Search Results (92)

Background: Abdominal aortic aneurysm (AAA) is a chronic inflammatory disease characterized by the proteolytic breakdown of the extracellular matrix. A clinical biomarker is needed for risk stratification and prognosis. Methods: In this single-center, 5-year observational study, 452 patients were enrolled: 343 with AAA (≥3 cm), and 109 controls (<3 cm). Plasma levels of six inflammatory proteins (human epididymis protein 4 (HE4), matrix metalloproteinase (MMP) 1 and 3, cathepsin S, chitinase 3 like-1, cathepsin S, and B-cell activating factor (BAFF)) were quantified at baseline. Patients were followed for a total of 5 years (60 months), and major adverse cardiovascular events (MACEs, defined as the composite of myocardial infarction, cerebrovascular attack, and cardiovascular-related death) were recorded. A Cox proportional hazard model was created using biomarker levels, age, sex, hypertension, hypercholesterolemia, diabetes mellitus, smoking status, and coronary artery disease to determine whether the baseline levels of these proteins were associated with MACEs over 5 years. Results: HE4, MMP-3, BAFF, and cathepsin S levels were significantly elevated in AAA patients compared to controls (all p < 0.05). HE4/WFDC2, MMP-3, and Chitinase 3-like 1 were significantly linearly associated with AAA diameter at baseline. With every normalized unit increase in HE4/WFDC2, MMP-3, and Chitinase 3-like 1, there was an increase in abdominal aortic diameter by 0.154 (95% CI: 0.032–0.276, p = 0.013), 0.186 (95% CI: 0.064–0.309, p = 0.003), and 0.231 (0.110–0.353, p < 0.001) centimeters, respectively. Among patients with AAA, elevated HE4 was associated with higher risk of MACEs (adjusted HR 1.249; 95% CI: 1.057–1.476; p = 0.009). Patients with high baseline HE4 (≥9.338 ng/mL) had significantly lower freedom from MACEs at 5 years (76.7% vs. 84.8%, p = 0.022). Conclusions: HE4 may be a potential prognostic biomarker that can be used to risk stratify patients with AAA to better personalize treatment strategies to reduce adverse events. Full article

Bio-based nanomaterials (B-NMs), such as silica oxide (SiO₂)- and lignin (Lig)- based nanoparticles (NPs) derived from biomass waste, have gained attention in the last few years in the view of promoting the sustainability principles in several applications. However, scarce data are available about their safety. Thus, a hazard-testing strategy was designed considering as a reference the safe-and-sustainable-by-design (SSbD) framework for chemicals and materials, prioritizing the use of new approach methodologies (NAMs), such as in vitro and adverse outcome pathways (AOPs) approaches, for generating data about the potential hazard of B-NMs. Literature research was performed to identify the adverse outcomes (AOs) related to the selected B-NMs. All the AOPs investigated shared at least oxidative stress, inflammation and cytotoxicity as key events (KEs) that were investigated in lung and immune cells. The tested B-NMs resulted either non-toxic or moderately toxic towards human cells, validating their biocompatibility when compared to reference NMs of similar composition, but not of bio-origin. However, attention should be given to possible AOs deriving after specific functionalization of the B-NMs. Considering the lack of knowledge in this field, the studies performed represent a step forward in the state of the art of the safety assessment of B-NMs. Full article

The construction industry is considered one of the most hazardous industries. The accidents associated with construction equipment are a leading cause of fatalities in the U.S., with one-quarter of all fatalities in the construction industry due to equipment-related incidents, including collisions, struck-by events, and rollovers. While close collaboration among multiple equipment and humans is common, conventional collision alert mechanisms for equipment usually rely on distance sensors with static thresholds, often resulting in too many false alarms, causing drivers’ ignorance. Considering the collaborative operation scenario, this research proposes and develops a dynamic-threshold alert system by recognizing hazardous events based on the types of nearby objects with their orientation or postures and their distances to the system carrier equipment based on image-based recognition and Sim2Real techniques. Two experiments were conducted, and the results show that the system successfully reduced a large number of false near-collision alarms for the collaboration scenarios. Although the accuracy of object recognition and image-based distance estimation is feasible for practical use, it is also easily degraded in the self-obstruction scenario or for equipment with large and movable parts due to incorrect recognition of the bounding boxes of the target objects. Full article

