage between animal genetics and meat science. Author and country collaboration networks reveal the presence of core research groups, primarily concentrated in Europe, with increasing international cooperation. Keyword co-occurrence and thematic evolution analyses identify three principal research directions: (i) genetic improvement and production traits, (ii) molecular mechanisms and genome-wide association studies, and (iii) meat quality and lipid composition. Overlay and thematic evolution analyses reveal a transition from traditional studies on carcass and growth traits toward genomic approaches and nutritional evaluation in recent years. Multiple Correspondence Analysis (MCA) further confirms the coexistence of production genetics, molecular biology, and meat quality as the field's main conceptual pillars. This study covers the gap of literature by summarizing research output on this individual topic. Overall, the presented work clarifies the intellectual structure, thematic development, and emerging trends in wild boar meat research, providing a valuable reference framework for future investigations integrating genomics, meat science, and nutritional evaluation.
Background/Objectives: Artificial intelligence (AI) is increasingly embedded within diagnostic imaging workflows, reshaping clinical decision-making, health system governance, and regulatory oversight. While technical advances in radiological AI have accelerated, governance mechanisms have struggled to keep pace with issues of bias, transparency, accountability, and lifecycle oversight. This study examines ethical, regulatory, and implementation challenges in AI-enabled diagnostic imaging, building on prior reviews that have often emphasised technical performance by integrating ethical risk domains with governance responses across the AI lifecycle. Methods: This study presents a PRISMA-ScR-informed systematic survey of 156 sources, including peer-reviewed publications, regulatory documents, policy reports, and professional guidance materials (2018-2025), synthesised through thematic analysis and lifecycle mapping spanning data acquisition, model development, deployment, monitoring, and continuous learning. Results: Drawing on both thematic insights derived from the reviewed literature and established ethical and regulatory frameworks, we propose a literature-derived conceptual ethical-governance framework organised around five pillars: equity and bias mitigation, explainability and transparency, accountability and oversight, privacy-preserving infrastructure, and adaptive regulatory alignment. Although illustrated through the Australian healthcare context, the framework is designed to be transferable to federated and multi-jurisdictional health systems. This review further identifies trust quantification as an underdeveloped but essential dimension of clinical AI governance, emphasising the need to integrate measurable indicators such as calibration, clinician-AI concordance, and patient acceptance into lifecycle-based evaluation. Conclusions: By bridging technical, ethical, and policy perspectives, this review proposes a structured conceptual governance framework to support safe, equitable, and trustworthy AI integration in digital health systems.
Adsorptive separation of propyne/propylene (C3H4/C3H6) using porous adsorbents offers a promising route toward energy-efficient production of polymer-grade C3H6. Currently, the prevailing adsorbents are ultramicroporous metal-organic frameworks (MOFs) that feature narrow channels and/or consist of inorganic anion pillars, which often lead to limited C3H4 uptake capacity and high isosteric enthalpy of adsorption. We report herein a highly porous and robust zirconium metal-organic framework, termed SJTU-520. This MOF incorporates shape-persistent molecular arrays in three-dimensional space derived from cyclotetrabenzoin, which function as selective sites for the preferential entrapment of C3H4 over C3H6, thus enabling high C3H4 capture capacity, record high C3H4/C3H6 uptake ratio at 1 bar and 298 K, and efficient C3H4/C3H6 separation at ambient conditions. Compared with the cyclotetrabenzoin and tetraacetate cyclotetrabenzoin-based supramolecular organic crystals, SJTU-520 exhibits significantly higher surface area (3650 m2/g versus 42 and 570 m2/g), leading to a C3H4 uptake boost by 6.1-fold and 3.7-fold at 298 K and 1 bar, without any compromise of the C3H4/C3H6 selectivity. The efficient C3H4/C3H6 separation was validated by extensive breakthrough experiments under various conditions with great recyclability and high productivity of polymer-grade C3H6 from a 10/90 C3H4/C3H6 mixture. Computational simulations revealed that the four benzene walls of the cyclotetrabenzoin macrocycle in SJTU-520 formed equidistant π-π interactions with the C≡C triple bond of encapsulated C3H4 molecule. This work illustrates a general and powerful strategy─the reticulation of intrinsically functional organic scaffolds into highly porous frameworks─toward creating bespoke materials with precisely tailored functionalities and enhanced properties.
