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MR2CPPIS: Accurate prediction of protein–protein interaction sites based on multi-scale Res2Net with coordinate attention mechanism

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computers in Biology and Medicine 2024年 176卷 108543-108543页

作者： Gong, Yinyin Li, Rui Liu, Yan Wang, Jilong Cao, Buwen Fu, Xiangzheng Li, Renfa Chen, Danny Z. College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan University Changsha410082 China Peng Cheng Laboratory Shenzhen518066 China College of Information and Electronic Engineering Hunan City University Yiyang413002 China Department of Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States

Proteins play a vital role in various biological processes and achieve their functions through protein–protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological methods for identifying PPIs are costly, labor-intensive, and time-consuming. The development of computational prediction methods for PPI sites offers promising alternatives. Most known deep learning (DL) methods employ layer-wise multi-scale CNNs to extract features from protein sequences. But, these methods usually neglect the spatial positions and hierarchical information embedded within protein sequences, which are actually crucial for PPI site prediction. In this paper, we propose MR2CPPIS, a novel sequence-based DL model that utilizes the multi-scale Res2Net with coordinate attention mechanism to exploit multi-scale features and enhance PPI site prediction capability. We leverage the multi-scale Res2Net to expand the receptive field for each network layer, thus capturing multi-scale information of protein sequences at a granular level. To further explore the local contextual features of each target residue, we employ a coordinate attention block to characterize the precise spatial position information, enabling the network to effectively extract long-range dependencies. We evaluate our MR2CPPIS on three public benchmark datasets (Dset 72, Dset 186, and PDBset 164), achieving state-of-the-art performance. The source codes are available at https://***/YyinGong/MR2CPPIS. © 2024 Elsevier Ltd

关键词： Forecasting

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High Hospitalization Rates and Risk Factors Among Frail Patients With Cirrhosis: A 10-year Population-based Cohort Study

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Clinical Gastroenterology and Hepatology 2025年第7期23卷 1152-1163页

作者： Hasjim, Bima J. Mohammadi, Mohsen Balbale, Salva N. Paukner, Mitchell Banea, Therese Shi, Haoyan Furmanchuk, Al'ona VanWagner, Lisa B. Zhao, Lihui Duarte-Rojo, Andres Doll, Julianna Mehrotra, Sanjay Ladner, Daniela P. Northwestern University Transplant Outcomes Research Collaborative (NUTORC) Comprehensive Transplant Center (CTC) Northwestern University Chicago Illinois United States Center for Engineering and Health McCormick School of Engineering and Applied Science Northwestern University Chicago Illinois United States Department of Industrial Engineering and Management Sciences McCormick School of Engineering Northwestern University Evanston IL United States Division of Gastroenterology and Hepatology Department of Medicine Northwestern University Feinberg School of Medicine Chicago Illinois United States Center for Health Services and Outcomes Research Institute of Public Health and Medicine & Northwestern Quality Improvement Research & Education in Surgery (NQUIRES) Department of Surgery Northwestern University Feinberg School of Medicine Chicago Illinois United States Center of Innovation for Complex Chronic Healthcare (CINCCH) Edward Hines Jr. VA Hospital Hines IL United States Division of Biostatistics Department of Preventive Medicine Northwestern University Feinberg School of Medicine Chicago Illinois United States Department of Mathematics Northwestern University Evanston IL United States Department of Computer Science McCormick School of Engineering Northwestern University Evanston IL United States Department of General Internal Medicine Feinberg School of Medicine Northwestern University Chicago Illinois United States Division of Digestive and Liver Diseases Department of Medicine University of Texas Southwestern Medical Center Dallas Texas United States Division of Transplantation Department of Surgery Northwestern University Feinberg School of Medicine Chicago Illinois United States

Background & Aims: Cirrhosis-related inpatient hospitalizations have increased dramatically over the past decade. We used a longitudinal dataset capturing a large metropolitan area in the United States from 2011 to 2021 to evaluate contemporary hospitalization rates and risk factors among frail patients with cirrhosis. Methods: We conducted a retrospective, longitudinal cohort study using the Chicago Area Patient-centered Outcomes research Network (CAPriCORN) database, an electronic health record repository that aggregates de-duplicated data across 7 health care systems in the Chicago metropolitan area, from 2011 to 2021. The primary outcome of our study was the rate of hospitalization encounters. Frailty was defined by the Hospital Frailty Risk Score. Hospitalization rates were reported per 100 patients per year, and a multivariable logistic regression analysis identified predictors of annual hospitalization probability. Results: During the study period, of 36,971 patients, 16,265 patients (44%) were hospitalized (compensated, 18.4%;decompensated, 81.6%). Hospitalization rates were highest in patients with decompensated cirrhosis, reaching nearly 77.3 hospitalizations/100 patients per year. Hospitalization rates among patients with compensated cirrhosis were also high (14.2 vs 77.3 hospitalization/100 patients per year), with odds of annual hospitalization 3 times (odds ratio, 3.1;95% confidence interval, 2.9-3.4) as high among compensated patients with intermediate frailty and 5 times (odds ratio, 5.2;95% confidence interval, 4.5-6.0) as high among those with severe frailty (compared with compensated patients with low frailty). Conclusion: Compensated and decompensated cirrhosis patients with intermediate to severe frailty face a substantially increased odds of annual hospitalizations compared with those with low frailty. Future work should focus on targeted interventions to incorporate routine frailty screenings into cirrhosis care and to ultimately minimize high

