Article
Chemistry, Multidisciplinary
Ana M. Garcia, Michele Melchionna, Ottavia Bellotto, Slavko Kralj, Sabrina Semeraro, Evelina Parisi, Daniel Iglesias, Paola D'Andrea, Rita De Zorzi, Attilio V. Vargiu, Silvia Marchesan
Summary: Self-assembling peptides with proline as a beta-breaker and diphenylalanine motif were studied for their ability to form diverse nanostructures. The stereo-configuration of amino acids played a crucial role in directing these peptides to assemble into nanoparticles, nanotapes, or fibrils. Additionally, the study found that heterochirality could strategically interfere with pathological processes, potentially offering future therapeutic applications with resistance to degradation and biocompatibility.
Article
Biochemical Research Methods
Yuan Zhao, Ying Zhang, Huilin Liu, Baoguo Sun
Summary: A chiroptical system based on chiral assembly graphene quantum dots was developed for visual testing of D-phenylalanine, and successfully applied to intracellular chiroptical imaging.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2022)
Review
Biotechnology & Applied Microbiology
Yongfang Zheng, Kejing Mao, Shixian Chen, Hu Zhu
Summary: Peptide assembly structures can form various highly ordered supramolecular architectures, and the design of peptide structures needs to consider factors such as amino acid sequence and chirality. Alteration in chirality can regulate the structure and bioactivity of peptide assemblies.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Engineering, Biomedical
Mingjing Zhu, Wenchao Zhong, Wei Cao, Qingbin Zhang, Gang Wu
Summary: This review summarizes the current knowledge on the design, molecular mechanisms, and applications of peptides in cartilage tissue engineering. Peptides, which can be chemically synthesized and mimic the functions of cartilaginous extracellular matrix and growth factors, show better stability and modifiability compared to natural biomaterials and recombinant growth factors. Studies have shown that peptides have a good efficacy in inducing chondrogenesis.
BIOACTIVE MATERIALS
(2022)
Article
Biochemistry & Molecular Biology
Fang-Yi Wu, Hsin-Chieh Lin
Summary: Synthetic bioactive aromatic peptide amphiphiles are recognized as key elements of emerging biomedical strategies due to their biocompatibility, design flexibility, and functionality. We investigated the self-assembly driving force of two supramolecular materials and found ordered π-π interactions and secondary structures in both compounds. In cell experiments, PFB-IKVAV showed promise as a potential supramolecular biomaterial for biomedical applications.
Article
Materials Science, Biomaterials
Alessia Ajovalasit, Carlos Redondo-Gomez, Maria Antonietta Sabatino, Babatunde O. Okesola, Kristin Braun, Alvaro Mata, Clelia Dispenza
Summary: This work presents a self-assembling hydrogel dressing that mimics the hierarchical structure of skin extracellular matrix by investigating the co-assembly behavior of a carboxylated variant of xyloglucan (CXG) with a peptide amphiphile (PA-H3) to generate hierarchical constructs with tuneable molecular composition, structure, and properties. The hydrogel dressing is characterized by its morphology and mechanical properties, and a preliminary biological evaluation has been carried out both in vitro with HaCat cells and in vivo in a mouse model.
REGENERATIVE BIOMATERIALS
(2021)
Review
Chemistry, Physical
Chun Yin Jerry Lau, Enrico Mastrobattista
Summary: Self-assembling peptides are a prominent class of supramolecular materials with good biocompatibility. Significant progress has been made in studying the supramolecular organization of peptide assemblies to control material properties. Peptide self-assembly is a complex pathway governed by the assembly pathway.
CURRENT OPINION IN COLLOID & INTERFACE SCIENCE
(2021)
Article
Biophysics
Chunqian Zhao, Hongyuan Chen, Fengshan Wang, Xinke Zhang
Summary: Amphiphilic self-assembling peptides are widely used in biomedical fields due to their good compatibility and potential for drug delivery. However, there are no defined rules for their design and development, and rational strategies are needed for research. These peptides have a variety of applications in drug delivery, including delivering hydrophobic drugs and vaccines.
