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scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

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Cell systems 2023年第4期14卷 302-311.e4页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

关键词： cell-cell interaction cellular communication gene regression network machine learning manifold alignment neural networks scRNA-seq single-cell RNA sequencing

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Characterization of the mitogenome ofCynoglossus Senegalensis(Pleuronectiformes: Cynoglossidae)

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Mitochondrial DNA Part B 2018年第2期3卷 1191-1192页

作者： Fantong Zealous Gietbong Nack-Keun Kim Sapto Andriyono Hyun-Woo Kim Department of Marine Biology Pukyong National University Busan Republic of KoreaKOICA-PKNU International Graduate Program of Fisheries Science Graduate School of Global Fisheries Pukyong National University Busan Republic of Korea Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of Korea Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of KoreaDepartment of Marine Fisheries and Marine Faculty Universitas Airlangga C Campus Jl. Mulyorejo Surabaya East Java Indonesia Department of Marine Biology Pukyong National University Busan Republic of KoreaInterdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of KoreaKOICA-PKNU International Graduate Program of Fisheries Science Graduate School of Global Fisheries Pukyong National University Busan Republic of Korea

The complete mitogenome of theSenegalese tonguesole,Cynoglossus senegalensiswas determined by Illumina MiSeq platform. The complete mitochondrial genome ofC. senegalensiswas 16,519 bp in length. The mitochondrial genome ofC. senegalensisshowed a cynoglosidae-characteristic gene organization, in which translocation of control region to the position between ND1 and tRNA-Gln gene, and also inversions in tRNA-Gln gene from L-strand position to H-strand position. Phylogenetic analysis showed thatC. senegalensisis most closely related toC. ***, which supports the previous result that genus Cynoglossidae is evolutionary paraphyletic.

关键词： Mitochondrial genome Cynoglossus senegalensis sole Cameroon Africa

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The complete mitogenome of Bagrid catfishChrysichthys nigrodigitatus(Siluriformes: Claroteidae)

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Mitochondrial DNA Part B 2018年第2期3卷 1239-1240页

作者： Nack-Keun Kim Fantong Zealous Gietbong Sapto Andriyono Ah Ran Kim Hyun-Woo Kim Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of Korea Department of Marine Biology Pukyong National University Busan Republic of KoreaKOICA-PKNU International Graduate Program of Fisheries Science Graduate School of Global Fisheries Pukyong National University Busan Republic of Korea Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of KoreaDepartment of Marine Fisheries and Marine Faculty Universitas Airlangga C Campus Jl. Mulyorejo Surabaya East Java Indonesia Department of Marine Biology Pukyong National University Busan Republic of Korea Interdisciplinary Program of Biomedical Mechanical and Electrical Engineering Pukyong National University Busan Republic of KoreaDepartment of Marine Biology Pukyong National University Busan Republic of Korea

We here report the complete mitochondrial genome ofChrysichthys nigrodigitatus, which is 16,514 bp in length. Mitogenome ofC. nigrodigitatusshowed the conserved 13 protein-coding genes, 22 tRNA genes, two rRNA genes, and two noncoding regions including the light-strand replication origin (OL) and a putative control region (CR). All tRNA genes were predicted to fold into the typical cloverleaf secondary structures with the typical base-pairing except for tRNA-Ser(AGC). Phylogenetic analysis with currently known complete mitogenome sequences in Siluriformes showed thatC. nigrodigitatusis most closely related toAuchenoglanis occidentalisforming a family Claroteidae cluster.

关键词： Chrysichthys nigrodigitatus mitochondrial genome catfish Cameroon Africa

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Viral evolution prediction identifies broadly neutralizing antibodies to existing and prospective SARS-CoV-2 variants

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Nature microbiology 2025年 2025 Jun 10页