关键词： Cirrhosis Frailty Hospitalizations

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Special Issue on Artificial Intelligence for Synthetic Biology

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ACS SYNTHETIC BIOLOGY 2024年第2期13卷 408-410页

作者： Martin, Hector Garcia Mazurenko, Stanislav Zhao, Huimin Biological Systems and Engineering Division Lawrence Berkeley National Laboratory Berkeley California 94720 United States BCAM − Basque Center for Applied Mathematics Bilbao 48009 Spain DOE Agile BioFoundry Emeryville California 94608 United States DOE Joint BioEnergy Institute Emeryville California 94608 United States Loschmidt Laboratories Department of Experimental Biology and RECETOX Faculty of Science Masaryk University Kamenice 5 625 00 Brno Czech Republic International Clinical Research Center St. Anne’s University Hospital Brno Pekarska 53 656 91 Brno Czech Republic Department of Chemical and Biomolecular Engineering University of Illinois at Urbana−Champaign Urbana Illinois 61801 United States

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Bilateral Contract for Load Frequency and Renewable Energy Sources Using advanced Controller

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computers, Materials & Continua 2022年第11期73卷 3165-3180页

作者： Krishan Arora Gyanendra Prasad Joshi Mahmoud Ragab Muhyaddin Rawa Ahmad H.Milyani Romany F.Mansour Eunmok Yang School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwara144001PunjabIndia School of Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia King Abdullah City for Atomic and Renewable Energy(K.A.CARE) RiyadhSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoul02707Korea

Reestablishment in power system brings in significant transformation in the power sector by extinguishing the possession of sound consolidated ***,the collaboration of various manufacturing agencies,autonomous power manufacturers,and buyers have created complex installation *** regular active load and inefficiency of best measures among varied associates is a huge *** sudden load deviation will give rise to immediate amendment in frequency and tie-line power *** is essential to deal with every zone’s frequency and tie-line power within permitted confines followed by fluctuations within the ***,it can be proficient by implementing Load Frequency Control under the Bilateral case,stabilizing the power and frequency distinction within the interrelated power *** the net deviation in multiple areas is possible by minimizing the unbalance of Bilateral Contracts with the help of proportional integral and advanced controllers like Harris Hawks *** proposed the advanced controller Harris Hawk optimizer-based model and validated it on a test *** experiment results show that the delay time is 0.0029 s and the settling time of 20.86 s *** model can also be leveraged to examine the decision boundaries of the Bilateral case.

关键词： Bilateral contract load frequency control optimization harris hawks optimizer

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Enabling technology and core theory of synthetic biology

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science China(Life sciences) 2023年第8期66卷 1742-1785页

作者： Xian-En Zhang Chenli Liu Junbiao Dai Yingjin Yuan Caixia Gao Yan Feng Bian Wu Ping Wei Chun You Xiaowo Wang Tong Si Faculty of Synthetic Biology Shenzhen Institute of Advanced TechnologyShenzhen 518055China Institute of Synthetic Biology Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300072China State Key Laboratory of Plant Cell and Chromosome Engineering Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Microbial Metabolism Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin 300308China Ministry of Education Key Laboratory of Bioinformatics Center for Synthetic and Systems BiologyBioinformatics DivisionBeijing National Research Center for Information Science and TechnologyDepartment of AutomationTsinghua UniversityBeijing 100084China

Synthetic biology provides a new paradigm for life science research(“build to learn”)and opens the future journey of biotechnology(“build to use”).Here,we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology,including synthesis and assembly of a genome,DNA storage,gene editing,molecular evolution and de novo design of function proteins,cell and gene circuit engineering,cell-free synthetic biology,artificial intelligence(AI)-aided synthetic biology,as well as *** also introduce the concept of quantitative synthetic biology,which is guiding synthetic biology towards increased accuracy and predictability or the real rational *** conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

