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Targeting the HER2-ELF3-KRAS axis: a novel therapeutic strategy for KRAS^G13D colorectal cancer

Molecular Cancer 2025年第1期24卷 1-22页

作者： Hwang, Soo-Yeon Seo, Yoojeong Park, Seojeong Kim, Seul-Ah Moon, Inhye Liu, Yi Kim, Seojeong Pak, Eun Seon Jung, Sehyun Kim, Hyeyoon Jeon, Kyung-Hwa Seo, Seung Hee Sung, Inyoung Lee, Heetak Park, So-Yeon Na, Younghwa Kim, Tae Il Kwon, Youngjoo College of Pharmacy Graduate School of Pharmaceutical Sciences Ewha Womans University Seoul 03760 South Korea Graduate Program in Innovative Biomaterials Convergence Ewha Womans University Seoul 03760 South Korea Division of Gastroenterology Department of Internal Medicine Yonsei University College of Medicine 50 Yonseiro Seodaemun-Gu Seoul 03722 South Korea BK21 FOUR Intelligence Computing Seoul National University Seoul South Korea Center for Genome Engineering Institute for Basic Science 55 Expo-Ro Yuseong-Gu Daejeon 34126 South Korea College of Pharmacy CHA University Pocheon 11160 South Korea

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, with KRAS mutations playing a significant role in its tumorigenesis. Among the KRAS variants, the G13D mutation is associated with poor prognosis and distinctive biological behaviors. This study focuses on the role of HER2, a critical prognostic and predictive biomarker, in modulating the unique characteristics of KRAS^G13D-mutated CRCs. We identified a novel transcriptional regulatory network involving HER2, ELF3, and KRAS, with ELF3 acting as a key transcription factor (TF) that regulates KRAS expression under conditions of HER2 overexpression. Our findings reveal that this HER2-ELF3-KRAS axis is exclusively activated in KRAS^G13D, driving aggressive oncogenic features and conferring resistance to cetuximab (CTX) therapy. Through comprehensive analysis of gene expression profiles, we demonstrated that HER2 is a crucial therapeutic target specifically for KRAS^G13D CRCs. To explore this further, we introduced YK1, a small molecule inhibitor designed to disrupt the ELF3-MED23 interaction, leading to the transcriptional downregulation of HER2 and KRAS. This intervention significantly attenuated the HER2-ELF3-KRAS axis, sensitizing KRAS^G13D CRCs to CTX and reducing their tumorigenic potential by inhibiting the epithelial-to-mesenchymal transition process. Our study underscores the importance of HER2 as a key determinant in the unique biological characteristics of KRAS^G13D CRCs and highlights the therapeutic potential of targeting the HER2-ELF3-KRAS axis. By presenting YK1 as a novel pharmacological approach, we provide a promising strategy for developing tailored interventions for KRAS^G13D CRCs, contributing to the ongoing efforts in precision medicine for CRCs. © The Author(s) 2025.

关键词： Colorectal cancer ELF3 HER2 HER2-ELF3-KRAS axis KRAS mutation KRASG13D Protein–protein interaction inhibitor Transcriptional regulation

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Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse

arXiv

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arXiv 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge computing environments presents significant challenges due to the limited computing resources of edge devices and the dynamic nature of wireless networks. This paper proposes a novel framework that integrates contract-inspired contest theory, Deep Reinforcement Learning (DRL), and GDMs to optimize image generation in these resource-constrained environments. The framework addresses the critical challenges of resource allocation and semantic data transmission quality by incentivizing edge devices to efficiently transmit high-quality semantic data, which is essential for creating realistic and immersive images. The use of contest and contract theory ensures that edge devices are motivated to allocate resources effectively, while DRL dynamically adjusts to network conditions, optimizing the overall image generation process. Experimental results demonstrate that the proposed approach not only improves the quality of generated images but also achieves superior convergence speed and stability compared to traditional methods. This makes the framework particularly effective for optimizing complex resource allocation tasks in mobile edge Metaverse applications, offering enhanced performance and efficiency in creating immersive virtual environments. © 2025, CC BY.

关键词： Mobile edge computing

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Adaptive Contextual Caching for Mobile Edge Large Language Model Service

arXiv

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arXiv 2025年

作者： Liu, Guangyuan Liu, Yinqiu Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui College of Computing and Data Science The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation (RAG) mitigates some challenges by integrating external knowledge bases, inefficient cache management can still result in high retrieval latency and frequent cache updates. To address these issues, we propose an Adaptive Contextual Caching (ACC) framework that anticipates user needs by proactively caching semantically relevant data for mobile-edge LLMs. ACC utilizes a deep reinforcement learning (DRL) module to refine cache replacement policies, balancing user context, document similarity, and the overhead associated with cache misses. Experimental results demonstrate that ACC increases cache hit rates to over 80% after only 11 training episodes, outperforming FIFO, LRU, and semantic-only caching while reducing retrieval latency by up to 40%. In particular, ACC also reduces local caching overhead (i.e., the cost of updating the cache when a miss occurs) by as much as 55%, enabling scalable, low-latency LLM services in resource-constrained edge environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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ZeroCAN: Anomaly-Based Zero-Day Attack Detection in Vehicular CAN Bus Networks

ZeroCAN: Anomaly-Based Zero-Day Attack Detection in Vehicula...

