Artificial intelligence in decoding muscle–organ crosstalk: Unveiling myokine networks and therapeutic frontiers by Ehsan Arabzadeh, Fatemeh Khanzadeh, Arezoo Kalhor

“…Advances in artificial intelligence (AI) are revolutionizing our ability to decode these complex interactions by predicting novel myokines, modeling signaling networks, and identifying therapeutic targets. …”
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Static network structure cannot stabilize cooperation among large language model agents. by Jin Han, Balaraju Battu, Ivan Romić, Talal Rahwan, Petter Holme

“…This raises a key question: Are LLMs about to emulate human behavior in cooperative dilemmas on networks? In this study, we examine networked interactions where agents repeatedly engage in the Prisoner's Dilemma within both well-mixed and structured network configurations, aiming to identify parallels in cooperative behavior between LLMs and humans. …”
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LLM-AIDSim: LLM-Enhanced Agent-Based Influence Diffusion Simulation in Social Networks by Lan Zhang, Yuxuan Hu, Weihua Li, Quan Bai, Parma Nand

“…This paper introduces an LLM-Enhanced Agent-Based Influence Diffusion Simulation (LLM-AIDSim) framework that integrates large language models (LLMs) into agent-based modelling to simulate influence diffusion in social networks. The proposed framework enhances traditional influence diffusion models by allowing agents to generate language-level responses, providing deeper insights into user agent interactions. …”
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MAHGA: Multi-Aspect Heterogeneous Graph Analysis for Harmful Speech Detection on Social Networks by Ryo Yoshida, Soh Yoshida, Mitsuji Muneyasu

“…Graph-based methods, particularly those employing graph neural networks, effectively capture these contextual interactions by modeling relationships within heterogeneous graphs and integrate diverse semantic elements derived through natural language processing. …”
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Semantic enhancement and change consistency network for semantic change detection in remote sensing images by Zhenghao Jiang, Biao Wang, Peng Zhang, Yanlan Wu, Zhiyuan Ye, Hui Yang

“…This paper proposes a semantic enhancement and change consistency network(SCNet). By enhancing the model's ability to extract semantic information from complex land-cover classes, we incorporate multi-scale adaptive modules, leveraging the efficient zero-shot capability of SAM2. …”
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MRDDA: a multi-relational graph neural network for drug–disease association prediction by Congzhou Chen, Yaozheng Zhou, Yinghong Li, Jin Xu, Demin Li, Lingfeng Wang

“…Biological entities such as drugs, genes, proteins, RNA, and diseases interact within a complex network. How to adequately extract the intrinsic relationships among them and accurately predict the drug-disease associations remains a challenge. …”
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Retrievable hydrogel networks with confined microalgae for efficient antibiotic degradation and enhanced stress tolerance by Minwen Jiang, Jie Zheng, Yi Tang, Hai Liu, Yawen Yao, Jianfei Zhou, Wei Lin, Yuan Ma, Jin Liu, Jiajing Zhou

“…Here we report bioprinted retrievable microalgae hydrogel networks (MHNs) by confining living microalgae in double-network hydrogels, which achieves enhanced antibiotic degradation (>99.3%) and recyclable ability. …”
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Unlocking the Potential of Gallic Acid-Based Metal Phenolic Networks for Innovative Adsorbent Design by Shella Permatasari Santoso, Artik Elisa Angkawijaya, Kuan-Chen Cheng, Shin-Ping Lin, Hsien-Yi Hsu, Chang-Wei Hsieh, Astrid Rahmawati, Osamu Shimomura, Suryadi Ismadji

“…Among various MPNs, metal ion gallic acid (GA) networks are particularly well-known for their exceptional stability, biological activity, and superior adsorption ability. …”
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Regression analysis and artificial neural networks for predicting pine species volume in community forests by Wenceslao Santiago-García

“…For the machine learning approach, multilayer perceptron (MLP) artificial neural networks (ANNs) were trained using four input variables: diameter at breast height, total tree height, species, and volume type. …”
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A Novel NeutroGraph Model for Dynamic Systems: Advancing NeutroStructures with Partially False Axioms in Interactive Digital Installation Art Design by Ziyuan Liu, Yixi Peng

