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Wang N, Wang X, Liu A, Wang W, Ding Y, Wu X, Du X. An image partition security-sharing mechanism based on blockchain and chaotic encryption. PLoS One 2024; 19:e0307686. [PMID: 39078999 PMCID: PMC11285975 DOI: 10.1371/journal.pone.0307686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 07/09/2024] [Indexed: 08/02/2024] Open
Abstract
To ensure optimal use of images while preserving privacy, it is necessary to partition the shared image into public and private areas, with public areas being openly accessible and private areas being shared in a controlled and privacy-preserving manner. Current works only facilitate image-level sharing and use common cryptographic algorithms. To ensure efficient, controlled, and privacy-preserving image sharing at the area level, this paper proposes an image partition security-sharing mechanism based on blockchain and chaotic encryption, which mainly includes a fine-grained access control method based on Attribute-Based Access Control (ABAC) and an image-specific chaotic encryption scheme. The proposed fine-grained access control method employs smart contracts based on the ABAC model to achieve automatic access control for private areas. It employs a Cuckoo filter-based transaction retrieval technique to enhance the efficiency of smart contracts in retrieving security attributes and policies on the blockchain. The proposed chaotic encryption scheme generates keys based on the private areas' security attributes, largely reducing the number of keys required. It also provides efficient encryption with vector operation acceleration. The security analysis and performance evaluation were conducted comprehensively. The results show that the proposed mechanism has lower time overhead than current works as the number of images increases.
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Affiliation(s)
- Na Wang
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Xiaochang Wang
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Aodi Liu
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Wenjuan Wang
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Yan Ding
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Xiangyu Wu
- PLA Information Engineering University, Zhengzhou, Henan, China
| | - Xuehui Du
- PLA Information Engineering University, Zhengzhou, Henan, China
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2
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Adanur Dedeturk B, Bakir-Gungor B. Aguhyper: a hyperledger-based electronic health record management framework. PeerJ Comput Sci 2024; 10:e2060. [PMID: 38855255 PMCID: PMC11157618 DOI: 10.7717/peerj-cs.2060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 04/25/2024] [Indexed: 06/11/2024]
Abstract
The increasing importance of healthcare records, particularly given the emergence of new diseases, emphasizes the need for secure electronic storage and dissemination. With these records dispersed across diverse healthcare entities, their physical maintenance proves to be excessively time-consuming. The prevalent management of electronic healthcare records (EHRs) presents inherent security vulnerabilities, including susceptibility to attacks and potential breaches orchestrated by malicious actors. To tackle these challenges, this article introduces AguHyper, a secure storage and sharing solution for EHRs built on a permissioned blockchain framework. AguHyper utilizes Hyperledger Fabric and the InterPlanetary Distributed File System (IPFS). Hyperledger Fabric establishes the blockchain network, while IPFS manages the off-chain storage of encrypted data, with hash values securely stored within the blockchain. Focusing on security, privacy, scalability, and data integrity, AguHyper's decentralized architecture eliminates single points of failure and ensures transparency for all network participants. The study develops a prototype to address gaps identified in prior research, providing insights into blockchain technology applications in healthcare. Detailed analyses of system architecture, AguHyper's implementation configurations, and performance assessments with diverse datasets are provided. The experimental setup incorporates CouchDB and the Raft consensus mechanism, enabling a thorough comparison of system performance against existing studies in terms of throughput and latency. This contributes significantly to a comprehensive evaluation of the proposed solution and offers a unique perspective on existing literature in the field.
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Affiliation(s)
| | - Burcu Bakir-Gungor
- Department of Computer Engineering, Abdullah Gul University, Kayseri, Turkey
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3
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Mutambik I, Lee J, Almuqrin A, Alharbi ZH. Identifying the Barriers to Acceptance of Blockchain-Based Patient-Centric Data Management Systems in Healthcare. Healthcare (Basel) 2024; 12:345. [PMID: 38338229 PMCID: PMC10855174 DOI: 10.3390/healthcare12030345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 01/19/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
A number of recent studies have shown that wastage and inefficiency are a significant problem in all global healthcare systems. One initiative that could radically improve the operational efficiency of health systems is to make a paradigm shift in data ownership-that is, to transition such systems to a patient-centric model of data management by deploying blockchain technology. Such a development would not only make an economic impact, by radically cutting wastage, but would deliver significant social benefits by improving patient outcomes and satisfaction. However, a blockchain-based solution presents considerable challenges. This research seeks to understand the principal factors, which act as barriers to the acceptance of a blockchain-based patient-centric data management infrastructure, in the healthcare systems of the GCC (Gulf Cooperation Council) countries. The study represents an addition to the current literature by examining the perspectives and views of healthcare professionals and users. This approach is rare within this subject area, and is identified in existing systematic reviews as a research gap: a qualitative investigation of motivations and attitudes among these groups is a critical need. The results of the study identified 12 key barriers to the acceptance of blockchain infrastructures, thereby adding to our understanding of the challenges that need to be overcome in order to benefit from this relatively recent technology. The research is expected to be of use to healthcare authorities in planning a way forward for system improvement, particularly in terms of successfully introducing patient-centric systems.
