Searchable Blockchain-Based Healthcare Information Exchange System to Enhance Privacy Preserving and Data Usability.

Ensuring the security and usability of electronic health records (EHRs) is important in health information exchange (HIE) systems that handle healthcare records. This study addressed the need to balance privacy preserving and data usability in blockchain-based HIE systems. We propose a searchable blockchain-based HIE system that enhances privacy preserving while improving data usability. The proposed methodology includes users collecting healthcare information (HI) from various Internet of Medical Things (IoMT) devices and compiling this information into EHR blocks for sharing on a blockchain network. This approach allows participants to search and utilize specific health data within the blockchain effectively. The results demonstrate that the proposed system mitigates the issues of traditional HIE systems by providing secure and user-friendly access to EHRs. The proposed searchable blockchain-based HIE system resolves the trade-off dilemma in HIE by achieving a balance between security and the data usability of EHRs.

Distributed Detour Routing Scheme for Link Failure with Minimized Overhead in LEO Satellite Networks.

The mobility of low Earth orbit (LEO) satellites causes the LEO satellite network to experience topology changes. Topology change includes periodic topology change that occurs naturally and unpredictable topology change that occurs due to instability of the inter-satellite link between satellites. Periodic and unpredictable topology change causes frequent topology change, requiring massive communications throughout the network due to frequent route convergence. LEO satellites have limited onboard power because they operate on batteries. The waste of limited satellite onboard resources shortens the lifespan of the satellite, and achieving stable end-to-end transmission is challenging for the network. In this regard, minimizing communication overhead is a fundamental consideration when designing a routing scheme. In this paper, we propose a distributed detour routing scheme with minimal communication overhead. This routing scheme consists of a rapid detour, selective flooding, and link recovery procedures. When a link failure occurs in the network, a rapid detour can detect link failure using only a precalculated routing table. Subsequently, selective flooding searches for the optimal detour point within the minimum hop region and flood to detour point. After link recovery, a procedure is defined to traverse the pre-detour path and switch it back to the original path. The simulation results show that the proposed routing scheme achieves a reduction of communication overhead by 97.6% compared with the n-hop flooding approach.

Monoclonal antibody Y01 prevents tauopathy progression induced by lysine 280-acetylated tau in cell and mouse models.

The spatiotemporal pattern of the spread of pathologically modified tau through brain regions in Alzheimer's disease (AD) can be explained by prion-like cell-to-cell seeding and propagation of misfolded tau aggregates. Hence, to develop targeted therapeutic antibodies, it is important to identify the seeding- and propagation-competent tau species. The hexapeptide 275VQIINK280 of tau is a critical region for tau aggregation, and K280 is acetylated in various tauopathies, including AD. However, the mechanism that links tau acetylated on lysine 280 (tau-acK280) to subsequent progression to neurodegenerative disease remains unclear. Here, we demonstrate that tau-acK280 is critical for tau propagation processes including secretion, aggregation, and seeding. We developed an antibody, Y01, that specifically targets tau-acK280 and solved the crystal structure of Y01 in complex with an acK280 peptide. The structure confirmed that Y01 directly recognizes acK280 and the surrounding residues. Strikingly, upon interaction with acetylated tau aggregates, Y01 prevented tauopathy progression and increased neuronal viability in neuron cultures and in tau-Tg mice through antibody-mediated neutralization and phagocytosis, respectively. Based on our observations that tau-acK280 is a core species involved in seeding and propagation activities, the Y01 antibody that specifically recognizes acK280 represents a promising therapeutic candidate for AD and other neurodegenerative diseases associated with tauopathy.

Derivation of site-specific derived concentration guideline levels at Korea Research Reactor 1 and 2 sites using probabilistic analysis.

The purpose of this study is to apply a probabilistic method to derive the derived concentration guideline levels for decommissioning of Korea Research Reactor 1 and 2. A total of seven parameters were found to be the sensitive parameters of the target nuclides. The DCGLs of Co-60 and H-3 were 0.063 Bq/g and 85.470 Bq/g, respectively. The concentrations of the gamma ray-emitting nuclides in the actual reactor sites were 7.7-215 times lower than the derived DCGLs for gamma ray-emitting nuclides.

