Hitachi Maxell (Japan)

This study aimed to estimate the relationship between finger function and cognitive function in patients with Alzheimer's disease (AD). Patients diagnosed with AD at the Outpatient Center for Comprehensive Care and Research on Memory Disorder of the National Center for Geriatrics and Gerontology underwent a 15-s bimanual alternating tapping task to measure finger movements. After finger movement measurements, we classified the severity of AD into mild and moderate and compared the finger movements. The Mann-Whitney U test and effect size were used to compare parameter values between the two groups (mild and moderate AD), and the calculated p values were corrected using the Bonferroni method. The Spearman rank correlation coefficient was calculated to determine the association between finger parameters and cognitive function (Mini-Mental Examination [MMSE]). Data from 163 patients with AD were analyzed. When comparing finger parameters between the mild AD (64 individuals) and moderate AD (99 individuals) groups, the moderate AD group demonstrated fewer taps (p = 0.005; r = 0.22) and a longer interval between taps with the thumb and index finger (p = 0.007; r = 0.21) than the mild AD group. The correlation between the MMSE score and finger function was weakly positive for the number of taps and weakly negative for the average of tapping interval. These parameters reflect the decline in finger function associated with the advanced stages of dementia and may help assess the severity of AD. Additionally, these findings may have clinical utility in assessing the severity of AD, potentially enhancing diagnostic accuracy for differentiating stages of AD.

All-solid-state lithium-ion batteries (LIBs), which have overwhelmingly higher thermal stability and longer calendar life compared to liquid-based LiBs, are suitable for environments where conventional liquid-based LIBs cannot be used, leading to dramatically expand their applications. In all-solid-state LIBs, sulfide-type solid electrolytes have been most extensively examined owing to their excellent conductivity and flexibility. Although applying the solid electrolytes enables to stable operation of the batteries even at 100oC, capacity moderately decreases during cycling under such severe conditions.This study examines high-temperature long-term cycle tests of all-solid-state Li[Li1/3Ti5/3]O4/LiCoO2 (LTO/LCO) batteries in order to clarify the origin of capacity fading at high temperature. For cycle tests, a three-electrode cell (MX-3E-5T-CWS, Tomcell, Japan) were used to monitor state-of-charges (SOCs) of LCO positive and LTO negative electrodes during cycling, because the imbalance of SOCs of the electrodes causes capacity fading even without material deterioration. All-solid LIBs used in this study were consisted of LTO negative and LCO positive electrodes, and argyrodite-type solid electrolyte (Li7-xPS6-xClx). The LTO and LCO electrodes were consisted of LTO:SE = 65:35 wt% and LCO:SE:AB = 73:26:1 wt%, respectively. The size of the electrodes was the same (9 mm diameter and 0.85 mm 9 thickness) and electrode weight was 0.10 g for LTO and 0.15 g for LCO electrodes. Li metal placed on the solid electrolyte was used as the reference electrode.Fig. (a) shows charge-discharge curves of the LTO/LCO cell before and after the cycle test. After cycling, the charge-discharge curves of both the LCO and LTO electrodes shifted to the right (higher capacity side), and the capacity decreased by the difference in the amount of shift between the two electrodes. This means that the capacity fading of the all-solid-state battery is caused by the imbalance of SOCs between LCO positive and LTO negative electrode, which is essentially the same capacity fading mechanism as that of liquid-based LIBs.To quantitatively analyze the SOC imbalance, side reaction current at both electrodes were estimated from a cumulative capacity plot (Fig. b). In the figure, the derivative of cumulative capacity at the end of charge and discharge corresponds to the side reaction current at LTO negative and LCO positive electrodes, respectively. As can be seen in Fig. (b), larger side reaction current at LCO than LTO electrodes indicates SE decomposition at LCO is faster than that at LTO. The capacity fading mechanism due to side reactions in all-solid-state LTO/LCO batteries is schematically illustrated in Fig. (c). Because of the formation of a local cell at each electrode consisting of Li insertion and side reactions, the current due to the Li insertion reaction, namely current efficiency differs between the electrodes. The difference in current efficiency between LTO and LCO electrodes induces the deviation of the SOC balance between the electrodes, resulting in a capacity fading of the battery without deterioration of active materials.From the above results, we will discuss the quantitative prediction of the lifetime for all-solid-state batteries based on the mass balance in the cell. Figure 1

BackgroundAging is the most significant risk factor for dementia. Alzheimer’s disease (AD) accounts for approximately 60–80% of all dementia cases in older adults. This study aimed to examine the relationship between finger movements and brain volume in AD patients using a voxel-based reginal analysis system for Alzheimer’s disease (VSRAD) software.MethodsPatients diagnosed with AD at the Center for Comprehensive Care and Research on Memory Disorders were included. The diagnostic criteria were based on the National Institute on Aging-Alzheimer’s Association. A finger-tapping device was used for all measurements. Participants performed the tasks in the following order: with their non-dominant hand, dominant hand, both hands simultaneously, and alternate hands. Movements were measured for 15 s each. The relationship between distance and output was measured. Magnetic resonance imaging measurements were performed, and VSRAD was conducted using sagittal section 3D T1-weighted images. The Z-score was used to calculate the severity of medial temporal lobe atrophy. Pearson’s product-moment correlation coefficient analyzed the relationship between the severity of medial temporal lobe atrophy and mean values of the parameters in the finger-tapping movements. The statistical significance level was set at <5%. The calculated p-values were corrected using the Bonferroni method.ResultsSixty-two patients were included in the study. Comparison between VSRAD and MoCA-J scores corrected for p-values showed a significant negative correlation with the extent of gray matter atrophy (r = -0. 52; p< 0.001). A positive correlation was observed between the severity of medial temporal lobe atrophy and standard deviation (SD) of the distance rate of velocity peak in extending movements in the non-dominant hand (r = 0. 51; p< 0.001).ConclusionsThe SD of distance rate of velocity peak in extending movements extracted from finger taps may be a useful parameter for the early detection of AD and diagnosis of its severity.

