Search Results (195)

Background/Objectives: Effective clinical leadership is a critical driver of healthcare quality, patient safety, and organisational performance. However, evidence on the leadership competencies of healthcare professionals in formal management roles remains fragmented. It is dispersed across professional groups, healthcare contexts, and conceptual frameworks, limiting opportunities for synthesis and cumulative knowledge development. This systematic review examined three questions: how clinical managers perceive their leadership competency; what challenges they encounter in exercising leadership roles; and what development mechanisms the literature identifies. Methods: A systematic review was conducted following PRISMA 2020 guidelines and registered in PROSPERO (CRD420261305279). Four databases were searched: Ovid MEDLINE, CINAHL, EMCARE, and Web of Science from January 2010 to February 2026. Two reviewers independently screened studies; methodological quality was assessed using the Mixed Methods Appraisal Tool (MMAT). Reported competencies were mapped to the five domains of the Clinical Leadership Competency Framework (CLCF) using narrative integrative synthesis. Results: Forty-nine studies were included across quantitative, qualitative, and mixed-methods designs from 24 countries. Competencies in the Working with Others and Demonstrating Personal Qualities domains were reported as strengths across the largest number of included studies. Competencies in Managing Services, Improving Services, and Setting Direction were reported as areas of weakness or developmental need across multiple studies. Leadership challenges included inadequate preparation, role ambiguity, limited authority, and organisational constraints. Development needs spanned formal training, strategic competency building, mentoring, and sustained organisational support. Conclusions: Clinical leadership competency is unevenly distributed across CLCF domains. This pattern reflects not only individual developmental gaps but also the organisational and contextual conditions that shape how leadership is enacted in practice. The findings support a contextual-relational model of clinical leadership. Both individual capability and enabling organisational conditions must be addressed to strengthen leadership effectiveness across healthcare systems. Full article

For decades, transportation planning has relied on utilitarian principles, which aim to maximize cumulative benefit by meeting the needs of the “average user.” This approach ignores fundamental differences between population groups and produces uniform solutions that fail to address the diverse needs of women, children, the elderly, and other disadvantaged populations. In response, there are growing calls for a transportation justice paradigm that emphasizes individuals’ ability to access meaningful opportunities according to their characteristics, abilities, and life circumstances. Autonomous Mobility on Demand (AMoD) holds the potential to transform future transportation systems. However, without deliberate planning, they risk replicating existing patterns of inequality for populations whose mobility needs differ from those of the average user. This study applies transportation justice principles to examine how AMoD systems can be designed to meet diverse user needs. Using a combination of an Autoencoder for learning reduced representations and an HDBSCAN clustering algorithm, the analysis identifies distinct travel patterns across socioeconomic groups. These findings reveal significant gaps between population segments, particularly among children and older adults, and demonstrate how AMoD systems could expand access to after-school activities, reduce social isolation among elderly women, and reduce various transportation-related social gaps by improving their ability to reach a wider range of opportunities. Full article

Background: Persistent lymph node metastases after neoadjuvant radiochemotherapy (RCT) for locally advanced rectal cancer indicate poor response to treatment. This study evaluated the long-term prognosis of patients with residual nodal disease following neoadjuvant RCT and total mesorectal excision (TME) in comparison with patients who underwent upfront TME without adjuvant radiotherapy. Methods: Consecutive patients with rectal adenocarcinoma and histopathologically confirmed lymph node metastases after TME were identified from the prospectively maintained database of the colorectal unit at Dresden-Friedrichstadt General Hospital. Patients with distant metastases, in-hospital mortality, or postoperative radiotherapy were excluded. The two groups were comprehensively compared regarding patient-, tumor-, and treatment-related characteristics. Cumulative local recurrence, time to recurrence, cancer-specific survival, and overall survival were analyzed using the Kaplan–Meier method. Results: Between 1996 and 2021, 155 eligible patients were identified, including 101 patients in the RCT group and 54 in the upfront surgery group. Baseline characteristics were largely comparable, except for a higher median age (70.5 vs. 64 years, p < 0.001) and a higher proportion of lymphovascular invasion (36.0% vs. 15.2%, p = 0.004) in the upfront surgery group. Ten-year local recurrence rates were similar between groups (21.0% [95% CI: 10.4–31.6] vs. 20.8% [95% CI: 8.5–33.1], p = 0.609). No significant differences were observed in time to recurrence or cancer-specific survival. Overall survival was lower in the upfront surgery group, most likely reflecting the substantially higher age of these patients. Conclusions: Despite more intensive treatment, patients with a persistent ypN-positive category have outcomes no better than untreated patients with node-positive disease after TME, indicating a biologically high-risk subgroup. Non-response is therefore a sign of a negative selection. These patients may lose the opportunity for optimal local tumor control during prolonged neoadjuvant treatment, underscoring the urgent need for reliable predictive markers to identify non-responders and guide individualized treatment strategies. Full article

