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Authors = Hao Chen

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35 pages, 21105 KiB  
Review
A Review: The Beauty of Serendipity Between Integrated Circuit Security and Artificial Intelligence
by Chen Dong, Decheng Qiu, Bolun Li, Yang Yang, Chenxi Lyu, Dong Cheng, Hao Zhang and Zhenyi Chen
Sensors 2025, 25(15), 4880; https://doi.org/10.3390/s25154880 (registering DOI) - 7 Aug 2025
Abstract
Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third [...] Read more.
Integrated circuits are the core of a cyber-physical system, where tens of billions of components are integrated into a tiny silicon chip to conduct complex functions. To maximize utilities, the design and manufacturing life cycle of integrated circuits rely on numerous untrustworthy third parties, forming a global supply chain model. At the same time, this model produces unpredictable and catastrophic issues, threatening the security of individuals and countries. As for guaranteeing the security of ultra-highly integrated chips, detecting slight abnormalities caused by malicious behavior in the current and voltage is challenging, as is achieving computability within a reasonable time and obtaining a golden reference chip; however, artificial intelligence can make everything possible. For the first time, this paper presents a systematic review of artificial-intelligence-based integrated circuit security approaches, focusing on the latest attack and defense strategies. First, the security threats of integrated circuits are analyzed. For one of several key threats to integrated circuits, hardware Trojans, existing attack models are divided into several categories and discussed in detail. Then, for summarizing and comparing the numerous existing artificial-intelligence-based defense strategies, traditional and advanced artificial-intelligence-based approaches are listed. Finally, open issues on artificial-intelligence-based integrated circuit security are discussed from three perspectives: in-depth exploration of hardware Trojans, combination of artificial intelligence, and security strategies involving the entire life cycle. Based on the rapid development of artificial intelligence and the initial successful combination with integrated circuit security, this paper offers a glimpse into their intriguing intersection, aiming to draw greater attention to these issues. Full article
(This article belongs to the Collection Integrated Circuits and Systems for Smart Sensor Applications)
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17 pages, 1786 KiB  
Article
Simulation and Control of Water Pollution Load in the Xiaoxingkai Lake Basin Based on a System Dynamics Model
by Yaping Wu, Dan Chen, Fujia Li, Mingming Feng, Ping Wang, Lingang Hao and Chunnuan Deng
Sustainability 2025, 17(15), 7167; https://doi.org/10.3390/su17157167 (registering DOI) - 7 Aug 2025
Abstract
With the rapid development of the social economy, human activities have increasingly disrupted water environments, and the continuous input of pollutants poses significant challenges for water environment management. Taking the Xiaoxingkai Lake basin as the study area, this paper develops a social–economic–water environment [...] Read more.
With the rapid development of the social economy, human activities have increasingly disrupted water environments, and the continuous input of pollutants poses significant challenges for water environment management. Taking the Xiaoxingkai Lake basin as the study area, this paper develops a social–economic–water environment model based on the system dynamics methodology, incorporating subsystems for population, agriculture, and water pollution. The model focuses on four key indicators of pollution severity, namely, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and ammonia nitrogen (NH3-N), and simulates the changes in pollutant loads entering the river under five different scenarios from 2020 to 2030. The results show that agricultural non-point sources are the primary contributors to TN (79.5%) and TP (73.7%), while COD primarily originates from domestic sources (64.2%). NH3-N is mainly influenced by urban domestic activities (44.7%) and agricultural cultivation (41.2%). Under the status quo development scenario, pollutant loads continue to rise, with more pronounced increases under the economic development scenario, thus posing significant sustainability risks. The pollution control enhancement scenario is most effective in controlling pollutants, but it does not promote socio-economic development and has high implementation costs, failing to achieve coordinated socio-economic and environmental development in the region. The dual-reinforcement scenario and moderate-reinforcement scenario achieve a balance between pollution control and economic development, with the moderate-reinforcement scenario being more suitable for long-term regional development. The findings can provide a scientific basis for water resource management and planning in the Xiaoxingkai Lake basin. Full article
16 pages, 10690 KiB  
Article
Clade-Specific Recombination and Mutations Define the Emergence of Porcine Epidemic Diarrhea Virus S-INDEL Lineages
by Yang-Yang Li, Ke-Fan Chen, Chuan-Hao Fan, Hai-Xia Li, Hui-Qiang Zhen, Ye-Qing Zhu, Bin Wang, Yao-Wei Huang and Gairu Li
Animals 2025, 15(15), 2312; https://doi.org/10.3390/ani15152312 - 7 Aug 2025
Abstract
 Porcine epidemic diarrhea virus (PEDV) continues to circulate globally, causing substantial economic losses to the swine industry. Historically, PEDV strains are classified into the classical G1, epidemic G2, and S-INDEL genotypes. Among these genotypes, the highly virulent and prevalent G2 genotype has been [...] Read more.