Abstract BackgroundAging is the most significant risk factor of dementia. Alzheimer’s disease accounts for approximately 60%–80% of all dementia cases in elderly individuals. This study aimed to examine the relationship between finger movements and brain function in patients with Alzheimer’s disease, using VSRAD, and explore the relationship between VSRAD and cognitive function (MoCA-J).MethodsPatients diagnosed with AD, at the Center for Comprehensive Care and Research on Memory Disorders, were included in the study. The diagnostic criteria were based on the National Institute on Aging-Alzheimer’s Association. Patients were excluded based on set criteria. A finger-tapping device was used for all measurements. Participants performed the following task, in order: non-dominant hand, dominant hand, simultaneously, and alternate hands. Movements were measured for 15 s each. The relationship between distance and output was measured. MRI measurements were performed, after which VSRAD was performed using sagittal section 3D T1-weighted images. The Z-score was used to calculate the degree of atrophy. Pearson’s product-moment correlation coefficient was used to analyze the relationship between the Z-score and mean values of the parameters in the finger-tapping movements. Statistical significance was set at p &lt; 0.05.ResultsSixty-two patients were included in the study. Z-scores for MoCA-J analysis, percentage of total brain atrophy in the white matter, and other VSRAD parameters showed varying negative correlations (r = -0. 28, p = 0. 035, r = -0. 31, p = 0. 020, and r = -0. 52, p &lt; 0. 001), respectively. Varying positive correlations between Z-score and the SD of distance rate of velocity peak in extending movements in the non-dominant hand were observed.ConclusionThe SD of distance rate of velocity peak in extending movements and the Z-score showed a significant relationship. An association between neuropsychological tests and overall degree of brain atrophy was also observed.

Abstract Trail making test (TMT) is one of the most extensively used neuropsychological tests. In this study, we examined the equivalence between the iPad version of TMT part A (iTMT-A) and the paper version of TMT part A (pTMT-A), and predicted the cognitive function with various data extracted from repeated TMT-A. Forty-two patients who performed five repeated TMT-A (1st–3rd: iTMT-A, 4th: pTMT-A, 5th: inverse version of iTMT-A) and Mini-Mental State Examination (MMSE) were included. The Kruskal–Wallis one-way analysis of variance revealed no statistical differences between the completion times of iTMT-A and pTMT-A. Factors contributing to the MMSE prediction were selected by stepwise multiple regression analysis and Bland–Altman plots. Then, the prediction abilities of the three models—multiple linear, partial least squares (PLS), and neural network regression—were compared. When using the completion time, the linear regression model with the 1st–5th results exhibited the highest prediction ability. However, when the move time and dwell time were used, the multiple linear and PLS regression models using the 1st and 2nd iTMT-A data exhibited the highest prediction ability. Compared with pTMT-A, iTMT-A extracted a large amount of data with fewer repetitions, and the prediction accuracy of cognitive function was improved.

Polylactic acid (PLA) is expected to replace many general-purpose plastics, especially those used for food packaging and agricultural mulch. In composting, the degradation speed of PLA is affected by the molecular weight, crystallinity, and microbial activity. PLA with a molecular weight of less than 10,000 has been reported to have higher decomposition rates than those with higher molecular weight. However, PLA degradation generates water-soluble products, including lactic acid, that decrease the pH of soil or compost. As acidification of soil or compost affects farm products, their pH should be controlled. Therefore, a method for determining suitable reaction conditions to achieve ideal decomposition products is necessary. This study aimed to determine suitable reaction conditions for generating preprocessed PLA with a molecular weight lower than 10,000 without producing water-soluble contents. To this end, we investigated the degradation of PLA using sub-critical water. The molecular weight and ratio of water-soluble contents (WSCs) affecting the pH of preprocessed products were evaluated through kinetic analysis, and crystallinity was analyzed through differential scanning calorimetry. Preprocessed PLA was prepared under the determined ideal conditions, and its characteristics in soil were observed. The results showed that the crystallization rate increased with PLA decomposition but remained lower than 30%. In addition, the pH of compost mixed with 40% of preprocessed PLA could be controlled within pH 5.4–5.5 over 90 days. Overall, soil mixed with the preprocessed PLA prepared under the determined ideal conditions remains suitable for plant growth.

We have developed a finger-tapping device with magnetic sensors, UB2, for the early detection of dementia. The goal of the present study is to develop a method for detecting abnormal segments in the finger tapping waveform in an objective way using machine learning and to evaluate the method in comparison with a human visual assessment. Fifteen-second right-hand finger tapping waveforms of 228 healthy volunteers were measured and cut into one-cycle taps. Fifteen features representing the properties of the one-cycle taps were extracted. As a result of applying a one-class support vector machine (SVM) with an outlier rate of 0.08, 1032 one-cycle taps (8.0%) were detected as abnormal among all 12,898 one-cycle taps. Among these abnormal ones, the features including many outliers (>30%) were the instances of freezing (small fluctuations) and the tap interval. These features correspond to those of which distribution were markedly biased. The visual assessment was likely to overestimate abnormality concerning the instances of freezing and the tap interval (>10%) and conversely underestimate abnormality concerning amplitude of distance/velocity or motion quantity (<; -10%).