COLLOIDS AND SURFACES B-BIOINTERFACES
(2021)
Article
Biotechnology & Applied Microbiology
Xuejiao Yang, Honglei Lu, Yinghua Tao, Hongyue Zhang, Huaimin Wang
Summary: This study reports a method to control the fiber alignment, chirality, and stiffness of aromatic peptide hydrogels through heterodimerization of enantiomeric mixtures. The relative ratio of L and D enantiomers can also regulate the adhesion and morphology of mammalian cells. This work provides a new strategy for controlling supramolecular chirality in materials science.
JOURNAL OF NANOBIOTECHNOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Carlo Diaferia, Elisabetta Rosa, Enrico Gallo, Giovanni Smaldone, Mariano Stornaiuolo, Giancarlo Morelli, Antonella Accardo
Summary: Peptide-based hydrogels, specifically the Fmoc derivatives of series K, are capable of self-assembly and gelation in aqueous solutions, with Fmoc-K3 hydrogel showing potential for tissue engineering applications by supporting cell adhesion, survival, and duplication. The gelification process is dependent on the balance of aggregation forces within the peptide sequences, such as van der Waals, hydrogen bonding, and pi-pi stacking.
Article
Nanoscience & Nanotechnology
Weikang Yu, Yu Sun, Wenyu Li, Xu Guo, Xuesheng Liu, Wanpeng Wu, Wanqi Yu, Jiajun Wang, Anshan Shan
Summary: To overcome the limitation of antimicrobial peptides (AMPs) in vivo application, a self-assembled AMPs library with specific nanostructures is developed. The self-assembled nanostructured antimicrobial micelles with improved pharmacological properties are achieved by PEGylation at the C-terminal of T9W (CT9W1000). CT9W1000 shows enhanced antibacterial activity against Pseudomonas aeruginosa and broader antibacterial spectrum. The stability of CT9W1000 micelles is also improved under various conditions. Moreover, CT9W1000 micelles exhibit good biocompatibility and highly effective treatment in an acute lung injury model induced by P. aeruginosa PAO1 without drug resistance, suggesting the potential clinical application.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Review
Engineering, Biomedical
Vincent P. A. Gray, Connor D. J. Amelung, Israt Jahan Duti, Emma G. Laudermilch, Rachel A. Letteri, Kyle J. Lampe
Summary: The rational design of bioactive microenvironments using peptides presents a significant challenge in biomaterials. By understanding the molecular and macroscopic features that govern assembly and morphology, peptides can be designed to mimic native tissue microenvironments. Characterization tools enable researchers to study molecular structure, morphology, and biological functionality. Peptide-based biomaterials have the potential for tissue engineering and regenerative medicine applications.
ACTA BIOMATERIALIA
(2022)
Article
Chemistry, Applied
Tamilselvan Mohan, Karin Stana Kleinschek, Rupert Kargl
Summary: This publication provides an overview of research on conjugates of polysaccharides and peptides, focusing on commonly encountered functional groups and chemical reactions. The distinct properties of conjugates and their applications in biomedical, drug delivery, biosensing, and tissue engineering fields are highlighted. Suggestions for further rigorous chemistries and analytics are proposed, along with an outlook on future developments in the field.
CARBOHYDRATE POLYMERS
(2022)
Letter
Biochemistry & Molecular Biology
Yusuke Gonda, Chiharu Ishii, Masashi Mita, Naoto Nishizaki, Yoshiyuki Ohtomo, Kenji Hamase, Toshiaki Shimizu, Jumpei Sasabe
Summary: Astrocytic DAO specifically regulates D-serine in the hindbrain, without affecting D-amino acid levels in the forebrain or periphery.