Background and Objectives: New Caledonia, an archipelago in the South Pacific, experienced an unprecedented conjunction of prolonged border closure during the COVID-19 pandemic (2020 to 2022) and marked influence of the El Niño/Southern Oscillation (ENSO). This context provided a unique opportunity to explore how environmental drivers, island isolation, and socio-demographic factors interact to shape infectious disease dynamics. This study aimed to assess the respective and combined effects of climatic variability, travel restrictions, and socio-demographic factors on the dynamics of four priority infectious diseases. Materials and Methods: We retrospectively analysed data from 2017 to 2023 on four infectious diseases: leptospirosis, dengue, influenza, and hepatitis A (HAV). Satellite precipitation data and the Multivariate El Niño/Southern Oscillation Index (MEI) were used. Socio-demographic and economic variables were gathered. Statistical analyses employed descriptive analysis and Generalized Additive Mixed Models to evaluate the associations between climatic events, travel restrictions, and disease circulation using the communal level as a random effect and time (daily) as a spline effect. Results: We analysed 878 cases of leptospirosis, 165 of HAV, 6607 of influenza, and 7377 dengue cases. Influenza was associated with rainfall before lockdown (Odds Ratio (OR) 0.7, Confidence interval 95%, (CI95%), (0.6–0.8)) and disappeared during lockdown but resurged post-reopening losing its meteorological association. Dengue epidemics declined, coinciding with the Wolbachia program and border closure, and were associated with lower MEI (OR 0.78, CI95% (0.6–1) during the 2017 to 2020 period. HAV cases were correlated with the MEI (OR: 1.8, CI95% (1–3.3)). Leptospirosis cases were associated with cumulative rainfall (OR 1.12 (1.1–1.2)) and lower education (OR 1.04, CI95% (1–1.1)) and decreased with water supply (OR 0.7, CI95% (0.5–0.8)). Conclusions: Our findings highlight how climatic conditions, mobility restrictions, and socio-environmental inequities differentially shape infectious disease risks in island ecosystems. These results reinforce the need for integrated One Health surveillance that jointly addresses environmental change, social vulnerability, and infectious disease prevention. Full article

This research examines how community support for sustainable tourism development is influenced by sustainable hospitality in protected park areas. This relationship focuses primarily on the effect of perceived eco-social performance (ESP) as an enhancement of the community’s perceived location-specific environmental attachment (CEA), leading to increased pro-sustainable tourism intentions through CEA. Despite the growing focus on sustainability within hospitality industries, there remains very little scholarly research that explores how local communities perceive sustainable hospitality practices and how these perceptions then manifest as emotional attachment, followed by behavioural support. To achieve the stated goal, researchers employed an explanatory sequential mixed-methods design to collect quantitative survey data from residents living in close proximity to a protected area destination, and the quantitative data were used separately to develop qualitative insights into residents’ support for sustainable tourism initiatives. Findings of this study reveal that perceived ESP significantly enhances CEA, providing an impetus for increased PSTI (via direct and indirect pathways) for communities in close proximity to a protected area destination. CEA further enhances PSTI significantly and acts as a significant mediator in the relationship between perception and behavioural support for sustainable tourism. Qualitative findings further indicate that eco-social hospitality practices fulfil the following: develop community pride; increase the sense of environmental responsibility among the community; and create opportunities for actively supporting sustainable tourism. These findings demonstrate that, while sustainable hospitality practices generate observable actions, they also create deeper psychological connections between communities and their environment. The cumulative findings from this study contribute to a greater understanding of how ESP can strategically contribute to growing the number of communities supporting sustainable tourism through the creation of CEA, thereby expanding the overall community’s intention to support sustainable tourism development. Full article