关键词： synthetic biology quantitative synthetic biology genome synthesis and assembly DNA storage molecular evolution de novo design computer-aided design cell engineering gene circuit chassis cell artificial intelligent(AI) biofoundry

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A hybrid FEM-PINN method for time-dependent partial differential equations

arXiv

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arXiv 2024年

作者： Feng, Xiaodong Shangguan, Haojiong Tang, Tao Wan, Xiaoliang Zhou, Tao Division of Science and Technology BNU-HKBU United International College Zhuhai519087 China School of Electrical and Computer Engineering Guangzhou Nanfang College Guangzhou510970 China Department of Mathematics Center for Computation and Technology Louisiana State University Baton Rouge70803 United States Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In this work, we present a hybrid numerical method for solving evolution partial differential equations (PDEs) by merging the time finite element method with deep neural networks. In contrast to the conventional deep learning-based formulation where the neural network is defined on a spatiotemporal domain, our methodology utilizes finite element basis functions in the time direction where the space-dependent coefficients are defined as the output of a neural network. We then apply the Galerkin or collocation projection in the time direction to obtain a system of PDEs for the space-dependent coefficients which is approximated in the framework of PINN. The advantages of such a hybrid formulation are twofold: statistical errors are avoided for the integral in the time direction, and the neural network’s output can be regarded as a set of reduced spatial basis functions. To further alleviate the difficulties from high dimensionality and low regularity, we have developed an adaptive sampling strategy that refines the training set. More specifically, we use an explicit density model to approximate the distribution induced by the PDE residual and then augment the training set with new time-dependent random samples given by the learned density model. The effectiveness and efficiency of our proposed method have been demonstrated through a series of numerical experiments. © 2024, CC BY.

关键词： Partial differential equations

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NIR-Responsive Methotrexate-Modified Iron Selenide Nanorods for Synergistic Magnetic Hyperthermic, Photothermal, and Chemodynamic Therapy

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ACS Applied Materials and Interfaces 2024年第20期16卷 25622-25636页

作者： Thirumurugan, Senthilkumar Muthiah, Kayalvizhi Samuvel Lin, Yu-Chien Dhawan, Udesh Liu, Wai-Ching Wang, An-Ni Liu, Xinke Hsiao, Michael Tseng, Ching-Li Chung, Ren-Jei No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Faculty of Science and Technology Technological and Higher Education Institute of Hong Kong Hong Kong New Territories999077 Hong Kong Scrona AG Grubenstrasse 9 Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Genomics Research Center Academia Sinica Taipei115 Taiwan Department and Graduate Institute of Veterinary Medicine School of Veterinary Medicine National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei10608 Taiwan

Breast cancer is a malignant tumor with a high mortality rate among women. Therefore, it is necessary to develop novel therapies to effectively treat this disease. In this study, iron selenide nanorods (FeSe2 NRs) were designed for use in magnetic hyperthermic, photothermal, and chemodynamic therapy (MHT/PTT/CDT) for breast cancer. To illustrate their efficacy, FeSe2 NRs were modified with the chemotherapeutic agent methotrexate (MTX). MTX-modified FeSe2 (FeSe2-MTX) exhibited excellent controlled drug release properties. Fe2+ released from FeSe2 NRs induced the release of •OH from H2O2 via a Fenton/Fenton-like reaction, enhancing the efficacy of CDT. Under alternating magnetic field (AMF) stimulation and 808 nm laser irradiation, FeSe2-MTX exerted potent hyperthermic and photothermal effects by suppressing tumor growth in a breast cancer nude mouse model. In addition, FeSe2 NRs can be used for magnetic resonance imaging in vivo by incorporating their superparamagnetic characteristics into a single nanomaterial. Overall, we presented a novel technique for the precise delivery of functional nanosystems to tumors that can enhance the efficacy of breast cancer treatment. © 2024 The Authors. Published by American Chemical Society

关键词： Magnetic resonance imaging

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Boosting Thermal Conductivity by Surface Plasmon Polaritons Propagating along a Thin Ti Film

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Physical Review Letters 2023年第17期130卷 176302-176302页

作者： Dong-min Kim Sinwoo Choi Jungwan Cho Mikyung Lim Bong Jae Lee Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea Center for Extreme Thermal Physics and Manufacturing Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea School of Mechanical Engineering Sungkyunkwan University Suwon 16419 South Korea Nano-Convergence Manufacturing Systems Research Division Korea Institute of Machinery and Materials Daejeon 34103 South Korea

We experimentally demonstrate boosted in-plane thermal conduction by surface plasmon polaritons (SPPs) propagating along a thin Ti film on a glass substrate. Due to the lossy nature of metal, SPPs can propagate over centimeter-scale distances even along a supported metal film, and the resulting ballistic heat conduction can be quantitatively validated. Further, for a 100-nm-thick Ti film on a glass substrate, a significant enhancement of in-plane thermal conductivity compared to bulk value (∼25%) is experimentally shown. This Letter will provide a new avenue to employ SPPs for heat dissipation along a supported thin film, which can be readily applied to mitigate hot-spot issues in microelectronics.