Article
Polymer Science
Samira Farjaminejad, Shahrokh Shojaei, Vahabodin Goodarzi, Hossein Ali Khonakdar, Majid Abdouss
Summary: Novel biomaterials based on glycerin, sebacic acid, succinic acid, and ε-caprolactone were introduced in this study. Bio-nanocomposites were prepared using organomontmorillonite and nano-hydroxyapatite, and their properties were assessed through various tests. The presence of succinic acid and ε-caprolactone improved sample characteristics and nanoparticles enhanced hydrophilicity.
EUROPEAN POLYMER JOURNAL
(2021)
Article
Engineering, Civil
Yongxuan Lai, Shipeng Yang, Anshu Xiong, Fan Yang, Lei Li, Xiaofang Zhou
Summary: In this article, the authors propose an algorithm called BMCF to solve the taxi-rider matching problem with appointment-based rider requests on a time-dependent road network. The algorithm efficiently integrates and processes both real-time and appointment-based requests, with dynamically adjustable and revocable assignments between vehicles and requests to maximize overall utility.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
An Liu, Yifan Zhang, Xiangliang Zhang, Guanfeng Liu, Yanan Zhang, Zhixu Li, Lei Zhao, Qing Li, Xiaofang Zhou
Summary: This paper proposes a method called At2vec that learns the representation of activity trajectories by considering spatio-temporal characteristics and activity semantics. The similarity between two trajectories is computed using multi-level attention mechanisms, allowing for mining user preferences and applying them to various online tasks.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Chao Wang, Haiyun Jiang, Tao Chen, Jingping Liu, Menghui Wang, Sihang Jiang, Zhixu Li, Yanghua Xiao
Summary: Text classification is crucial in natural language processing and data mining. Understanding the relationships between entities enhances entity semantics comprehension and supports text classification. This study improves existing text classification models by extracting entity features and employing hierarchical graph learning.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Fengmei Jin, Wen Hua, Thomas Zhou, Jiajie Xu, Matteo Francia, Maria E. Orlowska, Xiaofang Zhou
Summary: This paper investigates the problem of spatiotemporal entity linking using trajectory-based matching. It proposes an approach that utilizes effective and concise signatures extracted from trajectories for linking. The paper introduces several representation strategies and quantitative criteria for signature construction, as well as optimization methods for improving accuracy and efficiency. Extensive experiments on real-world datasets demonstrate the superiority of the proposed approach.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Xuanhao Chen, Yan Zhao, Guanfeng Liu, Rui Sun, Xiaofang Zhou, Kai Zheng
Summary: With the rise of GPS-enabled smartphones and social media platforms, geo-social networks have become popular tools for businesses to promote their products or services. This paper proposes a Similarity-aware Influence Maximization (SIM) model that takes into account users' spatio-temporal behavior to maximize the spread of influence. Extensive experiments demonstrate the efficiency and effectiveness of the proposed model.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Engineering, Civil
Dan He, Thomas Zhou, Xiaofang Zhou, Jiwon Kim
Summary: We study the k Maximum Trajectory Coverage Query, aiming to find k routes in a public transport system that can serve the maximum number of users with given journey trajectories. Existing studies only consider independent service without transfers, which leads to inferior results. To address this, we propose a greedy algorithm that considers both independent and aggregative services and outperforms competitors by up to 60% in accuracy.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Mengxuan Zhang, Lei Li, Goce Trajcevski, Andreas Zufle, Xiaofang Zhou
Summary: This paper discusses the challenges and methods for shortest path computation in frequently evolving small-world networks. By adopting Parallel Shortest-distance Labeling (PSL) as the construction method for 2-hop labeling and designing update mechanisms, the query efficiency and index maintenance effectiveness are improved.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Defu Lian, Jin Chen, Kai Zheng, Enhong Chen, Xiaofang Zhou
Summary: One-class collaborative filtering (OCCF) problems are common in recommendation systems, but suffer from data sparsity and lack of negative items. To address these challenges, a ranking-based implicit regularizer is proposed and used in a framework to improve recommendation quality. Efficient algorithms are developed to optimize model parameters and extensive evaluations are conducted on multiple datasets.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Information Systems