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Affiliation(s)
- Ibrahim Mutambik
- Department of Information Science, College of Humanities and Social Sciences, King Saud University, P.O. Box 11451, Riyadh 11437, Saudi Arabia;
| | - John Lee
- School of Informatics, The University of Edinburgh, 10 Crichton St., Edinburgh EH8 9AB, UK;
| | - Abdullah Almuqrin
- Department of Information Science, College of Humanities and Social Sciences, King Saud University, P.O. Box 11451, Riyadh 11437, Saudi Arabia;
| | - Zahyah H. Alharbi
- Department of Management Information Systems, College of Business Administration, King Saud University, P.O. Box 28095, Riyadh 11437, Saudi Arabia;
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4
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Mohsan SAH, Razzaq A, Ghayyur SAK, Alkahtani HK, Al-Kahtani N, Mostafa SM. Decentralized Patient-Centric Report and Medical Image Management System Based on Blockchain Technology and the Inter-Planetary File System. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14641. [PMID: 36429351 PMCID: PMC9690269 DOI: 10.3390/ijerph192214641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/22/2022] [Accepted: 11/03/2022] [Indexed: 06/16/2023]
Abstract
Several academicians have been actively contributing to establishing a practical solution to storing and distributing medical images and test reports in the research domain of health care in recent years. Current procedures mainly rely on cloud-assisted centralized data centers, which raise maintenance expenditure, necessitate a large amount of storage space, and raise privacy concerns when exchanging data across a network. As a result, it is critically essential to provide a framework that allows for the efficient exchange and storage of large amounts of medical data in a secure setting. In this research, we describe a unique proof-of-concept architecture for a distributed patient-centric test report and image management (PCRIM) system that aims to facilitate patient privacy and control without the need for a centralized infrastructure. We used an Ethereum blockchain and a distributed file system technology called the Inter-Planetary File System in this system (IPFS). Then, to secure a distributed and trustworthy access control policy, we designed an Ethereum smart contract termed the patient-centric access control protocol. The IPFS allows for the decentralized storage of medical metadata, such as images, with worldwide accessibility. We demonstrate how the PCRIM system design enables hospitals, patients, and image requestors to obtain patient-centric data in a distributed and secure manner. Finally, we tested the proposed framework in the Windows environment by deploying a smart contract prototype on an Ethereum TESTNET blockchain. The findings of the study indicate that the proposed strategy is both efficient and practicable.
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Affiliation(s)
| | - Abdul Razzaq
- Ocean College, Zhejiang University, Zheda Road 1, Zhoushan 316021, China
| | - Shahbaz Ahmed Khan Ghayyur
- Department of Computer Science and Software Engineering, International Islamic University, Islamabad 44000, Pakistan
| | - Hend Khalid Alkahtani
- Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
| | - Nouf Al-Kahtani
- Department of Health Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia
| | - Samih M. Mostafa
- Department of Computer Science, Faculty of Computers and Information, South Valley University, Qena 83523, Egypt
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Blockchain Traceability System in Complex Application Scenarios: Image-Based Interactive Traceability Structure. SYSTEMS 2022. [DOI: 10.3390/systems10030078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
To solve the problems exposed by the application of blockchain technology under complex scenarios, such as fraudulent use of data, hard to store huge amounts of data, and low traceability efficiency under an ultra-huge number of traceability requests, this paper constructs an image-based interactive traceability structure by using images as an enhancement. By adding pointers to raw image files, a specific file structure is formed for traceability, and the traceability process is separated from the verification process, therefore realizing the distributed traceability of “traceability off the chain and verification on the chain”. The experimental results show that, compared with the traditional blockchain traceability mode, the interactive traceability structure can reduce the data retrieval pressure and greatly improve the traceability efficiency of a specific transaction chain. With the growth of the span of the transaction chain, the traceability efficiency advantage of the interactive traceability structure becomes more obvious.