Purpose: Obesity, characterized by abnormal fat accumulation with comorbidities, continues to increase dramatically, particularly in the pediatric population. Identifying the environmental and genetic causes underlying the development of obesity during early childhood is crucial for establishing preventive and protective treatments for this complex disease. We aimed to investigate genetic variants related to non-syndromic early-onset childhood obesity. Methods: Whole-exome sequencing was performed in three independent consanguineous families with obesity, including three index cases and two additional affected siblings. Non-synonymous variants with minor allele frequency < 0.01 in all normal populations were filtered using the Genomize-SEQ Platform. Variant confirmations and familial segregations were analyzed by Sanger sequencing. Results: WES revealed a shared ATXN3 gene variant and two known variants of the SH2B1 and ADIPOQ genes, which were reported to be associated with obesity. Additionally, five heterozygous novel gene variants of the ANKK1, NEGR1, OGDH, ABCB1, and GSK3B genes were identified, which are predicted to cause excessive fat accumulation and disruption of energy balance in individuals. Conclusions: We suggest that the cumulative effects of all obesity-associated detected variants lead to the early-onset obesity phenotype observed in individuals. Hence, periodic follow-up and treatment opportunities are recommended for index cases, alongside the adoption of a more active lifestyle and healthy nutrition practices. Full article

Lower-grade gliomas (LGGs) often follow a relatively protracted clinical course; however, a substantial proportion eventually undergo malignant transformation to high-grade, treatment-refractory disease. This process has traditionally been interpreted in the context of stepwise histopathologic progression and recurrent genetic alterations. Increasing evidence, however, suggests that malignant transformation is more accurately understood as an evolutionary process shaped by the interplay among epigenetic constraints, cell-state plasticity, and selective pressures. In this review, we examine current evidence supporting a model in which early LGGs, particularly isocitrate dehydrogenase (IDH)-mutant tumors, are initially maintained in relatively restricted cellular states by metabolically imposed epigenetic programs, but progressively escape these constraints under the cumulative influence of therapy, hypoxia, immune remodeling, and genomic instability. We summarize recent advances demonstrating that progression from lower-grade to high-grade disease is accompanied by cell-state transitions characterized by altered lineage identity, acquisition of stem-like features, increased proliferative capacity, and adaptation to cellular stress. We further discuss how these transitions are reinforced by microenvironmental evolution, including vascular remodeling, extracellular matrix reorganization, and changes in immune composition, thereby creating conditions that favor clonal expansion, invasion, and therapeutic resistance. Particular attention is given to longitudinal, single-cell, and spatially resolved studies, which collectively indicate that malignant transformation is not a discrete event but a continuous process of evolutionary selection and phenotypic reprogramming. Finally, we discuss the translational implications of this framework for early risk stratification, biomarker development, and mechanism-based therapeutic intervention. By reframing malignant transformation in LGGs as a process of cell-state escape under persistent selective pressure, this review aims to provide an integrated view of glioma progression and to highlight new opportunities for precision monitoring and treatment. Full article

Background: The elderly are vulnerable to chronic diseases and altered lipid metabolism, leading to poor outcomes, including mortality. We investigated the association between Korean Medicine (KM) utilization, blood lipid levels, and health outcomes using the National Health Insurance Service Sample Cohort (NHIS-NSC) database. Methods: This retrospective cohort study included elderly participants who underwent health examinations (2009–2010). Participants were divided into KM and non-KM groups and matched 1:1 using propensity score matching (PSM) for age, sex, income, and comorbidities. Primary outcomes were mortality and disease diagnosis; secondary outcomes included medical spending and utilization. Results: After PSM, 13,044 subjects were analyzed. KM utilization was associated with a significantly lower risk of all-cause mortality (HR 0.93; 95% CI 0.87–1.00; p = 0.048). However, the hypolipidemia subgroup showed no significant differences in all-cause mortality and medical expenses compared to other lipid status subgroups. While the KM group showed a higher incidence of disease diagnosis (HR 1.09; 95% CI 1.04–1.14; p < 0.001), this may reflect increased healthcare engagement and proactive health-seeking behavior. Subgroup analysis revealed that statin users in the KM group had a significantly reduced mortality risk (HR 0.91; 95% CI 0.84–0.99; p = 0.022). Medical expenses and utilization were higher in the KM group. Being underweight or aged over 85 was associated with higher mortality. Conclusions: KM utilization is associated with reduced all-cause mortality after propensity score matching, particularly among statin users. Although KM users had a higher cumulative incidence of disease diagnosis, this potentially reflects increased diagnostic opportunities from prolonged survival. Hypolipidemia, underweight, and late-elderly status remain significant risk factors associated with frailty. KM may support improved survival in the elderly, warranting further prospective studies. Full article

