Search Results (2,100)

Mice genetically deficient in α-Klotho (henceforth Klotho) display accelerated aging. The mechanisms are only partially understood. Here, we examine how these relate to the 12 hallmarks of aging consisting of chronic inflammation (inflammaging), as well as damaging changes to the genome (DNA damage), telomeres, epigenetic regulation, proteostasis, nutrient sensing, mitochondria, stem cells, intercellular communication, macroautophagy, microbiome and cell replication (senescence). Inflammation aggravates the other hallmarks. We report that Klotho counters the majority of these hallmarks. It ameliorates mitochondrial function and reduces reactive oxygen species (ROS), telomere attrition and cellular senescence. It protects against inflammation by inhibiting NF-κB and the NLRP3 inflammasome. This applies to inflammaging, several chronic inflammatory diseases, atherosclerosis, diabetes, and Alzheimer’s disease. Klotho also counters some aging factors outside of these hallmarks. Low Klotho (often due to kidney disease) produces hyperphosphatemia, which injures cells (especially endothelial cells) and promotes aging. Another key action of Klotho is the mitigation of fibrosis in major organs (kidneys, heart, lungs and other), mainly through the inhibition of TGF-β and Wnt. Klotho also protects against muscle atrophy (sarcopenia)—a common feature of aging—and exhibits anti-cancer activity. We describe several factors that increase Klotho, and are potentially amenable to clinical therapy. Full article

The precision of data gathered from Ultra-Weak Fiber Bragg Grating (UWFBG) sensing technology is limited when measuring strain within asphalt pavements. To better understand its measurement mechanism and correct possible errors, this study examines the synergy deformation behavior between UWFBG and asphalt mixtures under loads. Initially, the mesoscopic model of asphalt mixture containing UWFBG was constructed using a discrete element model, followed by the validation of the model. Then, the propagation of microcracks at the interface between the asphalt mixture and UWFBG was analyzed, revealing damage characteristics of this material under various loading stages. Additionally, a quantitative relationship between the crack width and the monitoring strain was identified. The significant effect of introducing the sensor on crack propagation and interface debonding in strain response was also highlighted. The results indicate that when displacement exceeds 1.4 mm during a bending test, the number of both damage and microcracks increases markedly, with cracks progressively developing. Especially at the UWFBG interface subjected to a tensile load, microcrack growth rises sharply, leading to the failure of the interface. The mor-UWFBG interface is not the main damage location, but it is the most vulnerable location to damage and may be the one affecting the monitoring of UWFBG. Without sensors, a consistent linear relationship between monitoring strain and crack width is observed within the asphalt mixture. After introducing the UWFBG sensor, the strain-crack response of the asphalt mixture is divided into three stages: crack initiation, crack propagation, and interface debonding. When the crack width surpasses 0.03 mm, interface debonding significantly influences the strain growth rate, indicating the necessity of correcting the synergy deformation. Full article

Drought stress induces the excessive accumulation of hydrogen peroxide (H₂O₂), leading to oxidative damage and reduced crop productivity. This study presents a dual-function nanotechnology-based strategy for monitoring and mitigating drought-induced oxidative stress in cereal crops. Hierarchical CuO nanostructures were grown directly on copper substrates by hydrothermal oxidation, and the influence of growth time on morphology and hydrogen peroxide sensing performance was systematically evaluated. An optimal growth time of 3 h produced CuO nanoflower architectures with high surface area, yielding superior electrocatalytic activity toward H₂O₂ detection, with a low detection limit of 1.9 µM and high sensitivity of 11.92 mA·mM⁻¹·cm⁻². The optimized sensor enabled reliable quantification of H₂O₂ in oat (Avena sativa) and rye (Secale cereale) under drought stress, revealing species-dependent oxidative responses. In parallel, magnesium oxide (MgO) nanoparticles effectively alleviated drought-induced oxidative damage, reducing H₂O₂ accumulation by up to 63% in oat and 61% in rye and significantly improving plant growth and chlorophyll content. The integration of CuO-based sensing with MgO nanoparticle-assisted stress mitigation provides a robust framework for plant stress diagnostics and intervention, highlighting the potential of nanotechnology-enabled strategies for crop stress diagnostics and precision agriculture. Full article

