Dialogues in Clinical Neuroscience最新文献

This article is a historical review of the medical and psychiatric diagnoses associated with transgender people across epochs. Ancient Greek and Roman writings already mention gender change. Before a diagnosis even existed, historical documents described the lives of numerous people whom we would consider transgender today. The development of medical classifications took off in the nineteenth century, driven by the blooming of natural sciences. In the nineteenth century, most authors conflated questions of sexual orientation and gender. For example, the psychiatrist Krafft-Ebing reported cases of transgender people but understood them as paranoia, or as the extreme degree of severity in a dimension of sexual inversion. In the early 1900s, doctors such as Magnus Hirschfeld first distinguished homosexual and transgender behaviour. The usual term for transgender people was transvestite, before Harry Benjamin generalised the term transsexual in the mid-20th century. The term transgender became common in the 1970s. This article details the evolution of diagnoses for transgender people from DSM-III and ICD-10 to DSM-5 and ICD-11.

Background: A severe form of pathological social withdrawal, 'hikikomori,' has been acknowledged in Japan, spreading worldwide, and becoming a global health issue. The pathophysiology of hikikomori has not been clarified, and its biological traits remain unexplored.

Methods: Drug-free patients with hikikomori (n = 42) and healthy controls (n = 41) were recruited. Psychological assessments for the severity of hikikomori and depression were conducted. Blood biochemical tests and plasma metabolome analysis were performed. Based on the integrated information, machine-learning models were created to discriminate cases of hikikomori from healthy controls, predict hikikomori severity, stratify the cases, and identify metabolic signatures that contribute to each model.

Results: Long-chain acylcarnitine levels were remarkably higher in patients with hikikomori; bilirubin, arginine, ornithine, and serum arginase were significantly different in male patients with hikikomori. The discriminative random forest model was highly performant, exhibiting an area under the ROC curve of 0.854 (confidential interval = 0.648-1.000). To predict hikikomori severity, a partial least squares PLS-regression model was successfully created with high linearity and practical accuracy. In addition, blood serum uric acid and plasma cholesterol esters contributed to the stratification of cases.

Conclusions: These findings reveal the blood metabolic signatures of hikikomori, which are key to elucidating the pathophysiology of hikikomori and also useful as an index for monitoring the treatment course for rehabilitation.

Graph theoretical studies have been designed to investigate network topologies during life. Network science and graph theory methods may contribute to a better understanding of brain function, both normal and abnormal, throughout developmental stages. The degree to which childhood epilepsies exert a significant effect on brain network organisation and cognition remains unclear. The hypothesis suggests that the formation of abnormal networks associated with epileptogenesis early in life causes a disruption in normal brain network development and cognition, reflecting abnormalities in later life. Neurological diseases with onset during critical stages of brain maturation, including childhood epilepsy, may threaten this orderly neurodevelopmental process. According to the hypothesis that the formation of abnormal networks associated with epileptogenesis in early life causes a disruption in normal brain network development, it is then mandatory to perform a proper examination of children with new-onset epilepsy early in the disease course and a deep study of their brain network organisation over time. In regards, graph theoretical analysis could add more information. In order to facilitate further development of graph theory in childhood, we performed a systematic review to describe its application in functional dynamic connectivity using electroencephalographic (EEG) analysis, focussing on paediatric epilepsy.

Introduction: This narrative review of systematic reviews and meta-analyses aims at compiling available evidence in various aspects of neurocognitive functioning in Bipolar Disorder (BD). Methods: We conducted a MEDLINE literature search and identified 38 relevant systematic reviews and metaanalyses. Results: Current evidence suggests that BD is associated with cognitive impairment across multiple domains and during all clinical states. However, there is a considerable cognitive heterogeneity within BD, which cannot be explained by clinical subtypes, and the pattern of neurocognitive impairment in BD overlaps with other psychiatric conditions such as major depression and schizophrenia. Residual depressive symptoms, poor clinical course and higher number of manic episodes may negatively impact cognitive performance, which is a major predictor of general functioning in BD. Evidence from available prospective studies does not support the notion of progressive cognitive decline in BD while some evidence exists to suggest patients may show some improvements in cognitive functioning following the first manic episode. Furthermore, a subset of patients may show premorbid cognitive abnormalities that could signal an early neurodevelopmental aetiology. Preliminary findings from small studies identify potential pro-cognitive effects of Cognitive Remediation, erythropoietin, intranasal insulin, lurasidone, mifepristone, repetitive Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation in BD. Discussion: Longitudinal studies in high-risk individuals can provide a better understanding of the development and progression of neurocognitive impairment in BD. Largescale randomised control trials are needed to compare the pro-cognitive efficacy of various pharmacological and non-pharmacological interventions in different cognitive subgroups of patients at different stages of BD.

Introduction: A functional reciprocity between the gut microbiome and vagal nerve activity has been suggested, however, human studies addressing this phenomenon are limited.

Methods: Twenty-four-hour cardiac vagal activity (CVA) was assessed from 73 female participants (aged 24.5 ± 4.3 years). Additionally, stool samples were subjected to 16SrRNA gene analysis (V1-V2). Quantitative Insights Into Microbial Ecology (QIIME) was used to analyse microbiome data. Additionally, inflammatory parameters (such as CRP and IL-6) were derived from serum samples.

Results: Daytime CVA correlated significantly with gut microbiota diversity (r _sp = 0.254, p = 0.030), CRP (r _sp = -0.348, p = 0.003), and IL-6 (r _sp = -0.320, p = 0.006). When the group was divided at the median of 24 h CVA (Mdn = 1.322), the following features were more abundant in the high CVA group: Clostridia (Linear discriminant analysis effect size (LDA) = 4.195, p = 0.029), Clostridiales (LDA = 4.195, p = 0.029), Lachnospira (LDA = 3.489, p = 0.004), Ruminococcaceae (LDA = 4.073, p = 0.010), Faecalibacterium (LDA = 3.982, p = 0.042), Lactobacillales (LDA = 3.317, p = 0.029), Bacilli (LDA = 3.294, p = 0.0350), Streptococcaceae (LDA = 3.353, p = 0.006), Streptococcus (LDA = 3.332, p = 0.011). Based on Dirichlet multinomial mixtures two enterotypes could be detected, which differed significantly in CVA, age, BMI, CRP, IL-6, and diversity.

Conclusions: As an indicator of gut-brain communication, gut microbiome analysis could be extended by measurements of CVA to enhance our understanding of signalling via microbiota-gut-brain-axis and its alterations through psychobiotics.