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Exploring the mechanistic role of epidermal growth factor receptor activation in non-cancer kidney disease

BIOCELL 2025年第1期49卷 79-92页

作者： JU-YEON LEE DAEUN MOON JINU KIM Medical Course College of MedicineCatholic Kwandong UniversityGangneung25601Republic of Kore Department of Anatomy College of MedicineJeju National UniversityJeju63243Republic of Korea Interdisciplinary Graduate Program in Advanced Convergence Technology&Science Jeju National UniversityJeju63243Republic of Korea

The epidermal growth factor receptor(EGFR)is a transmembrane glycoprotein that plays a crucial role in signal transduction and cellular *** review explores the function of EGFR in kidney physiology and its implications for various kidney *** signaling is essential for kidney function and repair mechanisms,and its dysregulation significantly impacts both acute and chronic kidney *** review discusses the normal distribution of EGFR in kidney tubular segments,the mechanism of its activation and inhibition,and the therapeutic potential of EGFR-targeting antagonists and ***,it explores the pathophysiological characteristics observed in rodent models of kidney diseases through pharmacological and genetic inhibition of EGFR,highlighting therapeutic challenges and limitations such as species differences,variability in disease models,and potential adverse ***,the findings underscore the multifaceted role of EGFR in kidney diseases,influencing inflammation,fibrosis,and tissue *** complex involvement suggests that targeting EGFR may be a beneficial therapeutic strategy for managing these conditions,potentially mitigating inflammation and fibrosis while promoting tissue repair.

关键词： Epidermal growth factor receptor Chronic kidney disease Acute kidney injury Tubulointerstitial fibrosis

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MERNet: Multimodal Emotion Recognition in Conversation Network via Cross-Modal Knowledge Distillation and Contrastive Learning

MERNet: Multimodal Emotion Recognition in Conversation Netwo...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Sooyeon Hwang Gahgene Gweon Eunseong Kwon Interdisciplinary Program in Artificial Intelligence Seoul National University South Korea Graduate School of Convergence Science and Technology Seoul National University South Korea Dept. of Computer Science and Engineering POSTECH South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

Multimodal Emotion Recognition in Conversation (ERC) is a task of predicting the emotion of each utterance in a conversation by utilizing both verbal and non-verbal modalities. However, existing approaches often struggle to bridge cross-modal gaps, resulting in misaligned features and frequent misclassification of minority emotions into semantically similar majority emotions. To address these challenges, we propose MERNet, a framework that employs cross-modal knowledge distillation and contrastive learning to align multimodal features and effectively distinguish subtle emotions in conversations. Our framework consists of two stages: 1) guiding non-verbal modalities with the text modality to transfer knowledge and align their features, and 2) applying contrastive learning with emotion labels as anchors to distinguish subtle differences between similar emotions and address the class imbalance problem. Experiments conducted on two benchmark datasets, IEMOCAP and MELD, demonstrate that our MERNet outperforms existing state-of-the-art models.

关键词： Knowledge engineering Bridges Emotion recognition Visualization Computational modeling Contrastive learning Benchmark testing Linguistics Big Data

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Examining the Impact of Expression Fragmentation and Number Redundancy on Financial QA task

Examining the Impact of Expression Fragmentation and Number ...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Yoonjae Lee Kyung Seo Ki Gahgene Gweon Bugeun Kim Graduate School of Convergence Science and Technology Seoul National University South Korea Interdisciplinary Program in Artificial Intelligence Seoul National University South Korea Department of AI Chung-Ang University South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

The goal of financial QA is to generate solution equations by solving problems about financial reports. Current financial QA models can suffer from two issues: expression fragmentation and number redundancy. We conduct experiments to examine the impact of the two issues. The experimental results show that addressing the expression fragmentation issue in financial QA using EPT improves the execution accuracy by 0.09, and alleviating the number redundancy issue by removing redundant numbers in the input of the FinQANet generator improves the execution accuracy by 0.07.

关键词： Accuracy Computational modeling Redundancy Big Data Mathematical models Generators

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EXCESSIVE SUCROSE EXACERBATES HIGH FAT DIET-INDUCED HEPATIC INFLAMMATION AND FIBROSIS PROMOTING OSTEOARTHRITIS IN MICE MODEL

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Osteoarthritis and Cartilage 2025年 33卷 S139-S140页

作者： Yunhui Min Yunji Heo Dinesh Suminda Godagama Gamaarachchige minhye Kim myeongyeon shin Md. M. Ansari Young-Ok Son Interdisciplinary Graduate Program in Advanced Convergence Technology and Science Jeju National University Jeju Korea (the Republic of) Department of Animal Biotechnology Faculty of Biotechnology College of Applied Life Sciences Jeju National University Jeju-si Jeju-do Korea (the Republic of) Interdisciplinary Graduate Program in Advanced Convergence Technology and Science Jeju national University Jeju-si Jeju-do Korea (the Republic of)