Exercise-induced muscle damage (EIMD) has classically been attributed to localized mechanical disruption following eccentric contractions. Emerging evidence, however, indicates that EIMD represents a systems-level failure of stress integration within skeletal muscle rather than a purely mechanical lesion. Mechanical loading initiates disturbances in intracellular Ca²⁺ homeostasis, which interact with metabolic stress, redox imbalance, and immune activation to form self-reinforcing feedback loops. When compensatory capacity is exceeded, transient injury may shift toward maladaptive remodeling marked by mitochondrial dysfunction, ferroptosis, chronic inflammation, and impaired regeneration. Recent studies identify reactive oxygen species accumulation, iron-dependent lipid peroxidation, dysregulated energy sensing, and aberrant immune polarization as key molecular tipping points governing injury reversibility. Beyond their regenerative role, satellite cells act as integrators of metabolic history and epigenetic memory, linking repetitive injury to reduced muscle adaptability, age-related sarcopenia, and heightened metabolic disease risk. Here, we synthesize evidence from animal models, clinical studies, and multi-omics analyses to establish a systems biology framework for EIMD. We delineate the spatiotemporal interactions among mechanical, metabolic, oxidative, immune, and regenerative modules; identify regulatory nodes that determine adaptive repair versus pathological outcomes; and critically evaluate current nutritional, physical, pharmacological, and regenerative interventions from a mechanism-oriented perspective. Finally, we discuss how multi-omics, digital monitoring, and individualized rehabilitation may enable precision management of EIMD and advance understanding of muscle stress resilience and adaptive limits. Full article

Forest fires are a major concern due to their significant impact on the environment, economy, and wildlife habitats. Efficient early detection systems can significantly mitigate their devastating effects. This paper provides a comprehensive review of forest fire detection (FFD) techniques and traces their evolution from basic lookout-based methods to sophisticated remote sensing technologies, including recent Internet of Things (IoT)- and Unmanned Aerial Vehicle (UAV)-based sensor network systems. Historical methods, characterized primarily by human surveillance and basic electronic sensors, laid the foundation for modern techniques. Recently, there has been a noticeable shift toward ground-based sensors, automated camera systems, aerial surveillance using drones and aircraft, and satellite imaging. Moreover, the rise of Artificial Intelligence (AI), Machine Learning (ML), and the IoT introduces a new era of advanced detection capabilities. These detection systems are being actively deployed in wildfire-prone regions, where early alerts have proven critical in minimizing damage and aiding rapid response. All FFD techniques follow a common path of data collection, pre-processing, data compression, transmission, and post-processing. Providing sufficient power to complete these tasks is also an important area of research. Recent research focuses on image compression techniques, data transmission, the application of ML and AI at edge nodes and servers, and the minimization of energy consumption, among other emerging directions. However, to build a sustainable FFD model, proper sensor deployment is essential. Sensors can be either fixed at specific geographic locations or attached to UAVs. In some cases, a combination of fixed and UAV-mounted sensors may be used. Careful planning of sensor deployment is essential for the success of the model. Moreover, ensuring adequate energy supply for both ground-based and UAV-based sensors is important. Replacing sensor batteries or recharging UAVs in remote areas is highly challenging, particularly in the absence of an operator. Hence, future FFD systems must prioritize not only detection accuracy but also long-term energy autonomy and strategic sensor placement. Integrating renewable energy sources, optimizing data processing, and ensuring minimal human intervention will be key to developing truly sustainable and scalable solutions. This review aims to guide researchers and developers in designing next-generation FFD systems aligned with practical field demands and environmental resilience. Full article