作者： Fanchong Jian Anna Z Wec Leilei Feng Yuanling Yu Lei Wang Peng Wang Lingling Yu Jing Wang Jacob Hou Daniela Montes Berrueta Diana Lee Tessa Speidel LingZhi Ma Thu Kim Ayijiang Yisimayi Weiliang Song Lu Liu Sijie Yang Xiao Niu Tianhe Xiao Ran An Yao Wang Fei Shao Youchun Wang Simone Pecetta Xiangxi Wang Laura M Walker Yunlong Cao Biomedical Pioneering Innovation Center (BIOPIC) Peking University Beijing China. Changping Laboratory Beijing China. College of Chemistry and Molecular Engineering Peking University Beijing China. Moderna Inc. Cambridge MA USA. CAS Key Laboratory of Infection and Immunity National Laboratory of Macromolecules Institute of Biophysics Chinese Academy of Sciences Beijing China. University of Chinese Academy of Sciences Beijing China. School of Life Sciences Peking University Beijing China. Peking-Tsinghua Center for Life Sciences Tsinghua University Beijing China. Joint Graduate Program of Peking-Tsinghua-NIBS Academy for Advanced Interdisciplinary Studies Peking University Beijing China. Institute of Medical Biology Chinese Academy of Medical Science and Peking Union Medical College Kunming China. CAS Key Laboratory of Infection and Immunity National Laboratory of Macromolecules Institute of Biophysics Chinese Academy of Sciences Beijing China. xiangxi@***. University of Chinese Academy of Sciences Beijing China. xiangxi@***. Moderna Inc. Cambridge MA USA. laura.walker@***. Biomedical Pioneering Innovation Center (BIOPIC) Peking University Beijing China. yunlongcao@***. Changping Laboratory Beijing China. yunlongcao@***. Peking-Tsinghua Center for Life Sciences Tsinghua University Beijing China. yunlongcao@***.

Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) to future variants is needed. Here we use deep mutational scanning to predict viral receptor-binding domain evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wild-type-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs to the XBB.1.5 strain from 1% to 40% in an early pandemic set-up. Among these bnAbs, BD55-1205 showed potent activity to all tested variants. Cryogenic electron microscopy structural analyses revealed the receptor mimicry of BD55-1205, explaining its broad reactivity. Delivery of mRNA-lipid nanoparticles encoding BD55-1205-IgG in mice resulted in serum half-maximal neutralizing antibody titre values of ~5,000 to XBB.1.5, HK.3.1 and JN.1 variants. Combining bnAb identification using viral evolution prediction with the versatility of mRNA delivery technology can enable rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other pathogens with pandemic potential.

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Additive nanomanufacturing of lab-on-a-chip fluorescent peptide nanoparticle arrays for Alzheimer＇s disease diagnosis

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Bio-Design and Manufacturing 2018年第3期1卷 182-194页

作者： Leming Sun Zhen Fan Tao Yues Jun Yin Jianzhong FU Mingjun Zhang Department of Biomedical Engineering College ofEngineering Ohio State University Columbus OH 43210USA School of Life Sciences Northwestern PolytechnicalUniversity Xi'an 710072 Shaanxi China Department of Polymeric Materials School of MaterialScience and Engineering Tongji UniversityShanghai 201804 China Institute for Advanced Study TongjiUniversity Shanghai 200092 China School of Mechatronic Engineering and Automation Shanghai University Shanghai 200444 China The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering ZhejiangUniversity Hangzhou 310028 China Key Laboratory of 3D Printing Process and Equipment of Zhejiang Province School of Mechanical EngineeringZhejiang University Hangzhou 310028 China Dorothy M. Davis Heart & Lung Research Institute The OhioState University Wexner Medical Center Columbus OH43210 USA Interdisciplinary Biophysics Graduate Program Ohio StateUniversity Columbus OH 43210 USA

This paper proposes an additive nanomanufacturing approach to fabricate a personalized lab-on-a-chip fluorescent peptide nanoparticles （f-PNPs） array for simultaneous multi-biomarker detection that can be used in Alzheimer＇s disease （AD） diagnosis. We will discuss optimization techniques for the additive nanomanufacturing process in terms of reliability, yield and manufacturing efficiency. One contribution of this paper lies in utilization of additive nanomanufacturing techniques to fabricate a patient-specific customize-designed lab-on-a-chip device for personalized AD diagnosis, which remains a major challenge for biomedical engineering. Through the integrated bio-design and bio-manufacturing process, doctor＇s check- up and computer-aided customized design are integrated into the lab-on-a-chip array for patient-specific AD diagnosis. In addition, f-PNPs with targeting moieties for personalized AD biomarkers will be self-assembled onto the customized lab-on-a- chip through the additive nanomanufacturing process, which has not been done before. Another contribution of this research is the personalized lab-on-a-chip f-PNPs array for AD diagnosis utilizing limited human blood. Blood-based AD assessment has been described as ＂the holy grail＂ of early AD detection. This research created the computer-aided design, fabrication through additive nanomanufacturing, and validation of the f-PNPs array for AD diagnosis. This is a highly interdisciplinary research contributing to nanotechnology, biomaterials, and biomedical engineering for neurodegenerative disease. The conceptual work is preliminary with intent to introduce novel techniques to the application. Large-scale manufacturing based on the proposed framework requires extensive validation and optimization.