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Copper nanowire/multi-walled carbon nanotube com- posites as all-nanowire flexible electrode for fast-charging/ discharging lithium-ion battery

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Nano Research 2018年第2期11卷 769-779页

作者： Zhenxing Yin Sanghun Cho Duck-Jae You Yong-keon Ahn Jeeyoung Yoo Youn Sang Kim Program in Nano Science and Technology Graduate School of Convergence Science and Technology Seoul National University Seoul Republic of Korea Advanced Institutes of Convergence Technology Gyeonggi-do Republic of Korea

A novel lightweight three-dimensional （3D） composite anode for a fast-charging] discharging Li-ion battery （LIB） was fabricated entirely using one-dimensional （1D） nanomaterials, i.e., Cu nanowires （CuNWs） and multi-walled C nanotubes （MWCNTs）. Because of the excellent electrical conductivity, high-aspect ratio structures, and large surface areas of these nanomaterials, the CuNW-MWCNT composite （CNMC） with 3D structure provides significant advantages regarding the transport pathways for both electrons and ions. As an advanced binder-free anode, a CuNW-MWCNT composite film with a controllable thickness （~ 600 prn） exhibited a considerably low sheet resistance, and internal cell resistance. Furthermore, the random CuNW network with 3D structure acting as a rigid framework not only prevented MWCNT shrinkage and expansion due to aggregation and swelling but also minimized the effect of the volume change during the charge/discharge process. Both a half cell and a full cell of LIBs with the CNMC anode exhibited high specific capacities and Coulombic efficiendes, even at a high current. More importantly, we for the first time overcame the limitation of MWCNTs as anode materials for fast-charging]discharging LIBs （both half cells and full cells） by employing CuNWs, and the resulting anode can be applied to flexible LIBs. This innovative anode structure can lead to the development of ultrafast chargeable LIBs for electric vehides.

关键词： three-dimensional （3D）composite,all-nanowire electrode,fast chargeable batter3 fuN-cell Li-ion batteries（L1Bs）,flexible battery

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Integrating microbiome and metabolome analyses to unravel the role of inulin in enhancing the meat quality and bone health of ducks

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Scientific Reports 2025年第1期15.0卷 1-17页

作者： Li, Zemin Kim, Eunyoung Ko, Kayeon Liu, Anxin Lee, Yunkyoung Zhang, Guiguo Department of Animal Nutrition Shandong Agricultural University Taian City 271018 China Department of Food Science and Nutrition Jeju National University Jeju 63243 South Korea China-South Korea International Joint Laboratory of Functional Polysaccharides in Shandong Province Taian City 271018 China Key Laboratory of Efficient Utilization of Non-grain Feed Resources Taian City 271018 China Interdisciplinary Graduate Program in Advanced Convergence Technology & Science Jeju National University Jeju 63243 South Korea

Inulin, a natural dietary fiber, has various health-promoting bioactivities. However, the impacts of dietary inulin on duck productivity and overall health remain unclear. This study investigated the effects of inulin supplementation on systemic health and its underlying mechanisms by integrating the microbiota and metabolome analyses. One hundred twenty 16-day-old male Cherry Valley ducks with similar initial body weight (BW) were randomly assigned to 20 cages, with two treatments (6 ducks/cage and 10 cages/treatment): a basal diet (CON group) or a basal diet supplemented with 25 g inulin/kg (INU group). The 18-d feeding trials demonstrated that ducks fed the inulin-supplemented diet presented significantly improved growth performance, bone health, and meat quality compared with those in the control group (P < 0.05). Additionally, inulin supplementation reshaped the intestinal microbiota, increasing diversity and the abundance of Alistipes, Ligilactobacillus, and Streptococcus (P < 0.05). Metabolome analysis revealed that inulin feeding significantly modulated 13 metabolites (P < 0.05), which were enriched primarily in health-related metabolic pathways such as taurine and hypotaurine metabolism, steroid hormone biosynthesis, and histidine metabolism. Correlation analysis revealed a positive relationship among the modulated microbes and metabolites and improved healthy parameters. Overall, inulin supplementation improved the bone and muscle health of ducks by specifically modulating key gut microbes, metabolites, and associated metabolic pathways. These findings suggest that inulin supplementation represents a feasible nutritional strategy for improving the meat quality and bone health of intensively raised ducks. © The Author(s) 2025.