Graph Learning-Based Blockchain Phishing Account Detection with a Heterogeneous Transaction Graph.

Recently, cybercrimes that exploit the anonymity of blockchain are increasing. They steal blockchain users' assets, threaten the network's reliability, and destabilize the blockchain network. Therefore, it is necessary to detect blockchain cybercriminal accounts to protect users' assets and sustain the blockchain ecosystem. Many studies have been conducted to detect cybercriminal accounts in the blockchain network. They represented blockchain transaction records as homogeneous transaction graphs that have a multi-edge. They also adopted graph learning algorithms to analyze transaction graphs. However, most graph learning algorithms are not efficient in multi-edge graphs, and homogeneous graphs ignore the heterogeneity of the blockchain network. In this paper, we propose a novel heterogeneous graph structure called an account-transaction graph, ATGraph. ATGraph represents a multi-edge as single edges by considering transactions as nodes. It allows graph learning more efficiently by eliminating multi-edges. Moreover, we compare the performance of ATGraph with homogeneous transaction graphs in various graph learning algorithms. The experimental results demonstrate that the detection performance using ATGraph as input outperforms that using homogeneous graphs as the input by up to 0.2 AUROC.

Privacy Preservation in Patient Information Exchange Systems Based on Blockchain: System Design Study.

BACKGROUND: With the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required. OBJECTIVE: Our goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients' privacy in the EMRs through a medical information exchange process that includes data encryption and access control. METHODS: We propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient's EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework. RESULTS: We performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system's performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption-based data encryption method can effectively protect users' EMRs from forgery and privacy leak threats and provide data integrity. CONCLUSIONS: Blockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.

TLQP-21 mediated activation of microglial BV2 cells promotes clearance of extracellular fibril amyloid-ß.

ß-Amyloid (Aß) plaque in the brains of patients with Alzheimer's disease (AD) is mainly caused by impaired clearance of Aß by glial cells, including microglia and astrocytes. Because microglia play an important protective role in the central nervous system, many efforts have been made to identify agents that effectively improve microglial Aß phagocytosis. This study found that TLQP-21, which is cleaved from VGF (VGF nerve growth factor inducible) precursor protein, enhanced Aß phagocytosis and degradation by microglial BV2 cells. TLQP-21 also improved microglial phagocytic activity and promoted fibrillar amyloid-ß (fAß) uptake by microglial BV2 cells via a C3AR1-dependent mechanism. Moreover, TLQP-21 stimulated Aß degradation by enhancing lysosome activity, thereby enhancing fAß clearance. These results suggest that treatment with TLQP-21 may be a novel therapeutic strategy to efficiently enhance microglial Aß clearance in AD.

Predictors of abnormal brain computed tomography findings in patients with acute altered mental status in the emergency department.

OBJECTIVE: Brain computed tomography (CT) is commonly performed to diagnose acute altered mental status (AMS), a critically important symptom in many serious diseases. However, negative CT results are common, which result in unnecessary CT use. Therefore, this study aimed to determine the clinical factors associated with positive CT findings. METHODS: Patients with acute AMS selected from an emergency department-based registry were retrospectively evaluated. Patients with non-traumatic and noncommunicable diseases on initial presentation and with Glasgow Comal Scale scores of <15 were included in the study. RESULTS: Among the 367 brain CT results of patients with AMS during the study period, 146 (39.8%) were positive. In a multivariate analysis, the presence of focal neurologic deficit (odds ratio [OR], 132.6; 95% confidence interval [CI], 37.8 to 464.6), C-reactive protein level <2 mg/dL (OR, 3.9; 95% CI, 1.4 to 10.6), and Glasgow Comal Scale score <9 (OR, 2.4; 95% CI, 1.2 to 4.8) were significantly associated with positive brain CT results. CONCLUSION: The presence of focal neurologic deficit, initial Glasgow Comal Scale score of <9, and initial C-reactive protein levels of <2 mg/dL can facilitate the selection of brain CT to diagnose patients with acute AMS in the emergency department.