关键词： Nanomanufacturing Lab-on-a-chip Fluorescent peptide nanoparticle Alzheimer＇s disease Diagnosis

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Corrigendum to "Dual regulatory effects of neferine on amyloid-β and tau aggregation studied by in silico, in vitro, and lab-on-a-chip technology" [Biomed. Pharmacother. 172 (2024) 1-14/116226]

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Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 2024年 181卷 117686页

作者： Yunkwon Nam Ritu Prajapati Sujin Kim Soo Jung Shin Da Yeon Cheong Yong Ho Park Hyun Ha Park Danyou Lim Yoojeong Yoon Gyudo Lee Hyun Ah Jung Insu Park Dong-Hyun Kim Jae Sue Choi Minho Moon Department of Biochemistry College of Medicine Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Department of Food and Life Science Pukyong National University Busan 48513 Republic of Korea. Department of Biochemistry College of Medicine Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea Research Institute for Dementia Science Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Department of Biotechnology and Bioinformatics Korea University Sejong 30019 Republic of Korea Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong 30019 Republic of Korea. Department of Biomedical Engineering Konyang University Daejeon 35365 Republic of Korea. Department of Food Science and Human Nutrition Chonbuk National University Jeonju 54896 Republic of Korea. Department of Biomedical Engineering Konyang University Daejeon 35365 Republic of Korea. Electronic address: insupark@konyang.ac.kr. Departments of Pharmacology and Advanced Translational Medicine School of Medicine Konkuk University Seoul 05029 Republic of Korea. Electronic address: mose79@kku.ac.kr. Department of Food and Life Science Pukyong National University Busan 48513 Republic of Korea. Electronic address: choijs@pknu.ac.kr. Research Institute for Dementia Science Konyang University 158 Gwanjeodong-ro Seo-gu Daejeon 35365 Republic of Korea. Electronic address: hominmoon@konyang.ac.kr.

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Cover Feature: Synthesis and Photophysical Properties of Hexabenzocoronene-Tetrabenzoporphyrin Architectures (Eur. J. Org. Chem. 40/2020)

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European Journal of Organic Chemistry 2020年第40期2020卷

作者： Michael Ruppel Lampros-Pascal Gazetas Dr. Dominik Lungerich Dr. Norbert Jux Department of Chemistry and Pharmacy & Interdisciplinary Center for Molecular Materials (ICMM) Friedrich-Alexander University Erlangen-Nuremberg Nikolaus-Fiebiger-Str. 10 91058 Erlangen Germany Institute for Basic Science (IBS) 50 Yonsei-ro Seodaemun-gu Center for Nanomedicine 03722 Seoul Republic of Korea Graduate Program of Nano Biomedical Engineering (NanoBME) Advanced Science Institute Yonsei University 03722 Seoul Republic of Korea

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Using a Recurrent Neural Network Model for Classification of Tweets Conveyed Influenza-related Information 1

Using a Recurrent Neural Network Model for Classification of...

