Review
Integrative & Complementary Medicine
Chenyang Ai, Yi Zou, Hao Liu, Zheqiong Yang, Jinlei Xi
Summary: The prevalence of allergic disorders has increased, leading to a lower quality of life for patients and a higher demand for drugs to treat these diseases. Traditional Chinese medicine offers distinct benefits in treating allergic illnesses, such as long-term treatment maintenance, prevention of disease recurrence, and fewer adverse reactions. Recent developments in Chinese herbal formula, Chinese patent medicine, and active ingredients of traditional Chinese medicine have been analyzed, discussing their components, efficacy, and mechanisms of action. The importance of improving traditional Chinese herbal formulas and developing safe and effective Chinese patent medicines is emphasized in the field of traditional Chinese medicine research.
AMERICAN JOURNAL OF CHINESE MEDICINE
(2023)
Article
Integrative & Complementary Medicine
Jillian L. Capodice, Barbara M. Chubak
Summary: Traditional Chinese Medicine (TCM) is a comprehensive medical system that has been developed over thousands of years and is utilized in the treatment of COVID-19. This paper highlights the use of TCM in treating COVID-19, discussing concepts and challenges of integrating TCM into medical settings.
Review
Pharmacology & Pharmacy
Liu Liu, Lei Zhang, Ming Li
Summary: Lupus nephritis is a renal disease caused by systemic lupus erythematosus and has serious implications for patients. Traditional Chinese medicine has shown promising effects in alleviating the symptoms and improving the prognosis of LN patients. This review provides supplementary evidence for the development of TCM treatment for LN and serves as a reference for future research and clinical practice.
FRONTIERS IN PHARMACOLOGY
(2022)
Review
Plant Sciences
Liangshuai Liu, Heping Li, Guosheng Tan, Zhenjiang Ma
Summary: This study reviewed the use of traditional Chinese herbal medicine in treating amenorrhea caused by antipsychotic drugs and conducted a meta-analysis. The results showed that Chinese herbal medicine can effectively treat this condition, although it may take a long time to achieve satisfactory effectiveness.
JOURNAL OF ETHNOPHARMACOLOGY
(2022)
Review
Pharmacology & Pharmacy
Shan Wu, Chuanchi Wang, Dong Bai, Nanjie Chen, Jingqing Hu, Junhua Zhang
Summary: With the introduction of clinical epidemiology and evidence-based medicine, Traditional Chinese Herbal Medicine (TCHM) in China has improved and internationalization of Traditional Chinese Medicine (TCM) has accelerated. Many Chinese drug products have been approved for marketing in other countries, and several Chinese herbal preparations have been investigated in phase III clinical trials. However, international multi-center clinical trials of TCHM are rare and improvement in evaluation techniques and methods that meet international standards and TCHM characteristics is required.
FRONTIERS IN PHARMACOLOGY
(2023)
Review
Integrative & Complementary Medicine
Purumea Jun, Endang Rahmat, Chang-Hyun Han, Changsop Yang, Youngmin Kang
Summary: The decline in birth rates is a serious issue globally, with many countries implementing national programs to increase birth rates using traditional medicines. This review analyzed and compared herbal medicines from traditional Chinese medicine (TCM) and traditional Indonesian medicine (TIM) that pregnant women should avoid for preventing miscarriage and maintaining safety. Despite their differences, TCM and TIM share similarities in concept and treatment, especially regarding herbal medicines, making this review a useful reference for pregnant women to consume herbal medicines safely.
CHINESE JOURNAL OF INTEGRATIVE MEDICINE
(2021)
Article
Biochemistry & Molecular Biology
Muhammad Harith Zulkifli, Zafirah Liyana Abdullah, Nur Intan Saidaah Mohamed Yusof, Fazlin Mohd Fauzi
Summary: This article summarizes three in silico approaches for toxicity studies of Traditional Chinese medicine (TCM) herbal medicine, including machine learning, network toxicology, and molecular docking. Although these methods can provide data-driven toxicity prediction validated in vitro and/or in vivo, they are limited to single compound analysis and specific types of toxicity. Future studies should involve testing combinations of compounds to improve in silico toxicity modeling of TCM compounds.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Qiang Xu, Qiang Guo, Chun-Xia Wang, Song Zhang, Chuan-Biao Wen, Tao Sun, Wei Peng, Jun Chen, Wei-Hong Li
Summary: This paper highlights the significance of pathogenesis diagnosis in traditional Chinese medicine, introducing the concept of pathogenesis network (PN) and proposing a computational method called network differentiation (ND) that integrates the holism principle in systems science to optimize the diagnosis process.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2021)
Review
Plant Sciences
Ya-Ting Wang, Xiao-Le Wang, Zhen-Zhen Wang, Lan Lei, Die Hu, Yi Zhang
Summary: This review summarizes the antidepressant mechanisms of Xiao-Yao-San (XYS) and its active ingredients, which are reportedly correlated with monoamine neurotransmitter regulation, synaptic plasticity, and hypothalamic-pituitary-adrenal axis. XYS plays a critical role in the treatment of depression by regulating several factors and pathways. However, more clinical and animal studies are needed to further investigate the antidepressant function of XYS and provide more evidence and recommendations for its clinical application.