Yunyi Li, Yongjing Hao, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng, Xiaofang Zhou
Summary: This article proposes an Edge-Enhanced Global Disentangled Graph Neural Network (EGD-GNN) model to capture the relation information between items for global item representation and local user intention learning. Experimental results show that our model can achieve a significant improvement over state-of-the-art baselines and effectively distinguish item features.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2023)
Article
Computer Science, Artificial Intelligence
Yu Yang, Hongzhi Yin, Jiannong Cao, Tong Chen, Quoc Viet Hung Nguyen, Xiaofang Zhou, Lei Chen
Summary: Dynamic graphs are graphs whose structure changes over time. Existing approaches only consider dynamic graphs as a sequence of changes in vertex connections, ignoring the asynchronous nature of the dynamics where the evolution of each local structure starts at different times and lasts for various durations. To address this, we propose a novel representation of dynamic graphs as temporal edge sequences associated with joining time of vertices (ToV) and timespan of edges (ToE). We also introduce a time-aware Transformer to embed the dynamic connections and ToEs into learned vertex representations, along with encoding time-sensitive information. Our approach outperforms the state-of-the-art in various graph mining tasks and is efficient for embedding large-scale dynamic graphs.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Yongjing Hao, Tingting Zhang, Pengpeng Zhao, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Guanfeng Liu, Xiaofang Zhou
Summary: Sequential recommendation has become crucial in various Internet applications. Existing methods overlook the transition patterns between the features of items, while our proposed model enhances recommendation performance through learning feature-level and item-level sequences.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Mohsen Saaki, Saeid Hosseini, Sana Rahmani, Mohammad Reza Kangavari, Wen Hua, Xiaofang Zhou
Summary: This study highlights the importance of finding suitable individuals to answer questions using short content and identifies the challenges involved. The authors propose a novel embedding approach and recommendation system to overcome these challenges, and provide experimental results to demonstrate its effectiveness.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Yao Tian, Tingyun Yan, Xi Zhao, Kai Huang, Xiaofang Zhou
Summary: This paper proposes a novel indexing approach called LIMS, which uses data clustering, pivot-based data transformation techniques, and learned indexes to support efficient similarity query processing in metric spaces. LIMS partitions the underlying data into clusters with relatively uniform data distribution and utilizes a small number of pivots for data redistribution. Similar data are mapped into compact regions with totally ordinal mapped values. Machine learning models approximate the position of each data record on disk, and efficient algorithms are designed for range queries, nearest neighbor queries, and index maintenance with dynamic updates.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Yan Zhao, Kai Zheng, Yunchuan Li, Jinfu Xia, Bin Yang, Torben Bach Pedersen, Rui Mao, Christian S. Jensen, Xiaofang Zhou
Summary: In spatial crowdsourcing, mobile users are involved in spatio-temporal tasks that require travel to specific locations. The task assignment in spatial crowdsourcing is a challenging problem that needs to be addressed to maximize profits. This study introduces a profit-driven task assignment problem and proposes various algorithms, including an optimal algorithm based on tree decomposition and greedy algorithms based on random tuning optimization. Additionally, a heuristic algorithm based on ant colony optimization is provided to balance effectiveness and efficiency. Extensive experiments using real and synthetic data are conducted to evaluate the proposed methods.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Ming Dong, Bolong Zheng, Guohui Li, Chenliang Li, Kai Zheng, Xiaofang Zhou
Summary: This paper proposes a sequence-to-sequence model, called GCSSI, which takes wavefront as input to solve the problem of multiple rumor source detection. By adopting encoder-decoder structure and graph constraint based multi-task learning, the model estimates the reverse rumor dissemination at each time step and predicts sources in an end-to-end way.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2022)
