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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.

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This diagnostic tool may lead to the reduction of unnecessary treatments for non-neoplastic lesions.

The CC chemokines may play an important role in the pathogenesis of chronic inflammatory diseases including rheumatoid arthritis, and their effects are thought to be mediated through CCR1 receptors. Several nonpeptide CCR1 receptor antagonists that showed high affinity for human CCR1 receptors have been identified; however, their effectiveness in animal models of inflammatory diseases has been scarcely demonstrated, probably due to species selectivity of the antagonists. To elucidate the pathophysiological role of CCR1 receptors in murine models of disease, we looked for a potent antagonist for both murine and human CCR1 receptors. Screening of our chemical collection for inhibition of (125)I-MIP-1alpha binding to human CCR1 receptors transfected in CHO cells led to the identification of xanthene-9-carboxamide 1a as the lead compound. Derivatization of 1a by quaternarizing the piperidine nitrogen with various alkyl groups and by installing substituents into the xanthene moiety dramatically improved the inhibitory activity against both human and murine CCR1 receptors. As a result, 2q-1 showing IC(50) values of 0.9 and 5.8 nM for human and murine CCR1 receptors, respectively, was discovered. This compound is the first murine CCR1 receptor antagonist and may be a useful tool for clarifying the role of CCR1 receptors in murine models of disease.

A focused library approach identifying novel leads to develop a potent ORL1 antagonist is described. Beginning from a compound identified by random screening, an exploratory library that exhibited a diverse display of pharmacophores was designed. After evaluating ORL1 antagonistic activity, a highly focused library was designed based on 3D-pharmacophore similarity to known actives. A novel D-proline amide class was identified in this library and was found to possess potent ORL1 antagonistic activity.

Deterioration of diabetic nephropathy (DN) is largely determined by the degree of tubulointerstitial changes rather than the extent of histological changes in the glomeruli. Therefore, a tubular marker that accurately reflects tubulointerstitial damage may be an excellent biomarker for early detection or prediction of DN. Liver-type fatty-acid binding protein (L-FABP) is a 14 kDa small molecule that is expressed in the cytoplasm of human proximal tubules. In vivo experimental studies revealed that renal L-FABP gene expression was up-regulated by various stresses that cause tubulointerstitial damage, such as massive proteinuria, hyperglycemia, hypertension, ischemia and toxins, and that urinary excretion of L-FABP was increased. Recent clinical studies of patients with type 1 or type 2 diabetes demonstrated that urinary excretion of L-FABP derived from proximal tubules is a suitable biomarker for predicting and monitoring deterioration of renal function in DN. Moreover, therapeutic interventions with renoprotective effects reduced urinary L-FABP concentrations. Therefore, urinary L-FABP measured using the Human L-FABP ELISA Kit developed by CMIC Co., Ltd. (Tokyo, Japan) was confirmed as a newly established tubular biomarker by the Ministry of Health, Labour and Welfare in Japan in 2010. This review article summarizes the clinical significance of urinary L-FABP in DN.