 Porcine epidemic diarrhea virus (PEDV) continues to circulate globally, causing substantial economic losses to the swine industry. Historically, PEDV strains are classified into the classical G1, epidemic G2, and S-INDEL genotypes. Among these genotypes, the highly virulent and prevalent G2 genotype has been extensively studied. However, recent clinical outbreaks in China necessitate a reevaluation of the epidemiological and evolutionary dynamics of circulating strains. This study analyzed 37 newly sequenced S genes and public sequences to characterize the genetic variations of S-INDEL strains. Our analysis revealed that S-INDEL strains are endemic throughout China, with a phylogenetic analysis identifying two distinct clades: clade 1, comprising early endemic strains, and clade 2, representing a recently dominant, geographically restricted lineage in China. While inter-genotypic recombination has been documented, our findings also demonstrate that intra-genotypic and intra-clade recombination events contributed significantly to the emergence of clade 2, distinguishing its evolutionary pattern from clade 1. A comparative analysis identified 22 clade-specific amino acid changes, 11 of which occurred in the D0 domain. Notably, mutations at positively selected sites—113 and 114 within the D0 domain, a domain associated with pathogenicity—were specific to clade 2. A phylodynamic analysis indicated Germany as the epicenter of S-INDEL dispersal, with China acting as a sink population characterized by localized transmission networks and frequent recombination events. These results demonstrate that contemporary S-INDEL strains, specifically clade 2, exhibit unique recombination patterns and mutations potentially impacting virulence. Continuous surveillance is essential to assess the pathogenic potential of these evolving recombinant variants and the efficacy of vaccines against them.  Full article
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21 pages, 2994 KiB  
Article
A Multi-Omics Integration Framework with Automated Machine Learning Identifies Peripheral Immune-Coagulation Biomarkers for Schizophrenia Risk Stratification
by Feitong Hong, Qiuming Chen, Xinwei Luo, Sijia Xie, Yijie Wei, Xiaolong Li, Kexin Li, Benjamin Lebeau, Crystal Ling, Fuying Dao, Hao Lin, Lixia Tang, Mi Yang and Hao Lv
Int. J. Mol. Sci. 2025, 26(15), 7640; https://doi.org/10.3390/ijms26157640 - 7 Aug 2025
Abstract
Schizophrenia (SCZ) is a complex psychiatric disorder with heterogeneous molecular underpinnings that remain poorly resolved by conventional single-omics approaches, limiting biomarker discovery and mechanistic insights. To address this gap, we applied an artificial intelligence (AI)-driven multi-omics framework to an open access dataset comprising [...] Read more.
