Balance Measures Derived from Insole Sensor Differentiate Prodromal Dementia with Lewy Bodies

Dementia with Lewy bodies is the second most common type of neurodegenerative dementia, and identification at the prodromal stage$-$i.e., mild cognitive impairment due to Lewy bodies (MCI-LB)$-$is important for providing appropriate care. However, MCI-LB is often underrecognized because of its diversity in clinical manifestations and similarities with other conditions such as mild cognitive impairment due to Alzheimer's disease (MCI-AD). In this study, we propose a machine learning-based automatic pipeline that helps identify MCI-LB by exploiting balance measures acquired with an insole sensor during a 30-s standing task. An experiment with 98 participants (14 MCI-LB, 38 MCI-AD, 46 cognitively normal) showed that the resultant models could discriminate MCI-LB from the other groups with up to 78.0% accuracy (AUC: 0.681), which was 6.8% better than the accuracy of a reference model based on demographic and clinical neuropsychological measures. Our findings may open up a new approach for timely identification of MCI-LB, enabling better care for patients

MRI-based Brain Healthcare Quotients: A bridge between neural and behavioral analyses for keeping the brain healthy

Neurological and psychiatric disorders are a burden on social and economic resources. Therefore, maintaining brain health and preventing these disorders are important. While the physiological functions of the brain are well studied, few studies have focused on keeping the brain healthy from a neuroscientific viewpoint. We propose a magnetic resonance imaging (MRI)-based quotient for monitoring brain health, the Brain Healthcare Quotient (BHQ), which is based on the volume of gray matter (GM) and the fractional anisotropy (FA) of white matter (WM). We recruited 144 healthy adults to acquire structural neuroimaging data, including T1-weighted images and diffusion tensor images, and data associated with both physical (BMI, blood pressure, and daily time use) and social (subjective socioeconomic status, subjective well-being, post-materialism and Epicureanism) factors. We confirmed that the BHQ was sensitive to an age-related decline in GM volume and WM integrity. Further analysis revealed that the BHQ was critically affected by both physical and social factors. We believe that our BHQ is a simple yet highly sensitive, valid measure for brain health research that will bridge the needs of the scientific community and society and help us lead better lives in which we stay healthy, active, and sharp

Association of Fatigue and Stress With Gray Matter Volume

Stress is associated with a greater risk for various health problems including reduced gray matter volume (GMV) and density in a number of brain regions. Previous studies show that neuroimaging could be a means to objectively evaluate stress. However, to date, no definite neuroimaging-derived measures are available to detect stress. In this research we used the gray-matter brain healthcare quotient (GM-BHQ), an MRI-based quotient for monitoring brain health based on GMV, as an objective scale to measure the association of stress with the whole brain. We recruited 63 healthy adults to acquire structural T1-weighted images and stress levels evaluated using three representative stress scales: the Profile of Mood States (POMS), Perceived Stress Scale (PSS) and Chalder Fatigue Scale (CFS). We found that the GM-BHQ was sensitive to fatigue and the interaction between fatigue and stress

Cognitive clustering in schizophrenia patients, their first-degree relatives and healthy subjects is associated with anterior cingulate cortex volume

Cognitive impairments are a core feature in schizophrenia patients (SCZ) and are also observed in first-degree relatives (FR) of SCZ. However, substantial variability in the impairments exists within and among SCZ, FR and healthy controls (HC). A cluster-analytic approach can group individuals based on profiles of traits and create more homogeneous groupings than predefined categories. Here, we investigated differences in the Brief Assessment of Cognition in Schizophrenia (BACS) neuropsychological battery (six subscales) among SCZ, unaffected FR and HC. To identify three homogeneous and meaningful cognitive groups regardless of categorical diagnoses (SCZ, FR and HC), cognitive clustering was performed, and differences in the BACS subscales among the cognitive cluster groups were investigated. Finally, the effects of diagnosis and cognition on brain volumes were examined. As expected, there were significant differences in the five BACS subscales among the diagnostic groups. The cluster-analytic approach generated three meaningful subgroups: (i) neuropsychologically normal, (ii) intermediate impaired and (iii) widespread impaired. The cognitive subgroups were mainly affected by the clinical diagnosis, and significant differences in all BACS subscales among clusters were found. The effects of the diagnosis and cognitive clusters on brain volumes overlapped in the frontal, temporal and limbic regions. Frontal and temporal volumes were mainly affected by the diagnosis, whereas the anterior cingulate cortex (ACC) volumes were affected by the additive effects of diagnosis and cognition. Our findings demonstrate a cognitive continuum among SCZ, FR and HC and support the concept of cognitive impairment and the related ACC volumes as intermediate phenotypes in SCZ

