Machine learning-driven simplification of the hypomania checklist-32 for adolescent: a feature selection approach.

Background: The Hypomania Checklist-32 is widely used to screen for bipolar disorder, but its length can be challenging for adolescents with manic symptoms. This study aimed to develop a shortened version of the HCL-32 tailored for adolescents using machine learning techniques.

Methods: Data from 2,850 adolescents (mean age 15.

Refining antipsychotic treatment strategies in schizophrenia: discovery of genetic biomarkers for enhanced drug response prediction.

Schizophrenia (SCZ) is a severe mental disorder affecting around 1% of individuals worldwide. The variability in response to antipsychotic drugs (APDs) among SCZ patients presents a significant challenge for clinicians in determining the most effective medication. In this study, we investigated the biological markers and established a predictive model for APD response based on a large-scale genome-wide association study using 3269 Chinese schizophrenia patients.

Depressive symptoms among rural left-behind children and adolescents in China: a large-scale cross-sectional study.

Background: Left-behind children(LBC) in rural China are at increased risk for mental health problems, including depression. This study aimed to estimate the prevalence of depression and identify key associate factors among Chinese rural LBC.

Methods: A cross-sectional study was conducted using data from 36,612 LBC aged 6 to 18 years old across 596 data collection sites in Nanchong, Sichuan Province, China.

Individualized and Biomarker-Based Prognosis of Longitudinal Cognitive Decline in Early Symptomatic Alzheimer's Disease.

Background: Although individualized models using demographic, MRI, and biological markers have recently been applied in mild cognitive impairment (MCI), a similar study is lacking for patients with early Alzheimer's disease (AD) with biomarker evidence of abnormal amyloid in the brain.

Objective: We aimed to develop prognostic models for individualized prediction of cognitive change in early AD.

Methods: A total of 421 individuals with early AD (MCI or mild dementia due to AD) having biomarker evidence of abnormal amyloid in the brain were included in the current study.

The longitudinal relationships between problematic mobile phone use symptoms and negative emotions: a cross-lagged panel network analysis.

Background: The association between problematic mobile phone use (PMPU) and negative emotions in university students is not well understood in terms of causality and directionality. This study aims to clarify whether negative emotions trigger PMPU or whether the PMPU itself leads to increased negative emotions over time.

Methods: A two-wave longitudinal study was conducted involving 5568 Chinese freshmen who were surveyed at baseline and followed up after one academic year.

Clinical and Diagnostic Value of High-Density Lipoprotein-Based Inflammatory Indices and Lipid Ratios in Young Adults with Schizophrenia.

Purpose: This study aimed to assess High-density Lipoprotein (HDL)-based Inflammatory Indices and lipid profile changes in antipsychotic-naive first-episode schizophrenia (AN-FES) patients, chronic schizophrenia (CS) patients, and explore the clinical and predictive value of these parameters for schizophrenia.

Patients And Methods: The study cohort included 52 AN-FES patients, 46 CS patients, and 52 healthy controls (HCs), with an average age of 24 years. Upon admission, patients underwent complete blood count and lipid profile analyses.

The interplay of depressive symptoms and self-efficacy in adolescents: a network analysis approach.

Background: Self-efficacy, a critical psychological construct representing an individual's belief in their ability to control their motivation, behavior, and social environment. In adolescents, self-efficacy plays a crucial role in mental health, particularly concerning depressive symptoms. Despite substantial research, the complex interplay between self-efficacy and depressive symptoms in adolescents remains incompletely understood.

Exploring core symptoms of alcohol withdrawal syndrome in alcohol use disorder patients: a network analysis approach.

Background: Understanding the interplay between psychopathology of alcohol withdrawal syndrome (AWS) in alcohol use disorder (AUD) patients may improve the effectiveness of relapse interventions for AUD. Network theory of mental disorders assumes that mental disorders persist not of a common functional disorder, but from a sustained feedback loop between symptoms, thereby explaining the persistence of AWS and the high relapse rate of AUD. The current study aims to establish a network of AWS, identify its core symptoms and find the bridges between the symptoms which are intervention target to relieve the AWS and break the self-maintaining cycle of AUD.

Characterizing the clinical heterogeneity of early symptomatic Alzheimer's disease: a data-driven machine learning approach.

Introduction: Alzheimer's disease (AD) is highly heterogeneous, with substantial individual variabilities in clinical progression and neurobiology. Amyloid deposition has been thought to drive cognitive decline and thus a major contributor to the variations in cognitive deterioration in AD. However, the clinical heterogeneity of patients with early symptomatic AD (mild cognitive impairment or mild dementia due to AD) already with evidence of amyloid abnormality in the brain is still unknown.

Drug-induced enzyme activity inhibition and CYP3A4 genetic polymorphism significantly shape the metabolic characteristics of furmonertinib.

This study aimed to elucidate the impact of variations in liver enzyme activity, particularly CYP3A4, on the metabolism of furmonertinib. An in vitro enzyme incubation system was established for furmonertinib using liver microsomes and recombinant CYP3A4 baculosomes, with analytes detected by LC-MS/MS. The pharmacokinetic characteristics of furmonertinib were studied in vivo using Sprague-Dawley rats.

The Bridge Between Childhood Trauma and Alexithymia Among Adolescents with Depressive and Bipolar Disorders: A Network Bridge Analysis.

Childhood trauma and alexithymia are significant risk factors for adolescent mental health issues. Prior research has linked these factors to psychopathology, but the complexities of their interrelation remain underexplored. This study aims to elucidate the relationship between various forms of childhood trauma and alexithymia in adolescents with depressive and bipolar disorders.

Family and job microsystems as mediators between social integration and depression among rural-to-urban migrant workers in China: does having sons make a difference?

Background: Rural-to-urban migrant workers are a vulnerable group at risk of developing depression. Based on the social-ecological systems theory, this study investigates the impact of the lack of social integration on depression, considering the mediating roles of migrant workers' microsystems (family happiness and job burnout). Additionally, the study explores whether having sons influences these associations.

Effect of family intervention on relapse rate of Chinese patients with alcohol-dependent.

Objective: This study explored the impact of a family intervention on the relapse rate of Chinese patients with alcohol dependence.

Methods: A total of 151 male patients with alcohol dependence who were discharged from the Substance Dependence Department of the Wenzhou Seventh People's Hospital from January to December 2020 were selected. They were divided into the control ( = 73) and experimental ( = 78) groups.