Search Results (2,020)

Familial hypercholesterolemia (FH) is a common genetic disorder with a fairly constant worldwide prevalence of 1 case per 311 individuals worldwide. It is characterized by severe hypercholesterolemia from birth, early atherosclerosis and death from cardiovascular disease at a young age. Diagnosis and treatment from childhood are essential to reduce cardiovascular mortality. Many countries have developed a strategy of implementing pediatric screening, which has led to an increase in diagnoses. This paper evaluates the screening strategies implemented in different countries worldwide. First, we examined which schemes were preferred in various national contexts in Europe. Next, we evaluated the screening methods used in the US, Canada, Australia and Japan. Finally, we researched the screening strategies proposed in some low-resource countries, discovering the difficulties and limitations they face. We have highlighted a wide range of realities, from small-scale pilot studies to cutting-edge proposals. We have also emphasized that, while the topic is certainly of interest, it is burdened by multiple difficulties and unresolved questions. Full article

Multiple myeloma is a clonal plasma cell malignancy with a highly variable range of clinical manifestations. Over recent decades, substantial progress has been made in laboratory diagnostics, which has deepened our understanding of disease biology, improved risk stratification, and informed treatment strategies. In an era of transformation and innovation, conventional laboratory methods remain essential, as cutting-edge technologies might not be immediately accessible to all laboratories. Nonetheless, even widely used laboratory methodologies present many challenges, such as variability in assay performance, interpretative criteria, and standardization. This review by the Portuguese Multiple Myeloma Group of the Portuguese Society of Hematology provides a comprehensive overview and practical appraisal of current conventional laboratory methods employed for multiple myeloma diagnosis. Full article

Nickel-based alloys, including Inconel 718 and alloy 625, are indispensable in industries such as aerospace, marine, and nuclear energy due to their exceptional mechanical strength, high-temperature performance, and corrosion resistance. However, these very properties pose severe machining challenges, such as accelerated tool wear, poor surface finish, and high cutting forces. Although several studies have investigated coatings, lubrication strategies, and process optimization, a comprehensive and up-to-date integration of these advancements is still lacking. To address this gap, a systematic review was conducted using Web of Science and Scopus databases. The inclusion criteria focused on peer-reviewed journal and conference articles published in the last eleven years (2014–2025), written in English, and directly addressing machining of nickel-based alloys, with particular emphasis on tool coatings, lubrication/cooling technologies, and machinability optimization. Exclusion criteria included duplicate records, non-English documents, papers lacking experimental or modeling results, and studies unrelated to tool life or coating performance. Following this screening process, 101 high-quality articles were selected for detailed analysis. The novelty of this work lies in synthesizing comparative insights across TiAlN, TiSiN, and CrAlSiN coatings, alongside advanced lubrication methods such as HPC, MQL, nano-MQL, and cryogenic cooling. Results highlight that CrAlSiN coatings retain hardness up to 36 ± 2 GPa after exposure to 700 °C and extend tool life by 4.2× compared to TiAlN, while optimized cooling strategies reduce flank wear by over 30% and improve tool longevity by up to 133%. The integration of coating performance, thermal stability, and lubrication effects into a unified framework provides actionable guidelines for machining optimization. The study concludes by proposing future research directions, including hybrid coatings, real-time process monitoring, and sustainable lubrication technologies, to bridge the remaining gaps in machinability and promote industrial adoption. This integrative approach establishes a robust foundation for advancing machining strategies of nickel-based superalloys, ensuring improved productivity, reduced costs, and enhanced component reliability. Full article