Schizophrenia (SCZ) is a complex psychiatric disorder with heterogeneous molecular underpinnings that remain poorly resolved by conventional single-omics approaches, limiting biomarker discovery and mechanistic insights. To address this gap, we applied an artificial intelligence (AI)-driven multi-omics framework to an open access dataset comprising plasma proteomics, post-translational modifications (PTMs), and metabolomics to systematically dissect SCZ pathophysiology. In a cohort of 104 individuals, comparative analysis of 17 machine learning models revealed that multi-omics integration significantly enhanced classification performance, reaching a maximum AUC of 0.9727 (95% CI: 0.8889–1.000) using LightGBMXT, compared to 0.9636 (95% CI: 0.8636–1.0000) with CNNBiLSTM for proteomics alone. Interpretable feature prioritization identified carbamylation at immunoglobulin-constant region sites IGKC_K20 and IGHG1_K8, alongside oxidation of coagulation factor F10 at residue M8, as key discriminative molecular events. Functional analyses identified significantly enriched pathways including complement activation, platelet signaling, and gut microbiota-associated metabolism. Protein interaction networks further implicated coagulation factors F2, F10, and PLG, as well as complement regulators CFI and C9, as central molecular hubs. The clustering of these molecules highlights a potential axis linking immune activation, blood coagulation, and tissue homeostasis, biological domains increasingly recognized in psychiatric disorders. These results implicate immune–thrombotic dysregulation as a critical component of SCZ pathology, with PTMs of immune proteins serving as quantifiable disease indicators. Our work delineates a robust computational strategy for multi-omics integration into psychiatric research, offering biomarker candidates that warrant further validation for diagnostic and therapeutic applications. Full article
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24 pages, 10858 KiB  
Article
The Distribution Characteristics and Influencing Factors of Global Armed Conflict Clusters
by Mengmeng Hao, Shijia Ma, Dong Jiang, Fangyu Ding, Shuai Chen, Jun Zhuo, Genan Wu, Jiping Dong and Jiajie Wu
Systems 2025, 13(8), 670; https://doi.org/10.3390/systems13080670 - 7 Aug 2025
Abstract
Understanding the spatial dynamics and drivers of armed conflict is crucial for anticipating risk and informing targeted interventions. However, current research rarely considers the spatio-temporal clustering characteristics of armed conflicts. Here, we assess the distribution dynamics and driving factors of armed conflict from [...] Read more.
Understanding the spatial dynamics and drivers of armed conflict is crucial for anticipating risk and informing targeted interventions. However, current research rarely considers the spatio-temporal clustering characteristics of armed conflicts. Here, we assess the distribution dynamics and driving factors of armed conflict from the perspective of armed conflict clusters, employing complex network dynamic community detection methods and interpretable machine learning approaches. The results show that conflict clusters vary in terms of regional distribution. Sub-Saharan Africa boasts the highest number of conflict clusters, accounting for 37.9% of the global total and covering 40.4% of the total cluster area. In contrast, South Asia and Afghanistan, despite having a smaller proportion of clusters at 12.1%, hold the second-largest cluster area, which is 18.1% of the total. The characteristics of different conflict networks are influenced by different factors. Historical exposure, socio-economic deprivation, and spatial structure are the primary determinants of conflict patterns, while climatic variables contribute less prominently as part of a broader system of environmental vulnerability. Moreover, the influence of driving factors shows spatial heterogeneity. By integrating cluster-level analysis with interpretable machine learning, this study offers a novel perspective for understanding the multidimensional characteristics of armed conflicts. Full article
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12 pages, 1530 KiB  
Article
Effect of Aggregate Type on Asphalt–Aggregate Adhesion and Its Quantitative Characterization
by Liuxiao Chen, Junlin Li, Hao Xiang, Jun Zhang, Enlin Feng and Lin Kong
Materials 2025, 18(15), 3696; https://doi.org/10.3390/ma18153696 - 6 Aug 2025
Abstract
To study the effect of aggregate type on the adhesion between asphalt and aggregate, limestone, basalt, diabase, and 70# asphalt with SBS asphalt were selected. The mineral phase composition of the aggregates was analyzed by X-ray diffraction. The surface energy theory was used [...] Read more.
