Network pharmacology and molecular docking to explore mechanisms of clozapine-induced cardiac arrest.

Background: Clozapine is superior to all other antipsychotics in treating schizophrenia in terms of its curative efficacy; however, this drug is prescribed only as a last resort in the treatment of schizophrenia, given its potential to induce cardiac arrest. The mechanism of clozapine-induced cardiac arrest remains unclear, so we aimed to elucidate the potential mechanisms of clozapine-induced cardiac arrest using network pharmacology and molecular docking.

Methods: We identified and analyzed the overlap between potential cardiac arrest-related target genes and clozapine target genes.

Exploring the molecular targets of fingolimod and siponimod for treating the impaired cognition of schizophrenia using network pharmacology and molecular docking.

The treatment of cognitive impairment in schizophrenia is an unaddressed need due to the absence of novel treatments. Recent studies demonstrated that fingolimod and siponimod have neuroprotective effects in several neuropsychiatric disorders; however, their pharmacological mechanisms are unclear. The objective of this study was to identify potential molecular mechanisms of fingolimod and siponimod for improving cognition of schizophrenia through network pharmacology and molecular docking.

Molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania based on network pharmacology and molecular docking: Evidence from computational biology.

Background: Quetiapine monotherapy is recommended as the first-line option for acute mania and acute bipolar depression. However, the mechanism of action of quetiapine is unclear. Network pharmacology and molecular docking were employed to determine the molecular mechanisms of quetiapine bidirectional regulation of bipolar depression and mania.

Homotopic functional connectivity disruptions in schizophrenia and their associated gene expression.

It has been revealed that abnormal voxel-mirrored homotopic connectivity (VMHC) is present in patients with schizophrenia, yet there are inconsistencies in the relevant findings. Moreover, little is known about their association with brain gene expression profiles. In this study, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control VMHC differences from both the discovery (meta-analysis, including 9 studies with a total of 386 patients and 357 controls) and replication (separate group-level comparisons within two datasets, including a total of 258 patients and 287 controls) phases were performed to identify genes associated with VMHC alterations.

Genomic loci influence patterns of structural covariance in the human brain.

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia.

Background: Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity.

Validation of a modified Chinese-language version of the Davos Assessment of Cognitive Biases Scale (MCL-DACOBS) in a sample of Chinese patients with schizophrenia.

Introduction: The Davos Assessment of Cognitive Biases Scale (DACOBS) is widely used to assess cognitive biases in patients who have schizophrenia. However, the lack of a modified Chinese-language version of the DACOBS (MCL-DACOBS) precludes Chinese schizophrenic patients from treatment aimed at normalizing cognitive biases, impacting their prognosis. Here, we aimed to produce a DACOBS for China and test the validity and reliability of the resultant MCL-DACOBS.

Microglia and cognitive impairment in schizophrenia: translating scientific progress into novel therapeutic interventions.

Cognitive impairment is a core clinical feature of schizophrenia, exerting profound adverse effects on social functioning and quality of life in a large proportion of patients with schizophrenia. However, the mechanisms underlying the pathogenesis of schizophrenia-related cognitive impairment are not well understood. Microglia, the primary resident macrophages in the brain, have been shown to play important roles in psychiatric disorders, including schizophrenia.

Validation and reliability test of Chinese language patient-reported impact of symptoms in schizophrenia scale.

Background: Patient-reported outcomes, or subjective evaluations directly reflecting the patient's views, feelings, and judgments, are now being used to evaluate the outcomes of care and treatment of people with schizophrenia. In this study, we used an updated tool, the patient-reported impact of symptoms in schizophrenia scale (PRISS), translated into Chinese languages to assess the subjective experiences of schizophrenia patients.

Objective: This study aimed to test the psychometrics of the Chinese languages PRISS (CL-PRISS).

Validity and reliability of a Chinese version of the Bergen Work Addiction Scale.

Background: Work addiction (WA), which can impair personal relationships, engagement in recreational activities, and/or health, is a behavioral addiction. A tool for the early detection of WA in China is needed.

Objective: The aim of this study was to develop and determine the validity and reliability of a Chinese version of the Bergen Work Addiction Scale (C-BWAS).

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population.

Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment.

Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations.

Design, Setting, And Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort.

Heterogeneous brain dynamic functional connectivity patterns in first-episode drug-naive patients with major depressive disorder.

It remains challenging to identify depression accurately due to its biological heterogeneity. As people suffering from depression are associated with functional brain network alterations, we investigated subtypes of patients with first-episode drug-naive (FEDN) depression based on brain network characteristics. This study included data from 91 FEDN patients and 91 matched healthy individuals obtained from the International Big-Data Center for Depression Research.

Validity and reliability of a Chinese version of the self-evaluation of negative symptoms.

The negative symptoms of schizophrenia can be present at any clinical stage, but evaluating the negative symptoms always remains challenging. To screen the negative symptoms effectively, self-evaluation should be introduced. To date, professional psychiatrists used almost all of the scales available to screen the negative symptoms but could not obtain an accurate outcome.

Understanding the heterogeneity of dynamic functional connectivity patterns in first-episode drug naïve depression using normative models.

Background: The heterogeneity of the clinical symptoms and presumptive neural pathologies has stunted progress toward identifying reproducible biomarkers and limited therapeutic interventions' effectiveness for the first episode drug-naïve major depressive disorders (FEDN-MDD). This study combined the dynamic features of fMRI data and normative modeling to quantitative and individualized metrics for delineating the biological heterogeneity of FEDN-MDD.

Method: Two hundred seventy-four adults with FEDN-MDD and 832 healthy controls from International Big-Data Center for Depression Research were included.

Computing personalized brain functional networks from fMRI using self-supervised deep learning.

A novel self-supervised deep learning (DL) method is developed to compute personalized brain functional networks (FNs) for characterizing brain functional neuroanatomy based on functional MRI (fMRI). Specifically, a DL model of convolutional neural networks with an encoder-decoder architecture is developed to compute personalized FNs directly from fMRI data. The DL model is trained to optimize functional homogeneity of personalized FNs without utilizing any external supervision in an end-to-end fashion.

A borderline personality assessment for adolescents: Validity and reliability of the Chinese languages borderline personality features scale (short form version) for adolescents/children.

Background: Borderline personality disorder (BPD) is characterized by behavioral patterns that promote suffering in many adolescents and their guardians. Currently, early diagnosis of BPD mainly depends on the effective assessment of pathological personality traits (i.e.

Risk-to-befit ratios of consecutive antidepressants for heavy menstrual bleeding in young women with bipolar disorder or major depressive disorder.

The occurrence of heavy menstrual bleeding (HMB) induced by pharmacological agents has been reported in young adult women. This study aimed to investigate a possible association between the occurrence rates of HMB and different treatment methods such as antidepressant agents alone and in combination with other pharmacological agents. The examined cohort included young women (age 18-35 years, = 1,949) with bipolar disorder (BP) or major depressive disorder (MDD).