49 results on '"Deng, Shumin"'
Search Results
2. Tenuigenin promotes non-rapid eye movement sleep via the GABAA receptor and exerts somnogenic effect in a MPTP mouse model of Parkinson's disease
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Zhang, Di, Zhang, Wenjing, Deng, Shumin, Liu, Lu, Wei, Hua, Xue, Fenqin, Yang, Hui, Wang, Xiaomin, and Fan, Zheng
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- 2023
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3. Genetic variants in the promoters of let-7 are associated with the risk and age at onset of ischemic stroke: A case control study
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Wang, Yuye, Qiu, Luying, Jiang, Wenjuan, Chen, Meilin, He, Zhiyi, Wang, Yanzhe, and Deng, Shumin
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- 2023
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4. A comparison of Knowledge, attitude and practice (KAP) of nurses on nursing Post-stroke dysphagia patients between iii-A and ii-A hospitals in China: a propensity score-matched analysis
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Deng, Shumin, Mao, Xiaolan, Meng, Xianmei, Yu, Liping, Xie, Fei, Huang, Guiling, and Duan, Zhizhou
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- 2022
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5. Low-resource extraction with knowledge-aware pairwise prototype learning
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Deng, Shumin, Zhang, Ningyu, Chen, Hui, Tan, Chuanqi, Huang, Fei, Xu, Changliang, and Chen, Huajun
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- 2022
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6. Robust triple extraction with cascade bidirectional capsule network
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Zhang, Ningyu, Deng, Shumin, Ye, Hongbin, Zhang, Wei, and Chen, Huajun
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- 2022
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7. Neural symbolic reasoning with knowledge graphs: Knowledge extraction, relational reasoning, and inconsistency checking
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Chen, Huajun, Deng, Shumin, Zhang, Wen, Xu, Zezhong, Li, Juan, and Kharlamov, Evgeny
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- 2021
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8. Tweety homolog 3 promotes colorectal cancer progression through mutual regulation of histone deacetylase 7.
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Lu, Pengyan, Deng, Shumin, Liu, Jiaxin, Xiao, Qing, Zhou, Zhengwei, Li, Shuojie, Xin, Jiaxuan, Shu, Guang, Yi, Bo, and Yin, Gang
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COLORECTAL cancer ,COMPETITIVE endogenous RNA ,CANCER invasiveness ,GENE expression ,POLYMERASE chain reaction - Abstract
Colorectal cancer (CRC) is one of the leading cancers worldwide, with metastasis being a major cause of high mortality rates among patients. In this study, dysregulated gene Tweety homolog 3 (TTYH3) was identified by Gene Expression Omnibus database. Public databases were used to predict potential competing endogenous RNAs (ceRNAs) for TTYH3. Quantitative real‐time polymerase chain reaction, western blot, and immunohistochemistry were utilized to analyze TTYH3 and histone deacetylase 7 (HDAC7) levels. Luciferase assays confirmed miR‐1271‐5p directly targeting the 3′ untranslated regions of TTYH3 and HDAC7. In vitro experiments such as transwell and human umbilical vein endothelial cell tube formation, as well as in vivo mouse models, were conducted to assess the biological functions of TTYH3 and HDAC7. We discovered that upregulation of TTYH3 in CRC promotes cell migration by affecting the Epithelial–mesenchymal transition pathway, which was independent of its ion channel activity. Mechanistically, TTYH3 and HDAC7 functioned as ceRNAs, reciprocally regulating each other's expression. TTYH3 competes for binding miR‐1271‐5p, increasing HDAC7 expression, facilitating CRC metastasis and angiogenesis. This study reveals the critical role of TTYH3 in promoting CRC metastasis through ceRNA crosstalk, offering new insights into potential therapeutic targets for clinical intervention. [ABSTRACT FROM AUTHOR]
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- 2024
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9. Sexual Minority Stigma, Sexual Orientation Concealment, Social Support and Depressive Symptoms Among Men Who have Sex with Men in China: A Moderated Mediation Modeling Analysis
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Ding, Changmian, Chen, Xiangfan, Wang, Wei, Yu, Bin, Yang, Huimin, Li, Xiaoyan, Deng, Shumin, Yan, Hong, and Li, Shiyue
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- 2020
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10. Doctors’ Job Satisfaction and Its Relationships With Doctor-Patient Relationship and Work-Family Conflict in China : A Structural Equation Modeling
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Deng, Shumin, Yang, Ningxi, Li, Shiyue, Wang, Wei, Yan, Hong, and Li, Hao
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- 2018
11. Associations of gestational and the first year of life exposure to ambient air pollution with childhood eczema in Hubei, China
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Deng, Shumin, Huang, Danqin, Wang, Wei, Yan, Hong, Li, Shiyue, and Xiang, Hao
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- 2019
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12. Risk Prediction Models for Invasive Mechanical Ventilation in Patients with Autoimmune Encephalitis: A Retrospective Cohort Study.
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Xie, Shiyang, Chen, Meilin, Qiu, Luying, Li, Long, Deng, Shumin, Liu, Fang, Fu, Hefei, and Wang, Yanzhe
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ARTIFICIAL respiration ,MECHANICAL models ,PREDICTION models ,ENCEPHALITIS ,RESPIRATORY insufficiency - Abstract
Background and Objectives. Timely identification of developing severe respiratory failure in patients with autoimmune encephalitis (AE) is crucial to ensure prompt treatment with invasive mechanical ventilation (IMV), which can potentially improve the outcome. We aimed to develop a nomogram for requiring IMV based on easily available clinical characteristics. Methods. A multivariate predictive nomogram model was developed using the risk factors identified by LASSO regression and assessed by receiver operator characteristics (ROC) curve, calibration curve, and decision curve analysis. Results. The risk factors predictive of severe respiratory failure were male gender, impaired hepatic function, elevated intracranial pressure, and higher neuron-specific enolase. The final nomogram achieved an AUC of 0.770. After validation by bootstrapping, a concordance index of 0.748 was achieved. Conclusions. Our nomogram accurately predicted the risk of developing respiratory failure needing IMV in AE patients and provide clinicians with a simple and effective tool to guide treatment interventions in the AE patients. [ABSTRACT FROM AUTHOR]
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- 2023
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13. SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
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Deng, Shumin, Mao, Shengyu, Zhang, Ningyu, and Hooi, Bryan
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computation and Language (cs.CL) ,Machine Learning (cs.LG) - Abstract
Event-centric structured prediction involves predicting structured outputs of events. In most NLP cases, event structures are complex with manifold dependency, and it is challenging to effectively represent these complicated structured events. To address these issues, we propose Structured Prediction with Energy-based Event-Centric Hyperspheres (SPEECH). SPEECH models complex dependency among event structured components with energy-based modeling, and represents event classes with simple but effective hyperspheres. Experiments on two unified-annotated event datasets indicate that SPEECH is predominant in event detection and event-relation extraction tasks., Accepted by ACL 2023 Main Conference. Code is released at \url{https://github.com/zjunlp/SPEECH}
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- 2023
14. Association between HMGB1 genetic variants and ischemic stroke susceptibility, onset age, and recurrence risk among Chinese Han individuals
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Qiu, Luying, Li, Long, He, Zhiyi, Liu, Fang, Deng, Shumin, and Wang, Yanzhe
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Original Article - Abstract
Objectives: Ischemic stroke has long been a global health threat. Genetic factors, a looming risk for ischemic stroke, remain unexplored. The high-mobility group box 1 (HMGB1) protein showed a connection with the occurrence and development of ischemic stroke. This study was conducted to find whether frequent HMGB1 polymorphisms (rs1045411, rs1412125, and rs2249825) play a role in ischemic stroke susceptibility and recurrence risk. Methods: Our study was carried out in a Chinese Han population with a sample size of 871 patients and 858 age-matched healthy controls. Tag single nucleotide polymorphisms (tagSNPs) were selected by conventional protocols and DNA was extracted for genotype analysis after the participants had signed an informed consent. Comprehensive statistical analyses were conducted. Results: It was found that the C allele of the HMGB1 rs1412125 (OR = 1.263, 95% CI = 1.075-1.483, P = 0.004) and HMGB1 rs2249825 (adjusted OR = 2.464, 95% CI = 1.215-4.996, P = 0.012) variants was associated with a high risk of ischemic stroke, with the male subgroup carrying the TT allele of the HMGB1 rs1045411 variant tended to suffer more from the disease (adjusted OR = 3.600, 95% CI = 1.272-10.193, P = 0.016). A haplotype study also showed significant results (OR = 1.554, 95% CI = 1.246-1.938, P = 0.001). The rs1412125 polymorphism was highly associated with the chance of recurrence but not with the onset age (TC vs. TT: P = 0.034; CC vs. TT: P < 0.001). Cox regression analysis and stratified analysis were carried out with notable conclusions. Conclusions: Our study provided evidence for the association between HMGB1 polymorphisms and ischemic stroke susceptibility and recurrence, indicating that HMGB1 gene variants may be potential markers for first and secondary stroke prevention.
