Search Results (363)

Background and Clinical Significance: Anaplastic thyroid cancer (ATC) is a rare and aggressive malignancy with a poor prognosis, where median survival typically ranges from 4 to 10 months. Advances in genetic profiling, particularly the identification of BRAF mutations, offer new opportunities for targeted therapy. Case Presentation: This case report details the journey of a woman in her late 50s diagnosed with symptomatic ATC. Initial immunohistochemistry (IHC) testing for BRAF mutations returned negative results, leaving the patient with limited treatment options and prompting her to pursue medical assistance in dying (MAiD). However, next-generation sequencing (NGS) confirmed a ^V600EBRAF mutation, and a basis for targeted therapy. The patient began treatment with dabrafenib-trametinib, followed by pembrolizumab as second-line therapy, ultimately extending her life by nearly seven months. Conclusions: This case underscores the importance of rapid and comprehensive diagnostic approaches, particularly the higher sensitivity of NGS over IHC for detecting BRAF mutations. The complexities of accessing newer therapies in Canada’s single-payer healthcare system are also emphasized. The utilization of newer rapid diagnostic technologies can have a direct impact on directing treatment for ATC and other aggressive malignancies. Full article

An optimization method for the spare parts configuration of marine equipment is investigated based on spare parts support probability and utilization rate indicators. First, a general expression for the spare parts utilization rate is presented, and analytical expressions for the spare parts support probability and utilization rate are derived for Gamma-type spare parts with non-exponential life distributions, which are commonly found in marine spare parts. The relationship between two calculation methods for the utilization rate of exponential-type spare parts, as a special case of Gamma-type spare parts, is discussed. Second, as the analytical expression for the Gamma-type spare parts utilization rate is relatively complex, an approximate calculation method for the spare parts utilization rate is provided. Under the condition of given support probability requirements, the spare parts utilization rate is calculated through three approaches: theoretical calculation, approximate calculation, and simulation experiment. The calculation results demonstrate the validity of the analytical expression for the spare parts utilization rate and the applicability of the approximate algorithm. Furthermore, an approximate algorithm for the Weibull-type spare parts utilization rate is presented and verified through simulation calculations. Subsequently, considering both spare parts support probability requirements and utilization rate requirements, a spare parts configuration optimization model is established with the objective of maximizing the cost ratio, and the calculation procedures are provided. Finally, the feasibility of the spare parts configuration optimization model is illustrated through case analysis. Full article

Automotive components’ exposure to prolonged random loading not only accumulates fatigue damage but also causes material stiffness degradation. The degradation of material mechanical properties leads to stress redistribution within the structure, which in turn affects the structural fatigue life. Conventional frequency-domain fatigue life analysis methods often fail to take into account performance degradation, whereas time-domain approaches are constrained by computational inefficiency in dynamic response calculations. To address this, a time-domain fatigue life analysis is proposed, integrating Long Short-Term Memory (LSTM) networks with performance degradation modeling. First, short-term dynamic response data of engineering structures that contain stiffness degradation parameters are utilized to establish a training set, and an LSTM surrogate model is trained to rapidly predict stress responses in time- and degree-varying structural performance degradation. Second, the time-varying dynamic responses obtained from the LSTM surrogate model are related to the principles the fatigue damage accumulation and Miner’s criterion to quantify the stiffness degradation effects. A computational framework has been developed for fatigue life prediction through iterative alternation between dynamic response calculations and fatigue damage assessments. Case studies on notched plates demonstrate that the LSTM surrogate model approach ensures accuracy while reducing structural fatigue life analysis time by more than three orders of magnitude compared to the finite element method (FEM). Under the application of 20,000s random road loads, the damage value of the reinforced plate obtained by the surrogate model method that takes into account performance degradation is lower by 10–25% compared to that calculated by the frequency-domain or time-domain methods that neglect degradation. Full article

Lithium-ion batteries (LIBs) dominate energy storage for electric vehicles (EVs) due to their high energy density, long cycle life, and low self-discharge. However, high costs, complex manufacturing, and the requirement for advanced battery management systems (BMSs) constrain their broader deployment. Therefore, extending the utility of LIBs through reuse is essential for economic and environmental sustainability. Retired EV batteries with 70–80% state-of-health (SOH) can be repurposed in battery energy storage systems (BESSs) to support power grids. Effective reuse depends on accurate and rapid assessment of SOH and state-of-safety (SOS), which relies on precise state-of-charge (SOC) detection, particularly for aged LIBs with elevated thermal and electrochemical risks. This review systematically surveys SOC, SOH, and SOS detection methods for second-life LIBs, covering model-based, data-driven, and hybrid approaches, and highlights strategies for a fast and reliable evaluation. It further examines power electronics topologies and control strategies for integrating second-life LIBs into power grids, focusing on safety, efficiency, and operational performance. Finally, it analyzes key factors within the closed-loop supply chain, particularly reverse logistics, and provides guidance on enhancing adoption and supporting the establishment of circular battery ecosystems. This review serves as a comprehensive resource for researchers, industry stakeholders, and policymakers aiming to optimize second-life utilization of traction LIBs. Full article