To study the effect of aggregate type on the adhesion between asphalt and aggregate, limestone, basalt, diabase, and 70# asphalt with SBS asphalt were selected. The mineral phase composition of the aggregates was analyzed by X-ray diffraction. The surface energy theory was used to calculate the adhesion work and the work of flaking. The modified water boiling method combined with image processing technology was used to quantitatively characterize the flaking behavior of the asphalt. The results show that the aggregate type is closely related to the asphalt–aggregate adhesion. The mineral compositions of different types of aggregates vary significantly, with limestone, being a strongly alkaline aggregate predominantly comprising CaCO3, exhibiting better adhesion with asphalt. The contact angle test and modified boiling method also yielded the same results, and the adhesion relationship with asphalt was limestone > basalt > diabase. Image processing technology effectively characterizes the spalling situation of asphalt and conducts quantitative analysis. Full article
(This article belongs to the Section Construction and Building Materials)
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17 pages, 4422 KiB  
Systematic Review
The Impact of Blood Flow Restriction Training on Glucose and Lipid Metabolism in Overweight or Obese Adults: A Systematic Review and Meta-Analysis
by Hao Chen, Peng Liu, Yidi Deng, Haibo Cai, Pu Liang and Xin Jiang
Life 2025, 15(8), 1245; https://doi.org/10.3390/life15081245 - 6 Aug 2025
Abstract
Blood flow restriction training (BFRT) offers notable advantages, including simplicity and time efficiency. However, no meta-analysis has yet comprehensively evaluated its effects on glucose and lipid metabolism in overweight or obese adults. This meta-analysis examines the potential efficacy of BFRT in improving glycemic [...] Read more.
Blood flow restriction training (BFRT) offers notable advantages, including simplicity and time efficiency. However, no meta-analysis has yet comprehensively evaluated its effects on glucose and lipid metabolism in overweight or obese adults. This meta-analysis examines the potential efficacy of BFRT in improving glycemic and lipid control in overweight/obese adults. The literature was searched in six databases, with the search period up to 31 March 2025. A total of eight randomized controlled trials involving 267 participants were identified. Data were analyzed using Stata 18.0 and RevMan 5.4 with random effects models. Outcomes included fasting blood glucose (FBG), homeostasis model assessment of insulin resistance (HOMA-IR), and lipid profiles, and risk of bias and publication bias (Egger’s test) were assessed. BFRT significantly reduced FBG (Hedges’ g = −1.13, 95% CI: −1.65 to −0.62, p < 0.01; I2 = 66.34%) and HOMA-IR (Hedges’ g = −0.98, 95% CI: −1.35 to −0.61, p < 0.01; I2 = 17.33%) compared with the controls. However, no significant changes were observed in lipid profiles. Our analysis demonstrates that BFRT exhibits the favorable effect of improving glucose metabolism in overweight/obese adults; however, current evidence does not support significant advantages of BFRT for lipid metabolism improvement. Full article
(This article belongs to the Special Issue Focus on Exercise Physiology and Sports Performance: 2nd Edition)
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35 pages, 8516 KiB  
Article
Study on Stress Monitoring and Risk Early Warning of Flexible Mattress Deployment in Deep-Water Sharp Bend Reaches
by Chu Zhang, Ping Li, Zebang Cui, Kai Wu, Tianyu Chen, Zhenjia Tian, Jianxin Hao and Sudong Xu
Water 2025, 17(15), 2333; https://doi.org/10.3390/w17152333 - 6 Aug 2025
Abstract
This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 [...] Read more.