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A Novel Blockchain-Based Healthcare System Design and Performance Benchmarking on a Multi-Hosted Testbed. SENSORS 2022; 22:s22093449. [PMID: 35591142 PMCID: PMC9103768 DOI: 10.3390/s22093449] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/20/2022] [Accepted: 04/26/2022] [Indexed: 12/10/2022]
Abstract
As a result of the proliferation of digital and network technologies in all facets of modern society, including the healthcare systems, the widespread adoption of Electronic Healthcare Records (EHRs) has become the norm. At the same time, Blockchain has been widely accepted as a potent solution for addressing security issues in any untrusted, distributed, decentralized application and has thus seen a slew of works on Blockchain-enabled EHRs. However, most such prototypes ignore the performance aspects of proposed designs. In this paper, a prototype for a Blockchain-based EHR has been presented that employs smart contracts with Hyperledger Fabric 2.0, which also provides a unified performance analysis with Hyperledger Caliper 0.4.2. The additional contribution of this paper lies in the use of a multi-hosted testbed for the performance analysis in addition to far more realistic Gossip-based traffic scenario analysis with Tcpdump tools. Moreover, the prototype is tested for performance with superior transaction ordering schemes such as Kafka and RAFT, unlike other literature that mostly uses SOLO for the purpose, which accounts for superior fault tolerance. All of these additional unique features make the performance evaluation presented herein much more realistic and hence adds hugely to the credibility of the results obtained. The proposed framework within the multi-host instances continues to behave more successfully with high throughput, low latency, and low utilization of resources for opening, querying, and transferring transactions into a healthcare Blockchain network. The results obtained in various rounds of evaluation demonstrate the superiority of the proposed framework.
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Doran SJ, Al Sa’d M, Petts JA, Darcy J, Alpert K, Cho W, Sanchez LE, Alle S, El Harouni A, Genereaux B, Ziegler E, Harris GJ, Aboagye EO, Sala E, Koh DM, Marcus D. Integrating the OHIF Viewer into XNAT: Achievements, Challenges and Prospects for Quantitative Imaging Studies. Tomography 2022; 8:497-512. [PMID: 35202205 PMCID: PMC8875191 DOI: 10.3390/tomography8010040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/03/2022] [Accepted: 02/05/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose: XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and methods: The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included: ROI creation and editing tools for both contour- and mask-based regions; a "smart CT" paintbrush tool; the integration of NVIDIA's Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time. Results: Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has been downloaded more than 3700 times during the course of the development work reported here, demonstrating the impact of the work. Conclusions: The OHIF open-source, zero-footprint web viewer has been incorporated into the XNAT platform and is now used at many institutions worldwide. Further innovations are envisaged in the near future.
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Affiliation(s)
- Simon J. Doran
- Division of Radiotherapy and Imaging, Institute of Cancer Research, 15 Cotswold Rd, London SM2 5NG, UK;
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
| | - Mohammad Al Sa’d
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
- Cancer Imaging Centre, Department of Surgery & Cancer, Imperial College, London SW7 2AZ, UK
| | - James A. Petts
- Ovela Solutions Ltd., 20-22 Wenlock Road, London N1 7GU, UK;
| | - James Darcy
- Division of Radiotherapy and Imaging, Institute of Cancer Research, 15 Cotswold Rd, London SM2 5NG, UK;
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
| | - Kate Alpert
- Flywheel LLC, 1015 Glenwood Ave, Suite 300, Minneapolis, MN 55405, USA; (K.A.); (D.M.)
| | - Woonchan Cho
- Neuroimaging Informatics Analysis Center, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA;
| | - Lorena Escudero Sanchez
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
- Department of Radiology, University of Cambridge, Hills Rd, Cambridge CB2 0QQ, UK
- Cancer Research UK Cambridge Centre, University of Cambridge Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK
| | - Sachidanand Alle
- NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA; (S.A.); (A.E.H.); (B.G.)
| | - Ahmed El Harouni
- NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA; (S.A.); (A.E.H.); (B.G.)
| | - Brad Genereaux
- NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA; (S.A.); (A.E.H.); (B.G.)
| | - Erik Ziegler
- Open Health Imaging Foundation, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114, USA; (E.Z.); (G.J.H.)