Review
Biochemistry & Molecular Biology
Jose M. Prieto, Guillermo R. Schinella
Summary: This experimental review explores the relationship between Traditional Chinese Medicine (TCM) herbal drugs and lipid peroxidation in the context of topical inflammation. The study finds that certain herbal drugs with bitter and cold properties inhibit both lipid peroxidation and eicosanoids production, while sweet drugs specifically inhibit eicosanoids production. The therapeutic value of other drugs may be based on their actions on the Qi. The study suggests potential translation between the two medical systems and provides insights for the treatment of skin conditions.
Review
Biochemistry & Molecular Biology
Blanca Ibanez, Ana Melero, Alegria Montoro, Juan F. Merino-Torres, Jose M. Soriano, Nadia San Onofre
Summary: In recent years, there has been increasing interest in finding natural radioprotectors to mitigate the harmful effects of radiation. This review examines herbal preparations from Ayurvedic, Traditional Chinese, and Kampo Medicines that have demonstrated potential radioprotective effects. Ten herbal preparations, including Abana, Amalakyadi Churna, Amritaprasham, Brahma, Bu-zhong-yi-qi-tang (BZYQT), Chyavanaprasha, Cystone, Geriforte, Mentat, and Triphala, are highlighted for their potential radioprotective properties. Exploring the ethnobotany of traditional Asian medicine may lead to the discovery of new active compounds with radioprotective properties.
Review
Gastroenterology & Hepatology
Claudio Fiocchi, Dimitrios Iliopoulos
Summary: Systems biology is a rapidly advancing field that offers new insights into disease mechanisms, patient diagnosis, and drug development. By integrating omics-derived big data to identify biological networks and develop specific blockers, systems biology has the potential to revolutionize therapeutic strategies for complex diseases like IBD. Although still in its early stages, the implementation of systems biology in IBD research holds great promise for advancing our understanding and improving patient outcomes.
INFLAMMATORY BOWEL DISEASES
(2021)
Review
Plant Sciences
Myong Hak Ri, Yue Xing, Hong Xiang Zuo, Ming Yue Li, Hong Lan Jin, Juan Ma, Xuejun Jin
Summary: This review summarizes the regulatory mechanisms of natural compounds derived from traditional Chinese herbal medicines on the microglial response in animal models of ischemic stroke. The findings suggest that these compounds attenuate the M1 phenotype of microglia, which is involved in detrimental inflammatory response, while enhancing the neuroprotective M2 phenotype. Clinical trials also show significant and safe therapeutic effects, but further well-designed studies are needed.
Article
Environmental Sciences
Yi Wang, Yuan Li, Shuai Yang, Qi-Hao Wang, Shao-Cheng Si, Han-Yi Mei, Guo-Ming Liu, Xiang-Liang Pan, Yong-Ming Luo
Summary: Soil washing is an effective method for removing heavy metals from farmland soil, and the choice of washing agents is crucial for the efficiency of the removal. This study tested the potential of three residues of traditional Chinese herbal medicine extracts for Cd removal and identified the optimal conditions. The results showed that the extract from Prunus mume residues was a more feasible and environmentally friendly washing agent.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Pharmacology & Pharmacy
Liping Qu, Xiuli Li, Yin Xiong, Zhun Wang, Yuehua Zhou, Wenjun Zou, Jianyuan Tang, Mei Wang
Summary: Although TCM herbal remedies are popular in European patients, the access of multi-herbal TCM products to the EU market faces considerable obstacles. This study systematically analyzes the current advances in EU herbal monographs and combination herbal medicinal products (HMPs) granted in member states, and identifies the main features and challenges for multi-herbal TCM products. The results show that the EU is open to combination HMPs, but safety, efficacy, and justification of combinations are key elements for their market access.
PHARMACOLOGICAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Shumin Deng, Ningyu Zhang, Hui Chen, Chuanqi Tan, Fei Huang, Changliang Xu, Huajun Chen
Summary: Knowledge Extraction (KE) aims to extract structured information from raw texts, facing the challenge of low-resource problem and the need for utilizing correlation knowledge among classes. K-HPN leverages pairwise prototype learning on the hypersphere to identify inherent correlation among classes, improving the performance of low-resource KE.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Dongya Wu, Enhui Shen, Bowen Jiang, Yu Feng, Wei Tang, Sangting Lao, Lei Jia, Han-Yang Lin, Lingjuan Xie, Xifang Weng, Chenfeng Dong, Qinghong Qian, Feng Lin, Haiming Xu, Huabing Lu, Luan Cutti, Huajun Chen, Shuiguang Deng, Longbiao Guo, Tse-Seng Chuah, Beng-Kah Song, Laura Scarabel, Jie Qiu, Qian-Hao Zhu, Qin Yu, Michael P. Timko, Hirofumi Yamaguchi, Aldo Merotto, Yingxiong Qiu, Kenneth M. Olsen, Longjiang Fan, Chu-Yu Ye
Summary: This study provides genomic insights into the dual roles of Echinochloa species as weeds and crops, revealing the complex evolution and constrained disease-related gene copy numbers in Echinochloa. The research also uncovers deep population differentiation, herbicide resistance mutations, and limited domestication of barnyard millets. These results offer essential resources for studying plant polyploidization, adaptation, precision weed control, and millet improvements.
NATURE COMMUNICATIONS
(2022)
Article
Oncology
Yi-Long Wu, Ying Cheng, Huajun Chen, Haiyan Tu, Chongrui Xu, Zhen Wang, Ying Liu, Ying Xin, Haizhou Lou, Wei Wang, Kevin Chin, Dandan Li, Di Zhao, Yanfei Gao, Wenping Xu, Hongming Pan
Summary: This study evaluated the safety and pharmacokinetics of avelumab in Chinese patients with advanced solid tumors. The results were consistent with previous global studies, showing some therapeutic effects in Chinese patients.
Article
Materials Science, Multidisciplinary
Dan Wang, Xiaodan Wang, Hai Ma, Xiaodong Gao, Jiafan Chen, Shunan Zheng, Hongmin Mao, Huajun Chen, Xionghui Zeng, Ke Xu
Summary: A series of Dy3+ and Eu3+ implanted AlN films grown by HVPE method were prepared and their crystal structure, cathodoluminescence spectra, energy transfer mechanism and chromaticity properties were investigated. Results showed that the luminescence color of the films can be effectively controlled by changing the fluence of Eu3+.
Article
Engineering, Chemical
Haoyun Ye, Xiangdong Ni, Huajun Chen, Daolin Li, Wenlong Pan
Summary: This study aims to solve the problems of poor stability and poor synchronization of the pump-controlled dual motor in a hydraulic travel system during step input speed and external load disturbance. Different control strategies were compared, and it was found that the BP algorithm-based PID parameter self-tuning control method achieved the best performance with no overshoot and reduced target speed tracking time. The research results can provide reference for the design and application of constant speed control for pump-controlled dual-motor hydraulic travel systems.
Article
Medical Informatics
Haofen Wang, Huifang Du, Guilin Qi, Huajun Chen, Wei Hu, Zhuo Chen
Summary: This paper presents a method for building a COVID-19 knowledge graph that helps organize a large amount of information and improve its utilization value. The OpenKG-COVID19 is a large knowledge graph consisting of 10 subgraphs covering various topics related to COVID-19. It includes a vast amount of concepts, entities, properties, and facts, and will be continuously updated.
JMIR MEDICAL INFORMATICS
(2022)
Article
Multidisciplinary Sciences
Xin Shao, Chengyu Li, Haihong Yang, Xiaoyan Lu, Jie Liao, Jingyang Qian, Kai Wang, Junyun Cheng, Penghui Yang, Huajun Chen, Xiao Xu, Xiaohui Fan
Summary: The authors have developed a cell-cell communication inference method called SpaTalk, which utilizes a knowledge graph to analyze spatially resolved transcriptomic data, providing valuable insights into spatial intercellular tissue dynamics.