This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 m/s—the risk of structural failures such as displacement, flipping, or tearing of the mattress becomes significant. To improve construction safety and stability, the study integrates numerical modeling and on-site strain monitoring to analyze the mechanical response of flexible mattresses during deployment. A three-dimensional finite element model based on the catenary theory was developed to simulate stress distributions under varying flow velocities and angles, revealing stress concentrations at the mattress’s upper edge and reinforcement junctions. Concurrently, a real-time monitoring system using high-precision strain sensors was deployed on critical shipboard components, with collected data analyzed through a remote IoT platform. The results demonstrate strong correlations between mattress strain, flow velocity, and water depth, enabling the identification of high-risk operational thresholds. The proposed monitoring and early-warning framework offers a practical solution for managing construction risks in extreme riverine environments and contributes to the advancement of intelligent construction management for underwater revetment works. Full article
(This article belongs to the Section Oceans and Coastal Zones)
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16 pages, 4442 KiB  
Article
Faulted-Pole Discrimination in Shipboard DC Microgrids Using S-Transformation and Convolutional Neural Networks
by Yayu Yang, Zhenxing Wang, Ning Gao, Kangan Wang, Binjie Jin, Hao Chen and Bo Li
J. Mar. Sci. Eng. 2025, 13(8), 1510; https://doi.org/10.3390/jmse13081510 - 5 Aug 2025
Abstract
The complex topology of shipboard DC microgrids and the strong coupling between positive and negative poles during faults pose significant challenges for faulted-pole identification, especially under high-resistance conditions. To address these issues, this paper proposes a novel faulted-pole identification method based on S-Transformation [...] Read more.
The complex topology of shipboard DC microgrids and the strong coupling between positive and negative poles during faults pose significant challenges for faulted-pole identification, especially under high-resistance conditions. To address these issues, this paper proposes a novel faulted-pole identification method based on S-Transformation and convolutional neural networks (CNNs). Single-ended voltage and current measurements from the generator side are used to generate time–frequency spectrograms via S-Transformation, which are then processed by a CNN trained to classify the faulted pole. This approach avoids reliance on complex threshold settings. Simulation results on a representative shipboard DC microgrid demonstrate that the proposed method achieves high accuracy, fast response, and strong robustness, even under high-resistance fault scenarios. The method significantly enhances the selectivity and reliability of fault protection, offering a promising solution for advanced marine DC power systems. Compared to conventional fault-diagnosis techniques, the proposed model achieves notable improvements in classification accuracy and computational efficiency for line-fault detection. Full article
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18 pages, 6311 KiB  
Article
Unraveling the Excellent High-Temperature Oxidation Behavior of FeNiCuAl-Based Alloy
by Guangxin Wu, Gaosheng Li, Lijun Wei, Hao Chen, Yujie Wang, Yunze Qiao, Yu Hua, Chenyang Shi, Yingde Huang and Wenjie Yang
Materials 2025, 18(15), 3679; https://doi.org/10.3390/ma18153679 - 5 Aug 2025
Abstract
This study synthesized FeNiCuAlX high-entropy alloys (HEAs) (where X = Cr, Co, Mn) using arc melting and investigated their high-temperature oxidation behavior in air at 900 °C. The oxidation kinetics of all alloys followed a parabolic rate, with the oxidation rate constants (kp) [...] Read more.
This study synthesized FeNiCuAlX high-entropy alloys (HEAs) (where X = Cr, Co, Mn) using arc melting and investigated their high-temperature oxidation behavior in air at 900 °C. The oxidation kinetics of all alloys followed a parabolic rate, with the oxidation rate constants (kp) of FeNiCuAlCr, FeNiCuAlCo, and FeNiCuAlMn being approximately two to three orders of magnitude lower than that of the FeNiCu alloy. Specifically, FeNiCuAlCr exhibited the lowest kp value of 1.72 × 10−6 mg2·cm4/s, which is significantly lower than those of FeNiCuAlCo (3.29 × 10−6 mg2·cm4/s) and FeNiCuAlMn (1.71 × 10−5 mg2·cm4/s). This suggests that the addition of chromium promotes the formation of a dense Al2O3/Cr2O3 oxide layer, significantly enhancing the oxidation resistance. Furthermore, corrosion resistance was assessed through potentiodynamic polarization and electrochemical impedance spectroscopy in a 3.5% NaCl solution. FeNiCuAlCr demonstrated exceptional resistance to localized corrosion, as indicated by its low corrosion current density (45.7 μA/cm2) and high pitting potential (−0.21 V), highlighting its superior corrosion performance. Full article
(This article belongs to the Special Issue Characterization, Properties, and Applications of New Metallic Alloys)
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18 pages, 6413 KiB  
Article
A Recognition Method for Marigold Picking Points Based on the Lightweight SCS-YOLO-Seg Model
by Baojian Ma, Zhenghao Wu, Yun Ge, Bangbang Chen, He Zhang, Hao Xia and Dongyun Wang
Sensors 2025, 25(15), 4820; https://doi.org/10.3390/s25154820 - 5 Aug 2025
Abstract
Accurate identification of picking points remains a critical challenge for automated marigold harvesting, primarily due to complex backgrounds and significant pose variations of the flowers. To overcome this challenge, this study proposes SCS-YOLO-Seg, a novel method based on a lightweight segmentation model. The [...] Read more.