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1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Wang, Chen-Kai Singh, Onkar Tang, Zhao-Li Dai, Hong-Jie Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei Taiwan Department of Computer Science and Information Engineering National Taitung University Taitung Taiwan Interdisciplinary Program of Green and Information Technology National Taitung University Taitung Taiwan

ISBN: (纸本)9781948087070

Traditional disease surveillance systems depend on outpatient reporting and virological test results released by hospitals. These data have valid and accurate information about emerging outbreaks but it's often not timely. In recent years the exponential growth of users getting connected to social media provides immense knowledge about epidemics by sharing related information. Social media can now flag more immediate concerns related to outbreaks in real time. In this paper we apply the long short-term memory recurrent neural network (RNN) architecture to classify tweets conveyed influenza-related information and compare its performance with baseline algorithms including support vector machine (SVM), decision tree, naive Bayes, simple logistics, and naive Bayes multinomial. The developed RNN model achieved an F-score of 0.845 on the MedWeb task test set, which outperforms the F-score of SVM without applying the synthetic minority oversampling technique by 0.08. The F-score of the RNN model is within 1% of the highest score achieved by SVM with oversampling technique. © 2017 AFNLP

关键词： Support vector machines

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Silicone breast implant modification review: Overcoming capsular contracture

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Biomaterials Research 2018年第1期22卷 319-327页

作者： Shin, Byung Ho Kim, Byung Hwi Kim, Sujin Lee, Kangwon Choy, Young Bin Heo, Chan Yeong Seoul National University College of Medicine Department of Biomedical Engineering Seoul 03080 South Korea Seoul National University Department of Transdisciplinary Studies Graduate School of Convergence Science and Technology Seoul 08826 South Korea Seoul National University Interdisciplinary Program for Bioengineering College of Engineering Seoul 08826 South Korea Seoul National University Department of Plastic and Reconstructive Surgery College of Medicine Seoul 03080 South Korea Seoul National University Bundang Hospital Department of Plastic and Reconstructive Surgery Seongnam 13620 South Korea Seoul National University Institute of Medical and Biological Engineering Medical Research Center Seoul 03080 South Korea Advanced Institutes of Convergence Technology Suwon Gyeonggi-do 16229 South Korea

Background: Silicone implants are biomaterials that are frequently used in the medical industry due to their physiological inertness and low toxicity. However, capsular contracture remains a concern in long-term transplantation. To date, several studies have been conducted to overcome this problem. This review summarizes and explores these trends. Main body: First, we examined the overall foreign body response from initial inflammation to fibrosis capsule formation in detail and introduced various studies to overcome capsular contracture. Secondly, we introduced that the main research approaches are to inhibit fibrosis with anti-inflammatory drugs or antibiotics, to control the topography of the surface of silicone implants, and to administer plasma treatment. Each study examined aspects of the various mechanisms by which capsular contracture could occur, and addressed the effects of inhibiting fibrosis. Conclusion: This review introduces various silicone surface modification methods to date and examines their limitations. This review will help identify new directions in inhibiting the fibrosis of silicone implants. © 2018 The Author(s).

关键词： Capsular contracture Fibrosis Foreign body reaction Inflammation Modification Silicone implant

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Residue detection in the large intestine from colonoscopy video using the support vector machine method

Residue detection in the large intestine from colonoscopy vi...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： M. Cho H. J. Kong J. H. Kim B. Jeon K. S. Hong S. Kim Interdisciplinary Program in Bioengineering Graduate School Seoul National University Seoul Republic of Korea Department of Biomedical Engineering Chungnam National University College of Medicine Daejeon Korea Department of Gastroenterology Seoul National University Boramae Medical Center Seoul Korea Department of Gastroenterology Mediplex Sejong Hospital Incheon Korea Institute of Medical and Biological Engineering Medical Research Center Seoul National University Seoul Republic of Korea

ISBN: (纸本)9781538670804;9788993215168

As colonoscopy is the gold standard screening test for colorectal cancer, studies of applying image processing to colonoscopy video are increasing. When performing colonoscopy or applying image processing to colonoscopy video, the presence of a residue in the large intestine is a negative affecting factor. In this reason, the colonoscopist evaluates and records the colon cleanliness after performing colonoscopy. However, these assessments can be influenced by the subjectivity of the colonoscopist. In order to quantify the frequency of residues in the large intestine, we applied image processing and machine learning techniques to the digital images obtained from colonoscopy. Support vector machine technique was applied to distinguish informative frames from colonoscopy videos, and to classify residue frames and the others. The sensitivity, specificity, and accuracy were evaluated for five patients.

关键词： Colonoscopy Support vector machines Intestines Image processing Endoscopes Cancer Colon

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