Celiac disease (CeD) is an immune-mediated enteropathy triggered by gluten in genetically susceptible individuals, with a heterogeneous clinical spectrum spanning classical gastrointestinal symptoms, extraintestinal manifestations, and subclinical forms. We synthesize contemporary epidemiology, immunopathogenesis, and the updated 2025 European Society for the Study of Coeliac Disease diagnostic framework. Adaptive responses to deamidated gliadin peptides presented by human leukocyte antigen (HLA)-DQ2/DQ8, together with interleukin-15-driven activation of intraepithelial lymphocytes (IELs), culminate in villous atrophy, crypt hyperplasia, and increased IELs. Serology centered on tissue transglutaminase immunoglobulin A (tTG-IgA) with total immunoglobulin A assessment remains first-line, complemented by standardized duodenal sampling (≥4 distal + 2 bulb biopsies) and selective HLA typing. The guidelines conditionally endorse a no-biopsy pathway for adults <45 years with tTG-IgA ≥10× upper limit of normal confirmed on a second sample, emphasizing shared decision-making and exclusion of red flags. We delineate differential diagnoses (tropical sprue, Crohn’s disease, common variable immunodeficiency, small intestinal bacterial overgrowth) and contrast CeD with non-celiac gluten sensitivity, which lacks villous atrophy, disease-specific serology, and HLA association. Emerging tools (immunohistochemistry, CD3/CD8/γδ IELs, video capsule endoscopy, confocal laser endomicroscopy) and the limitations of salivary/fecal assays are reviewed. Early detection improves quality of life and reduces healthcare utilization. Future directions include artificial intelligence-assisted imaging, molecular immunophenotyping, and non-dietary therapeutics. Full article

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications. Full article

Neurorehabilitation has become increasingly data-enabled, yet the conditions that most strongly modulate recovery, sleep consolidation, circadian alignment, medication ecology, and social–environmental context are rarely captured or acted upon. This opinion paper argues that an exposome perspective, defined as the cumulative pattern of external and internal exposures and their biological imprints across the life course, is not ancillary to rehabilitation but foundational to making therapy learnable, timely, and equitable. We propose a pragmatic model that centers on a minimal exposure dataset collected in minutes and interpreted at the point of care. Two clinical exemplars illustrate feasibility and utility. First, sleep and circadian rhythms: brief actigraphy and standardized reporting can make daily alertness windows visible, allowing teams to align high-intensity sessions to receptive states and to justify environmental adjustments as clinical interventions. Second, anticholinergic burden: a simple, trackable index can be integrated with functional goals to guide deprescribing and optimize cognitive availability for training. Implementation hinges less on new infrastructure than on workflow design: a short intake that surfaces high-yield exposures; embedding targets, e.g., sleep efficiency thresholds or anticholinergic load reductions, into plans of care; enabling secure import of device data; and training staff to interpret rhythm metrics and burden scores. We outline a parallel research agenda comprising pragmatic trials of bundled, exposure-informed care; longitudinal cohorts with time-stamped exposure streams; and causal methods suited to time-varying confounding, all under explicit equity and ethics safeguards. By measuring a few modifiable exposures and linking them to routine decisions, neurorehabilitation can convert context from a source of unexplained variance into actionable levers that improve outcomes and narrow unjust gaps in recovery. Full article

Video Capsule Endoscopycapsule endoscopy (VCE) has emerged as a minimally invasive diagnostic tool for detecting and monitoring small bowel involvement in polyposis syndromes. VCE is included in the surveillance guidelines of Peutz-Jeghers syndrome. In the remaining familial polyposis syndromes, VCE may facilitate the early detection of polyps, when indicated, particularly in areas beyond the reach of conventional endoscopy, thereby aiding timely detection. Colon capsule endoscopy has been studied in symptomatic, screening and polyp surveillance populations and the second-generation colon capsule has demonstrated excellent detection rates for advanced neoplasia, however its role in colonic polyposis requires further research. The role of the panenteric capsule has not been explored in polyposis syndromes as a panintestinal examination. Despite its advantages, VCE has notable limitations; it may miss small, flat, or hidden lesions and lacks the capability for tissue sampling or therapeutic intervention. In the future, advances in imaging technology, extended battery life, and the integration of artificial intelligence (AI) are expected to further enhance the utility of VCE. Our review aims to focus on the applications of VCE in polyposis syndromes and future perspectives. Full article

