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Luo D, Tong Z, Wen L, Bai M, Jin X, Liu Z, Li Y, Xue W. DTNPD: A comprehensive database of drugs and targets for neurological and psychiatric disorders. Comput Biol Med 2024; 175:108536. [PMID: 38701592 DOI: 10.1016/j.compbiomed.2024.108536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 04/15/2024] [Accepted: 04/28/2024] [Indexed: 05/05/2024]
Abstract
In response to the shortcomings in data quality and coverage for neurological and psychiatric disorders (NPDs) in existing comprehensive databases, this paper introduces the DTNPD database, specifically designed for NPDs. DTNPD contains detailed information on 30 NPDs types, 1847 drugs, 514 drug targets, 64 drug combinations, and 61 potential target combinations, forming a network with 2389 drug-target associations. The database is user-friendly, offering open access and downloadable data, which is crucial for network pharmacology studies. The key strength of DTNPD lies in its robust networks of drug and target combinations, as well as drug-target networks, facilitating research and development in the field of NPDs. The development of the DTNPD database marks a significant milestone in understanding and treating NPDs. For accessing the DTNPD database, the primary URL is http://dtnpd.cnsdrug.com, complemented by a mirror site available at http://dtnpd.lyhbio.com.
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Affiliation(s)
- Ding Luo
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China
| | - Zhuohao Tong
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Lu Wen
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Mingze Bai
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
| | - Xiaojie Jin
- College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou, 730000, China
| | - Zerong Liu
- Central Nervous System Drug Key Laboratory of Sichuan Province, Sichuan Credit Pharmaceutical Co., Ltd, Sichuan, 646100, China; Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing, 400030, China
| | - Yinghong Li
- Chongqing Key Laboratory of Big Data for Bio Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
| | - Weiwei Xue
- School of Pharmaceutical Sciences, Chongqing University, Chongqing, 401331, China.
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Fu Y, Wang C, Wu Z, Zhang X, Liu Y, Wang X, Liu F, Chen Y, Zhang Y, Zhao H, Wang Q. Discovery of the potential biomarkers for early diagnosis of endometrial cancer via integrating metabolomics and transcriptomics. Comput Biol Med 2024; 173:108327. [PMID: 38552279 DOI: 10.1016/j.compbiomed.2024.108327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 03/07/2024] [Accepted: 03/17/2024] [Indexed: 04/17/2024]
Abstract
Endometrial cancer (EC) is one of the most common malignant tumors in women, and the increasing incidence and mortality pose a serious threat to the public health. Early diagnosis of EC could prolong the survival period and optimize the survivorship, greatly alleviating patients' suffering and social medical pressure. In this study, we collected urine and serum samples from the recruited patients, analyzed the samples using LC-MS approach, and identified the differential metabolites through metabolomic analysis. Then, the differentially expressed genes were identified through the systematic transcriptomic analysis of EC-related dataset from Gene Expression Omnibus (GEO), followed by network profiling of metabolic-reaction-enzyme-gene. In this experiment, a total of 83 differential metabolites and 19 hub genes were discovered, of which 10 different metabolites and 3 hub genes were further evaluated as more potential biomarkers based on network analysis. According to the KEGG enrichment analysis, the potential biomarkers and gene-encoded proteins were found to be involved in the arginine and proline metabolism, histidine metabolism, and pyrimidine metabolism, which was of significance for the early diagnosis of EC. In particular, the combination of metabolites (histamine, 1-methylhistamine, and methylimidazole acetaldehyde) as well as the combination of RRM2, TYMS and TK1 exerted more accurate discrimination abilities between EC and healthy groups, providing more criteria for the early diagnosis of EC.
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Affiliation(s)
- Yan Fu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China; Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China
| | - Chengzhao Wang
- College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Zhimin Wu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xiaoguang Zhang
- Core Facilities and Centers, Hebei Medical University, Shijiazhuang, 050017, China; College of Basic Medicine, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yan Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Xu Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Fangfang Liu
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yujuan Chen
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China
| | - Yang Zhang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
| | - Huanhuan Zhao
- Department of Obstetrics and Gynecology, The Fourth Hospital of Hebei Medical University, 050011, China.
| | - Qiao Wang
- School of Pharmacy, Hebei Medical University, Shijiazhuang, 050017, China.
