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Li Q, Yang Z, Chen K, Zhao M, Long H, Deng Y, Hu H, Jia C, Wu M, Zhao Z, Zhu H, Zhou S, Zhao M, Cao P, Zhou S, Song Y, Tang G, Liu J, Jiang J, Liao W, Zhou W, Yang B, Xiong F, Zhang S, Gao X, Jiang Y, Zhang W, Zhang B, He YL, Ran L, Zhang C, Wu W, Suolang Q, Luo H, Kang X, Wu C, Jin H, Chen L, Guo Q, Gui G, Li S, Si H, Guo S, Liu HY, Liu X, Ma GZ, Deng D, Yuan L, Lu J, Zeng J, Jiang X, Lyu X, Chen L, Hu B, Tao J, Liu Y, Wang G, Zhu G, Yao Z, Xu Q, Yang B, Wang Y, Ding Y, Yang X, Kai H, Wu H, Lu Q. Human-multimodal deep learning collaboration in 'precise' diagnosis of lupus erythematosus subtypes and similar skin diseases. J Eur Acad Dermatol Venereol 2024. [PMID: 38619440 DOI: 10.1111/jdv.20031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/09/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE. OBJECTIVES We aim to develop a multimodal deep learning system (MMDLS) for human-AI collaboration in diagnosis of LE subtypes. METHODS This is a multi-centre study based on 25 institutions across China to assist in diagnosis of LE subtypes, other eight similar skin diseases and healthy subjects. In total, 446 cases with 800 clinical skin images, 3786 multicolor-immunohistochemistry (multi-IHC) images and clinical data were collected, and EfficientNet-B3 and ResNet-18 were utilized in this study. RESULTS In the multi-classification task, the overall performance of MMDLS on 13 skin conditions is much higher than single or dual modals (Sen = 0.8288, Spe = 0.9852, Pre = 0.8518, AUC = 0.9844). Further, the MMDLS-based diagnostic-support help improves the accuracy of dermatologists from 66.88% ± 6.94% to 81.25% ± 4.23% (p = 0.0004). CONCLUSIONS These results highlight the benefit of human-MMDLS collaborated framework in telemedicine by assisting dermatologists and rheumatologists in the differential diagnosis of LE subtypes and similar skin diseases.
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Affiliation(s)
- Qianwen Li
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhi Yang
- Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, China
| | - Kaili Chen
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ming Zhao
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Hai Long
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yueming Deng
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Haoran Hu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chen Jia
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Meiyu Wu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhidan Zhao
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Huan Zhu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Suqing Zhou
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Mingming Zhao
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Pengpeng Cao
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Shengnan Zhou
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yang Song
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Guishao Tang
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Juan Liu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jiao Jiang
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Wei Liao
- Department of Dermatology, Hunan Children's Hospital, Changsha, China
| | - Wenhui Zhou
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Bingyi Yang
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Feng Xiong
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Suhan Zhang
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaofei Gao
- Department of Dermatology, Hunan Children's Hospital, Changsha, China
| | - Yiqun Jiang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Wei Zhang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Bo Zhang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Yan-Ling He
- Department of Dermatology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Liwei Ran
- Department of Dermatology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Chunlei Zhang
- Department of Dermatology, Peking University Third Hospital, Beijing, China
| | - Wenting Wu
- Department of Dermatology, Peking University Third Hospital, Beijing, China
| | - Quzong Suolang
- Department of Dermatology, People's Hospital of Tibet Autonomous Region, Lhasa, China
| | - Hanhuan Luo
- Department of Dermatology, People's Hospital of Tibet Autonomous Region, Lhasa, China
| | - Xiaojing Kang
- Department of Dermatology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Caoying Wu
- Department of Dermatology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China
| | - Hongzhong Jin
- Department of Dermatology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Lei Chen
- Department of Dermatology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China