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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Jonathan Rendel William Balte Harrison Kurunathan Hazem Ismail Ali Alexandre Dos Santos Roque Wagner Ourique De Morais Mahdi Fazeli Department for Computing and Electronics for Real-time and Embedded Systems (CERES) School of Information Technology (ITE) Halmstad University Halmstad Sweden CISTER/ISEP Polytechnic Institute of Porto Portugal Graduate Program of Electrical Engineering Federal University of Rio Grande do Sul - UFRGS Porto Alegre Brazil

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Zero-day attacks present a significant security threat to vehicular networks, exploiting vulnerabilities at both software and hardware levels within such systems that remain undiscovered. Mitigating these threats is essential to ensuring the safety and security of vehicular systems. Support Vector Machine (SVM) is a good candidate for anomaly detection of zero-day attacks within vehicular networks because it can handle highdimensional data and effectively distinguish between normal and abnormal patterns in complex and dynamic environments. A trained SVM on the normal operation data of in-vehicular network can identify flag deviations, thus making it effective in the detection of any previously unknown attack patterns, which is a common behaviour of zero-day attacks. In this paper, we introduce an anomaly detection method called “ZeroCAN” which models the behaviour of every single electronic control unit on the network with a separate SVM and a set of high-level features that capture the timing and data payload aspects of CANbus traffic. This approach achieves an anomaly detection rate of over $\mathbf{9 9 \%}$ and a false positive rate below $\mathbf{0. 0 1 \%}$ during normal operation in most cases.

关键词： Support vector machines Telecommunication traffic Feature extraction Data models Timing Security Vehicle dynamics Anomaly detection Standards Payloads

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multimodal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Assistive technology with device for self-inflating bag in neonatology

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Research on Biomedical Engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

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An Ultra Low-Energy VLSI Approximate Discrete Haar Wavelet Transform for ECG Data Compression 30

An Ultra Low-Energy VLSI Approximate Discrete Haar Wavelet T...

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30th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2023

作者： Cardozo, Arthur Rosa, Morgana M. A. Soares, Rafael Costa, Eduardo Bampi, Sergio Graduate Program on Computing Pelotas Brazil Graduate Program on Electronic Engineering and Computing Pelotas Brazil Porto Alegre Brazil

ISBN: (纸本)9798350326499

This work proposes an ultra-low-energy ECG data compression with VLSI DHWT-based (discrete Haar wavelet transform) architecture to enable storage and transmission in resource-constrained environments. We present original, pruned, and approximate DHWT (ODHWT, PDHWT, and AxDHWT, respectively) hardware architectures for ECG data compression at ultra-high energy efficiency. Our best proposal employing the AxDHWT hardware architecture requires just five additions only. Using a PDHWT technique to improve energy efficiency observes the evolution of the signal-to-noise ratio and the ultimate impact on the ECG data compression application. The DHWT-based configurations architecture proposal achieves a minimum compression ratio of 0.125 (i.e., 1/8) and a PRD (percent root difference) © 2023 IEEE.

关键词： Digital storage

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Investigating the computation of smoothed deceptive routes in topographic terrains for agent-based simulation systems

Investigating the computation of smoothed deceptive routes i...

引用

Computational Intelligence in Security, Defence and Biometrics (CISDB), IEEE Symposium on

作者： Luigi P. Souza Thiago R. S. Leão Crhistopher Lenhard Edison P. Freitas Luis A. L. Silva Graduate Program in Computer Science Federal Univ. of Santa Maria Santa Maria Brazil Undergraduate Course in Computer Science Federal Univ. of Santa Maria Santa Maria Brazil Institute of Informatics Federal Univ. of Rio Grande do Sul Porto Alegre Brazil Applied Computing Department Federal Univ. of Santa Maria Santa Maria Brazil

ISBN: (数字)9798331508296

ISBN: (纸本)9798331508302

The capacity to deceptively move in hilly terrains is fundamental to agents in simulation systems for tactical and strategic military training. Such an ability to deceive the adversary can ensure a relevant advantage by hiding the real goals of a mission. Using pairs of real and deceptive mission goals, this paper investigates the planning of realistic deceptive routes for simulated agents. With real-world terrain elevation maps, it shows how to explore pathfinding algorithms with relevant path-smoothing characteristics (Theta* and WJPS*, contrasting with the standard $A^{*}$ algorithm) in terrains with pronounced relief features. The study analyzes the effects of terrain elevation costs and the representation of relief contour lines on the determination of more realistic deceptive paths. This work also investigates how users can adjust a Last Topographic Deceptive Point ($L D P_{T}$) calculation to enhance the pathfinding algorithm’s ability to produce more deceptively dense and topographically aware routes. Experimental results for different deceptive topographic path planning strategies are evaluated according to statistical models showing that Theta*, despite being slower than the base $A^{*}$ method in most cases, generated smoothed paths while maintaining a similar deception density for the proposed strategies. On the other hand, WJPS outperformed both in execution time for certain strategies while maintaining the smoothed path characteristic and resulting in a path with lower deceptive capacity.

