Efficacy and Cost Effectiveness of the Acupuncture Treatment Using a New Skin Stimulus Tool Called M-Test Which Is a Measure Based on Symptoms Accompanied with Body Movements: A Pragmatic RCT Targeting Hemodialysis Patients

M-Test can simultaneously reduce hemodialysis patients' diverse symptoms. Its diagnosis and treatment are based on simple movements that can be performed by anyone and allow determining which meridians have problems by analyzing symptoms accompanied with movement. It also enables to conduct a safe and effective treatment with use of microcorn which is a noninvasive treatment tool. This time we conducted microcorn intervention on hemodialysis patients based on diagnosis of M-Test. As a result, almost all of the dialysis patients' complaints have been relieved while the score of HR-QOL increased. According to our calculation of cost effectiveness, it confirmed that it is very cost-effective

Exophiala dermatitidis infection in non-cystic fibrosis bronchiectasis

SummaryA 54-year-old female presented with an exacerbation of right middle lobe bronchiectasis. A bronchoscopic bronchial washing and repeated trials of sputum culture consistently recovered no other infectious agent except Exophiala dermatitidis. Her illness was improved by administrations of intravenous miconazole and nebulized amphotericin B when sputum cultures yielded no fungi, demonstrating a pathogenic role of the fungi. The present case illustrates E. dermatitidis as a pathogenic agent in non-cystic fibrosis bronchiectasis

Novel Concept of Motor Functional Analysis for Spinal Cord Injury in Adult Mice

In basic research on spinal cord injury (SCI), behavioral evaluation of the SCI animal model is critical. However, it is difficult to accurately evaluate function in the mouse SCI model due to the small size of mice. Although the open-field scoring scale is an outstanding appraisal method, supplementary objective tests are required. Using a compact SCANET system, in which a mouse carries out free movement for 5 min, we developed a novel method to detect locomotor ability. A SCANET system samples the horizontal coordinates of a mouse every 0.1 s, and both the speed and acceleration of its motion are calculated at each moment. It was found that the maximum speed and acceleration of motion over 5 min varied by injury severity. Moreover, these values were significantly correlated with open-field scores. The maximum speed and acceleration of SCI model mice using a SCANET system are objective, easy to obtain, and reproducible for evaluating locomotive function

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

Novel Concept of Motor Functional Analysis for Spinal Cord Injury in Adult Mice

In basic research on spinal cord injury (SCI), behavioral evaluation of the SCI animal model is critical. However, it is difficult to accurately evaluate function in the mouse SCI model due to the small size of mice. Although the open-field scoring scale is an outstanding appraisal method, supplementary objective tests are required. Using a compact SCANET system, in which a mouse carries out free movement for 5 min, we developed a novel method to detect locomotor ability. A SCANET system samples the horizontal coordinates of a mouse every 0.1 s, and both the speed and acceleration of its motion are calculated at each moment. It was found that the maximum speed and acceleration of motion over 5 min varied by injury severity. Moreover, these values were significantly correlated with open-field scores. The maximum speed and acceleration of SCI model mice using a SCANET system are objective, easy to obtain, and reproducible for evaluating locomotive function

A modified application of the luciferase immunoprecipitation systems for detecting antibodies to the G protein-coupled receptors

Background:　When multipass transmembrane molecules are located on the cell surface, there may be interaction with notonly bioactive molecules but also pathogenic molecules in areas protruding outside the cell. In antibody-mediated autoimmunedisorders, it has been found that the autoantibodies occasionally attack membrane molecules on the cell surface, thus causingthe disease such as myasthenia gravis. In such cases, highly sensitive autoantibody detection technology is required for earlydiagnosis. However, autoantibody analysis technology that is specialized for membrane molecules is still under development.Here we demonstrate a novel method for detecting of antibodies against the extracellular portions of multipass transmembranemolecules.Methods:　Antibodies for muscarinic acetylcholine receptor type3 (M3R) were detected with two kinds of luciferase immunoprecipitaionsystems (LIPS), conventional LIPS (cLIPS) and its modified application, termed modified LIPS (mLIPS). In mLIPS, antibodiesagainst extracellular portions of membrane molecules could be preferentially detected.Results:　An antibody to the amino-terminal portion of human M3R was detected with modified LIPS with a high sensitivity. Incontrast, an antibody to the carboxyl-terminal portion was not detected with mLIPS, because it did not interact with intracellularportions of M3R in living cells. We also found antibodies for M3R in a patient serum with Sjogren’s syndrome.Conclusion:　Our technology has a promising future, and we hope that it will be applied in the analysis of antibodies against adiverse range of multipass transmembrane molecules, including GPCRs

Grand Total EEG Score Can Differentiate Parkinson's Disease From Parkinson-Related Disorders

Background: Semi-quantitative electroencephalogram (EEG) analysis is easy to perform and has been used to differentiate dementias, as well as idiopathic and vascular Parkinson's disease.Purpose: To study whether a semi-quantitative EEG analysis can aid in distinguishing idiopathic Parkinson's disease (IPD) from atypical parkinsonian disorders (APDs), and furthermore, whether it can help to distinguish between APDs.Materials and Methods: A comprehensive retrospective review of charts was performed to include patients with parkinsonian disorders who had at least one EEG recording available. A modified grand total EEG (GTE) score evaluating the posterior background activity, and diffuse and focal slow wave activities was used in further analyses.Results: We analyzed data from 76 patients with a final diagnosis of either IPD, probable corticobasal degeneration (CBD), multiple system atrophy (MSA), or progressive supra-nuclear palsy (PSP). IPD patients had the lowest mean GTE score, followed those with CBD or MSA, while PSP patients scored the highest. However, none of these differences were statistically significant. A GTE score of ≤9 distinguished IPD patients from those with APD (p < 0.01) with a sensitivity of 100% and a specificity of 33.3%.Conclusion: The modified GTE score can distinguish patients with IPD from those with CBD, PSP or MSA at a cut-off score of 9 with excellent sensitivity but poor specificity. However, this score is not able to distinguish a particular form of APD from other forms of the disorder