| | - Qing Guo
- Department of Dermatology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Guangji Gui
- Department of Dermatology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Shanshan Li
- Department of Dermatology, The First Bethune Hospital of Jilin University, Changchun, China
| | - Henan Si
- Department of Dermatology, The First Bethune Hospital of Jilin University, Changchun, China
| | - Shuping Guo
- Department of Dermatology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Hong-Ye Liu
- Department of Dermatology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xiguang Liu
- Department of Dermatology, The Hei Long Jiang Provincial Hospital, Harbin, China
| | - Guo-Zhang Ma
- Department of Dermatology, The Hei Long Jiang Provincial Hospital, Harbin, China
| | - Danqi Deng
- Department of Dermatology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Limei Yuan
- Department of Dermatology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jianyun Lu
- Department of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jinrong Zeng
- Department of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xian Jiang
- Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoyan Lyu
- Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China
| | - Liuqing Chen
- Department of Dermatology, Wuhan No. 1 Hospital, Wuhan, China
| | - Bin Hu
- Department of Dermatology, Wuhan No. 1 Hospital, Wuhan, China
| | - Juan Tao
- Department of Dermatology, Wuhan Union Hospital of China, Wuhan, China
| | - Yuhao Liu
- Department of Dermatology, Wuhan Union Hospital of China, Wuhan, China
| | - Gang Wang
- Department of Dermatology, Xijing Hospital, Xi'an, China
| | - Guannan Zhu
- Department of Dermatology, Xijing Hospital, Xi'an, China
| | - Zhirong Yao
- Department of Dermatology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qianyue Xu
- Department of Dermatology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin Yang
- Dermatology Hospital of Southern Medical University, Guangzhou, China
| | - Yu Wang
- Dermatology Hospital of Southern Medical University, Guangzhou, China
| | - Yan Ding
- Hainan Provincial Hospital of Skin Disease, Haikou, China
| | - Xianxu Yang
- Hainan Provincial Hospital of Skin Disease, Haikou, China
| | - Hu Kai
- Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, China
| | - Haijing Wu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Qianjin Lu
- Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital of Central South University, Changsha, China
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Chinese Academy of Medical Sciences, Nanjing, China
- Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Nanjing, China
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Li WW, Guo YC, Zhan L, Ma GZ, Yang ZS, Liu CW, Shen ZX, Wang D, Zhang XA, Song XH, Yu B, Jia HY, Li XG, Zhang XL, Yang XR, Yang DJ, Pei XY. [Molecular epidemiology of Listeria monocytogenes isolated from ready-to-eat food in 2017 in China]. Zhonghua Yu Fang Yi Xue Za Zhi 2020; 54:175-180. [PMID: 32074706 DOI: 10.3760/cma.j.issn.0253-9624.2020.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To analyze the molecular characteristics of Listeria monocytogenes strains from ready-to eat food in China. Methods: A total of 239 Listeria monocytogenes strains isolated from ready-to-eat food in 2017, all strains underwent whole-genome sequencing (WGS) , and comparisons uncovered population structure derived from lineages, clonal complex, serogroups, antimicrobial susceptibility and virulence, which were inferred in silico from the WGS data. Core genome multilocus sequence typing was used to subtype isolates. Results: All strains were categorized into three different lineages, lineage Ⅱ was the predominant types in food, and IIa was the main serogroups. CC8, CC101 and CC87 were the first three prevalent CCs among 23 detected CCs, accounting for 49.4%. Only 4.6% (11 isolates) of tested strains harbored antibiotic resistance genes, which were mostly trimethoprim genes (7 isolates, 2.9%). All strains were positive for LIPI-1, and only a part of strains harbored LIPI-3 and LIPI-4, accounting for 13.8% (33 isolates) and 14.2% (34 isolates), respectively. ST619 carried both LIPI-3 and LIPI-4. 51.5% (123 isolates) of strains carried SSI-1, and all CC121 strains harbored SSI-2. Different lineages, serogroups and CCs can be separated obviously through cgMLST analysis, and 24 sublineages were highly concordant with CCs. Conclusion: Ⅱa was the main serogroups in ready-to-eat food isolates in China; CC8, CC101 and CC87 were the prevalent CCs, and CC87 isolates was hypervirulent isolates, cgMLST method can be adopted for prospective foodborne disease surveillance and outbreaks detection.