Association of Fatigue and Stress With Gray Matter Volume

Stress is associated with a greater risk for various health problems including reduced gray matter volume (GMV) and density in a number of brain regions. Previous studies show that neuroimaging could be a means to objectively evaluate stress. However, to date, no definite neuroimaging-derived measures are available to detect stress. In this research we used the gray-matter brain healthcare quotient (GM-BHQ), an MRI-based quotient for monitoring brain health based on GMV, as an objective scale to measure the association of stress with the whole brain. We recruited 63 healthy adults to acquire structural T1-weighted images and stress levels evaluated using three representative stress scales: the Profile of Mood States (POMS), Perceived Stress Scale (PSS) and Chalder Fatigue Scale (CFS). We found that the GM-BHQ was sensitive to fatigue and the interaction between fatigue and stress

Plasma levels of matrix metalloproteinase‐9 (MMP‐9) are associated with cognitive performance in patients with schizophrenia

Aim: Matrix metalloproteinase‐9 (MMP‐9) has been shown to modulate synaptic plasticity and may contribute to the pathophysiology of schizophrenia. This study investigated the peripheral levels of MMP‐9 and its association with cognitive functions in patients with schizophrenia to see the possible involvement of MMP‐9 in pathophysiology of schizophrenia, especially in cognitive decline. Methods: We measured the plasma levels of MMP‐9 in 257 healthy controls and 249 patients with schizophrenia, including antipsychotic drug–free patients. We also explored the possible association between plasma MMP‐9 levels and cognitive performance in healthy controls and patients with schizophrenia using the Wechsler Adult Intelligence Scale, Third Edition (WAIS‐ III), the Wechsler Memory Scale‐Revised (WMS‐R), and the Rey Auditory Verbal Learning Test (AVLT). Results: We found that the plasma levels of MMP‐9 were significantly higher in patients with schizophrenia, including antipsychotic drug–free patients, than in healthy controls. We found a significant negative association between plasma MMP‐9 levels and cognitive performance in controls and patients with schizophrenia. Conclusion: Together, these convergent data suggest a possible biological mechanism for schizophrenia, whereby increased MMP‐9 levels are associated with cognitive impairment

Plasma Levels of Soluble Tumor Necrosis Factor Receptor 2 (sTNFR2) Are Associated with Hippocampal Volume and Cognitive Performance in Patients with Schizophrenia

Background: An imbalance in the inflammatory tumor necrosis factor system, including soluble tumor necrosis factor receptor 2 (sTNFR2), may contribute to the pathophysiology of schizophrenia. Methods: We measured the plasma levels of sTNFR2 in 256 healthy controls and 250 patients with schizophrenia including antipsychotic drug-free patients and treatment-resistant patients. We also explored the possible association between plasma sTNFR2 levels and cognitive performance in healthy controls and patients with schizophrenia using the Wechsler Adult Intelligence Scale, Third Edition, the Wechsler Memory Scale-Revised, and the Rey Auditory Verbal Learning Test. An association between plasma sTNFR2 levels and hippocampal volume in controls and patients with schizophrenia was also investigated via MRI. Results: We found that the plasma levels of sTNFR2 were significantly higher in patients with schizophrenia, including both antipsychotic drug-free patients and treatment-resistant patients. We found a significant negative association between plasma sTNFR2 levels and cognitive performance in controls and patients with schizophrenia. Hippocampal volume was also negatively associated with plasma sTNFR2 levels in patients with schizophrenia. Conclusion: Together, these convergent data suggest a possible biological mechanism for schizophrenia, whereby increased sTNFR2 levels are associated with a smaller hippocampal volume and cognitive impairment