The Adolescent Brain Cognitive Development (ABCD) Study has substantially advanced developmental neuroscience through its large scale and open-science framework. This review synthesizes the study's significant statistical and methodological contributions over its first ten years, organized around the pillars of population neuroscience, longitudinal modeling, and causal inference. We first examine how ABCD's population-based design has prompted a reconsideration of how effect sizes are interpreted, helping to establish new benchmarks for distinguishing stable, biologically relevant signals from trivial associations in large-N contexts. We detail the computational innovations required to process high-dimensional data at scale, specifically highlighting new analytic tools like the Fast and Efficient Mixed Effects Algorithm (FEMA) framework for mass-univariate modeling and advanced strategies for managing selective attrition and missing data in large-scale longitudinal cohorts. In the domain of longitudinal and multilevel modeling, we discuss the transition from traditional cross-lagged designs to sophisticated frameworks - such as random-intercept cross-lagged panel models, latent growth curves, and parallel process models - that disentangle within-person developmental trajectories from stable between-person traits. We further highlight the study's role in advancing causal inference in observational research through "G-methods", marginal structural models, and quasi-experimental family-based designs. Finally, we explore how ABCD serves as a critical bridge for cross-cohort generalizability and lifespan validation using datasets like the UK Biobank. By contributing to new standards for reproducibility and methodological rigor, the ABCD Study has helped move neuroscience toward a "big data" era, providing a comprehensive statistical foundation for understanding the complex interplay between biology and environment during the transition to adulthood.
To deconstruct the evolutionary trajectory and intellectual structure of wearable devices for health management. The study executed a systematic bibliometric analysis of 2,463 high-quality publications from the Web of Science Core Collection (1997-2025). The findings reveal that the field entered an exponential growth phase post-2018, anchored by a bipolar dominance of the USA and China. While academic institutions drive innovation, the global collaborative network remains structurally fragmented. There were 637 keywords in total, key themes include "digital health," "wearable devices," "physical activity," "artificial intelligence." Research hotspots have crystallized around three strategic pillars: high-fidelity physiological sensing, AI-driven intelligent analytics, and clinical translation for proactive health. Furthermore, frontier trends indicate a critical pivot from generalized monitoring to the precision management of specific pathologies (e.g., cardiovascular diseases) and a technological shift toward energy-autonomous systems, by elucidating the pathway from technological incubation to clinical application. This study offers empirical evidence and strategic insights to guide future interdisciplinary synergy and the construction of interoperable data ecosystems for precision health management.
Despite growing interest in conservative kidney management (CKM) for older adults with advanced chronic kidney disease (CKD), little is known about the lived experiences of those involved in CKM care. This study aimed to explore the perceptions and experiences of patients, informal caregivers, nephrologists, and healthcare professionals participating in a coordinated home-based CKM pathway in France. Multicenter qualitative study using grounded theory. Participants were recruited from a regional, coordinated home-based CKM pathway involving 20 nephrology centers and a multidisciplinary care network across urban and semi-rural areas in northern France. Semi-structured interviews explored experiential themes and the perceived value of CKM in four stakeholder groups. Analysis used grounded theory with open, axial, and selective coding. Fifty-three participants were interviewed: 12 patients, 12 informal caregivers, 15 nephrologists, and 14 home-care professionals. Three interrelated themes emerged. First, CKM was perceived as a meaningful and legitimate alternative to dialysis, centered on remaining at home, preserving autonomy, and prioritizing quality of life. The decision not to dialyze was usually described as patient-driven and grounded in a rejection of dependence and hospitalization. Second, communication, decision-making, and coordination emerged as central but uneven pillars of the pathway. Introducing conservative care and discussing end-of-life preferences remained difficult, whereas the coordinating nurse consistently appeared as the key structural link between patients, caregivers, nephrologists, and community professionals. Third, informal caregivers occupied a central yet vulnerable position, combining emotional support, practical coordination, and symptom monitoring; although increasingly involved in organizing care, they frequently experienced substantial burden, anticipatory distress, and mutual protective silences within families. Single-region study; limited generalizability; possible selection bias. Conservative kidney management involves complex relational, emotional, and practical dynamics. Incorporating the perspectives of various stakeholders may help optimize coordinated, home-based care pathways tailored to older adults with advanced CKD.
