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Background Prior studies in patients with chronic obstructive pulmonary disease (COPD) had indicated a potential correlation between cadmium (Cd) exposure and reduction in lung function. Nevertheless, the influence of Cd exposure on the progression of COPD remained unknown. Exploring the relationship between Cd exposure and the progression of COPD was the aim of this investigation. Methods Stable COPD patients were enrolled. Blood samples were collected and lung function was evaluated. Regular professional follow-ups were conducted through telephone communications, outpatient services, and patients' hospitalization records. Results Each additional unit of blood Cd was associated with upward trend in acute exacerbation, hospitalization, longer hospital stay, and death within 2 years. Even after adjusting for potential confounding factors, each 1 unit rise in blood Cd still correlated with a rise in the frequencies of acute exacerbation, longer hospital stay, and death. Moreover, COPD patients with less smoking amount, lower lung function and without comorbidities were more vulnerable to Cd-induced disease deterioration. Conclusion Patients with COPD who have higher blood Cd concentration are susceptible to worse disease progression. Graphical Abstract

Background Exposure to cadmium (Cd) is associated with a reduction in lung function among patients with chronic obstructive pulmonary disease (COPD). The longitudinal relationship and mechanism underlying the link between Cd exposure and lung function changes among COPD patients are yet unknown. Methods The cohort study included 259 eligible patients who underwent regular professional follow-ups. Blood Cd levels and serum 8-iso-prostaglandin F2 alpha (8-iso-PGF2α) levels were assessed. Lung function was determined at baseline and follow-up research. The associations between changes in lung function and blood Cd concentration were analysed using multivariate linear and logistic regression models. Results Each 1-ppb elevation in blood Cd content resulted in a 0.420 L decrease in forced vital capacity (FVC), a 0.424 L decrease in forced expiratory volume in 1 s (FEV1), a 4.341% decrease in FEV1/FVC%, and a 8.418% decrease in FEV1% predicted in patients with COPD. Blood Cd concentration showed a positive correlation with serum 8-iso-PGF2α levels in a specific range. The relative contribution of increased serum levels of 8-iso-PGF2α to Cd-induced declines in FEV1, predicted FEV1%, and FEV1/FVC% were 2.08%, 8.08%, and 13.19%, respectively. Conclusion Blood Cd levels are associated with lung function changes in COPD patients. Oxidative stress is thought to be an important mediator in Cd-induced reduction of pulmonary function.

In the agricultural sector, farmers and agribusiness are confronted with a multitude of complex choices every day. These selections are influenced by multiple variables that significantly affect their outcomes. The primary source of revenue for a good deal of individuals is derived from the agricultural sector. The provision of precise and punctual predictions on crop yields has significant importance in facilitating informed investment choices and shaping agricultural policies. One of the challenges encountered is the presence of old or incomplete data about the accessibility of resources. This represents a significant obstacle in accurately ascertaining the present state of affairs. The process of evaluating becomes complex as a result of the diverse range of soil conditions and climatic factors. This research introduces a novel approach called Enhanced Gravitational Search Optimized based Gated Recurrent Unit (EGSO-GRU) for the purpose of calculating crop production. The dataset was first gathered and pre-processed using a normalization method. Enhanced independent component analyses (EICA) have been employed for the purpose of extracting features. To determine the suggest method achievement with regard to accuracy (95.89%), specificity (92.4%), MSE (0.071), RMSE (0.210) and MAE (0.199). The proposed method achieved greater crop prediction accuracy, outperforming the majority of the existing models. The necessity of this progress is vital to the successful operation of crops. The concept signifies a technological advancement aimed at optimizing agricultural resources, hence fostering enhanced productivity and long-term sustainability within the farming industry.