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- 2023
15. Continual Multimodal Knowledge Graph Construction
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Chen, Xiang, Zhang, Jintian, Wang, Xiaohan, Wu, Tongtong, Deng, Shumin, Wang, Yongheng, Si, Luo, Chen, Huajun, and Zhang, Ningyu
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Databases ,Computer Science - Artificial Intelligence ,Databases (cs.DB) ,Computation and Language (cs.CL) ,Computer Science - Multimedia ,Machine Learning (cs.LG) ,Multimedia (cs.MM) - Abstract
Multimodal Knowledge Graph Construction (MMKC) refers to the process of creating a structured representation of entities and relationships through multiple modalities such as text, images, videos, etc. However, existing MMKC models have limitations in handling the introduction of new entities and relations due to the dynamic nature of the real world. Moreover, most state-of-the-art studies in MMKC only consider entity and relation extraction from text data while neglecting other multi-modal sources. Meanwhile, the current continual setting for knowledge graph construction only consider entity and relation extraction from text data while neglecting other multi-modal sources. Therefore, there arises the need to explore the challenge of continuous multimodal knowledge graph construction to address the phenomenon of catastrophic forgetting and ensure the retention of past knowledge extracted from different forms of data. This research focuses on investigating this complex topic by developing lifelong multimodal benchmark datasets. Based on the empirical findings that several state-of-the-art MMKC models, when trained on multimedia data, might unexpectedly underperform compared to those solely utilizing textual resources in a continual setting, we propose a Lifelong MultiModal Consistent Transformer Framework (LMC) for continuous multimodal knowledge graph construction. By combining the advantages of consistent KGC strategies within the context of continual learning, we achieve greater balance between stability and plasticity. Our experiments demonstrate the superior performance of our method over prevailing continual learning techniques or multimodal approaches in dynamic scenarios. Code and datasets can be found at https://github.com/zjunlp/ContinueMKGC., Work in progress
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- 2023
16. Ursolic Acid Ameliorated Neuronal Damage by Restoring Microglia-Activated MMP/TIMP Imbalance in vitro.
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Qiu, Luying, Wang, Yaxuan, Wang, Yuye, Liu, Fang, Deng, Shumin, Xue, Weishuang, and Wang, Yanzhe
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- 2023
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17. LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings
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Xie, Xin, Li, Zhoubo, Wang, Xiaohan, Zhu, Yuqi, Zhang, Ningyu, Zhang, Jintian, Cheng, Siyuan, Tian, Bozhong, Deng, Shumin, Xiong, Feiyu, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Databases ,Computer Science - Artificial Intelligence ,Databases (cs.DB) ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Knowledge Graphs (KGs) often have two characteristics: heterogeneous graph structure and text-rich entity/relation information. Text-based KG embeddings can represent entities by encoding descriptions with pre-trained language models, but no open-sourced library is specifically designed for KGs with PLMs at present. In this paper, we present LambdaKG, a library for KGE that equips with many pre-trained language models (e.g., BERT, BART, T5, GPT-3), and supports various tasks (e.g., knowledge graph completion, question answering, recommendation, and knowledge probing). LambdaKG is publicly open-sourced at https://github.com/zjunlp/PromptKG/tree/main/lambdaKG, with a demo video at http://deepke.zjukg.cn/lambdakg.mp4 and long-term maintenance., Work in progress and the project website is https://zjunlp.github.io/project/promptkg/
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- 2022
18. Impact of air pollution and meteorological factors on incidence of allergic rhinitis: A low‐latitude multi‐city study in China.
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Luo, Xin, Hong, Haiyu, Lu, Yongtian, Deng, Shumin, Wu, Naigeng, Zhou, Qilin, Chen, Zhuanggui, Feng, Peiying, Zhou, Yuqi, Tao, Jin, Dai, Min, Zhang, Kun, Zhang, Pingping, Li, Yating, Xiong, Guowei, Cheng, Yun, Su, Jing, Li, Tingyuan, Chen, Jingyang, and Chao, Manhou
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ALLERGIC rhinitis ,AIR pollution ,AIR quality monitoring stations - Abstract
To conclude, we demonstrated that increases in air pollutant concentrations and changes in meteorological conditions are associated with number of outpatient visits for AR. Keywords: air pollutants; allergic rhinitis; distributed non-linear lag model; generalized additive model; meteorological factors EN air pollutants allergic rhinitis distributed non-linear lag model generalized additive model meteorological factors 1656 1659 4 06/02/23 20230601 NES 230601 Allergic rhinitis (AR) is characterized by nasal obstruction, pruritus, rhinorrhea, and sneezing, and it affects 10% to 40% of the population.[1] The prevalence of self-reported AR has been reported increasingly from 11.1% to 17.6% in China.[2] Climate change and air pollution are thought to be responsible for the global increase in allergic diseases.[[3]] However, most previous studies on air pollution or meteorological factors affecting AR have been conducted in a single- and medium-latitude city.[[5]] To find the association between daily air pollutants and meteorological factors and the incidence of AR, we conducted this low-latitude multi-city study in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. (B) Percent change (95% CI) of daily AR outpatient visits for each ten units increase in concentrations of six pollutants using different lag structures in GBA. [Extracted from the article]
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- 2023
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19. Genetic polymorphisms of pri-let-7f, gene–environment and gene–gene interactions, and associations with ischemic stroke risk in Liaoning Province.