This study compares hydrogen production pathways from water—using renewable-powered electrolysis (alkaline, water-based)—and biomass (gasification), under harmonized system boundaries and a common functional unit of 1 kg H₂ at 99.97% purity. It examines technological efficiency and environmental impacts, including cradle-to-gate Life Cycle Assessments (LCAs) of each pathway, focusing on global warming potential (GWP100), water consumption, land use, acidification, cumulative energy demand, and the critical minerals footprint. The analysis highlights the roles of water electrolysis and biomass gasification within South Africa’s energy landscape, considering the integration of renewable electricity, energy quality, and co-product allocation. Economic factors, such as the Levelized Cost of Hydrogen (LCOH), are evaluated alongside environmental indicators. The study emphasises the environmental challenges of biomass gasification, notably water use and emissions, and contrasts these with the climate benefits of renewable-powered electrolysis. It also reviews policy initiatives and government programs that support hydrogen and sustainable energy in South Africa, aligning with the SDGs. Overall, the findings underscore the trade-offs in hydrogen development, emphasising opportunities for resource utilisation while addressing deployment challenges. Full article

The Panoma Field in the Hugoton Embayment, Kansas, has produced significant gas resources from thousands of wells perforating the Permian Chase and Council Grove Groups. Variability in gas production from these formations is controlled by facies-influenced petrophysical properties. The use of geological facies data in numerical modeling is often limited to delineating regions of interest without intrinsic use in estimating petrophysical properties. Machine learning provides opportunities to integrate facies data into the numerical model-building process. In this study, we employ facies data in optimizing a numerical model permeability matrix scaling parameter using Monte Carlo Simulation of Markov Switching Dynamic Regression and machine learning. Realizations of the scaling parameter are included in a machine learning facies prediction workflow to identify the parameter that maximizes facies prediction accuracy, with test accuracy as high as 83%. A 3D numerical model was constructed to represent the interlayered carbonate, shale, and non-marine sandstones facies typical of the Council Grove intervals. Multiple field development and completion scenarios were evaluated to maximize cumulative gas recovery and assess the role of facies distribution on reservoir performance. History matching results of historical gas production demonstrate strong coupling between facies distribution and the optimized permeability, emphasizing the importance of facies data integration in reservoir property modeling and gas production estimation in Permian reservoirs. This implies that probabilistically constrained permeability scaling using the Monte Carlo and machine learning workflow produces more realistic modeling compared to traditional approaches. Full article

Climate warming puts new selective pressures on natural populations, but there are few quantitative measurements of selection in natural populations over protracted time periods. Observations made at the beginning and end ofa 47-year cumulative increase of 2.7 °C in the mean September temperature in Northern Minnesota, USA, permit quantitative estimation of selection against a suite of alleles at a single locus determining the expressionof dark color forms in populations of the meadow spittlebug, Philaenus spumarius (L.) (Hemiptera: Cercopoidea: Aphrophoridae). Alternative methods of estimation of the selection coefficient s, a measure of the intensity of selection, produce values of s = 0.0125 and 0.0218, respectively, corresponding to a disadvantage of about one to two percent per year or, since P. spumarius is univoltine, per round of selection. The existence of a locus under selection presents an opportunity for molecular localization and characterization of the genetic locus determining color form. Philaenus spumarius is of particular interest in Europe, as it is the major local vector of the bacterial plant pathogen Xylella fastidiosa. Full article

ALS is a multistep disease, in which (epi)genetic, environmental, and age-related processes, including senescence, converge over decades to reduce resilience resulting in self-sustaining symptomatic disease. The multistep model visualizes five to six impactful events in sporadic ALS, but fewer in those carrying high-penetrance mutations, such as SOD1, FUS, or C9orf72 expansions. The timing, duration, and cumulative effects of specific steps are presumed to have individual variability but, the steps themselves are inferred since they have not been observed and remain agnostic as to biological identity. Nevertheless, the model gives an opportunity to integrate genetics, aging, environmental exposures, and systems-level vulnerability into a single framework. Acting as step modifiers, environmental exposures including trauma lower the threshold for step acquisition, accelerate the accumulation of steps, influence the anatomical site of disease onset, and unmask preclinical disease. Because ALS emerges from the gradual collapse of multiple layers of biological robustness, tackling a single pathway will be insufficient and the multistep model forces a reconsideration of therapeutic timing and strategies. Protection against early-life insults, anti-aging, and anti-senescent therapies may curtail step accumulation preventing ALS from exceeding threshold and disease manifestation. Full article

