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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

Background: Coronavirus disease 2019 (COVID‐19) is known to cause not only respiratory but also neuropsychiatric symptoms, which are assumed to be derived from a cytokine storm and its effects on the central nervous systems. Patients with COVID‐19 who develop severe respiratory symptoms are known to show severe neuropsychiatric symptoms such as cerebrovascular disease and encephalopathy. However, the detailed clinical courses of patients with neuropsychiatric symptoms caused by mild or asymptomatic COVID‐19 remain poorly understood. Here, we present a case of COVID‐19 who presented with severe and prolonged neuropsychiatric symptoms subsequent to mild respiratory symptoms. Case presentation: A 55‐year‐old female with COVID‐19 accompanied by mild respiratory symptoms showed delusion, psychomotor excitement, and poor communication ability during quarantine outside the hospital. Considering her diminished respiratory symptoms, her neuropsychiatric symptoms were initially regarded as psychogenic reactions. However, as she showed progressive disturbance of consciousness accompanied by an abnormal electroencephalogram, she was diagnosed with post‐COVID‐19 encephalopathy. Although her impaired consciousness and elevated cytokine level improved after steroid pulse therapy, several neuropsychiatric symptoms, including a loss of concentration, unsteadiness while walking, and fatigue, remained. Conclusions: This case suggests the importance of both recognizing that even apparently mild COVID‐19‐related respiratory symptoms can lead to severe and persistent neuropsychiatric symptoms, and elucidating the mechanisms, treatment, and long‐term course of COVID‐19‐related neuropsychiatric symptoms in the future. [ABSTRACT FROM AUTHOR]