Accurate identification of picking points remains a critical challenge for automated marigold harvesting, primarily due to complex backgrounds and significant pose variations of the flowers. To overcome this challenge, this study proposes SCS-YOLO-Seg, a novel method based on a lightweight segmentation model. The approach enhances the baseline YOLOv8n-seg architecture by replacing its backbone with StarNet and introducing C2f-Star, a novel lightweight feature extraction module. These modifications achieve substantial model compression, significantly reducing the model size, parameter count, and computational complexity (GFLOPs). Segmentation efficiency is further optimized through a dual-path collaborative architecture (Seg-Marigold head). Following mask extraction, picking points are determined by intersecting the optimized elliptical mask fitting results with the stem skeleton. Experimental results demonstrate that SCS-YOLO-Seg effectively balances model compression with segmentation performance. Compared to YOLOv8n-seg, it maintains high accuracy while significantly reducing resource requirements, achieving a picking point identification accuracy of 93.36% with an average inference time of 28.66 ms per image. This work provides a robust and efficient solution for vision systems in automated marigold harvesting. Full article
(This article belongs to the Section Smart Agriculture)
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19 pages, 4660 KiB  
Article
Coordination Polymers Bearing Angular 4,4′-Oxybis[N-(pyridin-3-ylmethyl)benzamide] and Isomeric Dicarboxylate Ligands: Synthesis, Structures and Properties
by Yung-Hao Huang, Yi-Ju Hsieh, Yen-Hsin Chen, Shih-Miao Liu and Jhy-Der Chen
Molecules 2025, 30(15), 3283; https://doi.org/10.3390/molecules30153283 - 5 Aug 2025
Abstract
Reactions of the angular 4,4′-oxybis[N-(pyridin-3-ylmethyl)benzamide] (L) with dicarboxylic acids and transition metal salts afforded non-entangled {[Cd(L)(1,3-BDC)(H2O)]∙2H2O}n (1,3-BDC = 1,3-benzenedicarboxylic acid), 1; {[Cd(L)(1,4-HBDC)(1,4-BDC)0.5]∙2H2O}n (1,4-BDC = [...] Read more.