Background: Mesenchymal stem cells (MSCs) have drawn significant attention for their regenerative potential and therapeutic applicability across a range of conditions, including cardiovascular diseases and age-related frailty. Despite extensive preclinical studies, there remain gaps in understanding the long-term safety and efficacy of MSC therapy in humans. This study aimed to assess the safety of intravenous MSC administration, evaluate the mean major adverse cardiac and cerebrovascular event (MACCE)-free period, and identify potential risk factors for MACCE development in patients receiving MSC therapy for various indications. Methods: A retrospective observational study was conducted on 2504 patients (mean age: 54.09 ± 11.65 years) who received intravenous adipose-derived MSC (AD-MSC) therapy between October 2014 and December 2023 at the Omotesando Helene Clinic, Tokyo, Japan. Patients received MSC doses ranging from 100 million to 2 billion cells, with the majority receiving 1–2 billion cells per treatment. Statistical analyses included multivariate Cox proportional hazards regression and Kaplan–Meier survival analysis to evaluate MACCE risk factors and event-free duration. Results: Over the follow-up period, the MACCE rate was exceptionally low at 0.2%. Multivariate analysis identified age as a significant risk factor for MACCE (hazard ratio: 1.127; 95% CI: 1.0418–1.219; p = 0.0029), while sex and MSC dose showed no significant association. Minor adverse events occurred in 0.8% of patients, with no severe adverse events reported. The study found MSC therapy to be safe, with a low adverse event rate and minimal risk of MACCE. Conclusions: This study demonstrates the safety of intravenous MSC therapy in a large cohort of patients, with a low incidence of MACCE and minimal adverse effects. Age was the only significant predictor of MACCE risk. Further prospective randomized studies are needed to validate these findings and explore the potential of MSC therapy in reducing MACCE risk and improving clinical outcomes across diverse indications. Full article

Extreme heat events, or heatwaves, exert significant impacts on human society, ecosystems, and the economy. The continuous development of remote sensing technology has facilitated the acquisition of high-quality data for assessing health risks associated with these extreme heat events. This study systematically reviews the evaluation factors and assessment framework for a spatially explicit assessment of heat-related health risks. The contribution of geospatial big data, with a particular focus on satellite observations, to these assessments was investigated. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat surface temperature (LST) are identified as the two most widely utilized data sources for mapping heat hazards. The incorporation of multi-sensor observations, along with the implementation of spatiotemporal fusion and downscaling techniques, enhances both the spatial resolution and temporal frequency of heat hazard characterization. It is essential to consider issues of justice and equality in heat-resilient planning and mitigation practices. Integrating heatwave risk assessment results with analyses of urban morphology, land use functions and infrastructure can provide critical information for government agencies to strategically plan urban layout, functions, and public service facilities while optimizing and enhancing urban green infrastructures. Full article

In the extreme polar marine environment, safety risks pose a significant threat to drilling vessels. By conducting a safety risk assessment, potential hazards can be predicted and identified, thereby significantly reducing the frequency of accidents and promoting the sustained stability of economic activities. This paper investigates a Bayesian-network-based risk assessment model for polar drilling operations. Grey relational analysis was employed to identify the main risk factors. The model is trained using 525 valid incident sample data and is combined with expert knowledge. The accuracy rate is above 88%. Additionally, corresponding decision-making recommendations are provided through sensitivity analysis. The three most sensitive elements to fire nodes are human error, other causes, and equipment damage, with sensitivity coefficients of 0.046, 0.042, and 0.022, respectively. In terms of deck/handrail collision nodes, the highly sensitive elements are related to lifting (totally more than 0.1). For the events that have already transpired, the probabilities of most related nodes are 0.73 and 0.74, both of which are above 0.5, thereby validating the accuracy of forward and backward reasoning. Risk assessments based on Bayesian networks can offer pertinent decision-making recommendations and preventive measures. Full article