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Qiu, Luying, Wang, Yuye, Liu, Fang, Deng, Shumin, He, Zhiyi, Zheng, Wenxu, and Wang, Yanzhe
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- 2023
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20. Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
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Chen, Xiang, Li, Lei, Zhang, Ningyu, Liang, Xiaozhuan, Deng, Shumin, Tan, Chuanqi, Huang, Fei, Si, Luo, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Prompt learning approaches have made waves in natural language processing by inducing better few-shot performance while they still follow a parametric-based learning paradigm; the oblivion and rote memorization problems in learning may encounter unstable generalization issues. Specifically, vanilla prompt learning may struggle to utilize atypical instances by rote during fully-supervised training or overfit shallow patterns with low-shot data. To alleviate such limitations, we develop RetroPrompt with the motivation of decoupling knowledge from memorization to help the model strike a balance between generalization and memorization. In contrast with vanilla prompt learning, RetroPrompt constructs an open-book knowledge-store from training instances and implements a retrieval mechanism during the process of input, training and inference, thus equipping the model with the ability to retrieve related contexts from the training corpus as cues for enhancement. Extensive experiments demonstrate that RetroPrompt can obtain better performance in both few-shot and zero-shot settings. Besides, we further illustrate that our proposed RetroPrompt can yield better generalization abilities with new datasets. Detailed analysis of memorization indeed reveals RetroPrompt can reduce the reliance of language models on memorization; thus, improving generalization for downstream tasks. Code is available in https://github.com/zjunlp/PromptKG/tree/main/research/RetroPrompt., Accepted by NeurIPS 2022
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- 2022
21. Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
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Chen, Xiang, Zhang, Ningyu, Li, Lei, Deng, Shumin, Tan, Chuanqi, Xu, Changliang, Huang, Fei, Si, Luo, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Vision and Pattern Recognition (cs.CV) ,Computer Science - Computer Vision and Pattern Recognition ,Computation and Language (cs.CL) ,Computer Science - Multimedia ,Machine Learning (cs.LG) ,Multimedia (cs.MM) - Abstract
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have recently been successfully applied to tasks such as information retrieval, question answering, and recommendation system. Since most MKGs are far from complete, extensive knowledge graph completion studies have been proposed focusing on the multimodal entity, relation extraction and link prediction. However, different tasks and modalities require changes to the model architecture, and not all images/objects are relevant to text input, which hinders the applicability to diverse real-world scenarios. In this paper, we propose a hybrid transformer with multi-level fusion to address those issues. Specifically, we leverage a hybrid transformer architecture with unified input-output for diverse multimodal knowledge graph completion tasks. Moreover, we propose multi-level fusion, which integrates visual and text representation via coarse-grained prefix-guided interaction and fine-grained correlation-aware fusion modules. We conduct extensive experiments to validate that our MKGformer can obtain SOTA performance on four datasets of multimodal link prediction, multimodal RE, and multimodal NER. Code is available in https://github.com/zjunlp/MKGformer., Accepted by SIGIR 2022. Fix a severe bug
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- 2022
22. From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer
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Xie, Xin, Zhang, Ningyu, Li, Zhoubo, Deng, Shumin, Chen, Hui, Xiong, Feiyu, Chen, Mosha, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Databases ,Computer Science - Artificial Intelligence ,Databases (cs.DB) ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Knowledge graph completion aims to address the problem of extending a KG with missing triples. In this paper, we provide an approach GenKGC, which converts knowledge graph completion to sequence-to-sequence generation task with the pre-trained language model. We further introduce relation-guided demonstration and entity-aware hierarchical decoding for better representation learning and fast inference. Experimental results on three datasets show that our approach can obtain better or comparable performance than baselines and achieve faster inference speed compared with previous methods with pre-trained language models. We also release a new large-scale Chinese knowledge graph dataset AliopenKG500 for research purpose. Code and datasets are available in https://github.com/zjunlp/PromptKG/tree/main/GenKGC., Accepted by WWW 2022 Poster
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- 2022
23. OntoProtein: Protein Pretraining With Gene Ontology Embedding
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Zhang, Ningyu, Bi, Zhen, Liang, Xiaozhuan, Cheng, Siyuan, Hong, Haosen, Deng, Shumin, Lian, Jiazhang, Zhang, Qiang, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,ComputingMethodologies_PATTERNRECOGNITION ,Computer Science - Computation and Language ,Quantitative Biology - Biomolecules ,Computer Science - Artificial Intelligence ,FOS: Biological sciences ,Biomolecules (q-bio.BM) ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Self-supervised protein language models have proved their effectiveness in learning the proteins representations. With the increasing computational power, current protein language models pre-trained with millions of diverse sequences can advance the parameter scale from million-level to billion-level and achieve remarkable improvement. However, those prevailing approaches rarely consider incorporating knowledge graphs (KGs), which can provide rich structured knowledge facts for better protein representations. We argue that informative biology knowledge in KGs can enhance protein representation with external knowledge. In this work, we propose OntoProtein, the first general framework that makes use of structure in GO (Gene Ontology) into protein pre-training models. We construct a novel large-scale knowledge graph that consists of GO and its related proteins, and gene annotation texts or protein sequences describe all nodes in the graph. We propose novel contrastive learning with knowledge-aware negative sampling to jointly optimize the knowledge graph and protein embedding during pre-training. Experimental results show that OntoProtein can surpass state-of-the-art methods with pre-trained protein language models in TAPE benchmark and yield better performance compared with baselines in protein-protein interaction and protein function prediction. Code and datasets are available in https://github.com/zjunlp/OntoProtein., Accepted by ICLR 2022
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- 2022
24. DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
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Zhang, Ningyu, Xu, Xin, Tao, Liankuan, Yu, Haiyang, Ye, Hongbin, Qiao, Shuofei, Xie, Xin, Chen, Xiang, Li, Zhoubo, Li, Lei, Liang, Xiaozhuan, Yao, Yunzhi, Deng, Shumin, Wang, Peng, Zhang, Wen, Zhang, Zhenru, Tan, Chuanqi, Chen, Qiang, Xiong, Feiyu, Huang, Fei, Zheng, Guozhou, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population. DeepKE implements various information extraction tasks, including named entity recognition, relation extraction and attribute extraction. With a unified framework, DeepKE allows developers and researchers to customize datasets and models to extract information from unstructured data according to their requirements. Specifically, DeepKE not only provides various functional modules and model implementation for different tasks and scenarios but also organizes all components by consistent frameworks to maintain sufficient modularity and extensibility. We release the source code at GitHub in https://github.com/zjunlp/DeepKE with Google Colab tutorials and comprehensive documents for beginners. Besides, we present an online system in http://deepke.openkg.cn/EN/re_doc_show.html for real-time extraction of various tasks, and a demo video., Accepted by EMNLP 2022 System Demonstrations and the project website is http://deepke.zjukg.cn/
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- 2022
25. Learning to Ask for Data-Efficient Event Argument Extraction
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Ye, Hongbin, Zhang, Ningyu, Bi, Zhen, Deng, Shumin, Tan, Chuanqi, Chen, Hui, Huang, Fei, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Event argument extraction (EAE) is an important task for information extraction to discover specific argument roles. In this study, we cast EAE as a question-based cloze task and empirically analyze fixed discrete token template performance. As generating human-annotated question templates is often time-consuming and labor-intensive, we further propose a novel approach called "Learning to Ask," which can learn optimized question templates for EAE without human annotations. Experiments using the ACE-2005 dataset demonstrate that our method based on optimized questions achieves state-of-the-art performance in both the few-shot and supervised settings., work in progress
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- 2021
26. LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting
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Chen, Xiang, Li, Lei, Deng, Shumin, Tan, Chuanqi, Xu, Changliang, Huang, Fei, Si, Luo, Chen, Huajun, and Zhang, Ningyu
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Databases ,Computer Science - Artificial Intelligence ,Databases (cs.DB) ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Most NER methods rely on extensive labeled data for model training, which struggles in the low-resource scenarios with limited training data. Existing dominant approaches usually suffer from the challenge that the target domain has different label sets compared with a resource-rich source domain, which can be concluded as class transfer and domain transfer. In this paper, we propose a lightweight tuning paradigm for low-resource NER via pluggable prompting (LightNER). Specifically, we construct the unified learnable verbalizer of entity categories to generate the entity span sequence and entity categories without any label-specific classifiers, thus addressing the class transfer issue. We further propose a pluggable guidance module by incorporating learnable parameters into the self-attention layer as guidance, which can re-modulate the attention and adapt pre-trained weights. Note that we only tune those inserted module with the whole parameter of the pre-trained language model fixed, thus, making our approach lightweight and flexible for low-resource scenarios and can better transfer knowledge across domains. Experimental results show that LightNER can obtain comparable performance in the standard supervised setting and outperform strong baselines in low-resource settings. Code is in https://github.com/zjunlp/DeepKE/tree/main/example/ner/few-shot., Accepted by COLING 2022
- Published
- 2021
27. Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
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Zhang, Ningyu, Li, Luoqiu, Chen, Xiang, Deng, Shumin, Bi, Zhen, Tan, Chuanqi, Huang, Fei, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Vision and Pattern Recognition (cs.CV) ,Computer Science - Computer Vision and Pattern Recognition ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Large-scale pre-trained language models have contributed significantly to natural language processing by demonstrating remarkable abilities as few-shot learners. However, their effectiveness depends mainly on scaling the model parameters and prompt design, hindering their implementation in most real-world applications. This study proposes a novel pluggable, extensible, and efficient approach named DifferentiAble pRompT (DART), which can convert small language models into better few-shot learners without any prompt engineering. The main principle behind this approach involves reformulating potential natural language processing tasks into the task of a pre-trained language model and differentially optimizing the prompt template as well as the target label with backpropagation. Furthermore, the proposed approach can be: (i) Plugged to any pre-trained language models; (ii) Extended to widespread classification tasks. A comprehensive evaluation of standard NLP tasks demonstrates that the proposed approach achieves a better few-shot performance. Code is available in https://github.com/zjunlp/DART., Accepted by ICLR 2022
- Published
- 2021
28. HDAC5, negatively regulated by miR‐148a‐3p, promotes colon cancer cell migration.
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OuYang, Chunli, Shu, Guang, Liu, Jiaxin, Deng, Shumin, Lu, Pengyan, Li, Yimin, Gan, Yaqi, Xie, Bintao, Liu, Junwen, and Yin, Gang
- Abstract
Histone deacetylases (HDACs) are involved in many processes including tumor cell growth and proliferation and regulation of gene expression. To clarify the role of class IIa HDACs in the metastasis of colon adenocarcinoma, we used the class IIa HDAC inhibitor TMP269 and found that it effectively inhibited the migration ability of colon adenocarcinoma cells. Next, we silenced the member of class IIa HDACs and confirmed that the migratory ability of colon adenocarcinoma cells was significantly inhibited by silencing HDAC5 or HDAC7. HDAC5 plays a variety of roles in human cancers. Here, we examined the role of HDAC5 in colon adenocarcinoma. The results indicated that HDAC5 was highly expressed in tumor tissues and negatively correlated with the expression of miR‐148a‐3p. Moreover, the expression of HDAC5 was correlated with tumor progression. HDAC5 markedly increased the invasion and migration of cancer cells in vitro, an effect that could be inhibited by overexpression of miR‐148a‐3p. Following an intraperitoneal injection of colon adenocarcinoma cells in athymic nude mice, HDAC5 promoted tumor implant. Together, these findings showed that HDAC5 overexpression in colon adenocarcinoma is consistent with tumor progression and tumor cell migration and the impact of HDAC5 overexpression is reduced by miR‐148a‐3p. [ABSTRACT FROM AUTHOR]
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- 2022
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29. Fyn Polymorphisms are Associated with Distinct Personality Traits in Healthy Chinese-Han Subjects
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Li, Jingying, Ma, Huan, Deng, Shumin, Wu, Lijuan, Huang, Yinglin, and Zhu, Gang
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- 2011
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30. Association of adiponectin gene polymorphisms with the risk of ischemic stroke in a Chinese Han population
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Liu, Fang, He, Zhiyi, Deng, Shumin, Zhang, Hui, Li, Nan, and Xu, Jialiang
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- 2011
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31. Association of Apolipoprotein M Gene Polymorphisms with Ischemic Stroke in a Han Chinese Population
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Zhao, Dongxue, He, Zhiyi, Qin, Xue, Li, Lei, Liu, Fang, and Deng, Shumin
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- 2011
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32. On Robustness and Bias Analysis of BERT-based Relation Extraction
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Li, Luoqiu, Chen, Xiang, Ye, Hongbin, Bi, Zhen, Deng, Shumin, Zhang, Ningyu, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Machine Learning ,Artificial Intelligence (cs.AI) ,Computer Science - Computation and Language ,Computer Science - Databases ,Computer Science - Artificial Intelligence ,Databases (cs.DB) ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Machine Learning (cs.LG) ,Computer Science - Information Retrieval - Abstract
Fine-tuning pre-trained models have achieved impressive performance on standard natural language processing benchmarks. However, the resultant model generalizability remains poorly understood. We do not know, for example, how excellent performance can lead to the perfection of generalization models. In this study, we analyze a fine-tuned BERT model from different perspectives using relation extraction. We also characterize the differences in generalization techniques according to our proposed improvements. From empirical experimentation, we find that BERT suffers a bottleneck in terms of robustness by way of randomizations, adversarial and counterfactual tests, and biases (i.e., selection and semantic). These findings highlight opportunities for future improvements. Our open-sourced testbed DiagnoseRE is available in \url{https://github.com/zjunlp/DiagnoseRE}., work in progress
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- 2020
33. CYP4F2 gene V433M polymorphism is associated with ischemic stroke in the male Northern Chinese Han population
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Deng, Shumin, Zhu, Gang, Liu, Fang, Zhang, Hui, Qin, Xue, Li, Lei, and Zhiyi, He
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- 2010
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34. When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text Classification
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Deng, Shumin, Zhang, Ningyu, Sun, Zhanlin, Chen, Jiaoyan, and Chen, Huajun
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FOS: Computer and information sciences ,Computer Science - Computation and Language ,Computation and Language (cs.CL) ,Information Retrieval (cs.IR) ,Computer Science - Information Retrieval - Abstract
Text classification tends to be difficult when data are deficient or when it is required to adapt to unseen classes. In such challenging scenarios, recent studies have often used meta-learning to simulate the few-shot task, thus negating implicit common linguistic features across tasks. This paper addresses such problems using meta-learning and unsupervised language models. Our approach is based on the insight that having a good generalization from a few examples relies on both a generic model initialization and an effective strategy for adapting this model to newly arising tasks. We show that our approach is not only simple but also produces a state-of-the-art performance on a well-studied sentiment classification dataset. It can thus be further suggested that pretraining could be a promising solution for few-shot learning of many other NLP tasks. The code and the dataset to replicate the experiments are made available at https://github.com/zxlzr/FewShotNLP., AAAI student abstract
- Published
- 2019
35. Relationship between sexual sensation seeking and condom use among young men who have sex with men in China: testing a moderated mediation model.