Agricultural systems are under growing pressure, as soil degradation threatens food security and sustainable land use. Early detection through soil monitoring and precision agriculture is vital to prevent irreversible damage and enable timely conservation. This study evaluates a combined procedure based on electrical resistivity tomography and frequency-domain electromagnetic induction measurements, together with discrete soil sampling, to electrically characterize the soil, identify layers, and map the A horizon depth in a non-disturbing way. This work includes the design and implementation of a mounting electrode system, which reduces the installation time of electrical resistivity tomography surveys by 60% while maintaining data quality. The data were acquired in the oldest long-term agronomic experiment in South America, comprising seven rotation systems with three replicates each, totaling 21 rainfed plots, and representing contrasting management scenarios. Soil A horizon thickness maps of the entire experiment were obtained through two procedures. A comparison between mapping inputs, including all plots and only bare-soil plots, revealed minimal differences in unvegetated areas but notable discrepancies under plant cover, where vegetation increased fluctuations and noise. The present study provides a methodology for accurately assessing the spatial variability of the A horizon thickness by means of proximal sensing techniques. This contributes to the challenge of gathering fundamental soil information in a fast and cost-effective manner, critical for precision agricultura. Full article

As the “flagship” unit of the petrochemical industry, the operational status of ethylene cracking furnaces directly impacts the stability and efficiency of the entire production chain. During long-term operation under extreme temperatures and complex reaction environments, cracking furnace tubes face core bottlenecks primarily related to thermal and coking effects, such as coke deposition, tube metal overheating, and associated creep damage, which restrict the long-term, safe, and efficient operation of the unit. This paper systematically reviews the key technologies for condition monitoring of cracking furnace tubes, providing an in-depth analysis of various monitoring methods—from traditional infrared thermometry and acoustic emission to emerging optical fiber sensing—covering their working principles, application status, and inherent limitations. Furthermore, it elaborates on the evolution from mechanism-based “white-box” models to data-driven “black-box” models, and further to “gray-box” intelligent diagnostic models that integrate expert knowledge. Industrial application cases of integrated monitoring and diagnostic systems are also introduced. Finally, the paper critically addresses the current severe challenges in data fusion, model generalization, real-time performance, and cost-effectiveness, while outlining future development trends toward digital twins, cross-modal fusion, edge intelligence, and self-evolving systems. The aim is to provide valuable references for technological innovation and engineering applications in this field. Full article

Floods represent one of the most frequent and damaging natural hazards in Mediterranean mountain regions, where intense rainfall and complex topography amplify runoff and inundation risk. This study aims to delineate flood-susceptible zones in the Monti Lucretili area of central Italy, an environmentally sensitive and culturally significant landscape that hosts archeological remains and UNESCO listed dry-stone heritage using an integrated Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) approach. Fifteen (15) conditioning factors, including elevation, slope, rainfall, soil, lithology, land use/land cover, drainage density, and proximity to rivers and roads, were derived from open-access satellite remote sensing and spatial datasets. The AHP model produced a flood susceptibility index ranging from 1.806 to 4.465, reclassified into five categories from very low to very high zones. The resulting map indicates that low- and moderate-susceptibility zones dominate the study area, while high and very high classes are primarily concentrated along valleys and drainage corridors. Model validation indicates strong regional-scale predictive performance, with 85.36% of modeled flood-prone areas located within high- to very-high-susceptibility zones and an AUC value of 0.82. Overall, the study highlights the potential of open-access AHP–GIS modeling as a practical screening tool for flood susceptibility assessment and heritage-aware spatial planning in Mediterranean environments. Full article

Wind-induced roof-lifting accidents occur frequently in metal roofs, making the monitoring of wind uplift resistance an important part of building health monitoring. This paper proposes an integrated monitoring and reinforcement method for metal roofs using embedded fiber Bragg grating (FBG) smart rebars, develops smart rebars with both sensing and load-bearing functions, and conducts wind uplift tests in accordance with relevant standards. The experimental results show that: 1. The smart rebar can achieve high-frequency real-time monitoring at 100 Hz, accurately capture the dynamic force characteristics of the roof panel throughout the wind load application process, and precisely locate the damaged area. 2. The smart rebar and the roof panel form an integrally stressed “rebar–panel” system. Under wind load, they deform coordinately; the smart rebar uniformly transfers the load from local high-stress areas to the entire roof system, optimizing the force transmission path and avoiding premature damage caused by local stress exceeding the limit. During the experiment, it effectively restricts the deformation of the decorative panel and prevents secondary damage caused by “splashing”. 3. Based on the experimentally measured strain data and the degree of roof damage, a graded-control index system is established with a “first-level alarm threshold of 1800 με, second-level alarm threshold of 2400 με, and third-level alarm threshold of 3000 με”. Each level of alarm corresponds to relevant disposal measures, realizing closed-loop management from data monitoring to risk response. The smart rebar system serves both load-bearing and sensing functions, fulfilling the practical engineering needs of monitoring and enhancing the roof, thereby achieving the dual purposes of monitoring and reinforcement. Full article