This research aimed to apply a risk management methodology to multiple surface water sources in urban and rural areas of a developing country. The applied methodology enabled the identification of hazards, classification, and the prioritization of risks at 21 collection points in the rural area and 9 collection points in the urban area. Both rural and urban areas exhibited common events with a high-risk level, such as human access (100% in urban areas and 90% in rural areas), climatic events, and inadequate collection structures (100% of points in both urban and rural areas). However, rural areas presented specific risks associated with animal husbandry (70% of points with high risk), a lack of monitoring, limited infrastructure (30% of points with high risk), and wildlife, including birds and worms (50% of points with high risk in rural areas and 10% in urban points). On the other hand, urban areas faced challenges related to vandalism and sabotage (high risk in 40% of points). Understanding these similarities and differences permits integrated risk management among the various stakeholders who can contribute to risk management within a watershed. Full article

Coke oven gas (COG), as a by-product of the coking process and a mixture with a high hydrogen content, is an important potential component of the sustainable economy of the coking industry. Ongoing studies and analyses are looking at many opportunities for the utilization of coke oven gas, including for the production of hydrogen, methanol or other chemicals. However, it is important not to forget that all processes for the utilization of this gas may pose a potential hazard to humans and the environment. This is due to the physicochemical properties of COG and the content of flammable gases such as hydrogen, methane or carbon monoxide in its composition. Potential hazardous events are also related to the content of toxic substances in the composition of coke oven gas. The publication focuses on the occurrence of a fire or explosion as a result of the uncontrolled release of purified coke oven gas from the installation. The potential hazard zones associated with the occurrence of these phenomena are presented concerning different levels of hydrogen concentration in coke oven gas and the influence of selected factors on the range of these zones. Zones related to human deaths due to fire of coke oven gas reached a maximum range of about 130 m from the site of the failure, depending on the gas composition, level of damage and parameters of the installation. Zones related to human deaths due to the explosion of the coke oven gas did not occur. The zone related to the injury of humans as a result of the COG explosion reached a maximum range of about 12 m. Full article

Despite significant advances in technology and flood risk management, as well as the countless risk prevention initiatives undertaken by governments and institutions in recent decades, flood hazards persist in threatening human life and health, especially under the effects of climate change. To assess the effectiveness of the various programs or measures devised to protect human life and health from floods, it is crucial to measure and understand its impacts on society, establishing the capability to track indicators or metrics that reflect the spatial distribution and temporal progress of floods and their impacts. In this context, this study uses disaster loss data derived from international disaster databases adapted in regional context following the Nomenclature of Territorial Units for Statistics level 2 (or NUTS2), to examine the spatial distribution and temporal evolution of deaths, directly attributable to flood disasters. In addition, we explore the potential of currently available datasets in understanding and monitoring flood-related mortality, an important standardized progress indicator of flood disaster impacts. This study is framed within the United Nations’ Sustainable Development Goals (SDGs), recently adopted by the European Union, and is focused on the Union’s territories in the Mediterranean region, an area particularly sensitive to climate change. Results show interesting spatial patterns, and generally inconclusive temporal trends, although locally we see evidence of both an increase and a decline in flood mortality. In addition, this work discusses the currently available datasets potential, weaknesses and limitations, as well as the importance of tracking flood impacts on human life in a future increasingly influenced by extreme weather events and climate change. Full article

Lifeboats are life-saving equipment used when it is necessary to abandon a ship or, in some ships, for man-overboard situations (to collect persons from water). Every seafarer onboard a ship has a task related to lifeboat operation in an emergency. In order to master and practise the assigned tasks, be ready to react at any moment, and efficiently use life-saving equipment and appliances, seafarers on ships perform drills at prescribed intervals. Effective drill performance is of paramount importance, as it improves safety and enables crew members to practise lifeboat operations. However, although their primary role is life-saving, lifeboat drills have resulted in numerous accidents, causing injuries and fatalities, besides equipment damage. Therefore, it is necessary to prevent such unwanted events and discover their root causes. As the human factor is considered a significant cause of marine accidents, this paper aims to quantify human error probability (HEP) during lifeboat drills. In addition, because lifeboat drill accident data are scarce, this study adopted the Success Likelihood Index Method (SLIM) for human reliability analysis (HRA). Based on expert judgments, the tasks with the highest probability of human error and factors significantly influencing human performance during lifeboat drills are identified. According to the study results, the recovery of the lifeboat is the most hazardous phase with the highest HEP. In addition, the BN-SLIM is adopted to estimate the probability of human error during the recovery of the lifeboat. The task with the largest HEP is confirming the release lever is properly rested and hooks locked (HEP = 4.5%). Furthermore, the design and condition of equipment and Crew Competence are identified as the most important Performance-Shaping Factors (PSFs) that affect crew members’ performance. The BN-SLIM model was verified utilising a sensitivity analysis and validated by analysing real-life lifeboat drill accidents that occurred during lifeboat recovery. The results confirmed that the model could be used to analyse lifeboat accidents and for proactive preventive measures because most influencing factors are recognised, and acting on them can significantly reduce the HEP of the overall task, improve lifeboat safety, and save lives at sea. Full article