Reactions of the angular 4,4′-oxybis[N-(pyridin-3-ylmethyl)benzamide] (L) with dicarboxylic acids and transition metal salts afforded non-entangled {[Cd(L)(1,3-BDC)(H2O)]∙2H2O}n (1,3-BDC = 1,3-benzenedicarboxylic acid), 1; {[Cd(L)(1,4-HBDC)(1,4-BDC)0.5]∙2H2O}n (1,4-BDC = 1,4-benzenedicarboxylic acid), 2; {[Cu2(L)2(1,3-BDC)2]∙1.5H2O}n, 3; {[Ni(L)(1,3-BDC)(H2O)]∙2H2O}n, 4; {[Zn(L)(1,3-BDC)]∙4H2O}n, 5; {[Zn(L)(1,4-BDC)]∙2H2O}n, 6; and [Cd3(L)2(1,4-BDC)3]n, 7, which have been structurally characterized by using single-crystal X-ray diffraction. Complexes 15 and 7 are 2D layers, giving (64·8·10)(6)-2,4L3, (42·82·102)(42·84)2(4)2, (4·5·6)(4·55·63·7)-3,5L66, (64·8·10)(6)-2,4L3, interdigitated (84·122)(8)2-2,4L2 and (36·46·53)-hxl topologies, respectively, and 6 is a 1D chain with the (43·62·8)(4)-2,4C3 topology. The factors that govern the structures of 17 are discussed and the thermal properties of 17 and the luminescent properties of complexes 1, 2, 5 and 6 are investigated. The stabilities of complexes 1 and 5 toward the detection of Fe3+ ions are also evaluated. Full article
(This article belongs to the Special Issue Advances in Functional Polymers and Their Applications)
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12 pages, 2363 KiB  
Article
MCC950 Alleviates Fat Embolism-Induced Acute Respiratory Distress Syndrome Through Dual Modulation of NLRP3 Inflammasome and ERK Pathways
by Chin-Kuo Lin, Zheng-Wei Chen, Yu-Hao Lin, Cheng-Ta Yang, Chung-Sheng Shi, Chieh-Mo Lin, Tzu Hsiung Huang, Justin Ching Hsien Lu, Kwok-Tung Lu and Yi-Ling Yang
Int. J. Mol. Sci. 2025, 26(15), 7571; https://doi.org/10.3390/ijms26157571 - 5 Aug 2025
Abstract
Fat embolism is a critical medical emergency often resulting from long bone fractures or amputations, leading to acute respiratory distress syndrome (ARDS). The NOD-like receptor pyrin domain-containing 3 (NLRP3) inflammasome, a key regulator of innate immunity, is activated by reactive oxygen species and [...] Read more.
Fat embolism is a critical medical emergency often resulting from long bone fractures or amputations, leading to acute respiratory distress syndrome (ARDS). The NOD-like receptor pyrin domain-containing 3 (NLRP3) inflammasome, a key regulator of innate immunity, is activated by reactive oxygen species and tissue damage, contributing to inflammatory responses. This study examines the role of NLRP3 in fat embolism-induced ARDS and evaluates the therapeutic potential of MCC950, a selective NLRP3 antagonist. Fat embolism was induced by fatty micelle injection into the tail vein of Sprague Dawley rats. Pulmonary injury was assessed through lung weight gain as an edema indicator, NLRP3 expression via Western blot, and IL-1β levels using ELISA. Histological damage and macrophage infiltration were evaluated with hematoxylin and eosin staining. Fat embolism significantly increased pulmonary NLRP3 expression, lipid peroxidation, IL-1β release, and macrophage infiltration within four hours, accompanied by severe pulmonary edema. NLRP3 was localized in type I alveolar cells, co-localizing with aquaporin 5. Administration of MCC950 significantly reduced inflammatory responses, lipid peroxidation, pulmonary edema, and histological damage, while attenuating MAPK cascade phosphorylation of ERK and Raf. These findings suggest that NLRP3 plays a critical role in fat embolism-induced acute respiratory distress syndrome, and its inhibition by MCC950 may offer a promising therapeutic approach. Full article
(This article belongs to the Section Molecular Biology)
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16 pages, 11908 KiB  
Article
A Quinary-Metallic High-Entropy Electrocatalyst with Driving of Cocktail Effect for Enhanced Oxygen Evolution Reaction
by Jing-Yi Lv, Zhi-Jie Zhang, Hao Zhang, Jun Nan, Zan Chen, Xin Liu, Fei Han, Yong-Ming Chai and Bin Dong
Catalysts 2025, 15(8), 744; https://doi.org/10.3390/catal15080744 - 5 Aug 2025
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Abstract
The complex system of high-entropy materials makes it challenging to reveal the specific function of each site for oxygen evolution reaction (OER). Here, with nickel foam (NF) as the substrate, FeCoNiCrMo/NF is designed to be prepared by metal–organic frameworks (MOF) as a precursor [...] Read more.