NATURE COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Renjun Xu, Shuoying Liang, Lanyu Wen, Zhitong Guo, Xinyue Huang, Mingli Song, Jindong Wang, Xiaoxiao Xu, Huajun Chen
Summary: Heterogeneous Knowledge Amalgamation (HKA) algorithms aim to learn a versatile and lightweight student neural network by imitating the features of multiple pre-trained teachers. However, there are potential issues of feature overlap and negative transfer in the learned Common Feature Space (CFS). To address these challenges, the authors propose a Dual Discriminative Feature Alignment (DDFA) framework that promotes class-separability and decouples complex feature discrepancies among teachers and the student. Experimental results show that the learned student model is robust and outperforms its teachers in most cases.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Jie Liao, Jingyang Qian, Yin Fang, Zhuo Chen, Xiang Zhuang, Ningyu Zhang, Xin Shao, Yining Hu, Penghui Yang, Junyun Cheng, Yang Hu, Lingqi Yu, Haihong Yang, Jinlu Zhang, Xiaoyan Lu, Li Shao, Dan Wu, Yue Gao, Huajun Chen, Xiaohui Fan
Summary: Researchers have developed a deep learning framework-based spatial deconvolution algorithm called Bulk2Space, which can reveal spatial and cellular heterogeneity in bulk RNA-seq data. They used this algorithm to uncover the spatial variance of immune cells in different tumor regions, as well as the molecular and spatial heterogeneity of tissues during inflammation-induced tumorigenesis. In addition, they applied Bulk2Space to analyze bulk transcriptome data from mouse brain regions and reconstructed the hierarchical structure of the mouse isocortex and annotated previously unidentified cell types in the mouse hypothalamus.
NATURE COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Jianbo Hu, Jiyu Cui, Bin Gao, Lifeng Yang, Qi Ding, Yijian Li, Yiming Mo, Huajun Chen, Xili Cui, Huabin Xing
Summary: An efficient paradigm for materials design is developed by combining abandoned experimental data, computational structure descriptors, and random forest algorithm. As a case study, the adsorption properties of C2H2, C2H4, and CO2 in anion-pillared MOFs are precisely predicted, and several MOFs with top performance for CO2/C2H2 and C2H2/C2H4 separation are successfully explored and synthesized. A quantitative structure-properties relationship is also provided to offer more accurate and intuitive guidance.
Proceedings Paper
Computer Science, Artificial Intelligence
Yunzhi Yao, Shaohan Huang, Li Dong, Furu Wei, Huajun Chen, Ningyu Zhang
Summary: This paper proposes a simple model called Kformer, which utilizes pre-trained language models and knowledge injection in Transformer FFN layers to tackle knowledge-intensive tasks. The empirical results show that Kformer outperforms other knowledge injection technologies.
NATURAL LANGUAGE PROCESSING AND CHINESE COMPUTING, NLPCC 2022, PT I
(2022)
Proceedings Paper
Computer Science, Information Systems
Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen
Summary: Knowledge graph embedding methods simplify operations for in-KG and out-of-KG tasks by embedding entities and relations of a KG into continuous vector spaces. However, existing methods are not applicable to inductive settings and cannot handle inductive entity prediction. This paper proposes a model called MorsE that learns transferable meta-knowledge to generate entity embeddings without directly learning entity embeddings, and experiments show its significant improvement over baselines in inductive settings.
PROCEEDINGS OF THE 45TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '22)
(2022)
Proceedings Paper
Computer Science, Information Systems
Xiang Chen, Lei Li, Ningyu Zhang, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen
Summary: This study introduces a new approach for relation extraction by utilizing an open-book database to assist relation inference, achieving promising results.
PROCEEDINGS OF THE 45TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '22)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Lingbing Guo, Yuqiang Han, Qiang Zhang, Huajun Chen
Summary: Embedding-based methods in entity alignment have limitations in terms of ignoring semantic information and making shortsighted decisions. To address these limitations, we propose a reinforcement learning-based framework that can adapt to various embedding-based methods and consistently improve performance.
FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Yushan Zhu, Wen Zhang, Mingyang Chen, Hui Chen, Xu Cheng, Wei Zhang, Huajun Chen
Summary: Knowledge Graph Embedding (KGE) is a popular method for KG reasoning. However, high-dimensional KGEs require more resources and are not suitable for resource-limited applications. To address this issue, we propose a knowledge distillation method called DualDE, which builds a low-dimensional student KGE from a pre-trained high-dimensional teacher KGE.
WSDM'22: PROCEEDINGS OF THE FIFTEENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING
(2022)