The Internet of vehicles (IoV) is an Internet-of-things-based network in the area of transportation. It comprises sensors, network communication, automation control, and data processing and enables connectivity between vehicles and other objects. This study performed main path analysis (MPA) to investigate the trajectory of research regarding the IoV. Studies were extracted from the Web of Science database, and citation networks among these studies were generated. MPA revealed that research in this field has mainly covered media access control, vehicle-to-vehicle channels, device-to-device communications, layers, non-orthogonal multiple access, and sixth-generation communications. Cluster analysis and data mining revealed that the main research topics related to the IoV included wireless channels, communication protocols, vehicular ad hoc networks, security and privacy, resource allocation and optimization, autonomous cruise control, deep learning, and edge computing. By using data mining and statistical analysis, we identified emerging research topics related to the IoV, namely blockchains, deep learning, edge computing, cloud computing, vehicular dynamics, and fifth- and sixth-generation mobile communications. These topics are likely to help drive innovation and the further development of IoV technologies and contribute to smart transportation, smart cities, and other applications. On the basis of the present results, this paper offers several predictions regarding the future of research regarding the IoV.

With the continuing advancements in technologies (such as machine to machine, wireless telecommunications, artificial intelligence, and big data analysis), the Internet of Things (IoT) aims to connect everything for information sharing and intelligent decision-making. Swarm intelligence (SI) provides the possibility of SI behavior through collaboration in individuals that have limited or no intelligence. Its potential parallelism and distribution characteristics can be used to realize global optimization and solve nonlinear complex problems. This paper reviews representative SI algorithms and summarizes their applications in the IoT. The main focus consists in the analysis of SI-enabled applications to wireless sensor network (WSN) and discussion of related research problems in the WSN. Also, we concluded SI-based applications in other IoT fields, such as SI in UAV-aided wireless network. Finally, possible research prospects and future trends are drawn.

Due to the increased age of the global population, the proportion of the elderly population continues to rise. The safety of the elderly living alone is becoming an increasingly prominent area of concern. They often miss timely treatment due to undetected falls or illnesses, which pose risks to their lives. In order to address this challenge, the technology of indoor abnormal behavior detection has become a research hotspot. This paper systematically reviews detection methods based on sensors, video, infrared, WIFI, radar, depth, and multimodal fusion. It analyzes the technical principles, advantages, and limitations of various methods. This paper further explores the characteristics of relevant datasets and their applicable scenarios and summarizes the challenges facing current research, including multimodal data scarcity, risk of privacy leakage, insufficient adaptability of complex environments, and human adoption of wearable devices. Finally, this paper proposes future research directions, such as combining generative models, federated learning to protect privacy, multi-sensor fusion for robustness, and abnormal behavior detection on the Internet of Things environment. This paper aims to provide a systematic reference for academic research and practical application in the field of indoor abnormal behavior detection.

1-Nitropyrene (1-NP) is harmful to the respiratory system and can evoke acute lung injury (ALI). Pyroptosis and apoptosis, two important types of programmed cell death, are involved in the pathological process of ALI. However, the roles and mechanisms of pyroptosis and apoptosis on 1-NP-incurred ALI remain unclear. All the mice were exposed to a single dose of 1-NP (20 μg/mouse, dissolved in saline) or normal saline via intratracheal instillation. At different times after 1-NP exposure, the mice were sacrificed. Mouse lung epithelial (MLE-12) cells were incubated with 1-NP (5 μM), the indicators of pyroptosis and apoptosis were detected. Pulmonary pathological injury and inflammatory cell infiltration was observed in 1-NP-exposed mice. Additionally, the indicators of apoptosis, Bcl-2 was downregulated, Bad and Caspase-3, and apoptotic cells were increased in 1-NP-exposed mouse lungs and mouse lung epithelial (MLE-12) cells. Meanwhile, the proteins of GSDMD and Pro- and Cleaved Caspase-11 and the mRNAs of and , which are markers of pyroptosis, were increased after 1-NP treatment. Moreover, pretreatment with wedelolactone (WED), an antagonist of Caspase-11, alleviated 1-NP-induced ALI. As expected, pharmacological inhibition or genetic deletion of Caspase-11 abolished 1-NP-induced apoptosis and pyroptosis. Interestingly, 1-NP attenuated Caspase-11 proteasome degradation. Mechanistically, 1-NP downregulated the expression of SYVN1, an E3 ubiquitin ligase of Caspase-11. 1-NP promoted the interaction between SYVN1 and Caspase-11 and inhibited Caspase-11 ubiquitination and subsequent proteasome degradation. Transfection with SYVN1 overexpression plasmids abolished 1-NP-mediated the reduction of Caspase-11 ubiquitination-dependent degradation, apoptosis, and pyroptosis. These results revealed that acute 1-NP may induce ALI via Caspase-11-mediated apoptosis and pyroptosis by downregulating SYVN1.