Association of fear of COVID-19 and resilience with psychological distress among health care workers in hospitals responding to COVID-19: analysis of a cross-sectional study

BackgroundIt remains unclear how fear of COVID-19 and resilience are related to psychological distress based on occupations among healthcare workers (HCWs) in hospitals treating patients with COVID-19. We conducted a survey on the mental health of HCWs during the COVID-19 pandemic to determine the relationship between factors such as fear of COVID-19 and resilience as well as mental distress in each occupation of HCWs.MethodsWe conducted a web-based survey among HCWs at seven hospitals treating COVID-19 patients in Japan from December 24, 2020 to March 31, 2021. A total of 634 participants were analyzed, and information regarding their socio-demographic characteristics and employment status was collected. Several psychometric measures were used, including the Kessler’s Psychological Distress Scale (K6), the fear of COVID-19 Scale (FCV-19S), and the Resilience Scale (RS14). Factors related to psychological distress were identified by logistic regression analysis. The association between job title and psychological scales was examined by one-way ANOVA, and t-tests were conducted to examine the association between the FCV-19S and hospital initiatives.ResultsIt was found that nurses and clerical workers were associated with psychological distress without considering FCV-19S or RS14; in a model that included FCV-19S, FCV-19S was associated with psychological distress, but job title was not; when RS14 was considered, resilience was protective. In terms of occupation, FCV-19S was lower among physicians and higher among nurses and clerical workers, while RS14 was higher among physicians and lower among other occupations. Having access to in-hospital consultation regarding infection control as well as to psychological and emotional support was associated with lower FCV-19S.ConclusionBased on our findings, we can conclude that the level of mental distress differed by occupation and the differences in the fear of COVID-19 and resilience were important factors. In order to provide mental healthcare for HCWs during a pandemic, it is important to create consultation services that enable employees to discuss their concerns. In addition, it is important to take steps to strengthen the resilience of HCWs in preparation for future disasters

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis

<p>Abstract</p> <p>Background</p> <p>A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively.</p> <p>Results</p> <p>The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable.</p> <p>Conclusions</p> <p>With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites.</p

The effect of duration of illness and antipsychotics on subcortical volumes in schizophrenia: Analysis of 778 subjects

BackgroundThe effect of duration of illness and antipsychotic medication on the volumes of subcortical structures in schizophrenia is inconsistent among previous reports. We implemented a large sample analysis utilizing clinical data from 11 institutions in a previous meta-analysis.MethodsImaging and clinical data of 778 schizophrenia subjects were taken from a prospective meta-analysis conducted by the COCORO consortium in Japan. The effect of duration of illness and daily dose and type of antipsychotics were assessed using the linear mixed effect model where the volumes of subcortical structures computed by FreeSurfer were used as a dependent variable and age, sex, duration of illness, daily dose of antipsychotics and intracranial volume were used as independent variables, and the type of protocol was incorporated as a random effect for intercept. The statistical significance of fixed-effect of dependent variable was assessed.ResultsDaily dose of antipsychotics was positively associated with left globus pallidus volume and negatively associated with right hippocampus. It was also positively associated with laterality index of globus pallidus. Duration of illness was positively associated with bilateral globus pallidus volumes. Type of antipsychotics did not have any effect on the subcortical volumes.DiscussionA large sample size, uniform data collection methodology and robust statistical analysis are strengths of the current study. This result suggests that we need special attention to discuss about relationship between subcortical regional brain volumes and pathophysiology of schizophrenia because regional brain volumes may be affected by antipsychotic medication