The cement industry accounts for approximately 7–8% of global CO₂ emissions, primarily due to energy-intensive clinker production and limestone calcination. With cement demand continuing to rise, particularly in emerging economies, decarbonization has become an urgent global challenge. The objective of this study is to systematically map and synthesize existing evidence on technological pathways, policy measures, and economic barriers to four core decarbonization strategies: clinker substitution, energy efficiency, alternative fuels, as well as carbon capture, utilization, and storage (CCUS) in the cement sector, with the goal of identifying practical strategies that can align industry practice with long-term climate goals. A scoping review methodology was adopted, drawing on peer-reviewed journal articles, technical reports, and policy documents to ensure a comprehensive perspective. The results demonstrate that each mitigation pathway is technically feasible but faces substantial real-world constraints. Clinker substitution delivers immediate reduction but is limited by SCM availability/quality, durability qualification, and conservative codes; LC₃ is promising where clay logistics allow. Energy-efficiency measures like waste-heat recovery and advanced controls reduce fuel use but face high capital expenditure, downtime, and diminishing returns in modern plants. Alternative fuels can reduce combustion-related emissions but face challenges of supply chains, technical integration challenges, quality, weak waste-management systems, and regulatory acceptance. CCUS, the most considerable long-term potential, addresses process CO₂ and enables deep reductions, but remains commercially unviable due to current economics, high costs, limited policy support, lack of large-scale deployment, and access to transport and storage. Cross-cutting economic challenges, regulatory gaps, skill shortages, and social resistance including NIMBYism further slow adoption, particularly in low-income regions. This study concludes that a single pathway is insufficient. An integrated portfolio supported by modernized standards, targeted policy incentives, expanded access to SCMs and waste fuels, scaled CCUS investment, and international collaboration is essential to bridge the gap between climate ambition and industrial implementation. Key recommendations include modernizing cement standards to support higher clinker replacement, providing incentives for energy-efficient upgrades, scaling CCUS through joint investment and carbon pricing and expanding access to biomass and waste-derived fuels. Full article

Building energy flexibility is essential for integrating renewables, optimizing energy use, and ensuring grid stability. While renewable and storage systems are increasingly used in buildings, poorly designed storage strategies often cause supply-demand mismatches, and a comprehensive, indicator-based assessment approach for quantifying flexibility remains lacking. Therefore, this study designs customized energy storage regulation strategies and constructs a comprehensive energy flexibility assessment scheme to address key issues in supply-demand coordination and energy flexibility evaluation. LSTM and Rolling-XGB methods are used to predict building energy consumption and PV generation, respectively. Based on battery safety constraints, a data-driven battery energy storage system (BESS) model simulates battery behavior to evaluate and compare building energy flexibility under two scenarios: (1) uncoordinated PV-BESS, and (2) coordinated PV-BESS with load forecasting. A practical validation was conducted using a net-zero-carbon building as the case study. Simulation results show that the data-driven BESS model improves building energy flexibility and reduces electricity costs through optimized battery sizing, tailored storage strategies, and consideration of local time-of-use tariffs. In the case study, local energy coverage reached 62.75%, surplus time increased to 34.77%, and costs were cut by nearly 40% compared to the PV-only scenario, demonstrating the significant benefits brought by the proposed BESS model that integrates load forecasting and PV generation prediction features. Full article

Offshore reservoirs in the high water-cut stage present significant development challenges, including declining production, complex remaining oil distribution, and the inadequacy of conventional evaluation methods to capture intricate flow dynamics. To overcome these limitations, this study introduces a novel approach based on flow diagnostics for performance evaluation and potential adjustment. The method integrates key metrics such as time-of-flight (TOF) and the dynamic Lorenz coefficient, supported by reservoir engineering principles and numerical simulation, to construct a multi-parameter evaluation system. This system, which also incorporates injection–production communication volume and inter-well fluid allocation factors, precisely quantifies and visualizes waterflood displacement processes and sweep efficiency. Applied to the QHD32 oilfield, this framework was used to establish specific thresholds for operational adjustments. These include criteria for infill drilling (waterflooded ratio < 45%, remaining oil thickness > 6 m, TOF > 200 days), conformance control (TOF < 50 days, dynamic Lorenz coefficient > 0.5), and artificial lift optimization (remaining oil thickness ratio > 2/3, TOF > 200 days). Field validation confirmed the efficacy of this approach: an additional cumulative oil production of 165,600 m³ was achieved from infill drilling in the C29 well group, while displacement adjustments in the B03 well group increased oil production by 2.2–3.8 tons/day, demonstrating a significant enhancement in waterflooding performance. This research provides a theoretical foundation and a technical pathway for the refined development of offshore heavy oil reservoirs at the ultra-high water-cut stage, offering a robust framework for the sustainable management of analogous reservoirs worldwide. Full article

