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Plastic films have previously displayed tremendous potential to increase water use efficiency in farmland and the yield of cash crops; however, long-term use of plastic film in soils can influence soil physiological and biochemical characteristics and change its biota. The present study aimed to investigate the effects of residual plastic film pollution on soil microbe community structure and fertility in Xinjiang province, China. Residual plastic film-contaminated soil and non-contaminated soil in Xinjiang farmland were selected for this study. The results indicated that residual plastic film pollution changed the structure of the soil biological community by significantly decreasing and increasing the abundance of Actinomycetes and Proteobacteria, respectively; further, the pollution decreased soil organic matter and inorganic nitrogen content by downregulating microbial genes related to soil carbon and nitrogen cycles and decreasing related enzymatic activities. The present results indicated that long-term residual plastic film exposure (more than 10 years) in farmland significantly decreases soil fertility and alters the microbial community structure.

Integrating digital twins (DTs) into smart grid systems within the Internet of Smart Grid Things (IoSGT) ecosystem brings novel opportunities but also security challenges. Specifically, advanced machine learning (ML)-based Deepfake technologies enable adversaries to create highly realistic yet fraudulent DTs, threatening critical infrastructures’ reliability, safety, and integrity. In this paper, we introduce Authenticating Networked Computerized Handling of Representations for Smart Grid security (ANCHOR-Grid), an innovative authentication framework that leverages Electric Network Frequency (ENF) signals as real-world anchors to secure smart grid DTs at the frontier against Deepfake attacks. By capturing distinctive ENF variations from physical grid components and embedding these environmental fingerprints into their digital counterparts, ANCHOR-Grid provides a robust mechanism to ensure the authenticity and trustworthiness of virtual representations. We conducted comprehensive simulations and experiments within a virtual smart grid environment to evaluate ANCHOR-Grid. We crafted both authentic and Deepfake DTs of grid components, with the latter attempting to mimic legitimate behavior but lacking correct ENF signatures. Our results show that ANCHOR-Grid effectively differentiates between authentic and fraudulent DTs, demonstrating its potential as a reliable security layer for smart grid systems operating in the IoSGT ecosystem. In our virtual smart grid simulations, ANCHOR-Grid achieved a detection rate of 99.8% with only 0.2% false positives for Deepfake DTs at a sparse attack rate (1 forged packet per 500 legitimate packets). At a higher attack frequency (1 forged packet per 50 legitimate packets), it maintained a robust 97.5% detection rate with 1.5% false positives. Against replay attacks, it detected 94% of 5 s-old signatures and 98.5% of 120 s-old signatures. Even with 5% injected noise, detection remained at 96.5% (dropping to 88% at 20% noise), and under network latencies from <5 ms to 200 ms, accuracy ranged from 99.9% down to 95%. These results demonstrate ANCHOR-Grid’s high reliability and practical viability for securing smart grid DTs. These findings highlight the importance of integrating real-world environmental data into authentication processes for critical infrastructure and lay the foundation for future research on leveraging physical world cues to secure digital ecosystems.

The metaverse concept has been evolving from static, pre-rendered virtual environments to a new frontier: the real-time metaverse. This survey paper explores the emerging field of real-time metaverse technologies, which enable the continuous integration of dynamic, real-world data into immersive virtual environments. We examine the key technologies driving this evolution, including advanced sensor systems (LiDAR, radar, cameras), artificial intelligence (AI) models for data interpretation, fast data fusion algorithms, and edge computing with 5G networks for low-latency data transmission. This paper reveals how these technologies are orchestrated to achieve near-instantaneous synchronization between physical and virtual worlds, a defining characteristic that distinguishes the real-time metaverse from its traditional counterparts. The survey provides a comprehensive insight into the technical challenges and discusses solutions to realize responsive dynamic virtual environments. The potential applications and impact of real-time metaverse technologies across various fields are considered, including live entertainment, remote collaboration, dynamic simulations, and urban planning with digital twins. By synthesizing current research and identifying future directions, this survey provides a foundation for understanding and advancing the rapidly evolving landscape of real-time metaverse technologies, contributing to the growing body of knowledge on immersive digital experiences and setting the stage for further innovations in the Metaverse transformative field.

The rapid adoption of Metaverse technologies in healthcare, particularly for elder safety monitoring, has introduced new security challenges related to the authenticity of virtual representations. As healthcare providers increasingly rely on avatars and digital twins to monitor and interact with elderly patients remotely, ensuring the integrity of these virtual entities becomes paramount. This paper introduces SAVE (Securing Avatars in Virtual Environments), an emerging framework that leverages environmental fingerprinting based on Electric Network Frequency (ENF) signals to authenticate avatars and detect potential deepfake attacks in virtual healthcare settings. Unlike conventional authentication methods that rely solely on digital credentials, SAVE anchors virtual entities to the physical world by utilizing the unique temporal and spatial characteristics of ENF signals. We implement and evaluate SAVE in a Microverse-based nursing home environment designed for monitoring elderly individuals living alone. We evaluated SAVE using a prototype system with Raspberry Pi devices and multiple environmental sensors, demonstrating effectiveness across three attack scenarios in a 30-minute experimental window. Through the experimental evaluation of three distinct attack scenarios, unauthorized device attacks, device ID spoofing, and replay attacks using intercepted data, our system demonstrates high detection accuracy with minimal false positives. Results show that by comparing ENF fingerprints embedded in transmitted data with reference ENF signals, SAVE can effectively identify tampering and ensure the authenticity of avatar updates in real time. The SAVE approach enhances the security of virtual healthcare monitoring without requiring additional user intervention, making it particularly suitable for elderly care applications where ease of use is essential. Our findings highlight the potential of physical environmental fingerprints as a robust security layer for virtual healthcare systems, contributing to safer and more trustworthy remote monitoring solutions for vulnerable populations.