Self-esteem and psychological well-being are fundamental pillars of individuals' integral development, especially during the university stage, when students face multiple personal challenges and intense academic demands. This study aimed to determine whether self-esteem and psychological well-being predicted life satisfaction among university students in southern Peru. The sample of 506 university students, aged 18 to 30 years (M = 22.1; SD = 2.84), participated in this cross-sectional predictive study. The data were collected from three universities in southern Peru via non-probabilistic convenience sampling. The instruments were the Rosenberg Self-Esteem Scale, the BIEPS-A Psychological Well-Being Scale for Adults, and the Satisfaction with Life Scale. Hierarchical regression analysis was performed. Hierarchical regression showed that psychological well-being dimensions (ΔR²=0.426) and self-esteem (ΔR²=0.157) significantly predicted life satisfaction, explaining 59.6% of the variance, while sociodemographic variables showed no significant contribution (R²=0.013,p = 0.240). Self-esteem was the strongest predictor in the final model (unstandardized B = 0.363, SE = 0.026, β = 0.572,p < 0.001), followed by the psychological well-being dimension of social bonds (B = 0.424,SE = 0.087,β = 0.185,p < 0.001). The self-esteem and psychological well-being dimensions are significant predictors of life satisfaction among university students in southern Peru, with self-esteem also operating as a mediating mechanism linking psychological well-being to life satisfaction.
Considerable evidence has accumulated over the past two decades demonstrating that Escherichia coli, specifically adherent-invasive E. coli, contributes to the pathogenesis of Crohn's disease. Adherent-invasive E. coli can adhere to and invade intestinal epithelial cells, survive, and replicate within macrophages, thereby enabling a key mechanism that induces chronic inflammation. Despite extensive knowledge of the molecular interactions between adherent-invasive E. coli and the host from these studies, translating this knowledge into targeted therapy remains limited.In this review, we summarize current and proposed treatments to prevent or eliminate adherent-invasive E. coli colonization. We provide a theoretical framework that categorizes these strategies into four main pillars: direct pathogen targeting (e.g., antibiotics, phage therapy), blockade of bacterial virulence factors (e.g., anti-adhesive compounds, QseC inhibitors), host-mediated clearance (e.g., autophagy inducers), and ecological intervention/restoration (e.g., fecal microbiota transplantation, Probiotic, Prebiotic and Probiotics). Finally, we discuss new modalities, including predatory bacteria, siderophore immunization, and other approaches. This review identifies the latest weapons against adherent-invasive E. coli, synthesizes experimental and clinical evidence to provide a comprehensive view of this evolving therapeutic arsenal, and offers ideas for future treatment of Crohn's disease.
Not fully grasping the concepts of relativity can lead to misunderstandings about the fundamental background of synchrotron emission. Here we deal with some intriguing cases, in which the relevant `speed of light' is not the invariant c but the speed with respect to a moving object. This specifically affects two pillars of synchrotron radiation: the Lorentz length contraction and the Doppler shift. We propose a teaching strategy relying on new versions of simple `thought' experiments. Besides putting synchrotron radiation on solid foundations, the approach amazingly leads to a unique link-described by Einstein as `remarkable'-between special relativity and quantum mechanics.
Engaging knowledge users, including patient partners and health-system partners, in embedded health services research is increasingly recognized as essential for strengthening the relevance of research and improving the quality and equity of health services and is foundational to the success of team science. Existing engagement frameworks, however, often capture experiences at single time points and do not fully reflect relational dimensions over time such as trust, reciprocity, shared decision-making, and equity which can impact the outputs and outcomes of partnered research. There remains limited evidence describing how engagement unfolds or what conditions support or hinder meaningful, equitable partnerships in research. This study will address this gap by examining the ripple effects of a long-standing researcher-knowledge user partnership and identifying the relational and structural factors that sustain it. This qualitative, participatory study will be guided by critical patient-oriented research (cPOR), an approach that centres equity, shares power, and structurally situates lived/living experiences throughout the research process. In alignment with cPOR principles, patient partners and health-system partners are co-researchers across all stages of the study from inception through to development of data collection tools and will partner in analysis and interpretation. The study will be conducted within the Lung Health Equity Advisory Committee, a partnership co-established to address inequities in lung health, where patient partners, clinicians, policymakers, program implementers, and researchers have worked together since 2020. Data collection will be informed by patient engagement tools, such as the Engaging with Purpose Patient Engagement Framework, to assess experiences across five pillars: Co-Build, Support, Mutual Respect, Inclusiveness, and Impact, using document analysis and annual surveys. Analysis will be guided by the theoretical concept of ripple effects, to explore how engagement processes, outputs, and outcomes accumulate and influence subsequent phases of work. Data will be analysed using combined deductive-inductive content analysis, with triangulation across all data sources. Preliminary findings will be synthesized with partners through Ripple Effects Mapping (REM), a participatory approach that supports collective interpretation, visualization of impact pathways, and opportunities for continuous improvement. This study offers a novel approach to understanding the experiences and impact of long-standing research-knowledge user partnerships that are not bound by a specific project or timeline. By exploring this relational approach to engagement, we will generate nuanced insights into how knowledge-user engagement is built, experienced, and adapted over time within an equity-oriented partnership. The exploration of ripple effects is expected to strengthen real-time learning and partnership dynamics while offering a transferable model for other research teams seeking to embed iterative, partner-guided improvement into engagement practices that are sustained over time. Working closely with patients, community members, and people who plan and deliver healthcare helps make research more useful and can improve the quality and fairness of care. However, most ways of exploring engagement practices capture people’s experiences as snapshots at different points in time, and do not adequately unpack how aspects such as trust, shared decision-making, and fairness may impact long-standing relationships. This study will help fill this gap by looking at how engagement is experienced over time in a long-standing partnership and by identifying the relationship and system factors that help support meaningful and impactful partnerships.This study will use an approach that focuses on equity, shared decision-making, and lived/living experiences. Patient partners and health-system partners who have been working together since 2020 in the Lung Health Equity Advisory Committee to improve lung health outcomes for all have co-designed this study and research approach. They will help analyse and understand the results. We will collect information from project documents and surveys and work together to create a ripple effects map that visually traces how engagement activities, relationships, and collective decision-making contribute to outcomes and development of novel projects over time.This study will help us better understand how sustained partnerships are built, experienced, and can be improved over time. It will also provide a model that other research teams can use to understand and sustain how they work with partners for greater impact.