Evaluating innovation and optimising its role in the inventions is fundamental for applied research, that requires planning the use of available resources. Traditional assessment approaches often miss to capture how innovation stagnates between the ideation and prototyping phases (the Valley of Death), and to learn how innovation emerges from intermediate-steps contributed by individuals. This paper focuses on tracing innovation as an approach enabling mapping of pathways of intermediate-steps and opportunities for valorising unplanned outcomes. We adopt a qualitative case study to explore how innovation pathways can be conceptualised through technological readiness levels. The operational settings of an EU-funded project defined the boundaries of the study. A network analysis explored relationships among themes that emerged from respondents involved in the activities, following an inductive approach to derive themes from data. Findings indicate that intermediate innovation steps, including failures, are viewed as cumulative contributions to novelty. Their documentation is seen as an investment for unlocking latent value embedded in distributed knowledge. Within this scope, we outline a blockchain-based knowledge graph as a proof-of-concept for tracing cumulative contributions, identifying breakthroughs leading to technological maturity and supporting generation of hypothesis grounded on experimental trials. As a result, we suggest that paths recombining prior knowledge into novelty encode latent value that can be interpreted as a function of the network topology, and propose a conceptual framework for analysing value by means of information theory metrics applicable to innovation graphs. Full article

Parkinson’s disease (PD) is a progressive and heterogeneous neurodegenerative disorder and one of the fastest-growing causes of neurological disability worldwide. Although historically defined by motor manifestations resulting from nigrostriatal dopaminergic degeneration, PD is now recognized as a multisystem disorder. Non-motor features—including autonomic dysfunction, neuropsychiatric symptoms, cognitive impairment, and sleep-related disorders—frequently precede motor onset by years or even decades, delineating a clinically meaningful prodromal phase. The aetiology of PD reflects a complex interplay between genetic susceptibility and environmental exposures. Approximately 20% of cases are linked to identifiable pathogenic variants, most commonly in LRRK2, GBA1, and SNCA, whereas the majority arise from cumulative interactions among environmental factors, lifestyle determinants, and common genetic risk variants rather than from single causal mechanisms. Despite substantial advances in understanding disease biology, current therapies remain fundamentally symptomatic. Dopaminergic pharmacotherapy and device-aided interventions improve motor function and, in selected contexts, functional outcomes, but they do not modify disease progression. Non-motor symptoms remain a dominant driver of disability and reduced quality of life. Recent conceptual frameworks propose redefining PD as a biologically defined α-synucleinopathy. Emerging biomarkers, including α-synuclein seed amplification assays in cerebrospinal fluid and peripheral tissues, offer unprecedented opportunities to define biological disease, enable early detection, and stratify patients. However, biomarker positivity currently informs diagnosis and classification rather than prognostication or therapeutic selection, and validated intermediate endpoints linking biomarker change to sustained functional benefit remain lacking. Consequently, translation into disease-modifying therapies has been constrained by late-stage intervention, reliance on clinically defined populations, limited trial generalizability, and marked global inequities in access to advanced diagnostics and treatments. This narrative review synthesizes current evidence on PD epidemiology, diagnosis, aetiology, progression, and treatment, emphasizing gene–environment interactions, convergence on shared pathogenic pathways, limitations of existing therapeutic paradigms, and the as-yet unrealized potential of biologically informed precision care. Full article

Therapeutic inertia in lipid-lowering treatment remains a striking paradox of modern cardiovascular medicine: at a time when the causal role of LDL-cholesterol in atherosclerotic disease is unequivocal and potent therapies are widely available, a substantial proportion of high- and very-high-risk patients still fail to receive timely treatment intensification. Contemporary European and international data consistently show fewer than one in three patients in secondary prevention achieve guideline-recommended LDL-C targets, revealing a persistent and unacceptable gap between scientific evidence and clinical reality. This narrative review examines therapeutic inertia as a key explanatory framework for this gap, describing its epidemiology, mechanisms, and clinical consequences in secondary cardiovascular prevention. We summarize the main physician-, patient-, and system-level determinants and propose recurrent clinician “phenotypes” of inertia that may help explain why opportunities are missed even in the highest-risk patients. The consequences are profound: therapeutic inertia contributes to what we propose as the conceptual framework of an “avoidable atherosclerotic burden”, the cumulative vascular injury that accrues each period in which LDL-C remains above target, translating into higher rates of avoidable cardiovascular events, and increased healthcare costs. Emerging strategies such as upfront combination therapy, decision-support systems, structured lipid pathways, and the integration of artificial intelligence offer practical tools to shift lipid management from reactive to proactive care. Overcoming therapeutic inertia is therefore not merely a matter of improving process metrics, but a clinical and ethical imperative. Closing the gap between evidence and practice requires transforming optimal lipid management from an exception into a system-level default, ensuring that every patient receives the full benefit of therapies proven to save lives. This work proposes a novel characterization of clinician ‘phenotypes’ and the concept of ‘avoidable atherosclerotic burden’ as a framework to understand and address this gap. Full article