Safe landings are imperative to accomplish NASA’s Artemis goal to enable human exploration on the Moon, including sample collection missions. However, a process known as plume surface interaction (PSI) presents a significant hazard to lunar landings. PSI occurs when the engine exhaust of a lander interacts with the surface ejecting large amounts of regolith particles at high velocities that can interfere with the landing, disturb the surface, and damage hardware. To better understand PSI, the particle impact event (PIE) sensor is being developed to measure the kinetic energy and the flux of ejecta during landings, to quantify the potential damage, and to quantify the ejecta displaced. Multiple parameters were estimated to define the PIE instrument requirements. These estimates demonstrate that ejecta can travel at velocities of up to 800 m/s and impact the surrounding area with energies of up to 400 µJ. A significant amount of ejecta can be deposited several 10 s of meters away from the landing site, modifying the surface and causing dust-related challenges. The PIE sensor will be launched for the first time in an upcoming lunar lander. Then, PIE measurements will be used to improve PSI prediction capabilities and develop mitigation strategies to ensure safe landings. Full article

In response to the urgent global threat posed by human-induced extreme climate hazards, heatwaves are still systematically under-reported and under-researched in Thailand. This region is confronting a significant rise in heat-related mortality, which has resulted in hundreds of deaths, underscoring a pressing issue that needs to be addressed. This research article is one of the first to present a solution for assessing heatwave dynamics, using machine learning (ML) algorithms and geospatial technologies in this country. It analyzes heatwave metrics like heatwave number (HWN), heatwave frequency (HWF), heatwave duration (HWD), heatwave magnitude (HWM), and heatwave amplitude (HWA), combining satellite-derived land surface temperature (LST) data with ground-based air temperature ($T_{\mathrm{air}}$) observations from 1981 to 2019. The result reveals significant marked increases in both the frequency and intensity of daytime heatwaves in peri-urban areas, with the most pronounced changes being a 0.45-day/year in HWN, a 2.00-day/year in HWF, and a 0.27-day/year in HWD. This trend is notably less pronounced in urban areas. Conversely, rural regions are experiencing a significant escalation in nighttime heatwaves, with increases of 0.39 days/year in HWN, 1.44 days/year in HWF, and 0.14 days/year in HWD. Correlation analysis ($p<0.05$) reveals spatial heterogeneity in heatwave dynamics, with robust daytime correlations between $T_{\mathrm{air}}$ and LST in rural (HWN, HWF, HWD, $r>0.90$) and peri-urban (HWM, HWA, $r>0.65$) regions. This study emphasizes the importance of considering microclimatic variations in heatwave analysis, offering insights for targeted intervention strategies. It demonstrates how enhancing remote sensing with ML can facilitate the spatial–temporal analysis of heatwaves across diverse environments. This approach identifies critical risk areas in Thailand, guiding resilience efforts and serving as a model for managing similar microclimates, extending the applicability of this study. Overall, the study provides policymakers and stakeholders with potent tools for climate action and effective heatwave management. Furthermore, this research contributes to mitigating the impacts of extreme climate events, promoting resilience, and fostering environmental sustainability. Full article