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Wang, Wei, Yan, Hong, Duan, Zhizhou, Yang, Huiming, Li, Xiaoyan, Ding, Changmian, Deng, Shumin, and Li, Shiyue
- Subjects
HIV infections ,HUMAN sexuality ,CROSS-sectional method ,ATTITUDES toward sex ,HEALTH literacy ,SEX customs ,FACTOR analysis ,MEN who have sex with men ,CONDOMS ,DATA analysis software - Abstract
The present study incorporated a moderated mediation model to explore the role of attitude towards condom use in mediating the link between sexual sensation seeking (SSS) and condom use and whether this indirect link was modified by HIV-related knowledge among Chinese YMSM. Survey data were collected from a cross-sectional study conducted in Wuhan, China and 373 YMSM were recruited. The mediation and moderated mediation modelling analyses were performed with the software SPSS PROCESS macro. Mediation analysis indicated that attitude towards condom use partly mediated the link between SSS and condom use (indict effect = −0.158, P < 0.001). Moderation analysis found HIV-related knowledge acted as a moderator in the relationship between SSS and attitude towards condom use (interact effect = 0.089, P = 0.001). Final moderated mediation analysis demonstrated that the indirect effect from SSS to condom use through attitude towards condom use was moderated by HIV-related knowledge, that is the interaction between HIV-related knowledge and SSS was positively associated with attitude towards condom use (β = 0.101, P < 0.001). Therefore, increased YMSM-specific HIV-related knowledge education programs need to be conducted. Further longitudinal research is required to verify the findings of this study. [ABSTRACT FROM AUTHOR]
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- 2021
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36. Association of Apolipoprotein C3 Genetic Polymorphisms with the Risk of Ischemic Stroke in the Northern Chinese Han Population.
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Wang, Yanzhe, Yin, Xiaoyu, Li, Lei, Deng, Shumin, and He, Zhiyi
- Subjects
APOLIPOPROTEIN C ,LIPID metabolism ,STROKE risk factors ,SINGLE nucleotide polymorphisms ,GENOTYPES - Abstract
The apolipoprotein C3 (APOC3) gene, which is a member of the APOA1/C3/A4/A5 gene cluster, plays a crucial role in lipid metabolism. Dyslipidemia is an important risk factor for ischemic stroke. In the present study, we performed a hospital-based case—control study of 895 ischemic stroke patients and 883 control subjects to examine the effects of four APOC3 single nucleotide polymorphisms (SNPs) (rs2854116, rs2854117, rs4520 and rs5128) on the risk of ischemic stroke in a northern Chinese Han population. The SNaPshot Multiplex sequencing assay was used for SNP genotyping, and the potential association of genotype distributions and allele frequencies with ischemic stroke was analyzed statistically. Compared with the GG genotype, the CC+GC genotype of rs5128 was significantly associated with an increased risk in females (adjusted OR = 3.38, 95% CI = 1.82–6.28, P <0.01) after all of the risk factors were adjusted for with logistic regression analyses. A similar relationship was found between the rs4520 polymorphism and ischemic stroke risk in Han Chinese women. Under a recessive genetic model, the TT+TC genotypes of this variant increased ischemic stroke risk (adjusted OR = 2.05; 95% CI = 1.28–3.29; P <0.01). Haplotype analysis revealed that in males, the T-C-T-C haplotype of rs2854116-rs2854117-rs4520-rs5128 was significantly more frequent in the ischemic stroke group than in the control group (OR = 1.49, 95% CI = 1.18–1.87, P<0.01). The results of our study indicate that the APOC3 polymorphisms contribute to ischemic stroke susceptibility in females in the northern Chinese Han population. [ABSTRACT FROM AUTHOR]
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- 2016
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37. Ursolic Acid Reduces the Metalloprotease/Anti-Metalloprotease Imbalance in Cerebral Ischemia and Reperfusion Injury [Corrigendum].
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Wang, Yanzhe, He, Zhiyi, and Deng, Shumin
- Published
- 2021
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38. Genetic Polymorphism in PDE4D Gene and Risk of Ischemic Stroke in Chinese Population: A Meta-Analysis.
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Liu, Xu, Zhu, Ruixia, Li, Lei, Deng, Shumin, Li, Qu, and He, Zhiyi
- Subjects
GENETIC polymorphisms ,STROKE risk factors ,META-analysis ,CASE-control method ,SINGLE nucleotide polymorphisms ,MOLECULAR genetics ,CEREBROVASCULAR disease - Abstract
Background: Stroke is the second most common cause of death and major cause of disability worldwide. The SNP 83 in PDE4D gene has been suggested as a risk factor in ischemic stroke, but direct evidence from genetic association studies remains inconclusive even in Chinese population. Methods: Meta-analysis of case-control studies on the relationship between SNP 83 in PDE4D gene and susceptibility to ischemic stroke in Chinese population published domestically and abroad from January 2003 to September 2012. Results: 9 case-control studies were selected. Meta-analysis results showed that the significant association between SNP 83 and ischemic stroke was found under the dominant model (OR = 1.34, 95% CI: 1.20–1.49) and recessive model (OR = 1.45, 95% CI: 1.19–1.76) in Chinese population. In subgroup meta-analysis, SNP 83 and atherothrombotic stroke, rather than lacunar stroke, showed the significant association under the dominant model (OR = 1.69, 95% CI: 1.41–2.01) and recessive model (OR = 1.47, 95% CI: 1.04–2.06). Conclusions: The results suggest that SNP 83 in PDE4D gene is significantly associated with susceptibility to ischemic stroke in Chinese population. [ABSTRACT FROM AUTHOR]
- Published
- 2013
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39. Knowledge graph embeddings for dealing with concept drift in machine learning.