关键词： Plasmons Polaritons Thermal conductivity

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Cryo-EM structures of human m6A writer complexes

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细胞研究（英文版） 2022年第11期32卷 982-994页

作者： Shichen Su Shanshan Li Ting Deng Minsong Gao Yue Yin Baixing Wu Chao Peng Jianzhao Liu Jinbiao Ma Kaiming Zhang State Key Laboratory of Genetic Engineering Collaborative Innovation Center of Genetics and DevelopmentMultiscale Research Institute of Complex SystemsDepartment of Biochemistry and BiophysicsSchool of Life SciencesFudan UniversityShanghaiChina MOE Key Laboratory for Cellular Dynamics and Division of Life Sciences and Medicine University of Science and Technology of ChinaHefeiAnhuiChina MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringZhejiang UniversityHangzhouZhejiangChina National Facility for Protein Science in Shanghai Zhangjiang LaboratoryShanghai Advanced Research InstituteChinese Academy of ScienceShanghaiChina State Key Laboratory of Genetic Engineering Collaborative Innovation Center of Genetics and DevelopmentMultiscale Research Institute of Complex SystemsDepartment of Biochemistry and BiophysicsSchool of Life SciencesFudan UniversityShanghaiChina Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Guangdong-Hong Kong Joint Laboratory for RNA MedicineRNA Biomedical InstituteMedical Research CenterSun Yat-Sen Memorial HospitalSun Yat-Sen UniversityGuangzhouGuangdongChina

N6-methyladenosine(m6A)is the most abundant ribonucleotide modification among eukaryotic messenger *** m6A"writer"consists of the catalytic subunit m6A-METTL complex(MAC)and the regulatory subunit m6A-METTL-associated complex(MACOM),the latter being essential for enzymatic ***,we report the cryo-electron microscopy(cryo-EM)structures of MACOM at a 3.0-A resolution,uncovering that WTAP and VIRMA form the core structure of MACOM and that ZC3H13 stretches the conformation by binding ***,the 4.4-? resolution cryo-EM map of the MACOM-MAC complex,combined with crosslinking mass spectrometry and GST pull-down analysis,elucidates a plausible model of the m6A writer complex,in which MACOM binds to MAC mainly through WTAP and METTL3 *** combination with in vitro RNA substrate binding and m6A methyltransferase activity assays,our results illustrate the molecular basis of how MACOM assembles and interacts with MAC to form an active m6A writer complex.

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Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization

Cyber-Security Knowledge Graph Generation by Hierarchical No...

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International Symposium on Digital Forensic and Security (ISDFS)

作者： Ryan Barron Maksim E. Eren Manish Bhattarai Selma Wanna Nicholas Solovyev Kim Rasmussen Boian S. Alexandrov Charles Nicholas Cynthia Matuszek Theoretical Division Los Alamos National Laboratory Los Alamos USA Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Maryland USA Advanced Research in Cyber Systems Los Alamos National Laboratory Los Alamos USA

ISBN: (数字)9798350330366

ISBN: (纸本)9798350330373

Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume of scientific papers. As this textual data continues to expand, the importance of document organization methods becomes increasingly crucial for extracting actionable insights hidden within large text datasets. Knowledge Graphs (KGs) serve as a means to store factual information in a structured manner, providing explicit, interpretable knowledge that includes domain-specific information from the cybersecurity scientific literature. One of the challenges in constructing a KG from scientific literature is the extraction of ontology from unstructured text. In this paper, we address this topic and introduce a method for building a multi-modal KG by extracting structured ontology from scientific papers. We demonstrate this concept in the cybersecurity domain. One modality of the KG represents observable information from the papers, such as the categories in which they were published or the authors. The second modality uncovers latent (hidden) patterns of text extracted through hierarchical and semantic non-negative matrix factorization (NMF), such as named entities, topics or clusters, and keywords. We illustrate this concept by consolidating more than two million scientific papers uploaded to arXiv into the cyber-domain, using hierarchical and semantic NMF, and by building a cyber-domain-specific KG.

关键词： Semantics Digital forensics Buildings Knowledge graphs Organizations Ontologies Data models

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