The frequency and severity of natural or human-induced disaster events, such as floods, earthquakes, hurricanes, fires, pandemics, hazardous material spills, groundwater contamination, structural failures, explosions, etc., as well as their impacts, have greatly increased in recent decades due to population growth and extensive urbanization, among other factors. The World Bank estimates that the total cost of cities’ and communities’ vulnerability to these types of disasters could reach more than USD 300 billion per year by 2030. However, it has been argued that investment to improve the quality and resilience of engineered physical assets that are the backbone of modern societies, such as critical infrastructure, industrial facilities, and buildings, could significantly contribute to more sustainable and prosperous societies. Engineered assets are key to the delivery of essential services, such as transport, food, water, electricity supply, health and safety, etc. Some of these physical assets are integrated into asset systems and national or regional networks, with life cycles of several decades or even centuries. It is, therefore, of great importance that strategies and life cycle decisions, such as those related to short- and long-term capital investment planning, maintenance strategies, operational plans, and asset disposal, lead to the maximization of the value derived from these assets. Moreover, it is essential that the achievement of these goals is sustainable over time. Organizations dealing with engineering assets, both public and private, must, therefore, integrate sustainability and resilience concerns into everyday operations, using budgets that are often restricted, while also meeting demanding performance requirements in risky and uncertain environments. This Special Issue collates a selection of papers reporting the latest research and case studies regarding the trends and emerging strategies used to address these challenges, with contributions discussing how asset management principles and techniques can help to push the boundaries of sophistication and innovation to improve the life cycle management of engineered assets to ensure more sustainable and resilient cities and societies. Full article

Increased medical attention is needed as the prevalence of autism spectrum disorder (ASD) rises. Both cardiovascular disorder (CVD) and hyperlipidemia are closely associated with adult ASD. Shank3 plays a key genetic role in ASD. We hypothesized that Shank3 contributes to CVD development in young adults with ASD. In this study, we investigated whether Shank3 facilitates the development of atherosclerosis. Using Gene Set Enrichment Analysis software (Version No.: GSEA-4.0.3), we analyzed the data obtained from Shank3 knockout mice (Gene Expression Omnibus database), a human population-based study cohort (from Taiwan’s National Health Insurance Research Database), and a Shank3 knockdown cellular model. Shank3 knockout upregulated the expression of genes of cholesterol homeostasis and fatty acid metabolism but downregulated the expression of genes associated with inflammatory responses. Individuals with autism had higher risks of hyperlipidemia (adjusted hazard ratio (aHR): 1.39; p < 0.001), major adverse cardiac events (aHR: 2.67; p < 0.001), and stroke (aHR: 3.55; p < 0.001) than age- and sex-matched individuals without autism did. Shank3 downregulation suppressed tumor necrosis factor-α-induced fatty acid synthase expression; vascular cell adhesion molecule 1 expression; and downstream signaling pathways involving p38, Jun N-terminal kinase, and nuclear factor-κB. Thus, Shank3 may influence the development of early-onset atherosclerosis and CVD in ASD. Furthermore, regulating Shank3 expression may reduce inflammation-related disorders, such as atherosclerosis, by inhibiting tumor necrosis factor-alpha-mediated inflammatory cascades. Full article

Different sediment-related disasters due to torrential hazards, such as flash floods, debris flows, and landslides, can occur in an Alpine torrential catchment. When protecting infrastructure and human lives, different structural and non-structural protection measures can be used to mitigate permanent and future risks. An overview of the mitigation measures constructed near the Krvavec ski resort in northwest Slovenia (Central Europe) is presented. In May 2018, an extreme debris flood occurred in this area, causing significant economic damage. After the May 2018 event, different field investigations (i.e., geological and topographic surveys) and modeling applications (e.g., hydrological modeling, debris flow) have been conducted with the purpose of preparing the required input data for the design of protection measures against such disasters in future—due to climate change, more disasters are expected to happen in this torrential watershed. The mitigation includes the restoration of local streams, the construction of a large slit check dam for sediment retention, the construction of several smaller check dams and the construction of 16 flexible net barriers with an estimated ~8000 m³ retention volume for controlling in-channel erosion in steep torrential streams. Additionally, in order to observe and monitor potential future extreme events, an extensive monitoring system has been established in the investigated area. This monitoring system will cover measurements of flexible net corrosion, the estimation of concrete abrasion at check dams, periodical geodetic surveys using small drones (UAV), hydro-meteorological measurements using rainfall gauges and water level sensors. The recent extreme floods of August 2023 also hit this part of Slovenia, and this combination of technical countermeasures withstood the event and prevented large amounts of coarse debris from being transported to the downstream section and devastating infrastructure, as was the case in May 2018 during a less extreme event. Therefore, such mitigation measures can also be used in other torrential catchments in the Alpine environment. Full article