India's 243 million adolescents (21% of the population) face nutritional deficiencies, sexual and reproductive health concerns, mental health disorders, and rising non-communicable diseases (NCDs). Despite policies like Rashtriya Kishor Swasthya Karyakram (RKSK), major implementation gaps remain across public health facilities. This scoping review, guided by Arksey and O'Malley's framework and PRISMA-ScR guidelines, assessed adolescent health services at Health and Wellness Centers, Primary Healthcare Centers, and Sub-Health Centers from 2015 to 2025. Three electronic databases were searched, with standardized data extraction, expert consultation and thematic analysis mapped RKSK's four pillars. Study quality was appraised using the MMAT (2018 version). Out of 1,371 records, only 11 met the inclusion criteria. Just 12.5% of facilities provided dedicated adolescent services. A study by Prasad et al. in 2024 reported that only 12.5% of assessed facilities provided dedicated adolescent-specific services and 6% of HWCs offered adolescent care. Barriers comprised lack of privacy, staff shortages, provider bias against unmarried youth (25%), supply chain issues, weak referral systems, poor intersectoral coordination, cultural stigma, and the need for parental consent requirements. Opportunities exist through digital health (78% smartphone use among adolescents), Stakeholder consultation participants estimated adolescent smartphone access at about 78% in the Sikar district. Public-Private Partnerships (PPP), community engagement, and innovative service models. Despite strong policy frameworks, persistent gaps are evident, with malnutrition (27.4% stunted growth) and rising obesity rates highlighting the urgency. Strengthening services demands political commitment, adequate financing, and culturally sensitive approaches to transform adolescent health and leverage India's demographic potential.
The colloquy stimulating this response has, at its root, the behaviour of the individual healthcare practitioner. Our response suggests the need for a more holistic, system based approach where the individual is couched within a context that includes the relationships of the work, the working environment and the society within which all are situated. We explore this concept basing our arguments on the four pillars of bioethics - beneficence, non-malevolence, autonomy and justice. We provide a view on the influence of contextual features and how these might provoke professional behaviour change, commenting on the rightness and professional necessity of shifting our stance and communication methods.
Develop an evidence-based practice (EBP) mentorship program framework. Despite the widespread call for EBP adoption, EBP competency in healthcare remains low. An integrative literature review across 3 databases on EBP mentorship programs was conducted in August 2025. A total of 21 English-language articles were included in the review. Five core pillars for successful EBP mentorship programs were identified: corporate considerations, mentor development, program design, education, and outcome measurement. Nursing administrators are uniquely positioned to bridge the gap between academia and EBP implementation through mentorship programs that drive EBP competencies, develop champions, and build a sustained culture of inquiry.
A personalized rather than "one-size-fits-all" approach is essential when weaning patients from microaxial flow pumps (Impella). We detail, for the first time, a structured, stepwise, multimodal, bedside strategy to guide safe and effective discontinuation from a microaxial flow pump, based on echocardiography, reconditioning, and use of inotropes, Impella support, stepwise reduction titrated according to hemodynamics, and lung ultrasound with VExUS when appropriate ("E.R.I.L." protocol). Integrating these 4 pillars into daily clinical practice, E.R.I.L. aims to identify the optimal timing for discontinuation of microaxial flow pump use, whether used as isolated mechanical circulatory support or combined with V-A ECMO (ECPELLA), thereby minimizing device-related complications while preserving the duration of support needed to achieve sustained left ventricular recovery.