关键词： Bone health Duck Inulin Meat quality Metabolome Microbiome

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XERICO as a target for engineering stress-resilient crops: Mechanisms, applications, and future directions

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Plant Physiology and Biochemistry 2025年 225卷 110013页

作者： Im, Jong Hee Kim, Won-Chan Han, Kyung-Hwan Ko, Jae-Heung Department of Horticulture Michigan State University East Lansing 48824 MI United States Interdisciplinary Graduate Program in Advanced Convergence Technology and Science Jeju National University Jeju 63243 South Korea DOE Great Lakes Bioenergy Research Center Michigan State University East Lansing 48824 MI United States School of Applied Biosciences Kyungpook National University Daegu 41566 South Korea Department of Forestry Michigan State University East Lansing 48824 MI United States of Green-Bio Science Kyung Hee University Yongin 17104 South Korea

XERICO's capacity to enhance ABA-driven stress responses across diverse crops, its regulatory crosstalk with other hormonal pathways, and its compatibility with advanced genetic engineering tools highlight its central role in sustainable agriculture. Leveraging XERICO in crop improvement programs aligns with the urgent need to mitigate the impacts of climate-induced stress in agriculture, offering a pathway toward resilient and high-yielding crops. By enabling crops to withstand drought and other environmental stresses, XERICO-based biotechnological approaches hold transformative potential for global food security and environmental sustainability. © 2025 Elsevier Masson SAS

关键词： ABA regulation Climate resilience Drought tolerance Environmental stress Genetic engineering Sustainable agriculture XERICO

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Environmental Chromium Exposure Drives Osteoarthritis Pathogenesis via NF-κB–Hif-2α/Zip8 Signaling in Articular Cartilage

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Osteoarthritis and Cartilage 2025年 33卷 S376-S377页

作者： Dinesh Suminda Godagama Gamaarachchige Yunhui Min Yunji Heo minhye Kim myeongyeon shin Md. M. Ansari Young-Ok Son Interdisciplinary Graduate Program in Advanced Convergence Technology and Science Jeju National University Jeju Korea(the Republic of) Animal biothchnology jeju national university Jeju-si Korea(the Republic of) Next Generation Convergence Science and Technology Cooperative Course Jeju National University Jeju Korea (the Democratic People's Republic of) Department of Animal Biotechnology Jeju National University Jeju Jeju self-governing Province Korea (the Republic of)

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Meter-scale heterostructure printing for high-toughness fiber electrodes in intelligent digital apparel

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Nature Communications 2025年第1期16卷 1-10页

作者： Lee, Gun-Hee Lee, Yunheum Seo, Hyeonyeob Jo, Kyunghyun Yeo, Jinwook Kim, Semin Bae, Jae-Young Kim, Chul Majidi, Carmel Kang, Jiheong Kang, Seung-Kyun Ryu, Seunghwa Park, Seongjun Medical Research Center Seoul National University Seoul South Korea Departments of Cogno-Mechatronics Engineering and Optics & Mechatronics Engineering Pusan National University Busan South Korea Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea Department of Mechanical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea Graduate School of Semiconductor Technology Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea Department of Materials Science and Engineering Seoul National University Seoul South Korea Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA United States Department of Chemistry Seoul National University Seoul Seoul South Korea School of Transdisciplinary Innovations Seoul National University Seoul South Korea Department of Biomedical Science College of Medicine Seoul National University Seoul South Korea Interdisciplinary Program in Bioengineering College of Engineering Seoul National University Seoul South Korea Department of Transdisciplinary Medicine Seoul National University Hospital Seoul South Korea

Intelligent digital apparel, which integrates electronic functionalities into clothing, represents the future of healthcare and ubiquitous control in wearable devices. Realizing such apparel necessitates developing meter-scale conductive fibers with high toughness, conductivity, stable conductance under deformation, and mechanical durability. In this study, we present a heterostructure printing method capable of producing meter-scale (~50 m) biphasic conductive fibers that meet these criteria. Our approach involves encapsulating deformable liquid metal particles (LMPs) within a functionalized thermoplastic polyurethane matrix. This encapsulation induces in situ assembly of LMPs during fiber formation, creating a heterostructure that seamlessly integrates the matrix’s durability with the LMPs’ superior electrical performance. Unlike rigid conductive materials, deformable LMPs offer stretchability and toughness with a low gauge factor. Through precise twisting using an engineered annealing machine, multiple fiber strands are transformed into robust, electrically stable meter-scale electrodes. This advancement enhances their practicality in various intelligent digital apparel applications, such as stretchable displays, wearable healthcare systems, and digital controls. © The Author(s) 2025.

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