“…The model is applied to a social interaction network, demonstrating its ability to capture axiom partiality. …”
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Coating Dormant Collagenase‐Producing Bacteria with Metal‐Anesthetic Networks for Precision Tumor Therapy by Qiuju Han, Fengmin Yang, Mian Chen, Mengmeng Zhang, Lu Wang, Hongxia Wang, Jinyao Liu, Zhenping Cao

“…By metal‐phenolic complexation and π–π stacking interactions, a Fe3+‐propofol network is formed on bacterial surface. …”
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The adverse effects of bisphosphonates in breast cancer: A systematic review and network meta-analysis. by Christopher Jackson, Alexandra L J Freeman, Zśofia Szlamka, David J Spiegelhalter

“…We carried out pairwise and network meta-analyses to estimate the size of any adverse effects potentially related to bisphosphonates. …”
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Effects of Different Individuals and Verbal Tones on Neural Networks in the Brain of Children with Cerebral Palsy by Ryosuke Yamauchi, Hiroki Ito, Ken Kitai, Kohei Okuyama, Osamu Katayama, Kiichiro Morita, Shin Murata, Takayuki Kodama

“…Therefore, we examined the differences between mothers and other individuals, such as physical therapists (PTs), in their verbal interactions with children with cerebral palsy who have poor communication abilities, as well as the neurological and physiological effects of variations in the tone of their speech. …”
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Dual Impact of Information Complexity and Individual Characteristics on Information and Disease Propagation by Yaqiong Wang, Jinyi Sun, Zhanxin Ma

“…Through systematic simulation experiments, this paper analyzes the mechanisms of information complexity, individual compromise, and cognitive ability in the evolution of propagation. This study shows that the interactive effects of individual characteristics and information complexity have a significant impact on disease spread. …”
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YOLO-UIR: A Lightweight and Accurate Infrared Object Detection Network Using UAV Platforms by Chao Wang, Rongdi Wang, Ziwei Wu, Zetao Bian, Tao Huang

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BCTDNet: Building Change-Type Detection Networks with the Segment Anything Model in Remote Sensing Images by Wei Zhang, Jinsong Li, Shuaipeng Wang, Jianhua Wan

“…Moreover, an interactive attention module bridges SAM with a Convolutional Neural Network, enabling seamless interaction between fine-grained structural information and deep semantic features. …”
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scPRINT: pre-training on 50 million cells allows robust gene network predictions by Jérémie Kalfon, Jules Samaran, Gabriel Peyré, Laura Cantini

“…Abstract A cell is governed by the interaction of myriads of macromolecules. Inferring such a network of interactions has remained an elusive milestone in cellular biology. …”
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ACNet: An Attention–Convolution Collaborative Semantic Segmentation Network on Sensor-Derived Datasets for Autonomous Driving by Qiliang Zhang, Kaiwen Hua, Zi Zhang, Yiwei Zhao, Pengpeng Chen

“…In intelligent vehicular networks, the accuracy of semantic segmentation in road scenes is crucial for vehicle-mounted artificial intelligence to achieve environmental perception, decision support, and safety control. …”
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Network pharmacology analyses and corresponding validation of the mechanistic effects of Yangyin Tongnao Granules in ischemic stroke by Jiaying Yu, Qianqian Chen, Xiaotong Dou, Rongjin Zhu, Jiehong Yang, Weifeng Jin, Haitong Wan, Li Yu, Yangyang Zhang

“…These results offer support for the network pharmacology results, demonstrating the ability of YYTN to exert therapeutic benefits in IS by modulating HIF-1α, VEGFA, and PAI-1 gene and protein expression.…”
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GNNSeq: A Sequence-Based Graph Neural Network for Predicting Protein–Ligand Binding Affinity by Somanath Dandibhotla, Madhav Samudrala, Arjun Kaneriya, Sivanesan Dakshanamurthy

“…To overcome these limitations, we developed GNNSeq, a novel hybrid machine learning model that integrates a Graph Neural Network (GNN) with Random Forest (RF) and XGBoost. …”
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