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Chen, Jiaoyan, Lécué, Freddy, Pan, Jeff Z., Deng, Shumin, and Chen, Huajun
- Abstract
Data stream learning has been largely studied for extracting knowledge structures from continuous and rapid data records. As data is evolving on a temporal basis, its underlying knowledge is subject to many challenges. Concept drift,
1 1 This work is addressing the challenge concept drift in machine learning as opposed to concept drift in the Semantic Web community where "concept" (class) meaning in ontology TBox shifts from versioning, iterations or modifications. Note that changes in ABox alone can also lead to concept drift in learning from ontology streams.. as one of core challenge from the stream learning community, is described as changes of statistical properties of the data over time, causing most of machine learning models to be less accurate as changes over time are in unforeseen ways. This is particularly problematic as the evolution of data could derive to dramatic change in knowledge. We address this problem by studying the semantic representation of data streams in the Semantic Web, i.e., ontology streams. Such streams are ordered sequences of data annotated with ontological vocabulary. In particular we exploit three levels of knowledge encoded in ontology streams to deal with concept drifts: i) existence of novel knowledge gained from stream dynamics, ii) significance of knowledge change and evolution, and iii) (in)consistency of knowledge evolution. Such knowledge is encoded as knowledge graph embeddings through a combination of novel representations: entailment vectors, entailment weights, and a consistency vector. We illustrate our approach on classification tasks of supervised learning. Key contributions of the study include: (i) an effective knowledge graph embedding approach for stream ontologies, and (ii) a generic consistent prediction framework with integrated knowledge graph embeddings for dealing with concept drifts. The experiments have shown that our approach provides accurate predictions towards air quality in Beijing and bus delay in Dublin with real world ontology streams. [ABSTRACT FROM AUTHOR]- Published
- 2021
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40. Clear cell renal cell carcinoma located in sinus renalis confused with renal pelvis mass in image
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Wu, Pengjie, Wei, Dong, Zhang, Liqing, Deng, Shumin, Zhu, Gang, and Wang, Jianye
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- 2015
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41. Structured Knowledge Base as Prior Knowledge to Improve Urban Data Analysis.
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Zhang, Ningyu, Li, Xiaoqian, Zhang, Yiyi, Deng, Shumin, Chen, Huajun, Chen, Xi, and Chen, Jiaoyan
- Subjects
INTERNET of things ,SMART cities ,ENERGY management - Abstract
Urban computing at present often relies on a large number of manually extracted features. This may require a considerable amount of feature engineering, and the procedure may miss certain hidden features and relationships among data items. In this paper, we propose a method to use structured prior knowledge in the form of knowledge graphs to improve the precision and interpretability in applications such as optimal store placement and traffic accident inference. Specifically, we integrate sub-graph feature extraction, sub-knowledge graph gated neural networks, and kernel-based knowledge graph convolutional neural networks as ways of incorporating large urban knowledge graphs into a fully end-to-end learning system. Experiments using data from several large cities showed that our method outperforms the baseline methods. [ABSTRACT FROM AUTHOR]
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- 2018
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42. Association of PDE4D and IL-1 gene polymorphism with ischemic stroke in a Han Chinese population
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Li, Nan, He, Zhiyi, Xu, Jialiang, Liu, Fang, Deng, Shumin, and Zhang, Hui
- Subjects
- *
GENETIC polymorphisms , *CLEVER Hans (Horse) , *PHOSPHODIESTERASES , *INTERLEUKIN-1 , *INFLAMMATION , *MEDICAL statistics ,HEALTH of Chinese people - Abstract
Abstract: Background: The single-nucleotide polymorphisms (SNPs) of the phosphodiesterase 4D (PDE4D) and interleukin-1 (IL-1) genes are associated with increased risk for the development of ischemic stroke (IS) in whites. However, little is known about whether this association could also occur in Han Chinese. Method: A total of 371 patients with IS and unrelated healthy controls were recruited and the SNPs of the PDE4D (83T/C), (87T/C), IL-1 (−889C/T) and IL-1 (−511C/T) were characterized, respectively, by polymerase chain reactions-restriction fragment length polymorphism (PCR-RFLP). The genotype and allele frequencies of these SNPs in this population were statistically analyzed. Results: The genotype and allele frequencies of the PDE4D (87T/C) and IL-1 (−511C/T) were similar between IS patients and controls. In contrast, the frequencies of CC genotype and C allele of the PDE4D (83T/C) and the T allele frequency of IL-1 (−889C/T) in IS patients were significantly higher than that in healthy controls (p =0.001, p =0.003 and p =0.02, respectively), independent of the conventional risk factors. The values of odds ratio (OR) reached at OR=1.603; 95%CI=1.032–2.489; p =0.036 for the CC genotype of the PDE4D (83T/C) and OR=1.913; 95%CI=1.621–2.375; p =0.034 for the TT genotype of the IL-1 (−889C/T), respectively. Conclusions: the SNPs of the PDE4D (83T/C) and IL-1 (−889C/T) were associated with increased risk for the development of IS in Northern Han Chinese. [Copyright &y& Elsevier]
- Published
- 2010
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43. Association between HMGB1 genetic variants and ischemic stroke susceptibility, onset age, and recurrence risk among Chinese Han individuals.
- Author
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Qiu L, Li L, He Z, Liu F, Deng S, and Wang Y
- Abstract
Objectives: Ischemic stroke has long been a global health threat. Genetic factors, a looming risk for ischemic stroke, remain unexplored. The high-mobility group box 1 (HMGB1) protein showed a connection with the occurrence and development of ischemic stroke. This study was conducted to find whether frequent HMGB1 polymorphisms (rs1045411, rs1412125, and rs2249825) play a role in ischemic stroke susceptibility and recurrence risk., Methods: Our study was carried out in a Chinese Han population with a sample size of 871 patients and 858 age-matched healthy controls. Tag single nucleotide polymorphisms (tagSNPs) were selected by conventional protocols and DNA was extracted for genotype analysis after the participants had signed an informed consent. Comprehensive statistical analyses were conducted., Results: It was found that the C allele of the HMGB1 rs1412125 (OR = 1.263, 95% CI = 1.075-1.483, P = 0.004) and HMGB1 rs2249825 (adjusted OR = 2.464, 95% CI = 1.215-4.996, P = 0.012) variants was associated with a high risk of ischemic stroke, with the male subgroup carrying the TT allele of the HMGB1 rs1045411 variant tended to suffer more from the disease (adjusted OR = 3.600, 95% CI = 1.272-10.193, P = 0.016). A haplotype study also showed significant results (OR = 1.554, 95% CI = 1.246-1.938, P = 0.001). The rs1412125 polymorphism was highly associated with the chance of recurrence but not with the onset age (TC vs. TT: P = 0.034; CC vs. TT: P < 0.001). Cox regression analysis and stratified analysis were carried out with notable conclusions., Conclusions: Our study provided evidence for the association between HMGB1 polymorphisms and ischemic stroke susceptibility and recurrence, indicating that HMGB1 gene variants may be potential markers for first and secondary stroke prevention., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (AJTR Copyright © 2023.)
