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Compromised mitochondrial electron transport chain (ETC) activities are associated with depression in humans and rodents. However, the effects of the enhancement of mitochondrial ETC activities on depression remain elusive. We recently reported that an extremely low-frequency electromagnetic field (ELF-EMF) of as low as 10 μT induced hormetic activation of mitochondrial ETC complexes in human/mouse cultured cells and mouse livers. Chronic social defeat stress (CSDS) for 10 consecutive days caused behavioral defects mimicking depression in mice, and using an ELF-EMF for two to six weeks ameliorated them. CSDS variably decreased the mitochondrial ETC proteins in the prefrontal cortex (PFC) in 10 days, which were increased by an ELF-EMF in six weeks. CSDS had no effect on the mitochondrial oxygen consumption rate in the PFC in 10 days, but using an ELF-EMF for six weeks enhanced it. CSDS inactivated SOD2 by enhancing its acetylation and increased lipid peroxidation in the PFC. In contrast, the ELF-EMF activated the Sirt3-FoxO3a-SOD2 pathway and suppressed lipid peroxidation. Furthermore, CSDS increased markers for mitophagy, which was suppressed by the ELF-EMF in six weeks. The ELF-EMF exerted beneficial hormetic effects on mitochondrial energy production, mitochondrial antioxidation, and mitochondrial dynamics in a mouse model of depression. We envisage that an ELF-EMF is a promising therapeutic option for depression. [ABSTRACT FROM AUTHOR]

Background. The differential diagnosis of a patient with cognitive, behavioral, and motor symptoms is broad. There is much overlap between neurocognitive disorders due to frontotemporal dementia and other subcortical dementia. A less known diagnosis, cerebellar cognitive affective syndrome (CCAS), should also be considered. Case History. A 29‐year‐old female presented with ataxia and left‐sided weakness. CSF showed oligoclonal bands, and MRI showed multiple white matter lesions with some atrophy. She was diagnosed with multiple sclerosis (MS). At age 35, she developed frontal lobe symptoms and executive dysfunction; she was diagnosed with MS with bipolar disorder. Neuropsychological evaluation at that time showed significant deficits in multiple cognitive domains. Subsequent MRI showed progressive frontotemporal atrophy, and FDG‐PET uncovered hypometabolism in the frontotemporal lobes and cerebellum. At age 38, her behavior worsened with aggression, and she was started on olanzapine. She responded well with decreased agitation and improved motivation and attention. Compared with previous scans, most recent MRI and FDG‐PET showed interval increase in cerebellar atrophy with increase in hypometabolism in the cerebellum, respectively. Conclusion. Based on cerebellar, affective, and subcortical cognitive examination findings, our diagnosis is probable CCAS. The cerebellum should be considered as a possible etiology of frontal subcortical cognitive impairment. [ABSTRACT FROM AUTHOR]

Aim: Depressive disorder is often evaluated using established rating scales. However, consistent data collection with these scales requires trained professionals. In the present study, the "rater & estimation‐system" reliability was assessed between consensus evaluation by trained psychiatrists and the estimation by 2 models of the AI‐MADRS (Montgomery‐Asberg Depression Rating Scale) estimation system, a machine learning algorithm‐based model developed to assess the severity of depression. Methods: During interviews with trained psychiatrists and the AI‐MADRS estimation system, patients responded orally to machine‐generated voice prompts from the AI‐MADRS structured interview questions. The severity scores estimated from two models of the AI‐MADRS estimation system, the max estimation model and the average estimation model, were compared with those by trained psychiatrists. Results: A total of 51 evaluation interviews conducted on 30 patients were analyzed. Pearson's correlation coefficient with the scores evaluated by trained psychiatrists was 0.76 (95% confidence interval 0.62–0.86) for the max estimation model, and 0.86 (0.76–0.92) for the average estimation model. The ANOVA ICC rater & estimation‐system reliability with the evaluation scores by trained psychiatrists was 0.51 (−0.09 to 0.79) for the max estimation model, and 0.75 (0.55–0.86) for the average estimation model. Conclusion: The average estimation model of AI‐MADRS demonstrated substantially acceptable rater & estimation‐system reliability with trained psychiatrists. Accumulating a broader training dataset and the refinement of AI‐MADRS interviews are expected to improve the performance of AI‐MADRS. Our findings suggest that AI technologies can significantly modernize and potentially revolutionize the realm of depression assessments. [ABSTRACT FROM AUTHOR]