- Radical Imaging LLC, 188 Annie Moore Rd, Bolton, MA 01740-1140, USA
| | - Gordon J. Harris
- Open Health Imaging Foundation, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114, USA; (E.Z.); (G.J.H.)
- Department of Radiology, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114, USA
- Harvard Medical School, 25 Shattuck St., Boston, MA 02115, USA
| | - Eric O. Aboagye
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
- Cancer Imaging Centre, Department of Surgery & Cancer, Imperial College, London SW7 2AZ, UK
| | - Evis Sala
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
- Department of Radiology, University of Cambridge, Hills Rd, Cambridge CB2 0QQ, UK
- Cancer Research UK Cambridge Centre, University of Cambridge Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK
| | - Dow-Mu Koh
- CRUK National Cancer Imaging Translational Accelerator, UK; (M.A.S.); (L.E.S.); (E.O.A.); (E.S.); (D.-M.K.)
- Department of Radiology, Royal Marsden Hospital, Downs Rd, Sutton SM2 5PT, UK
| | - Dan Marcus
- Flywheel LLC, 1015 Glenwood Ave, Suite 300, Minneapolis, MN 55405, USA; (K.A.); (D.M.)
- Neuroimaging Informatics Analysis Center, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA;
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SVBE: searchable and verifiable blockchain-based electronic medical records system. Sci Rep 2022; 12:266. [PMID: 34997109 PMCID: PMC8741810 DOI: 10.1038/s41598-021-04124-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/14/2021] [Indexed: 11/29/2022] Open
Abstract
Central management of electronic medical systems faces a major challenge because it requires trust in a single entity that cannot effectively protect files from unauthorized access or attacks. This challenge makes it difficult to provide some services in central electronic medical systems, such as file search and verification, although they are needed. This gap motivated us to develop a system based on blockchain that has several characteristics: decentralization, security, anonymity, immutability, and tamper-proof. The proposed system provides several services: storage, verification, and search. The system consists of a smart contract that connects to a decentralized user application through which users can transact with the system. In addition, the system uses an interplanetary file system (IPFS) and cloud computing to store patients’ data and files. Experimental results and system security analysis show that the system performs search and verification tasks securely and quickly through the network.
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Jabarulla MY, Lee HN. A Blockchain and Artificial Intelligence-Based, Patient-Centric Healthcare System for Combating the COVID-19 Pandemic: Opportunities and Applications. Healthcare (Basel) 2021; 9:1019. [PMID: 34442156 PMCID: PMC8391524 DOI: 10.3390/healthcare9081019] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/16/2021] [Accepted: 07/28/2021] [Indexed: 12/30/2022] Open
Abstract
The world is facing multiple healthcare challenges because of the emergence of the COVID-19 (coronavirus) pandemic. The pandemic has exposed the limitations of handling public healthcare emergencies using existing digital healthcare technologies. Thus, the COVID-19 situation has forced research institutes and countries to rethink healthcare delivery solutions to ensure continuity of services while people stay at home and practice social distancing. Recently, several researchers have focused on disruptive technologies, such as blockchain and artificial intelligence (AI), to improve the digital healthcare workflow during COVID-19. Blockchain could combat pandemics by enabling decentralized healthcare data sharing, protecting users' privacy, providing data empowerment, and ensuring reliable data management during outbreak tracking. In addition, AI provides intelligent computer-aided solutions by analyzing a patient's medical images and symptoms caused by coronavirus for efficient treatments, future outbreak prediction, and drug manufacturing. Integrating both blockchain and AI could transform the existing healthcare ecosystem by democratizing and optimizing clinical workflows. In this article, we begin with an overview of digital healthcare services and problems that have arisen during the COVID-19 pandemic. Next, we conceptually propose a decentralized, patient-centric healthcare framework based on blockchain and AI to mitigate COVID-19 challenges. Then, we explore the significant applications of integrated blockchain and AI technologies to augment existing public healthcare strategies for tackling COVID-19. Finally, we highlight the challenges and implications for future research within a patient-centric paradigm.
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Affiliation(s)
| | - Heung-No Lee
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea;
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