Background: Mood disorders are very common among adolescents and include mainly bipolar disorder (BD) and major depressive disorder (MDD), with overlapping depressive symptoms that pose a significant challenge to realizing a rapid and accurate differential diagnosis in clinical practice. Misdiagnosis of BD as MDD can lead to inappropriate treatment and detrimental outcomes, including a poorer ultimate clinical and functional prognosis and even an increased risk of suicide. Therefore, it is of great significance for clinical management to identify clinical symptoms or features and biological markers that can accurately distinguish BD from MDD. With the aid of bibliometric analysis, we explore, visualize, and conclude the important directions of differential diagnostic studies of BD and MDD in adolescents.Materials and methods: A literature search was performed for studies on differential diagnostic studies of BD and MDD among adolescents in the Web of Science Core Collection database. All studies considered for this article were published between 2004 and 2023. Bibliometric analysis and visualization were performed using the VOSviewer and CiteSpace software.Results: In total, 148 publications were retrieved. The number of publications on differential diagnostic studies of BD and MDD among adolescents has been generally increasing since 2012, with the United States being an emerging hub with a growing influence in the field. Boris Birmaher is the top author in terms of the number of publications, and the Journal of Affective Disorders is the most published journal in the field. Co-occurrence analysis of keywords showed that clinical characteristics, genetic factors, and neuroimaging are current research hotspots. Ultimately, we comprehensively sorted out the current state of research in this area and proposed possible research directions in future.Conclusion: This is the first-ever study of bibliometric and visual analyses of differential diagnostic studies of BD and MDD in adolescents to reveal the current research status and important directions in the field. Our research and analysis results might provide some practical sources for academic scholars and clinical practice.

Midbrain dopamine (DA) neurons are essential for regulating movement, emotion, and reward, with their dysfunction closely linked to Parkinson’s disease (PD). While DA neurons in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) have known overlapping roles in behaviors such as depression and reward, their distinct contributions to subtle spontaneous behaviors remain insufficiently understood. In this study, we utilized a 3D behavioral analysis platform powered by machine learning to explore motor and nuanced behavioral changes in a subacute MPTP mouse model of PD. This investigative approach was combined with cell-type-specific genetic ablation of DA neurons in both the SNc and VTA. Our findings highlight significant deficits in rearing, walking, and hunching behaviors correlated with the loss of SNc DA neurons, but not VTA DA neurons, alongside increased overall movement, reduced movement precision, and pronounced right-sided lateralization. These subtle features, particularly rearing deficits and lateralization, emerge as critical behavioral biomarkers of SNc DA neuron loss, thereby enhancing the translational relevance of PD models.