The ability of the human liver to both synthesize extracellular matrix(ECM), as well as regulate fibrogenesis, are integral functions to maintaining homoeostasis. Chronic liver injury stimulates fibrogenesis in response to the imbalance between ECM accumulation and fibrosis resolution. Liver disease that induces fibrogenesis is associated with multiple risk factors like hepatitis infection, schistosomiasis, alcohol, certain drugs, toxicants and emerging aetiology like diabetes and obesity. The activation of hepatic stellate cells (HSCs), whose function is to generate and accumulate ECM, is a pivotal event in liver fibrosis. Simultaneously, HSCs selectively promote regulatory T-cells (Tregs) in an interleukin-2–dependent pattern that displays a dual relationship. On the one hand, Tregs can protect HSCs from NK cell attack, while on the other hand, they demonstrate an inhibitory effect on HSCs. This paper reviews the dual role of Tregs in liver fibrogenesis which includes its promotion of immunosuppression, as well as its activation of fibrosis. In particular, the balance between Tregs and the Th17 cell population, which produce interleukin (IL)-17 and IL-22, is explored to demonstrate their key role in maintaining homoeostasis and immunoregulation. The contradictory roles of Tregs in liver fibrosis in different immune microenvironments and molecular pathways need to be better understood if they are to be deployed to manage this disease.

Objectives We aimed to investigate the role of [ 68 Ga]FAPI-04 and [ 18 F]FDG dual-tracer PET/CT for the initial assessment of gastric cancer and to explore the factors associated with their uptake. Methods This study enrolled 62 patients with histopathologically confirmed gastric cancer. We compared the diagnostic performance of [ 68 Ga]FAPI-04, [ 18 F]FDG, and combined dual-tracer PET/CT. The standardized uptake value (SUV) and tumor-to-background ratio (TBR) were also measured, and the factors that influence tracer uptake were analyzed. Results [ 68 Ga]FAPI-04 PET/CT detected more primary lesions (90.3% vs 77.4%, p = 0.008) and peritoneal metastases (91.7% vs 41.7%, p = 0.031) and demonstrated higher SUV max and TBR values ( p < 0.001) of primary lesions compared to [ 18 F]FDG PET/CT. Dual-tracer PET/CT significantly improved the diagnostic sensitivity for the detection of distant metastases, compared with stand-alone [ 18 F]FDG (97.1% vs 73.5%, p = 0.008) or [ 68 Ga]FAPI-04 (97.1% vs 76.5%, p = 0.016) PET/CT. Subsequently, treatment strategies were changed in nine patients following [ 68 Ga]FAPI-04 and [ 18 F]FDG dual-tracer PET/CT. Nevertheless, [ 68 Ga]FAPI-04 uptake was primarily influenced by the size and invasion depth of the tumor. Both [ 68 Ga]FAPI-04 and [ 18 F]FDG PET/CT showed limited sensitivity for detecting early gastric cancer (EGC) (37.5% vs 25.0%, p > 0.05). Conclusions In this initial study, [ 68 Ga]FAPI-04 and [ 18 F]FDG dual-tracer PET/CT were complementary and improved sensitivity for the detection of distant metastases pre-treatment in gastric cancer and could improve treatment stratification in the future. [ 68 Ga]FAPI-04 had limited efficacy in detecting EGC. Key Points • [ 68 Ga]FAPI-04 and [ 18 F]FDG dual-tracer PET/CT are complementary to each other for improving diagnostic sensitivity in the initial evaluation of distant metastases from gastric cancer. • [ 68 Ga]FAPI-04 PET/CT showed limited sensitivity in detecting EGC. • Need for further validation in a larger multi-centre prospective study.