Aim: The present study aimed to examine the association between copy number variations (CNVs) in parkin (PRKN) and schizophrenia (SCZ) and autism spectrum disorder (ASD) in a large case–control sample. Method: Array comparative genomic hybridization was performed on 3111 cases with SCZ, 1236 cases with ASD, and 2713 controls. We systematically prioritized likely pathogenic CNVs (LP‐CNVs) in PRKN and examined their association with SCZ and ASD. Results: In total, 3014 SCZ cases (96.9%), 1205 ASD cases (97.5%), and 2671 controls (98.5%) passed quality control. We found that monoallelic carriers of LP‐CNVs in PRKN were common (70/6890, 1.02%) and were not at higher risk of SCZ (p = 0.29) or ASD (p = 0.72). We observed that the distribution pattern of LP‐CNVs in the Japanese population was consistent with those in other populations. We also identified a patient diagnosed with SCZ and early‐onset Parkinson's disease carrying biallelic pathogenic CNVs in PRKN. The absence of Parkinson's symptoms in 10 other monoallelic carriers of the same pathogenic CNV further reflects the lack of effect of monoallelic pathogenic variants in PRKN in the absence of a second hit. Conclusion: The present findings suggest that monoallelic CNVs in PRKN do not confer a significant risk for SCZ or ASD. However, further studies to investigate the association between biallelic CNVs in PRKN and SCZ and ASD are warranted. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia is a relatively common disorder, with a lifetime prevalence of about 1%. Family history is the most important risk factor for schizophrenia, consistent with a genetic contribution to its etiology. Recent human genetic studies reported that some common variants located within BCL9 are associated with schizophrenia in the Chinese population, but not associated with bipolar disorder in the Caucasian population. Methods: Single nucleotide variant (SNP) prioritization sample was comprised of 575 patients with schizophrenia and 564 healthy controls with no personal or family history of psychiatric illness. For SNP association analysis, we used an independent Japanese sample set (replication sample) comprising 1464 cases and 1171 controls. For the analysis of cognitive performance, we investigated 115 cases and 87 controls using Continuous Performance Test (CPT-IP) and the Wisconsin Card Sorting Test Keio version (WCST). Meta-analysis was performed using a combined Japanese total sample (N=3735) and a Chinese sample from a previous study. Results: In the replication sample set, we did not detect any association in 2 SNPs (rs672607 and rs10494252) and schizophrenia. Meta-analysis of rs672607 showed significant association (p-value 0.012, odds ratio 0.855). There was a significant (p

Introduction: Drug‐induced extrapyramidal syndrome (EPS) remains a major problem in clinical psychiatry. This study aimed to examine the factor structure of drug‐induced extrapyramidal symptoms observed in patients with schizophrenia and assessed using the Drug‐Induced Extrapyramidal Symptoms Scale (DIEPSS). Methods: The participants were 1478 patients with a diagnosis of schizophrenia whose EPS was assessed using the DIEPSS in India, Indonesia, Japan, Malaysia, and Taiwan in the 2016 REAP AP‐4 study. The records of the participants were randomly divided into two subgroups: the first for exploratory factor analysis of the eight DIEPSS items, and the second for confirmatory factor analysis. Results: The factor analysis identified three factors: F1 (gait and bradykinesia), F2 (muscle rigidity and tremor), and F3 (sialorrhea, akathisia, dystonia, and dyskinesia). Conclusion: The results suggest that the eight individual items of the DIEPSS could be composed of three different mechanisms: acute parkinsonism observed during action (F1), acute parkinsonism observed at rest (F2), and central dopaminergic mechanisms with pathophysiology other than acute parkinsonism (F3). [ABSTRACT FROM AUTHOR]

The course of delirium is associated with increased hospital costs, healthcare complications, increased mortality, and long‐term poor outcomes. Despite delirium being long recognised as one of the most important prognostic components of patients with illnesses, delirium remains poorly understood, effective management options are limited, and no effective treatment has yet been established. This review evaluated the effects of delirium on mortality, institutionalisation, and dementia in various situations to clarify its prognostic seriousness to elucidate important areas for clinical practice and future research. The effect of delirium on mortality in COVID‐19 patients was similar to that in other diseases. The effect of delirium on mortality in patients with delirium between the ages of 18 and 65 may be higher than in those with delirium aged over 65, but studies are scarce. Promoting recognition of delirium at all ages is needed. With careful attention to the specific factors in younger patients that contribute to delirium, healthcare providers may be able to decrease the poor impact of delirium on clinical outcomes. Evaluation of the association between interventions for delirium such as sedation in present clinical practice and the prognosis of delirium is lacking, and further clinical studies are essential. [ABSTRACT FROM AUTHOR]