Background/objectives: High-quality pediatric critical care includes supporting children nearing the end-of-life (EOL) and their families. Cataloging existing interventions for children dying in the neonatal or pediatric intensive care unit (NICU, PICU) establishes critical areas for future research. In this scoping review, we evaluated characteristics of PICU EOL interventions. Methods: A librarian guided a search of OVID Medline, CINAHL, OVID PsycINFO, OVID Embase, Cochrane Central, and Web of Science, plus backwards and forwards reference searching. We included interprofessional interventions, defined as any systematic change (e.g., educational programs, symptom management, electronic medical record, etc.), for children dying from any cause. Studies were independently screened by two reviewers. Data were extracted by one team member and reviewed by a second. We extracted intervention elements, contextual factors, implementation barriers/facilitators, and generated frequencies from qualitative coding. Results: Of 11,643 screened articles, 44 met the inclusion criteria. Most were in neonatal ICUs (n = 28/44, 64%) and general PICUs (n = 10/44, 23%). Most interventions aimed to improve clinician knowledge (25/44, 57%), augment clinical structures and processes (n = 11/44, 25%), or enhance communication (n = 8/44, 18%). Common delivery methods included clinical practice changes (n = 25/44, 57%; e.g., protocols, order sets [n = 12]), and educational sessions (n = 20/44, 45%). Outcomes included clinician knowledge (n = 17/44, 39%), qualitative feedback (n = 18/44, 41%), feasibility/acceptability (n = 12/44, 27%), or treatment utilization (n = 11/44, 25%). Few examined families’ mental health (n = 3, 7%) or bereavement (n = 2, 5%). Few reported implementation facilitators or barriers. Conclusions: Most included studies targeted clinician outcomes through education. Designing, testing, and implementing interventions focused on family outcomes is a critical next step. Full article

Background: Psoriasis has a huge impact on a patient’s life. Treatment dissatisfaction and non-adherence are common among patients with psoriasis, partly due to discordance between individual preferences and recommended treatments. The modern strategy for psoriasis should be focused on human-centric treatment that recognizes the needs and preferences of patients with a goal for safe, effective, quality and acceptable health services for a lifetime. The aim of this analysis was to capture patients’ preferences with moderate-to-severe psoriasis regarding various treatment attributes. Methods: A specialized questionnaire containing four attributes with three levels, each, was used, followed by an orthogonal plan based on conjoint analysis. Nine combinations of therapeutic scenarios were produced as a result, to investigate participants’ preferences. Respondents were asked to rank alternatives from best to worst. Results: The risk of developing pneumonia or other serious infections within a decade seems to be higher in patients with an implied assigned value of 37. The second attribute was the type and frequency of the administration with a value of 27, followed by the treatment effectiveness with great improvement of body surface with a value of 25. The lowest utility (11) was the sustainability of early remission of psoriasis. Conclusions: Psoriasis patients want safe, effective and easy to administer treatments. Full article

As a large-scale flexible structure, the free-vibration characteristics of a horizontal single-axis solar tracking bracket (HSSTB) hold significance for its dynamic optimization design. However, due to material fabrication, construction processes, and harsh field service environments, structural parameters such as the elastic modulus inevitably exhibit uncertainty, leading to discrepancies between actual free-vibration characteristics and design values. This study considers the randomness of the steel elastic modulus and conducts a global sensitivity analysis of a real-life five-column HSSTB. First, the Kriging method is employed to build a surrogate model to describe the natural frequencies of the HSSTB and its stochastic parameters, which enables efficient evaluation of the statistical characteristics of the HSSTB’s natural frequencies. Further, the Sobol indices are utilized to quantify the influence of parameter randomness on the natural frequencies. The results indicate that the mean values of the first five natural frequencies are slightly lower than the design values. The first, fourth, and fifth natural frequencies of the five-column HSSTB are predominantly influenced by the middle three columns, while the second and third natural frequencies are more susceptible to the two edge columns. Full article

This study investigates the relationship between community commercial center spaces and elderly behavior, focusing on governance mechanisms that shape these spaces and their impact on enhancing elderly life and the community environment. Field research was conducted in the ‘Guohe 1000’ community commercial project in Shanghai, targeting individuals aged 60 and above with independent mobility, including wheelchair users. Through behavioral observation and interviews, both individual and group activities were examined, emphasizing behavioral patterns, spatial domains, and social interactions. Findings reveal that factors such as gender, age, and social networks are positively correlated with the spatial development of community commercial centers. To foster elderly-friendly environments, improvements are needed in utilization balance, secondary activity spaces, age-sensitive design, and operational management. The paper’s novelty lies in two aspects: first, it broadens research into community commercial centers by tracing the construction process of spatial forms; second, it applies environmental behaviorism and environmental gerontology frameworks to integrate individual and collective elderly behaviors into systematic data collection and quantitative analysis. Together, these insights contribute to more inclusive strategies for designing and managing community commercial complexes that support active aging and enhance urban social sustainability. Full article