Background: One of the primary strategies for preventing and reducing infectious diseases is vaccination. There are numerous licensed vaccinations of various kinds that can prevent viral infection by triggering the immune system’s reaction to specific antigens beforehand. To elicit a stronger immune response, however, two elements of the immune system—humoral and cellular immunity—should be addressed. Since they target proteins that are difficult to alter, recent innovative techniques for vaccine delivery systems—such as liposomes, nanogels, microemulsions, etc.—have shown excellent immunogenicity qualities. Methods: PubMed, ScienceDirect, and Google Scholar were used as the databases for literature search, and keywords such as “Virosomes”, “Hemagglutinin”, and “IRIV” were selected to ensure relevant articles were included. Results: This article examines a cutting-edge method called virosomes, which are an effective way to deliver pharmaceutically active ingredients that target a variety of illnesses and ailments, as well as vaccines. This resulted from the fact that virosomes possess numerous structural characteristics that might trigger sophisticated immune reactions by utilizing the inactivated virus’s envelope or by imitating it through recombinant methods. Conclusions: Here, we will walk you through the history of virosome development, explore various manufacturing techniques, provide an overview of the latest patents, and conclude with the potential for more virosomal revolutions. Full article

Tool wear detection is very important in CNC machine tool cutting. Once the tool is excessively worn, it is not only easy to cause the workpiece to be scrapped, but even to damage the machine. Therefore, common external turning tools of CNC machines are studied. The effect of tool nose wear on machining accuracy was analyzed by a building mathematical model. According to different wear conditions, a linear detection method based on edge images and input features was proposed to detect the main and secondary cutting edges, which helped determine the theoretical center of the tool nose and build a morphological visual model. For different error cases, the axial and radial error compensation strategies were proposed, respectively. By comparing the experimental data of four kinds of workpieces before and after compensation machining, the average errors of them were reduced separately, and the maximum value reached 79.2%, which verified the effectiveness of the compensation strategy. The intelligent compensation strategies will significantly improve the micro-machining accuracy and efficiency of the external turning tools in CNC machines. Full article

To overcome the challenges of conventional low-carbon retrofits for existing buildings—such as high construction volume, cost, and implementation difficulty—this study proposes a minimally invasive design and optimization method for Photovoltaic–Energy Storage–Direct Current–Flexible (PEDF) systems. The goal is to maximize energy savings and economic benefits while minimizing physical intervention. First, the minimally invasive retrofit challenge is decomposed into two coupled problems: (1) collaborative PV-ESS layout optimization and (2) flexible energy management optimization. A co-optimization framework is then developed to address them. For the layout problem, a model with multiple constraints is established to minimize retrofitting workload and maximize initial system performance. A co-evolutionary algorithm is employed to handle the synergistic effects of electrical pathways on equipment placement, efficiently obtaining an optimal solution set that satisfies the minimally invasive requirements. For the operation problem, an energy management model is developed to maximize operational economy and optimize grid interactivity. A deep reinforcement learning (DRL) agent is trained to adaptively make optimal charging/discharging decisions. Case simulations of a typical office building show that the proposed method performs robustly across various scenarios (e.g., office, commercial, and public buildings). It achieves an energy saving rate exceeding 20% and reduces operational costs by 10–15%. Moreover, it significantly improves building–grid interaction: peak demand is reduced by 33%, power fluctuations are cut by 75%, and voltage deviation remains below 5%. The DRL-based policy outperforms both rule-based strategies and the DDPG algorithm in smoothing grid power fluctuations and increasing the PV self-consumption rate. Full article