- Published
- 2023
44. Ursolic acid promotes microglial polarization toward the M2 phenotype via PPARγ regulation of MMP2 transcription.
- Author
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Wang Y, Qiu L, Deng S, Liu F, He Z, Li M, and Wang Y
- Subjects
- Rats, Animals, Matrix Metalloproteinase 2 genetics, Matrix Metalloproteinase 2 metabolism, Matrix Metalloproteinase 2 pharmacology, Matrix Metalloproteinase 9 genetics, Matrix Metalloproteinase 9 metabolism, Signal Transduction, Lipopolysaccharides, Anti-Inflammatory Agents pharmacology, Phenotype, Ursolic Acid, PPAR gamma metabolism, PPAR gamma pharmacology, Microglia
- Abstract
Microglia, which are the primary inflammatory cells of the brain, can undergo phenotypic switching between M1 and M2 polarization, which have opposing effects on inflammation. Peroxisome proliferator-activated receptor gamma (PPARγ) is a member of the nuclear receptor family of ligand-inducible transcription factors, and PPARγ is known to regulate M2 macrophage polarization. Previous studies have shown that the natural pentacyclic triterpenoid ursolic acid (3β-hydroxy-urs-12-en-28-oic acid; UA) influences microglial activation. Additionally, UA increases tissue inhibitor matrix metalloproteinase 1 (TIMP1), while greatly reducing the release of matrix metalloproteinase 2 (MMP2) and MMP9 in a PPARγ-dependent manner. Here, we examined the anti-inflammatory properties of UA by observing how well it promotes the phenotypic transition of lipopolysaccharide (LPS) and interferon gamma (IFNγ)-activated BV2 microglia from M1 to M2 polarization. To determine if PPARγ is involved in the underlying molecular pathway, we treated rats with UA and the PPARγ inhibitor BADGE. We also investigated the mechanisms by which PPARγ controls transcription from the MMP2 promoter. The in-vitro experiments showed that UA shifted LPS/IFNγ-activated BV2 microglia from the M1 to the M2 phenotype, which was associated with a reduction in the neurotoxic factors MMP2 and MMP9, and an increase in the anti-inflammatory factor TIMP1. Co-treatment with increased MMP2 and MMP9 synthesis while decreasing TIMP1 release, indicating that UA has anti-inflammatory effects on LPS/IFNγ-activated BV2 cells via activation of PPARγ. Next, we found that PPARγ directly influences MMP2 transcriptional activity by identifying the crucial peroxisome proliferator response element (PPRE) among five potential PPREs in the MMP2 promoter. These results suggest that UA has a protective anti-inflammatory effect against neuroinflammatory toxicity, which is exerted by direct activation of PPARγ and selectively modulates microglial polarization and suppresses MMP2 formation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)
- Published
- 2023
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45. TREM2 improves neurological dysfunction and attenuates neuroinflammation, TLR signaling and neuronal apoptosis in the acute phase of intracerebral hemorrhage.
- Author
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Liu S, Cao X, Wu Z, Deng S, Fu H, Wang Y, and Liu F
- Abstract
Neuroinflammation contributes to secondary brain injury following intracerebral hemorrhage (ICH). Triggering receptor expressed on myeloid cells 2 (TREM2) confers strong neuroprotective effect by suppressing neuroinflammatory response in experimental ischemic stroke. This study aimed to clarify the neuroprotective role of TREM2 and potential underlying mechanism in a mouse model of ICH and in vitro . Adeno-associated virus (AAV) and green fluorescent protein-lentivirus (GFP-LV) strategies were employed to enhance TREM2 expression in the C57/BL6 mice and BV2 cells, respectively. The adult male C57/BL6 mice were subjected to ICH by administration of collagenase-IV in 1 month after the AAV particles injection. An in vitro ICH model was performed with oxygen hemoglobin in BV2 cells. Toll-like receptor 4 (TLR4) antagonist TAK242 was applied at 6 h following ICH. Neurological function, TREM2, pro-inflammatory cytokines, brain water content and Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining were evaluated at 24 h following ICH. TLR4, NF-κB and mitogen-activated protein kinases (MAPK) signaling pathways were also determined by Western blot analysis at the same time point. The levels of TREM2 were increased at 12 h, peaked at 24 h and recovered on 7d following ICH. TREM2 overexpression ameliorated ICH induced neurological dysfunction, inhibited neuroinflammation, and attenuated apoptosis and brain edema. Further mechanistic study revealed that TREM2 overexpression inhibited TLR4 activation and NF-κB and MAPK signaling pathways. ICH increased the percentage of TUNEL-positive cells, which was markedly decreased by TREM2 overexpression. A similar improvement was also observed by the administration of TAK242 following ICH. TREM2 improves neurological dysfunction and attenuates neuroinflammation and neuronal apoptosis in the acute phase of ICH, which is, at least in part, mediated by negatively regulating TLR4 signaling pathway. These findings highlight TREM2 as a potential target for early brain injury following ICH., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Cao, Wu, Deng, Fu, Wang and Liu.)
- Published
- 2022
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46. Transperineal-incision urethrectomy combined with laparoscopic prostatectomy for a male patient with squamous cell carcinoma involving distal plus proximal urethra and untypical symptoms-a case report.
- Author
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Wang M, Yang M, Wu P, Deng S, Wang J, Chen J, Wang J, and Liu M
- Abstract
Primary urethral carcinoma (PUC) is a rare malignancy, covering less than 1% of all genitourinary cancers. Different tumor location, classified as tumor in distal or proximal urethra, represents different characteristics and often leads to different treatment modality. However, data on the surgical approach for PUC involving both distal and proximal urethra remains rare. In this case, we presented a 75-year-old man with untypical symptoms of perineal mass and unspecific frequent and painful urination. Results of multiparametric magnetic resonance imaging (mp-MRI), positron emission tomography/computed tomography (PET/CT) scan, and percutaneous biopsy revealed a cT2N1M0 PUC involving both distal and proximal urethra. Given the request of patients for a normal penile appearance after surgery, a transperineal-incision urethrectomy combined with laparoscopic prostatectomy and iliac lymphadenectomy was performed with optimal outcomes. The results of histopathological analysis revealed a moderately-high differentiated PUC with no positive lymph node. Post-operative recovery was uneventful. On first visit 1-month after surgery, physical examination revealed a satisfactory wound healing and appearance of penis and no recurrent lesions were found on mp-MRI. This is a rare case with untypical symptoms indicating that patients with PUC involving both distal and proximal urethra may present with no symptoms of urethral stricture but only non-specific lower urinary symptoms. The surgical approach we proposed in this case proves to be a safe and feasible one to completely resect the tumor and preserve a normal appearance of penis, thus worth to be applied in the specific patient population., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tau-20-984). The authors have no conflicts of interest to declare., (2021 Translational Andrology and Urology. All rights reserved.)
- Published
- 2021
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47. Ursolic Acid Ameliorates Inflammation in Cerebral Ischemia and Reperfusion Injury Possibly via High Mobility Group Box 1/Toll-Like Receptor 4/NFκB Pathway.