Enhancing ultra-capacitor (UC) utilization and mitigating battery stress are pivotal for improving the energy management efficiency and service life of hybrid energy storage systems (HESSs). Conventional energy management strategies (EMSs), however, rely on fixed parameters and therefore struggle to allocate power flexibly or reduce battery degradation. This paper proposes a VMD-LSTM-based EMS that incorporates auto-tuning weight and constraint to address these limitations. First, a VMD-LSTM predictor was proposed to improve the velocity and road gradient prediction accuracy, thus leading an accurate power demand for EMS and enabling real-time parameter adaptation, especially in the nonlinear area. Second, the model predictive controller (MPC) was adopted to construct the EMS by solving a multi-objective problem using quadratic programming. Third, a combination of rule-based and fuzzy logic-based strategies was introduced to adjust the weights and constraints, optimizing UC utilization while alleviating the burden on batteries. Simulation results show that the proposed scheme boosts UC utilization by 10.98% and extends battery life by 19.75% compared to traditional MPC. These gains underscore the practical viability of intelligent, optimizing EMSs for HESSs. Full article

The increasing frequency of extreme high-temperature events has led to deteriorating thermal stability in power transmission lines and accelerated life of transformers. Conventional unit commitment (UC) employs static line rating (SLR) and neglects transformer lifetime degradation, posing hidden risks to system security in high-temperature and heavy-load scenarios. To address this challenge, this paper proposes a dispatch method that incorporates dynamic line rating (DLR) and transformer life loss under extreme high-temperature conditions. First, the conductor temperature-rise mechanism is formulated using the thermal balance theory, upon which a temperature-dependent DLR calculation model is developed. Second, the coupling relationship between transformer hot-spot temperature, load ratio, and ambient temperature is quantified, and an ambient temperature-driven transformer life cost function is formulated using linear damage accumulation theory. Finally, a unit commitment (UC) optimization model is established to minimize unit generation costs, transformer lifetime loss costs, and wind curtailment penalties costs, while satisfying power balance, transmission capacity, and other operational constraints. Simulation results on the IEEE 39-bus system demonstrate that, compared to conventional models, the proposed method improves transmission capacity utilization in high-temperature conditions by 12%, reduces transformer life loss costs by 69%, and lowers total operating costs by 4.9%. Full article

As a major energy producer and consumer, China has witnessed rapid growth in carbon emissions, which are closely linked to changes in regional climate and the environment. Water, energy, and food (W-E-F) are the three most critical components of human production and daily life, and achieving the coordinated development of these three resources and connecting them with climate change through the carbon emissions generated during their utilization processes has become a key issue for realizing regional ecological sustainable development. This study constructs a dynamic two-stage network slack-based measure-data envelopment analysis (SBM-DEA) model, which integrates the water–energy–food (W-E-F) system with the climate change process to evaluate China’s comprehensive ecological efficiency from 2011 to 2022, and adopts the Dagum Gini coefficient decomposition, kernel density estimation, hierarchical clustering, and geographical detector model to analyze provincial panel data, thereby assessing efficiency patterns, regional differences, and driving mechanisms. The novelty and contributions of this study can be summarized in three aspects. First, it establishes a unified framework that incorporates the W-E-F nexus and climate change into a dynamic network SBM-DEA model, enabling a more systematic assessment of ecological efficiency. Second, it uncovers that interregional overlap effects and policy-driven factors are the dominant sources of spatial and temporal disparities in ecological efficiency. Third, it further quantifies the interactive effects among key driving factors using Geodetector, thus offering practical insights for regional coordination and policy design. The results show that China’s national ecological efficiency is at a medium level. Southern China has consistently maintained a leading position, while provinces in northwest and southwest China have remained relatively backward; the efficiency of the water–energy–food integration stage is relatively high, whereas the efficiency of the climate change stage is medium and exhibits significant temporal fluctuations. Interregional differences are the main source of efficiency gaps; ecological quality, environmental protection efforts, and population size are identified as the primary driving factors, and their interaction effects have intensified spatial heterogeneity. In addition, sub-indicator analysis reveals that the efficiency related to total wastewater, air pollutant emissions, and agricultural pollution shows good synergy, while the efficiency associated with sudden environmental change events is highly volatile and has weak correlations with other undesirable outputs. These findings deepen the understanding of the water–energy–food-climate system and provide policy implications for strengthening ecological governance and regional coordination. Full article