Making effective decisions about scaling up on-farm irrigation practices to the district level requires a comprehensive assessment of irrigation management at the farm level. In this context, a bucket-type water mass balance model was developed, calibrated, and validated over five irrigation seasons on a 121-hectare rice farm located in the lower Ter River valley (north-east Spain), to assess the water use efficiency and the impact of different irrigation practices on water savings. The model was implemented considering the spatial variability of the soils within the farm. It showed a satisfactory performance in both the calibration (2020, 2021, 2022) and validation (2023, 2024) cropping seasons, with NSE values greater than 0.50, PBIAS lower than ±20%, and RSR lower than 0.70. After model validation, the simulation of alternative water management practices revealed that the 10-day fixed-turn irrigation reduced irrigation water use by 30% compared to the traditional water management, although it may negatively impact rice yield. Simulations of an early irrigation cut-off at the end of the season and dry seeding with delayed flooding accounted for 17% and 15% irrigation water savings, respectively. The implementation of the no-runoff practice only accounted for a 6% reduction in water use. The water-saving potential of the simulated strategies was mainly driven by shortening the flooded period of rice paddies, thus demonstrating that managing the ponding water level is critical to diminishing water use in rice irrigation. Full article

Background/Objectives: The variability in the structure of the deep cerebral venous system in neonates is increasingly recognised, as are the vascular structural factors involved in the development of the germinal matrix/intraventricular haemorrhage (GM/IVH) in premature infants. We aimed to characterise the ultrasound patterns of these veins in different categories of newborns and to assess if there is a correlation between certain patterns and angles and the presence of GM/IVH. Methods: One hundred neonates (68 at-term and 32 preterm) were included in this research. The pattern of venous drainage and the angle at the confluence between the terminal vein (TV) and internal cerebral vein (ICV) were identified on coronal sections through the anterior fontanel. The normal pattern was considered as that in which the confluence between the TV and the ICV could be identified, and the atypical pattern was considered the situation in which no confluence or terminal vein was identified. Results: There was no statistically significant difference regarding the normal or atypical venous patterns between the groups (p < 0.443), neither regarding the angles between TV and ICV between term and preterm neonates (p < 0.279—left; p < 0.718—right), and singletons and twins (p < 0.745 left; p < 0.418 right), or between the angles on the left and on the right in the whole group (p < 0.121 and the subgroups of term (p < 0.440) and preterm neonates (p < 0.092). The mean value of the angle at the confluence between the TV and the ICV on the left, was significantly lower in the premature infants with GM/IVH (124.90° vs. 137.02°; p = 0.012), being a good predictor for the occurrence of the lesion (AUC = 0.793; IC 95%: 0.580–1.006; p = 0.018), with a sensitivity of 79%, a specificity of 67%, and a cut-off value of 126.90°. In patients with GM/IVH, the angle was significantly lower on the side with the haemorrhage than on the side without haemorrhage (p < 0.043). Conclusions: There is no difference in the central venous pattern or angle at the confluence of the TV and the ICV between different categories of neonates. The angle at the confluence between the TV and ICV could identify the cases at risk for GM/IVH as well as the side of occurrence of the haemorrhage, offering the opportunity of developing personalised prevention strategies. The lack of an MRI comparator of these measurements limits the practical importance of this study. Full article

Intelligent ventilation systems can optimize airflow regulation to enhance mining safety and reduce energy consumption, driving green development in mineral resource extraction. This paper systematically elaborates on the overall architecture, cutting-edge advances, and core technologies of current intelligent mining ventilation. Building upon this foundation, a comprehensive intelligent mine ventilation solution encompassing the entire process of ventilation design, optimization, and operation is constructed based on a five-layer architecture, integrating key technologies such as intelligent sensing, real-time solving, airflow regulation, and remote control, providing an overarching framework for smart mine ventilation development. To address the computational efficiency bottleneck of traditional methods, an improved loop-solving method based on minimal independent closed loops is realized, achieving near real-time analysis of ventilation networks. Furthermore, a multi-level airflow regulation strategy is realized, including the methods of optimization control based on mixed integer linear programming and equipment-driven demand-based regulation, effectively resolving the challenges of calculating nonlinear programming models. Case studies indicate that the intelligent ventilation system significantly enhances mine safety and efficiency, leading to approximately 10–20% energy saving, a 40–60% quicker emergency response, and an average increase of about 20% in the utilization of fresh air at working faces through its remote and real-time control capabilities. Full article