Traditional post-earthquake structural health monitoring (SHM) methods based on dedicated sensors lack scalability due to installation and maintenance demands, leaving most buildings unmonitored. This study investigates the use of existing in-building surveillance cameras to infer structural demand by tracking earthquake-induced building motion. The proposed methodology repurposes ceiling-mounted surveillance cameras to estimate the inter-story drift (IDR) which is directly correlated with structural damage using FEMA guidelines. Shake-table experiments spanning a wide range of excitation intensities and dominant frequencies demonstrate that off-the-shelf surveillance cameras can estimate displacement with accuracy similar to dedicated vision-based SHM setups. To establish operating limits, we quantify how temporal sampling (frame rate) and spatial sampling (video resolution) affect drift estimation accuracy. We also evaluate peak drift/IDR estimation accuracy and peak timing sensitivity under reduced temporal sampling. The results highlight the potential of widely available camera networks as a low-cost, scalable, and rapidly deployable sensing network for post-earthquake assessment. Full article

Structural health monitoring (SHM) based on Lamb waves relies on sensors to acquire structural response signals. However, sensor data acquisition is severely constrained under complex damage conditions. Digital twins (DTs) can enhance damage monitoring capabilities in Lamb wave SHM by integrating simulation and experimental sensor data. Nevertheless, performance remains limited by discrepancies in signal distribution between digital and physical domains, as well as cross-domain optimization conflicts. This study proposes a digital twin-driven dual-stage adversarial and transfer learning method with multi-objective optimization (DT-DSATMO) for Lamb wave-based structural damage localization under limited sensing conditions. Firstly, a strategy for hierarchical feature enhancement and conditional generation incorporating physical prior knowledge is introduced to construct distribution-consistent feature representations in the digital domain. Secondly, it achieves adaptive alignment between the two domains via a lightweight domain adversarial transfer network, improving cross-domain feature transferability. Furthermore, a Pareto frontier-based multi-objective optimization strategy is employed to balance damage localization accuracy, cross-domain robustness, and feature consistency. The proposed method is experimentally validated on a representative aircraft wing-box panel equipped with four lead zirconate titanate (PZT) sensors. The case study results show that it substantially enhances damage localization accuracy and cross-domain generalization under limited sensing data. Full article

Background and Objectives: Hypocalcemia due to hypoparathyroidism (HypoPTH) is the most common complication following thyroid surgery, typically resulting from iatrogenic removal, tissue damage, or compromised vascularization of the parathyroid glands. Patients with persistent HypoPTH are at risk for long-term complications such as osteoporosis, cardiac dysfunction, and renal impairment. Lifelong regulation of calcium levels is therefore essential to prevent morbidity and mortality associated with these complications. In this study, we aimed to evaluate the functional engraftment efficacy of 3D bioprinted human parathyroid tissue constructs in a xenograft model in vivo. Materials and Methods: Primary cells obtained from freshly excised human parathyroid tissue specimens were isolated and 3D bioprinted using alginate-based bioink. The bioprinted tissue constructs were implanted into CD1 athymic mice. Histopathological evaluation of the grafted constructs was performed at different time points. In addition, surface calcium-sensing receptor (CaSR) expression was assessed by immunofluorescence as an indicator of functional parathyroid tissue engraftment. Results: The presence of CaSR on parathyroid cells within the 3D-printed scaffolds confirmed the persistence of functional parathyroid cells following implantation. In tissue samples obtained during the first, second, and third weeks after implantation, CaSR positivity was consistently observed in the parathyroid cells. However, at the three-month follow-up, the pores within the scaffolds were found to be filled with calcified material and replaced by fibrotic tissue. At this stage, the absence of parathyroid hormone (PTH) expression indicated a loss of functional activity in the grafted biomaterial. Conclusions: Human primary parathyroid cells were successfully isolated, and a functional, hormone-active parathyroid tissue substitute was developed ex vivo using 3D-bioprinted hydrogel scaffolds combined with autologous cells. Although short-term functional engraftment was achieved, long-term graft viability and hormonal activity were limited due to scaffold degradation and fibrosis. These findings indicate the necessity for further improvement in scaffold biocompatibility to enhance the therapeutic potential of 3D-bioprinted parathyroid tissue constructs for in vivo applications. Full article

