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BackgroundThe integrity of data in a clinical trial is essential, but the current data management process is too complex and highly labor-intensive. As a result, clinical trials are prone to consuming a lot of budget and time, and there is a risk for human-induced error and data falsification. Blockchain technology has the potential to address some of these challenges. ObjectiveThe aim of the study was to validate a system that enables the security of medical data in a clinical trial using blockchain technology. MethodsWe have developed a blockchain-based data management system for clinical trials and tested the system through a clinical trial for breast cancer. The project was conducted to demonstrate clinical data management using blockchain technology under the regulatory sandbox enabled by the Japanese Cabinet Office. ResultsWe verified and validated the data in the clinical trial using the validation protocol and tested its resilience to data tampering. The robustness of the system was also proven by survival with zero downtime for clinical data registration during a Amazon Web Services disruption event in the Tokyo region on August 23, 2019. ConclusionsWe show that our system can improve clinical trial data management, enhance trust in the clinical research process, and ease regulator burden. The system will contribute to the sustainability of health care services through the optimization of cost for clinical trials.

BackgroundDigital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. ObjectiveThe aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. MethodsWe developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. ResultsElectronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. ConclusionsBlockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may provide a novel solution that enables both accessibility and data transparency without a third party such as a contract research organization.

The accurate prediction of neurological outcomes in patients with cervical spinal cord injury (SCI) is difficult because of heterogeneity in patient characteristics, treatment strategies, and radiographic findings. Although machine learning algorithms may increase the accuracy of outcome predictions in various fields, limited information is available on their efficacy in the management of SCI. We analyzed data from 165 patients with cervical SCI, and extracted important factors for predicting prognoses. Extreme gradient boosting (XGBoost) as a machine learning model was applied to assess the reliability of a machine learning algorithm to predict neurological outcomes compared with that of conventional methodology, such as a logistic regression or decision tree. We used regularly obtainable data as predictors, such as demographics, magnetic resonance variables, and treatment strategies. Predictive tools, including XGBoost, a logistic regression, and a decision tree, were applied to predict neurological improvements in the functional motor status (ASIA [American Spinal Injury Association] Impairment Scale [AIS] D and E) 6 months after injury. We evaluated predictive performance, including accuracy and the area under the receiver operating characteristic curve (AUC). Regarding predictions of neurological improvements in patients with cervical SCI, XGBoost had the highest accuracy (81.1%), followed by the logistic regression (80.6%) and the decision tree (78.8%). Regarding AUC, the logistic regression showed 0.877, followed by XGBoost (0.867) and the decision tree (0.753). XGBoost reliably predicted neurological alterations in patients with cervical SCI. The utilization of predictive machine learning algorithms may enhance personalized management choices through pre-treatment categorization of patients.

Real-time imaging of single-molecule fluorescence with a zero-mode waveguide (ZMW) was achieved. With modification of the ZMW geometry, the signal-to-background ratio is twice that obtainable with a conventional ZMW. The improved signal-to-background ratio makes it possible to visualize individual binding--release events between chaperonin GroEL and cochaperonin GroES at a concentration of 5 [micro]M. Two rate constants representing two-timer kinetics in the release of GroES from GroEL were measured with the ZMW, and the measurements agreed well with those made with a total internal reflection fluorescence microscopy. These results indicate that the novel ZMW makes feasible the direct observation of protein--protein interaction at an intracellular concentration in real time.

Abstract Background Kleine-Levin syndrome is a rare sleep disorder of unknown etiology. It is characterized by intermittent periods of excessive sleepiness, cognitive disturbances and behavioral abnormalities. Nine cases of familial Kleine-Levin syndrome have been identified, but there are no reported cases describing twins that are affected by the syndrome. Case presentation We report the cases of 16-year-old monozygotic twin boys who both suffered from Kleine-Levin syndrome. In both cases, the onset of the first episode was preceded by an influenza infection. During symptomatic periods they slept for the entire day except for meals and bathroom visits. Actimetry recordings revealed that during symptomatic periods, daily activity was lower than that of asymptomatic periods, on the other hand, activity during the night was significantly higher in symptomatic periods than asymptomatic periods. Polysomnography (PSG) data during symptomatic periods revealed a decrease in sleep efficiency. Human leukocyte antigen (HLA) typing revealed no DQB1*02 loci. They were administered lithium carbonate but the beneficial effect was limited. Conclusions Our observations suggest that Kleine-Levin syndrome may be due to genetic and autoimmune processes, although etiologic relationship to specific HLA type remains controversial.

State‐dependent modulation of sensory systems has been studied in many organisms and is possibly mediated through neuromodulators such as monoamine neurotransmitters. Among these, dopamine is involved in many aspects of animal behaviour, including movement control, attention, motivation and cognition. However, the precise neural mechanism underlying dopaminergic modulation of behaviour induced by sensory stimuli remains poorly understood. Here, we used Drosophila melanogaster to show that dopamine can modulate the optomotor response to moving visual stimuli including noise. The optomotor response is the head‐turning response to moving objects, which is observed in most sight‐reliant animals including mammals and insects. First, the effects of the dopamine system on the optomotor response were investigated in mutant flies deficient in dopamine receptors D1R1 or D1R2, which are involved in the modulation of sleep‐arousal in flies. We examined the optomotor response in D1R1 knockout (D1R1 KO) and D1R2 knockout (D1R2 KO) flies and found that it was not affected in D1R1 KO flies; however, it was significantly reduced in D1R2 KO flies compared with the wild type. Using cell‐type‐specific expression of an RNA interference construct of D1R2, we identified the fan‐shaped body, a part of the central complex, responsible for dopamine‐mediated modulation of the optomotor response. In particular, pontine cells in the fan‐shaped body seemed important in the modulation of the optomotor response, and their neural activity was required for the optomotor response. These results suggest a novel role of the central complex in the modulation of a behaviour based on the processing of sensory stimulations. [ABSTRACT FROM AUTHOR]

The NLRP3 inflammasome is a molecular complex that translates signals from pathogens and tissue damage into inflammatory responses, and plays crucial roles in numerous neurological diseases. Activation of the NLRP3 inflammasome leads to caspase‐1 dependent cleavage of pro‐IL‐1β to form mature IL‐1β. By acting on the P2X7 purinergic receptor, extracellular ATP is one of the major stimuli that activates the NLRP3 inflammasome. Although microglia express multiple purinergic receptors, their roles in inflammasome‐mediated inflammation are largely unknown. We studied the role of the P2Y12 receptor, a metabotropic P2Y receptor enriched in microglia, on inflammation in vitro. Inhibition of the microglial P2Y12 receptor by PSB0739 or siRNA knockdown suppressed IL‐1β release. P2Y12 receptor‐deficient microglia displayed markedly attenuated IL‐1β mRNA expression and release. P2Y12 receptor blockade also suppressed IL‐6 production. Both IL‐1β and IL‐6 responses were augmented by extracellular ADP or ADP‐βS and were abrogated by PSB0739. Mechanistically, ADP‐βS potentiated NF‐κB activation. In addition, ADP altered mitochondrial membrane potential in combination with ATP and increased the number of caspase‐1 positive cells through the P2Y12 receptor. These results elucidate a novel inflammatory mechanism by which extracellular ADP acts on the P2Y12 receptor to activate NF‐κB and the NLRP3 inflammasome to enhance microglial inflammation. [ABSTRACT FROM AUTHOR]