Cancer cells frequently display fundamentally altered cellular metabolism, which provides the biochemical foundation and directly contributes to tumorigenicity and malignancy. Rewiring of metabolic programmes, such as aerobic glycolysis and increased glutamine metabolism, are crucial for cancer cells to shed from a primary tumor, overcome the nutrient and energy deficit, and eventually survive and form metastases. However, the role of lipid metabolism that confers the aggressive properties of malignant cancers remains obscure. The present review is focused on key enzymes in lipid metabolism associated with metastatic disease pathogenesis. We also address the function of an important membrane structure-lipid raft in mediating tumor aggressive progression. We enumerate and integrate these recent findings into our current understanding of lipid metabolic reprogramming in cancer metastasis accompanied by new and exciting therapeutic implications.

Cancer immunotherapy, encompassing both experimental and standard-of-care therapies, has emerged as a promising approach to harnessing the immune system for tumor suppression. Experimental strategies, including novel immunotherapies and preclinical models, are actively being explored, while established treatments, such as immune checkpoint inhibitors (ICIs), are widely implemented in clinical settings. This comprehensive review examines the historical evolution, underlying mechanisms, and diverse strategies of cancer immunotherapy, highlighting both its clinical applications and ongoing preclinical advancements. The review delves into the essential components of anticancer immunity, including dendritic cell activation, T cell priming, and immune surveillance, while addressing the challenges posed by immune evasion mechanisms. Key immunotherapeutic strategies, such as cancer vaccines, oncolytic viruses, adoptive cell transfer, and ICIs, are discussed in detail. Additionally, the role of nanotechnology, cytokines, chemokines, and adjuvants in enhancing the precision and efficacy of immunotherapies were explored. Combination therapies, particularly those integrating immunotherapy with radiotherapy or chemotherapy, exhibit synergistic potential but necessitate careful management to reduce side effects. Emerging factors influencing immunotherapy outcomes, including tumor heterogeneity, gut microbiota composition, and genomic and epigenetic modifications, are also examined. Furthermore, the molecular mechanisms underlying immune evasion and therapeutic resistance are analyzed, with a focus on the contributions of noncoding RNAs and epigenetic alterations, along with innovative intervention strategies. This review emphasizes recent preclinical and clinical advancements, with particular attention to biomarker-driven approaches aimed at optimizing patient prognosis. Challenges such as immunotherapy-related toxicity, limited efficacy in solid tumors, and production constraints are highlighted as critical areas for future research. Advancements in personalized therapies and novel delivery systems are proposed as avenues to enhance treatment effectiveness and accessibility. By incorporating insights from multiple disciplines, this review aims to deepen the understanding and application of cancer immunotherapy, ultimately fostering more effective and widely accessible therapeutic solutions. Highlights • Various aspects of immunotherapy, from its historical evolution to modern strategies and clinical applications, are explored. • Immunotherapeutic approaches, including cancer vaccines and oncolytic virus therapy, are discussed. • The efficacy and mechanisms of immune checkpoint inhibitors and adoptive cell therapies are evaluated. • The complexities of the tumor microenvironment and mechanisms of immune evasion are highlighted. • Advances in cytokines, chemokines, nanotechnology, and combination therapies that enhance immunotherapy effectiveness are outlined. Questions • What are the primary strategies and modalities employed in cancer immunotherapy? • How does the tumor microenvironment influence the efficacy of cancer immunotherapy? • What are the key challenges in developing effective cancer vaccines and adoptive cell therapies? • How do molecular and genetic factors, including noncoding RNAs and epigenetic modifications, contribute to immunotherapy resistance? • What are the future directions for enhancing the efficacy and accessibility of cancer immunotherapy?