This paper presents the structural health monitoring (SHM) system applied to a 9 m composite outer wing box (OWB) specifically designed for a brand-new regional aircraft to detect barely visible impact damage (BVID) based on structural response data. The approach relies on different technologies to offer multilevel diagnosis, including impact detection as well as disbonding identification, localization, and sizing. The use of different sensing techniques based on piezoelectric transducers and distributed fiber optic sensors deployed all over wing structures is explored. Different features are simultaneously extracted from the propagating waves and from light scattering, able to detect low-energy BVID impact. In addition, the combined use of static and dynamic interrogation allows the estimation of the delamination surface after impact with good accuracy. The final test results on the OWB provided effectiveness in detecting, localizing, and tracking impact damage in the composite structure, ensuring long-term reliability and safety, as well as characterizing barely visible damage by a fully integrated onboard SHM system. Full article

This paper presents a comprehensive real-time forecasting and mapping cycle of a regional flood event, encompassing quantitative precipitation forecasting, runoff production and routing, and inundation mapping. The objective of this study is to highlight the significant uncertainties inherent in each step of the fully automated cycle, despite the utilization of state-of-the-art models and remote sensing technologies. The case study focuses on a significant flood event that occurred in the Turkey River and Upper Iowa River, in rural Iowa, United States, resulting in localized damage and disruption to several small communities. The novelty of this study is that it demonstrates the limited utility of satellite-based remote sensing in the absence of other forecasting and mapping system elements, emphasizing the need for the timely integration of information from diverse sources to accurately forecast and map floods. To achieve this, we assembled and analyzed precipitation data from weather radars, streamflow estimates derived from river stages and rating curves, and cross-sectional data from river channels to characterize the movement of the flood wave. These data were integrated into hydrologic and hydraulic models to generate flood inundation estimates for the more severely affected areas. Remote sensing imagery was obtained and used as reference to assess the accuracy of the modeled inundated areas. Our findings illustrate that, despite the increasing availability of satellite data sources, there are still significant limitations to tracking inundation using satellite remote sensing, particularly for medium-sized basins. Flood modeling processes are not merely complementary to satellite-based flood estimation, but essential for comprehensive flood risk assessment. Full article

Fiber Bragg Gratings (FBGs) are essential components in fiber-optic sensing systems owing to their high sensitivity, compact structure, and immunity to electromagnetic interference, and have been widely applied in structural health monitoring, aerospace, energy, and biomedical fields. Conventional FBG fabrication methods, including standing-wave, two-beam interference and phase mask methods, rely heavily on the photosensitivity of optical fibers and are limited in terms of fabrication flexibility and grating structural diversity. Femtosecond Laser Direct Writing (FLDW) has emerged as a prospective approach for FBG fabrication due to its nonlinear absorption mechanism, low thermal damage, three-dimensional processing capability and broad material compatibility. This review summarizes recent progress in FLDW-FBGs, with particular emphasis on the characteristics of point-by-point (PbP), line-by-line (LbL) and plane-by-plane (Pl-by-Pl) methods. The implementation of these methods in various fiber, including standard single-mode fibers, sapphire fibers, and polymer optical fibers, is discussed in detail. In addition, recent advances in FBG-based sensing applications under extreme environments, as well as in biomedical sensing and optical fiber communication, are reviewed. Key challenges related to fabrication efficiency, process stability, and microstructural characterization are further analyzed. Finally, potential development directions toward improved controllability, structural design flexibility, and engineering applicability of FLDW-FBGs are outlined. Full article