Candida auris has emerged as a global public health threat due to its high mortality rates, multidrug resistance, and rapid transmission in healthcare settings. This study reports the first documented cases of C. auris candidemia in Portugal, comprising eight isolates from candidemia and colonised patients admitted to a major hospital in northern Portugal in 2023. Whole-genome sequencing (WGS) was performed to determine the phylogenetic relationships of the isolates, which were classified as belonging to Clade I. Genome sequencing also enabled the detection of missense mutations in antifungal resistance genes, which were correlated with antifungal susceptibility profiles determined according to EUCAST (European Committee on Antimicrobial Susceptibility Test) protocols and guidelines. All isolates exhibited resistance to fluconazole and amphotericin B according to the recently established EUCAST epidemiological cut-offs (ECOFFs). Most of the isolates showed a resistant phenotype to anidulafungin and micafungin. All isolates were resistant to caspofungin. Missense mutations identified included Y132F in ERG11, E709D in CDR1, A583S in TAC1b, K52N and E1464K in SNQ2, K74E in CIS2, M192I in ERG4, a novel mutation S237T in CRZ1, and variants in GCN5, a gene involved in chromatin remodelling and stress-response regulation. Identifying known and novel mutations highlights the evolution of antifungal resistance mechanisms in C. auris. These findings underscore the need for further research to understand C. auris resistance pathways and to guide effective clinical management strategies. Full article

Office is one of the core sectors within the buildings sector, attracting tens of billions of dollars in global real estate investment flows. Most of these are achieved through non-listed investments, where office real estate represents one of the major sectoral investment exposures for many global institutional real estate investors and investment managers. The rising interest rates in recent years have been a significant concern, impacting the global real estate markets significantly. Based on these premises and by using quarterly total returns of non-listed office real estate across the US, UK, Germany, Canada, and Australia from June 2008 to June 2024, this research assesses the risk-adjusted performance and portfolio diversification benefits of non-listed office real estate across the five markets over both interest rate cut and interest rate hike cycles. The results empirically validate the added-value role of non-listed office real estate in institutional multi-asset portfolios across the UK, Germany, Canada, and Australia during the interest rate hike cycle preceding the COVID recession. In the 10% capped real estate allocation, the average allocation was 0.7% in the UK, 0.4% in Germany, 0.7% in Canada, and 9.1% in Australia. Over the interest rate hike cycle after the COVID recession, Australian non-listed office real estate offered enhanced benefits as part of the multi-asset portfolio, constituting an average of 0.8% in the capped real estate allocation. In the global non-listed office real estate portfolio, the US dominated the portfolio across varying interest rate cycles, with an average allocation of approximately 65%. The average allocation to Australia was 24.2% over the interest rate hike cycles, while the average allocation to Germany was 32.0% over the interest rate cut cycles. These findings offer institutional real estate investors and investment managers critical and practical insights into how the investment performance and portfolio construction strategy of office assets—an essential component of the buildings sector and a major non-listed real estate investment exposure for global institutional real estate investors—respond to macro-financial and interest rate cycles. The investment implications of the findings are also discussed. Full article

Knee osteoarthritis (OA) is a complex condition with varying pain, functional limitations, and structural changes. Traditional classification using radiographic grades may not fully reflect individual patient experiences. This study aimed to establish WOMAC score cut-offs for KL grades and identify knee OA phenotypes through cluster analysis in a cohort of 99 adults, examining functional and radiological status, factors such as age, sex, body mass index (BMI), comorbidities, and psychological status. Receiver operating characteristic (ROC) analysis helped establish WOMAC cut-off scores related to KL grades, and cluster analysis identified phenotypic subgroups. The analysis showed that higher WOMAC scores correlated with advanced KL grades, leading to a five-tier classification of symptomatic severity: minimal or no symptoms (≤24), mild (25–41), moderate (42–69), severe (70–86), and extreme (≥87). Cluster analysis identified four distinct phenotypic groups: (1) younger patients exhibiting minimal symptoms and low KL grades; (2) individuals with moderate disease are characterized by functional deficits; (3) patients presenting with moderate-to-severe symptoms and significant joint narrowing; and (4) a subgroup experiencing severe pain, high levels of disability, advanced KL grades, elevated psychological distress, and an increased BMI. The study supports WOMAC cut-offs as key indicators of knee OA severity and shows that cluster analysis can reveal distinct phenotypes, underscoring the need for personalized management strategies in knee OA treatment. Full article