The complex system of high-entropy materials makes it challenging to reveal the specific function of each site for oxygen evolution reaction (OER). Here, with nickel foam (NF) as the substrate, FeCoNiCrMo/NF is designed to be prepared by metal–organic frameworks (MOF) as a precursor under an argon atmosphere. XRD analysis confirms that it retains a partial MOF crystal structure (characteristic peak at 2θ = 11.8°) with amorphous carbon (peaks at 22° and 48°). SEM-EDS mapping and XPS demonstrate uniform distribution of Fe, Co, Ni, Cr, and Mo with a molar ratio of 27:24:30:11:9. Electrochemical test results show that FeCoNiCrMo/NF has excellent OER characteristics compared with other reference prepared samples. FeCoNiCrMo/NF has an overpotential of 285 mV at 100 mA cm−2 and performs continuously for 100 h without significant decline. The OER mechanism of FeCoNiCrMo/NF further reveal that Co and Ni are true active sites, and the dissolution of Cr and Mo promote the conversion of active sites into MOOH following the lattice oxygen mechanism (LOM). The precipitation–dissolution equilibrium of Fe also plays an important role in the OER process. The study of different reaction sites in complex systems points the way to designing efficient and robust catalysts. Full article
(This article belongs to the Special Issue Non-Novel Metal Electrocatalytic Materials for Clean Energy)
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18 pages, 3940 KiB  
Article
CTCF Represses CIB2 to Balance Proliferation and Differentiation of Goat Myogenic Satellite Cells via Integrin α7β1–PI3K/AKT Axis
by Changliang Gong, Huihui Song, Zhuohang Hao, Zhengyi Zhang, Nanjian Luo and Xiaochuan Chen
Cells 2025, 14(15), 1199; https://doi.org/10.3390/cells14151199 - 5 Aug 2025
Viewed by 83
Abstract
Skeletal muscle development is a critical economic trait in livestock, governed by myogenic satellite cell regulation. Integrins mediate mechanical anchorage to the ECM and enable ECM–intracellular signaling. CIB2, as an EF-hand-domain protein involved in mechanotransduction, shows significant developmental regulation in goat muscle. [...] Read more.
Skeletal muscle development is a critical economic trait in livestock, governed by myogenic satellite cell regulation. Integrins mediate mechanical anchorage to the ECM and enable ECM–intracellular signaling. CIB2, as an EF-hand-domain protein involved in mechanotransduction, shows significant developmental regulation in goat muscle. Although the role of CIB2 in skeletal muscle growth is poorly characterized, we observed pronounced developmental upregulation of IB2 in postnatal goat muscle. CIB2 expression increased >20-fold by postnatal day 90 (P90) compared to P1, sustaining elevation through P180 (p < 0.05). Functional investigations indicated that siRNA-mediated knockdown of CIB2 could inhibit myoblast proliferation by inducing S-phase arrest (p < 0.05) and downregulating the expression of CDK4/Cyclin D/E. Simultaneously, CIB2 interference treatment was found to decrease the proliferative activity of goat myogenic satellite cells, yet it significantly promoted differentiation by upregulating the expression of MyoD/MyoG/MyHC (p < 0.01). Mechanistically, CTCF was identified as a transcriptional repressor binding to an intragenic region of the CIB2 gene locus (ChIP enrichment: 2.3-fold, p < 0.05). Knockdown of CTCF induced upregulation of CIB2 (p < 0.05). RNA-seq analysis established CIB2 as a calcium signaling hub: its interference activated IL-17/TNF and complement cascades, while overexpression suppressed focal adhesion/ECM–receptor interactions and enriched neuroendocrine pathways. Collectively, this study identifies the CTCF-CIB2–integrin α7β1–PI3K/AKT axis as a novel molecular mechanism that regulates the balance of myogenic fate in goats. These findings offer promising targets for genomic selection and precision breeding strategies aimed at enhancing muscle productivity in ruminants. Full article
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