Skin photoaging results primarily from chronic ultraviolet (UV) exposure, which disrupts dermal homeostasis and promotes cellular senescence. Dermal papilla cell-conditioned medium (DPC-CM) has emerged as a promising cell-free approach for skin rejuvenation. This study aimed to explore the anti-photoaging effects of DPC-CM and its potential regulation of ferroptosis. Mouse dermal papilla cells and skin fibroblasts were isolated and characterized. A photoaging model was established using UVA-irradiated fibroblasts, followed by treatment with DPC-CM at two concentrations, the ferroptosis inhibitor ferrostatin-1 (FER-1), or retinoic acid. UVA exposure led to reduced cell viability, impaired migration, increased senescence, elevated iron and reactive oxygen species levels, decreased glutathione, and altered expression of ferroptosis-related markers including nuclear factor erythroid 2-related factor 2 (NRF2), glutathione peroxidase 4 (GPX4), and solute carrier family 7 member 11 (SLC7A11). These changes were partially reversed by DPC-CM and FER-1. Proteomic analysis revealed that proteins in both dermal papilla cells and DPC-CM are associated with ferroptosis pathways. In vivo, DPC-CM significantly attenuated UVA-induced dermal aging. Collectively, these findings demonstrate that DPC-CM protects against photoaging by modulating ferroptosis, supporting its therapeutic potential in oxidative stress-related skin disorders.

Androgenetic alopecia (AGA) is a global challenge, affecting a large number of people worldwide. Efficacy of the existed treatments can barely meet the demands of patients. Patients who are poorly responding to those treatments are seeking for a more effective and suitable technique to treat their disease. Low-level light therapy (LLLT) is a newly developed technique, which has been proved to stimulate hair growth. Based on the function principle of LLLT in other domains and refer to the published literatures, we write this review to neaten and elucidate the possible mechanism of LLLT in the treatment of AGA. A review of published literature which is associated with keywords LLLT, photobiomodulation, AGA, treatment, hair growth, and mechanism was performed to elucidate the proposed mechanism of LLLT in the treatment of AGA. The present study shows that LLLT can accelerate hair growth in AGA patients. The proposed mechanism of LLLT in treating AGA may vary among different specialists. But we can summarize the consensual mechanisms as follows; low-level light absorbed by chromophores can lead to the production of nitric oxide (NO) and the modulation of reactive oxygen species (ROS). These mobilized molecules subsequently activate redox-related signaling pathways in hair follicle cells and perifollicular cells. Finally, these activated cells participate in the regrowth of hair follicle. Even though the efficacy of LLLT in the treatment of AGA in both men and women has already been confirmed, the present studies focusing on discovering LLLT are still inadequate and unsystematic. More studies are needed to standardize the optimum treatment parameters applied in promoting hair growth and determine the long-term safety and efficacy of LLLT. Current recognitions about the mechanisms of LLLT, mainly focused on the molecules that may take effect, neglected different cellular components that are functional in the hair follicle macro-environment.

The convergence of the Internet of Physical–Virtual Things (IoPVT) and the Metaverse presents a transformative opportunity for safety and health monitoring in outdoor environments. This concept paper explores how integrating human activity recognition (HAR) with the IoPVT within the Metaverse can revolutionize public health and safety, particularly in urban settings with challenging climates and architectures. By seamlessly blending physical sensor networks with immersive virtual environments, the paper highlights a future where real-time data collection, digital twin modeling, advanced analytics, and predictive planning proactively enhance safety and well-being. Specifically, three dimensions of humans, technology, and the environment interact toward measuring safety, health, and climate. Three outdoor cultural scenarios showcase the opportunity to utilize HAR–IoPVT sensors for urban external staircases, rural health, climate, and coastal infrastructure. Advanced HAR–IoPVT algorithms and predictive analytics would identify potential hazards, enabling timely interventions and reducing accidents. The paper also explores the societal benefits, such as proactive health monitoring, enhanced emergency response, and contributions to smart city initiatives. Additionally, we address the challenges and research directions necessary to realize this future, emphasizing AI technical scalability, ethical considerations, and the importance of interdisciplinary collaboration for designs and policies. By articulating an AI-driven HAR vision along with required advancements in edge-based sensor data fusion, city responsiveness with fog computing, and social planning through cloud analytics, we aim to inspire the academic community, industry stakeholders, and policymakers to collaborate in shaping a future where technology profoundly improves outdoor health monitoring, enhances public safety, and enriches the quality of urban life.

The traditional Chinese medicine Shen-ling-bai-zhu-san (SLBZS) is described in “Tai Ping Hui Min He Ji Ju Fang.” SLBZS has been shown to be effective against many gastrointestinal diseases. The present study aimed to investigate the effect of SLBZS on experimental colitis in mice and to define the potential mechanisms. Our data suggest that compared to the model group, SLBZS treatment increases mouse body weight and colon length, decreases the DAI score, and improves colonic injury. SLBZS reduces the production of cytokines (IL-1β, IL-18, and TNF-α) in colon tissue and mouse colonic mucosal epithelial (MCME) cells. Mechanistically, SLBZS inhibits inflammation by inhibiting the MAPK and NF-κB signaling pathways. Further mechanistic analyses showed that SLBZS attenuates the expression levels of pyroptosis-related genes, including NLRP3, ASC, and GSDMD-N in the colons of mice. In addition, SLBZS restores the levels of the colon tight junction proteins ZO-1 and occludin, suggesting that it protects colonic barrier integrity and ameliorates the progression of colitis. In this paper, we demonstrate that SLBZS attenuates DSS-induced ulcerative colitis injury in mice via the MAPK/NF-κB and pyroptosis signaling pathway. These results indicate that SLBZS is a potential drug for the treatment of UC.