关键词： Training Hands Biometrics Costs Path planning Planning Security Standards Computational intelligence

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HAAQI-Net: A Non-Intrusive Neural Music Audio Quality Assessment Model for Hearing Aids

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 1877-1892页

作者： Dyah A. M. G. Wisnu Stefano Rini Ryandhimas E. Zezario Hsin-Min Wang Yu Tsao Taiwan International Graduate Program—Social Network and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan College of Informatics National Chengchi University Taipei Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Electrical Engineering Chung Yuan Christian University Taiwan

This paper introduces HAAQI-Net, a non-intrusive music audio quality assessment model for hearing aid users. Unlike traditional methods such as Hearing Aid Audio Quality Index (HAAQI), which requires intrusive reference signal comparisons, HAAQI-Net offers a more accessible and computationally efficient alternative. Leveraging a bidirectional long short-term memory architecture with attention mechanisms and features extracted from a pre-trained BEATs model, it can predict HAAQI scores directly from music audio clips and hearing loss patterns. The experimental results demonstrate that, compared to the traditional HAAQI as the reference, HAAQI-Net achieves a linear correlation coefficient (LCC) of 0.9368, a Spearman's rank correlation coefficient (SRCC) of 0.9486, and a mean squared error (MSE) of 0.0064, while significantly reducing the inference time from 62.52 seconds to 2.54 seconds. Furthermore, a knowledge distillation strategy was applied, reducing the parameters by 75.85% and inference time by 96.46%, while maintaining strong performance (LCC: 0.9071, SRCC: 0.9307, MSE: 0.0091). To expand its capabilities, HAAQI-Net was adapted to predict subjective human scores, mean opinion score (MOS), by fine-tuning. This adaptation significantly improved the prediction accuracy. Furthermore, the robustness of HAAQI-Net was evaluated under varying sound pressure level (SPL) conditions, revealing optimal performance at a reference SPL of 65 dB, with the accuracy gradually decreasing as SPL deviated from this point. The advancements in subjective score prediction, SPL robustness, and computational efficiency position HAAQI-Net as a reliable solution for music audio quality assessment, significantly contributing to the development of efficient and accurate models in audio signal processing and hearing aid technology.

关键词： Hearing aids Quality assessment Training Feature extraction Speech processing Auditory system Computational modeling Adaptation models Transformers Multiple signal classification

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Effects of Spatial Uniformity of Continuous and Pulse Laser Irradiation on the Microstructure and Mechanical Properties of Ti-6Al-4V in Powder Bed Fusion

SSRN

引用

SSRN 2025年

作者： Moon, Seunghwan Ji, Seungmuk Ko, Yoonseok Lee, Min-Su Jun, Tea-Sung Kim, Dong-Ik Yeo, Jong-Souk School of Integrated Technology College of Computing Yonsei University Seoul03722 Korea Republic of BK21 Graduate Program in Intelligent Semiconductor Technology Yonsei University Seoul03722 Korea Republic of Seoul02792 Korea Republic of Department of Mechanical Engineering Incheon National University Incheon22012 Korea Republic of Hankook Precision Works 45 Munpyeongseo-ro Daedeok-gu Daejeon34303 Korea Republic of

Laser beam powder bed fusion (PBF-LB/M) with Ti-6Al-4V (Ti64) powder is a promising method for fabricating medical implants owing to its ability to fabricate precise structures and the biocompatibility of the fabricated material. The use of a pulsed laser source in a PBF-LB/M system has been proposed for stable irradiation with an appropriate amount of energy. In this study, the pulse width modulation (PWM) method was adapted into a PBF-LB/M machine with a laser that operates in both continuous wave (CW) and pulsed wave modes. The effects of CW and PWM lasers on the microstructure and mechanical properties of the fabricated material based on the volumetric energy density (VED) calculated using the average power were compared. Results revealed that the uniform distribution of energy irradiation across the entire region ensured the similarity in the porosities and Vickers hardness tendencies conferred by CW and PWM lasers in the specimens according to the VED. In contrast, the spatially nonuniform distribution of the laser irradiation resulted in a significantly higher porosity in the specimen fabricated using the PWM laser than that produced using the CW laser at the same VED, resulting in reduced compressive yield strength. Additionally, the electron backscattered diffraction analysis of the grain structures in the fabricated specimens revealed that there were no significant differences in the average grain size, phase distribution, and misorientation angle of the samples produced using CW and PWM lasers at the same VED. However, sharper grains with a grain shape aspect ratio of less than 0.3 were 7% higher in specimens produced using the PWM laser. This study highlights the possibility of fabricating medical implants with desired patient bone-specific microstructure and mechanical properties. © 2025, The Authors. All rights reserved.

关键词： Vickers hardness

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