- Author
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Wang Y, Li L, Deng S, Liu F, and He Z
- Abstract
Toll-like receptors (TLRs) play key roles in cerebral ischemia and reperfusion injury by inducing the production of inflammatory mediators, such as interleukins (ILs) and tumor necrosis factor-alpha (TNF-α). According to recent studies, ursolic acid (UA) regulates TLR signaling and exhibits notable anti-inflammatory properties. In the present study, we explored the mechanism by which UA regulates inflammation in the rat middle cerebral artery occlusion and reperfusion (MCAO/R) model. The MCAO/R model was induced in male Sprague-Dawley rats (MCAO for 2 h, followed by reperfusion for 48 h). UA was administered intragastrically at 0.5, 24, and 47 h after reperfusion. The direct high mobility group box 1 (HMGB1) inhibitor glycyrrhizin (GL) was injected intravenously after 0.5 h of ischemia as a positive control. The degree of brain damage was estimated using the neurological deficit score, infarct volume, histopathological changes, and neuronal apoptosis. We assessed IL-1β, TNF-α, and IL-6 levels to evaluate post-ischemic inflammation. HMGB1 and TLR4 expression and phosphorylation of nuclear factor kappa-light-chain-enhancer of activated B cell (NFκB) were also examined to explore the underlying mechanism. UA (10 and 20 mg/kg) treatment significantly decreased the neurological deficit scores, infarct volume, apoptotic cells, and IL-1β, TNF-α, and IL-6 concentrations. The infarct area ratio was reduced by (33.07 ± 1.74), (27.05 ± 1.13), (27.49 ± 1.87), and (39.74 ± 2.14)% in the 10 and 20 mg/kg UA, GL, and control groups, respectively. Furthermore, UA (10 and 20 mg/kg) treatment significantly decreased HMGB1 release and the TLR4 level and inactivated NFκB signaling. Thus, the effects of intragastric administration of 20 mg/kg of UA and 10 mg/kg of GL were similar. We provide novel evidence that UA reduces inflammatory cytokine production to protect the brain from cerebral ischemia and reperfusion injury possibly through the HMGB1/TLR4/NFκB signaling pathway.
- Published
- 2018
- Full Text
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48. The association between apolipoprotein A1-C3-A5 gene cluster promoter polymorphisms and risk of ischemic stroke in the northern Chinese Han population.
- Author
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Wang Y, Liu F, Li L, Deng S, and He Z
- Subjects
- Brain Ischemia complications, Case-Control Studies, Ethnicity genetics, Female, Gene Frequency genetics, Genetic Association Studies, Genetic Predisposition to Disease, Haplotypes genetics, Humans, Logistic Models, Male, Middle Aged, Multigene Family, Stroke complications, Apolipoprotein A-I genetics, Apolipoprotein A-V genetics, Apolipoprotein C-III genetics, Asian People genetics, Brain Ischemia genetics, Polymorphism, Single Nucleotide genetics, Promoter Regions, Genetic genetics, Stroke genetics
- Abstract
Objective Given its effects on lipid metabolism, the apolipoprotein A1-C3-A5 ( APOA1-C3-A5) gene cluster is thought to play an important role in ischemic stroke pathogenesis. Here, we evaluated whether the APOA1-C3-A5 cluster is associated with ischemic stroke in the northern Chinese Han population. Methods This case-control study analyzed 812 patients with ischemic stroke and 844 healthy controls with regard to four APOA1-C3-A5 cluster promoter single nucleotide polymorphisms (SNPs), rs670, rs2854116, rs2854117, and rs662799, using the SNaPshot Multiplex sequencing assay. Potential associations among ischemic stroke, genotyping, and allele frequencies were assessed. Results APOA1 rs670 CT/TT genotypes, APOA5 rs662799 AG/GG genotypes, and the APOC3 rs2854116 CC genotype were associated with an increased risk of ischemic stroke according to multivariate logistic analysis after adjusting for confounding factors. A significantly increased risk for ischemic stroke was also identified among high-risk haplotypes (C-C-T-A and T-T-C-A) for rs670-rs2854116-rs2854117-rs662799. Conclusion This study showed that rs670, rs2854116, and rs662799 SNPs of the APOA1-C3-A5 cluster are associated with ischemic stroke in the northern Chinese Han population.
- Published
- 2017
- Full Text
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49. Ursolic acid reduces the metalloprotease/anti-metalloprotease imbalance in cerebral ischemia and reperfusion injury.
- Author
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Wang Y, He Z, and Deng S
- Subjects
- Administration, Oral, Animals, Benzhydryl Compounds administration & dosage, Benzhydryl Compounds pharmacology, Benzhydryl Compounds therapeutic use, Brain Ischemia enzymology, Brain Ischemia metabolism, Disease Models, Animal, Epoxy Compounds administration & dosage, Epoxy Compounds pharmacology, Epoxy Compounds therapeutic use, Male, Neuroprotective Agents administration & dosage, Neuroprotective Agents therapeutic use, Rats, Rats, Sprague-Dawley, Reperfusion Injury enzymology, Reperfusion Injury metabolism, Triterpenes administration & dosage, Triterpenes pharmacology, Ursolic Acid, Brain Ischemia drug therapy, Metalloproteases antagonists & inhibitors, Metalloproteases metabolism, Neuroprotective Agents pharmacology, Reperfusion Injury drug therapy, Triterpenes therapeutic use
- Abstract
Background: Activators of PPARs, particularly PPARγ, may be effective neuroprotective drugs against inflammatory responses in cerebral ischemia and reperfusion injury. Ursolic acid (UA) may act as a PPARγ agonist and serve as an anti-inflammatory agent. In this study, we used a rat middle cerebral artery occlusion and reperfusion model to examine how UA acts as a neuroprotective agent to modulate the metalloprotease/anti-metalloprotease balance., Methods: The middle cerebral artery occlusion and reperfusion model (occlusion for 2 hours followed by reperfusion for 48 hours) was induced in male Sprague Dawley rats. UA was administered intragastrically 0.5, 24, and 47 hours after reperfusion. Bisphenol A diglycidyl ether (a PPARγ antagonist) was intraperitoneally administered 1, 24.5, and 47.5 hours after reperfusion. Forty-eight hours after reperfusion, neurological deficits and infarct volume were estimated. The PPARγ level and the metalloprotease/anti-metalloprotease balance were examined by Western blotting and immunohistochemistry. The activation of MAPK signaling pathways was also assessed., Results: UA-treated (5, 10, or 20 mg/kg) rats showed significant improvement in neurological deficit score, infarct volume, and the number of intact neurons compared with control rats (P<0.01). Both the PPARγ protein level and the percentage of PPARγ-positive cells were increased in the UA-treated groups (P<0.01). Compared with the control group, the UA-treated groups exhibited reduced protein levels of MMP2, MMP9, and activated MAPKs (P<0.01) but an increased level of TIMP1 (P<0.01). UA exerted its protective effects in a dose-dependent manner. Co-treatment with UA and bisphenol A diglycidyl ether completely abolished the UA-induced changes in PPARγ expression; however UA continued to exert a significant but partial neuroprotective effect., Conclusion: UA can act as a PPARγ agonist to improve the metalloprotease/anti-metalloprotease balance, possibly by inhibiting the activation of the MAPK signaling pathway, thereby attenuating cerebral ischemia and reperfusion injury. Therefore, UA may serve as a novel neuroprotective therapeutic agent.
- Published
- 2016
- Full Text
- View/download PDF
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