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Hong Y, Xu H, Liu Y, Zhu S, Tian C, Chen G, Zhu F, Tao L. DDID: a comprehensive resource for visualization and analysis of diet-drug interactions. Brief Bioinform 2024; 25:bbae212. [PMID: 38711369 DOI: 10.1093/bib/bbae212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/01/2024] [Accepted: 04/21/2024] [Indexed: 05/08/2024] Open
Abstract
Diet-drug interactions (DDIs) are pivotal in drug discovery and pharmacovigilance. DDIs can modify the systemic bioavailability/pharmacokinetics of drugs, posing a threat to public health and patient safety. Therefore, it is crucial to establish a platform to reveal the correlation between diets and drugs. Accordingly, we have established a publicly accessible online platform, known as Diet-Drug Interactions Database (DDID, https://bddg.hznu.edu.cn/ddid/), to systematically detail the correlation and corresponding mechanisms of DDIs. The platform comprises 1338 foods/herbs, encompassing flora and fauna, alongside 1516 widely used drugs and 23 950 interaction records. All interactions are meticulously scrutinized and segmented into five categories, thereby resulting in evaluations (positive, negative, no effect, harmful and possible). Besides, cross-linkages between foods/herbs, drugs and other databases are furnished. In conclusion, DDID is a useful resource for comprehending the correlation between foods, herbs and drugs and holds a promise to enhance drug utilization and research on drug combinations.
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Affiliation(s)
- Yanfeng Hong
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Hongquan Xu
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Yuhong Liu
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Sisi Zhu
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Chao Tian
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Gongxing Chen
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
- Innovation Institute for Affiliated Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou 330110, China
| | - Lin Tao
- Key Laboratory of Elemene Class Anti-cancer Chinese Medicines, School of Pharmacy, Hangzhou Normal University, Hangzhou 311121, China
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Liu L, Yang L, Cao S, Gao Z, Yang B, Zhang G, Zhu R, Wu D. CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides. Brief Bioinform 2024; 25:bbae190. [PMID: 38678388 PMCID: PMC11056021 DOI: 10.1093/bib/bbae190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/28/2024] [Accepted: 04/09/2024] [Indexed: 04/30/2024] Open
Abstract
Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development.
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Affiliation(s)
- Lei Liu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Liu Yang
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Suqi Cao
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Zhigang Gao
- Department of General Surgery, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
| | - Bin Yang
- Shanghai Southgene Technology Co., Ltd., Shanghai 201203, China
| | - Guoqing Zhang
- National Genomics Data Center & Bio-Med Big Data Center, Chinese Academy of Sciences Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, P. R. China
| | - Ruixin Zhu
- Department of Gastroenterology, Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200072, P. R. China
| | - Dingfeng Wu
- National Center, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, P. R. China
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Zhou Y, Chen Z, Yang M, Chen F, Yin J, Zhang Y, Zhou X, Sun X, Ni Z, Chen L, Lv Q, Zhu F, Liu S. FERREG: ferroptosis-based regulation of disease occurrence, progression and therapeutic response. Brief Bioinform 2024; 25:bbae223. [PMID: 38742521 PMCID: PMC11091744 DOI: 10.1093/bib/bbae223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/25/2024] [Accepted: 04/21/2024] [Indexed: 05/16/2024] Open
Abstract
Ferroptosis is a non-apoptotic, iron-dependent regulatory form of cell death characterized by the accumulation of intracellular reactive oxygen species. In recent years, a large and growing body of literature has investigated ferroptosis. Since ferroptosis is associated with various physiological activities and regulated by a variety of cellular metabolism and mitochondrial activity, ferroptosis has been closely related to the occurrence and development of many diseases, including cancer, aging, neurodegenerative diseases, ischemia-reperfusion injury and other pathological cell death. The regulation of ferroptosis mainly focuses on three pathways: system Xc-/GPX4 axis, lipid peroxidation and iron metabolism. The genes involved in these processes were divided into driver, suppressor and marker. Importantly, small molecules or drugs that mediate the expression of these genes are often good treatments in the clinic. Herein, a newly developed database, named 'FERREG', is documented to (i) providing the data of ferroptosis-related regulation of diseases occurrence, progression and drug response; (ii) explicitly describing the molecular mechanisms underlying each regulation; and (iii) fully referencing the collected data by cross-linking them to available databases. Collectively, FERREG contains 51 targets, 718 regulators, 445 ferroptosis-related drugs and 158 ferroptosis-related disease responses. FERREG can be accessed at https://idrblab.org/ferreg/.
