Changes of anhedonia and cognitive symptoms in first episode of depression and recurrent depression, an analysis of data from NSSD.

Background: Anhedonia and cognitive impairment are core features of major depressive disorder (MDD), and are essential to the treatment and prognosis. Here, we aimed to investigate anhedonia and its cognitive correlates between first episode of depression (FED) and recurrent depression (RD), which was part of the National Survey on Symptomatology of Depression.

Methods: In this study, 1400 drug naïve FED patients and 487 on medicine RD patients were included.

Age of onset for major depressive disorder and its association with symptomatology.

Background: The age of onset (AOO) is a key factor for heterogeneity in major depressive disorder (MDD). Looking at the effect of AOO on symptomatology may improve clinical outcomes. This study aims to examine whether and how AOO affects symptomatology using a machine learning approach and latent profile analysis (LPA).

Short- and Long-Term Influences of Benzodiazepine and Z-Drug Use in Patients with Bipolar Disorder Combined Sleep Disturbance during Affective Period: A Nine-Month Follow-Up Analysis.

Background: Sleep disturbances and benzodiazepine (BZD)/Z-drug use are common in patients with bipolar disorder (BD).

Objective: To investigate the short- and long-term effects of BZD/Z-drug use during acute affective episode.

Methods: Participants diagnosed with BD as well as sleep disturbance chose BZDs/Z-drugs or not at will.

Analysis of Seasonal Clinical Characteristics in Patients With Bipolar or Unipolar Depression.

This study was to investigate the characteristics of seasonal symptoms and non-enzymatic oxidative stress in the first hospitalized patients with bipolar and unipolar depression, aiming to differentiate bipolar depression from unipolar depression and reduce their misdiagnosis. A total of 450 patients with bipolar depression and 855 patients with depression were included in the present study. According to the season when the patients were admitted to the hospital due to the acute onset of depression, they were further divided into spring, summer, autumn and winter groups.

PAID study design on the role of PKC activation in immune/inflammation-related depression: a randomised placebo-controlled trial protocol.

Background: Inflammation that is mediated by microglia activation plays an important role in the pathogenesis of depression. Microglia activation can lead to an increase in the levels of proinflammatory cytokines, including TNF-α, which leads to neuronal apoptosis in the specific neural circuits of some brain regions, abnormal cognition and treatment-resistant depression (TRD). Protein kinase C (PKC) is a key regulator of the microglia activation process.

Common cellular and molecular mechanisms and interactions between microglial activation and aberrant neuroplasticity in depression.

It has been suggested that inflammation is involved in the pathophysiology of depression. As tissue-specific macrophages in the central nervous system (CNS), microglia play an important role in neuroinflammation. Resident microglia become activated towards the pro-inflammatory (M1) phenotype or the anti-inflammatory (M2) phenotype during neuroinflammation.

Internet-Based Management for Depressive Disorder.

The advances in the Internet and related technologies may lead to changes in professional roles of psychiatrists and psychotherapists. The application of artificial intelligence (AI) and electronic measurement-based care (eMBC) in the treatment of depressive disorder has addressed more interest. AI could play a role in population health management and patient administration as well as assist physicians to make a decision in the real-world clinical practice.

Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.

Background: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general hospitals in China leads to possible misdiagnosis. Looking at the symptomatology of first-visit patients with MDD in different mental health services, and identifying predictors of health-seeking behavior using machine learning may help to improve diagnostic accuracy.

Methods: 1500 patients first diagnosed with MDD were recruited from 16 psychiatric hospitals and 16 general hospitals across China.

Subtypes of treatment-resistant depression determined by a latent class analysis in a Chinese clinical population.

Background: This study aimed to explore subtypes of treatment-resistant depression (TRD).

Methods: Latent class analysis (LCA) was performed on clinical and demographic data collected from 375 patients with TRD. Clinical variables were compared across subtypes.