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Affiliation(s)
- W W Li
- Department of Risk Surveillance, China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - Y C Guo
- Department of Risk Surveillance, China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - L Zhan
- Microbiology Laboratory, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - G Z Ma
- Institute of Pathogen Microbiology and Bio-Testing, Shaanxi Provincial Center for DiseaseControl and Prevention, Xian 710054, China
| | - Z S Yang
- Division of Health Inspection, Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - C W Liu
- Institute of Nutrition and Food Safety, Jiangxi Provincial Center for Disease Control and Prevention, Nanchang 330029, China
| | - Z X Shen
- Microbiology Laboratory, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang 050024, China
| | - D Wang
- Institute of Nutrition and Food Safety, Beijing Provincial Center for Disease Control and Prevention, Beijing 100013, China
| | - X A Zhang
- Institute of Nutrition and Food Safety, Beijing Provincial Center for Disease Control and Prevention, Beijing 100013, China
| | - X H Song
- Division of disinfection Surveillance, Shanxi Provincial Center for Disease Control and Prevention, Taiyuan 030012, China
| | - B Yu
- Institute of Health Inspection, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - H Y Jia
- Microbiology Laboratory, Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - X G Li
- Microbiology Laboratory, Guangxi Provincial Center for Disease Control and Prevention, Nanning 530028, China
| | - X L Zhang
- Institute of Health Inspection, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 450046, China
| | - X R Yang
- Microbiology Laboratory, Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610044, China
| | - D J Yang
- Department of Risk Surveillance, China National Center for Food Safety Risk Assessment, Beijing 100022, China
| | - X Y Pei
- Department of Risk Surveillance, China National Center for Food Safety Risk Assessment, Beijing 100022, China
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Huang CQ, Ma GZ, Tao MD, Ma XL, Feng J, Liu QX. The Relationship between Renal Injury and Change in Vitamin D Metabolism in Aged Rats with Insulin Resistance or Type 2 Diabetes Mellitus. J Int Med Res 2008; 36:289-95. [PMID: 18380939 DOI: 10.1177/147323000803600211] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Insulin resistance (IR), IR treated with vitamin D, IR treated with 1α-hydroxyvitamin D (1α-(OH)D), type 2 diabetes mellitus (T2DM), T2DM treated with vitamin D and T2DM treated with 1a-(OH)D were studied in animal models using aged Wistar rats. Glucose infusion rates and levels of urinary albumin (UA), serum 25-hydroxyvitamin D (25-(OH)D) and 1, 25-dihydroxyvitamin D (1, 25-(OH)2D) were measured. T2DM rats had higher UA than IR or normal rats, and levels of 25-(OH)D in all models were similar. IR rats had higher 1, 25-(OH)2D levels than T2DM rats, and had lower 1, 25-(OH)2D levels than normal rats. Treating IR or T2DM rats with vitamin D had no effect on 25-(OH)D or 1, 25-(OH)2D. Administration of 1α-(OH)D significantly increased 1, 25-(OH)2D in IR rats to above-normal levels, and significantly increased 1, 25-(OH)2D in T2DM rats to normal levels. In IR or T2DM, abnormal vitamin D metabolism is characterized by 1, 25-(OH)2D deficiency and is related to renal injury.
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Affiliation(s)
- CQ Huang
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
| | - GZ Ma
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
| | - MD Tao
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
| | - XL Ma
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
| | - J Feng
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
| | - QX Liu
- Geriatrics Department, Third Hospital of Mian Yang, Mian Yang, Sichuan, China
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