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Affiliation(s)
- Yuan Zhou
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
| | - Zhen Chen
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Mengjie Yang
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
| | - Fengyun Chen
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
| | - Jiayi Yin
- Department of Clinical Pharmacy, The First Affiliated Hospital, Zhejiang University School of Medicine
| | - Yintao Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xuheng Zhou
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xiuna Sun
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Ziheng Ni
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
| | - Lu Chen
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
| | - Qun Lv
- Department of Respiratory, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 311121, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 330110, China
| | - Shuiping Liu
- Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines, Engineering Laboratory of Development and Application of Traditional Chinese Medicines, Collaborative Innovation Center of Traditional Chinese Medicines of Zhejiang Province, School of Pharmacy, and Department of Respiratory Medicine of Affiliated Hospital, Hangzhou Normal University, Hangzhou, 311121, China
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Zheng T, Zheng Z, Zhou H, Guo Y, Li S. The multifaceted roles of COL4A4 in lung adenocarcinoma: An integrated bioinformatics and experimental study. Comput Biol Med 2024; 170:107896. [PMID: 38217972 DOI: 10.1016/j.compbiomed.2023.107896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 12/03/2023] [Accepted: 12/23/2023] [Indexed: 01/15/2024]
Abstract
BACKGROUND Abnormal expression of collagen IV subunits has been reported in cancers, but the significance is not clear. No study has reported the significance of COL4A4 in lung adenocarcinoma (LUAD). METHODS COL4A4 expression data, single-cell sequencing data and clinical data were downloaded from public databases. A range of bioinformatics and experimental methods were adopted to analyze the association of COL4A4 expression with clinical parameters, tumor microenvironment (TME), drug resistance and immunotherapy response, and to investigate the roles and underlying mechanism of COL4A4 in LUAD. RESULTS COL4A4 is differentially expressed in most of cancers analyzed, being associated with prognosis, tumor stemness, immune checkpoint gene expression and TME parameters. In LUAD, COL4A4 expression is down-regulated and associated with various TME parameters, response to immunotherapy and drug resistance. LUAD patients with lower COL4A4 have worse prognosis. Knockdown of COL4A4 significantly inhibited the expression of cell-cycle associated genes, and the expression and activation of signaling pathways including JAK/STAT3, p38, and ERK pathways, and induced quiescence in LUAD cells. Besides, it significantly induced the expression of a range of bioactive molecule genes that have been shown to have critical roles in TME remodeling and immune regulation. CONCLUSIONS COL4A4 is implicated in the pathogenesis of cancers including LUAD. Its function may be multifaceted. It can modulate the activity of LUAD cells, TME remodeling and tumor stemness, thus affecting the pathological process of LUAD. COL4A4 may be a prognostic molecular marker and a potential therapeutic target.
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Affiliation(s)
- Tiaozhan Zheng
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, Zhuang Autonomous Region, 530021, PR China
| | - Zhiwen Zheng
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, Zhuang Autonomous Region, 530021, PR China
| | - Hanxi Zhou
- Department of Pathology, Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang Province, PR China
| | - Yiqing Guo
- Department of Pathology, Taizhou Hospital, Wenzhou Medical University, Linhai, Zhejiang Province, PR China
| | - Shikang Li
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, Zhuang Autonomous Region, 530021, PR China.
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Rigden DJ, Fernández XM. The 2024 Nucleic Acids Research database issue and the online molecular biology database collection. Nucleic Acids Res 2024; 52:D1-D9. [PMID: 38035367 PMCID: PMC10767945 DOI: 10.1093/nar/gkad1173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 12/02/2023] Open
Abstract
The 2024 Nucleic Acids Research database issue contains 180 papers from across biology and neighbouring disciplines. There are 90 papers reporting on new databases and 83 updates from resources previously published in the Issue. Updates from databases most recently published elsewhere account for a further seven. Nucleic acid databases include the new NAKB for structural information and updates from Genbank, ENA, GEO, Tarbase and JASPAR. The Issue's Breakthrough Article concerns NMPFamsDB for novel prokaryotic protein families and the AlphaFold Protein Structure Database has an important update. Metabolism is covered by updates from Reactome, Wikipathways and Metabolights. Microbes are covered by RefSeq, UNITE, SPIRE and P10K; viruses by ViralZone and PhageScope. Medically-oriented databases include the familiar COSMIC, Drugbank and TTD. Genomics-related resources include Ensembl, UCSC Genome Browser and Monarch. New arrivals cover plant imaging (OPIA and PlantPAD) and crop plants (SoyMD, TCOD and CropGS-Hub). The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Over the last year the NAR online Molecular Biology Database Collection has been updated, reviewing 1060 entries, adding 97 new resources and eliminating 388 discontinued URLs bringing the current total to 1959 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.
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Affiliation(s)
- Daniel J Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Crown Street, Liverpool L69 7ZB, UK
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