Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.

Background: Variations in symptoms and indistinguishable depression episodes of unipolar depression (UD) and bipolar disorder (BD) make the discrimination difficult and time-consuming. For adolescents with high disease prevalence, an efficient diagnostic tool is important for the discrimination and treatment of BU and UD.

Methods: This multi-center cross-sectional study involved 1587 UD and 246 BD adolescents aged 12-18.

Pulmonary embolism incidence among patient admitted under psychiatry department: a case-control study.

Background: Pulmonary embolism (PE) is a serious and potentially life-threatening condition that requires prompt diagnosis and treatment. Identifying risk factors and diagnostic markers can aid in the early detection and management of this condition.

Methods: This case-control study examined 10,077 patients admitted to Shenzhen Kangning Hospital's psychiatry facility in 2020.

Public mental health services in Southern China and related health outcomes among individuals living with severe mental illness.

Background: Although national policies in China are comprehensive and instructive, a wide disparity exists between different cities. The current status of public mental health services by region in China remains unclear. This study aimed to investigate policies related to public mental health services, the contact coverage of public mental health services and outcomes of service users.

Linking Self-Esteem to Problematic Mobile Phone Use: A Moderated Mediation Model of Fear of Missing Out and Ruminative Subtypes.

Low self-esteem has been identified as a risk factor for problematic mobile phone use (PMPU). However, the magnitude of self-esteem's effect on PMPU varied across different studies. Drawing on the Interaction of Person-Affect-Cognition-Execution model and the response styles theory, this study developed a moderated mediation model to investigate the mediating role of fear of missing out (FoMO) and the moderating roles of ruminative subtypes (i.

Network analysis of depressive symptoms and C-reactive protein levels in major depressive disorder.

Background: C-reactive protein (CRP) levels have been implicated in the severity and symptomatology of major depressive disorder (MDD). The aim of this study was to explore the structure of depressive symptoms in patients with MDD according to different groups of CRP levels using network analysis.

Methods: The study included 864 individuals (mean age = 54.

Spatiotemporal discoordination of brain spontaneous activity in major depressive disorder.

Background: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotemporal topology (SPT), capturing both the hierarchy and dynamic attributes of brain activity in depressive disorder patients.

Spatio-temporal learning and explaining for dynamic functional connectivity analysis: Application to depression.

Background: Functional connectivity has been shown to fluctuate over time. The present study aimed to identifying major depressive disorders (MDD) with dynamic functional connectivity (dFC) from resting-state fMRI data, which would be helpful to produce tools of early depression diagnosis and enhance our understanding of depressive etiology.

Methods: The resting-state fMRI data of 178 subjects were collected, including 89 MDD and 89 healthy controls.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls.

(+)4-cholesten-3-one/sodium alginate/gelatin hydrogel for full-thickness wound repair and skin regeneration.

(+)4-cholesten-3-one has been proved to have potential wound healing effect in the process of wound regeneration. This study aimed to evaluate the effect of (+)4-cholesten-3-one/sodium alginate/gelatin on skin injury and reveal its potential molecular mechanism. First, we prepared sodium alginate/gelatin hydrogel (SA/Gel hydrogel) with different ratios and tested their characteristics.

Impact pathways of personality and psychosocial stress on depression among adult community residents in China: a fuzzy-set qualitative comparative analysis.

Objective: Depression is a common mental illness with a high prevalence rate and is a significant contributor to the global burden of diseases. Various factors are associated with depression, and its etiology is complex. Instead of focusing on single-factor effects, this study aimed to explore a combination of high-risk factor sets for depression among adult community residents.

Advancing ASD identification with neuroimaging: a novel GARL methodology integrating Deep Q-Learning and generative adversarial networks.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects an individual's behavior, speech, and social interaction. Early and accurate diagnosis of ASD is pivotal for successful intervention. The limited availability of large datasets for neuroimaging investigations, however, poses a significant challenge to the timely and precise identification of ASD.

Structural and functional abnormalities across clinical stages of psychosis: A multimodal neuroimaging investigation.

Background: Structural and functional neurobiological abnormalities have been observed in schizophrenia. Previous studies have concentrated on specific illness stages, obscuring relationships between functional/structural changes and disorder progression. The present study aimed to quantify structural and functional abnormalities across different clinical stages using functional near-infrared spectroscopy (fNIRS) and structural magnetic resonance imaging (sMRI).

ESF1 and MIPEP proteins promote estrogen receptor-positive breast cancer proliferation and are associated with patient prognosis.

Background: Estrogen receptor-positive (ER+) breast cancer accounts for two-thirds of all breast cancers, and its early and late recurrences still threaten patients' long-term survival and quality of life. Finding candidate tumor antigens and potential therapeutic targets is critical to addressing these unmet needs.

Method: The isobaric tags for relative and absolute quantitation (iTRAQ) proteomic analysis was employed to identify the differentially expressed proteins (DEPs) between ER + breast cancer and corresponding adjacent normal tissue.