Prediction of stroke patients’ bedroom-stay duration: machine-learning approach using wearable sensor data

Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for activity outside their bedrooms. To address this issue, it is necessary to record the duration of stroke patients staying in their bedrooms, but it is impractical for medical providers to do this manually during their daily work of providing care. Although an automated approach using wearable devices and access points is more practical, implementing these access points into medical facilities is costly. However, when combined with machine learning, predicting the duration of stroke patients staying in their bedrooms is possible with reduced cost. We assessed using machine learning to estimate bedroom-stay duration using activity data recorded with wearable devices.Method: We recruited 99 stroke hemiparesis inpatients and conducted 343 measurements. Data on electrocardiograms and chest acceleration were measured using a wearable device, and the location name of the access point that detected the signal of the device was recorded. We first investigated the correlation between bedroom-stay duration measured from the access point as the objective variable and activity data measured with a wearable device and demographic information as explanatory variables. To evaluate the duration predictability, we then compared machine-learning models commonly used in medical studies.Results: We conducted 228 measurements that surpassed a 90% data-acquisition rate using Bluetooth Low Energy. Among the explanatory variables, the period spent reclining and sitting/standing were correlated with bedroom-stay duration (Spearman’s rank correlation coefficient (R) of 0.56 and −0.52, p < 0.001). Interestingly, the sum of the motor and cognitive categories of the functional independence measure, clinical indicators of the abilities of stroke patients, lacked correlation. The correlation between the actual bedroom-stay duration and predicted one using machine-learning models resulted in an R of 0.72 and p < 0.001, suggesting the possibility of predicting bedroom-stay duration from activity data and demographics.Conclusion: Wearable devices, coupled with machine learning, can predict the duration of patients staying in their bedrooms. Once trained, the machine-learning model can predict without continuously tracking the actual location, enabling more cost-effective and privacy-centric future measurements

Modification of i-GONAD Suitable for Production of Genome-Edited C57BL/6 Inbred Mouse Strain

Improved genome editing via oviductal nucleic acid delivery (i-GONAD) is a novel method for producing genome-edited mice in the absence of ex vivo handling of zygotes. i-GONAD involves the intraoviductal injection of clustered regularly interspaced short palindromic repeats (CRISPR) ribonucleoproteins via the oviductal wall of pregnant females at 0.7 days post-coitum, followed by in vivo electroporation (EP). Unlike outbred Institute of Cancer Research (ICR) and hybrid mouse strains, genome editing of the most widely used C57BL/6J (B6) strain with i-GONAD has been considered difficult but, recently, setting a constant current of 100 mA upon EP enabled successful i-GONAD in this strain. Unfortunately, the most widely used electroporators employ a constant voltage, and thus we explored conditions allowing the generation of a 100 mA current using two electroporators: NEPA21 (Nepa Gene Co., Ltd.) and GEB15 (BEX Co., Ltd.). When the current and resistance were set to 40 V and 350–400 Ω, respectively, the current was fixed to 100 mA. Another problem in using B6 mice for i-GONAD is the difficulty in obtaining pregnant B6 females consistently because estrous females often fail to be found. A single intraperitoneal injection of low-dose pregnant mare’s serum gonadotrophin (PMSG) led to synchronization of the estrous cycle of these mice. Consequently, approximately 51% of B6 females had plugs upon mating with males 2 days after PMSG administration, which contrasts with the case (≈26%) when B6 females were subjected to natural mating. i-GONAD performed on PMSG-treated pregnant B6 females under conditions of average resistance of 367 Ω and average voltage of 116 mA resulted in the production of pregnant females at a rate of 56% (5/9 mice), from which 23 fetuses were successfully delivered. Nine (39%) of these fetuses exhibited successful genome editing at the target locus

Role of hepcidin upregulation and proteolytic cleavage of ferroportin 1 in hepatitis C virus-induced iron accumulation.

Hepatitis C virus (HCV) is a pathogen characterized not only by its persistent infection leading to the development of cirrhosis and hepatocellular carcinoma (HCC), but also by metabolic disorders such as lipid and iron dysregulation. Elevated iron load is commonly observed in the livers of patients with chronic hepatitis C, and hepatic iron overload is a highly profibrogenic and carcinogenic factor that increases the risk of HCC. However, the underlying mechanisms of elevated iron accumulation in HCV-infected livers remain to be fully elucidated. Here, we observed iron accumulation in cells and liver tissues under HCV infection and in mice expressing viral proteins from recombinant adenoviruses. We established two molecular mechanisms that contribute to increased iron load in cells caused by HCV infection. One is the transcriptional induction of hepcidin, the key hormone for modulating iron homeostasis. The transcription factor cAMP-responsive element-binding protein hepatocyte specific (CREBH), which was activated by HCV infection, not only directly recognizes the hepcidin promoter but also induces bone morphogenetic protein 6 (BMP6) expression, resulting in an activated BMP-SMAD pathway that enhances hepcidin promoter activity. The other is post-translational regulation of the iron-exporting membrane protein ferroportin 1 (FPN1), which is cleaved between residues Cys284 and Ala285 in the intracytoplasmic loop region of the central portion mediated by HCV NS3-4A serine protease. We propose that host transcriptional activation triggered by endoplasmic reticulum stress and FPN1 cleavage by viral protease work in concert to impair iron efflux, leading to iron accumulation in HCV-infected cells