Objective: The dorsolateral prefrontal cortex (dlPFC) is strongly associated with mood symptoms. This study used functional near-infrared spectroscopy (fNIRS) technology to explore the features of brain neural activity in the dlPFC of anxious and depressed college students, during an emotional autobiographical memory task, and to understand the differences in brain cognitive mechanisms caused by anxiety and depression. Methods: A simple random sampling method was used to test 440 college students at a university with a healthy control group (HC, 220 participants), a pure depression group (PD, 92 participants), and a pure anxiety group (PA, 128 participants). The average oxyhemoglobin in the dlPFC of the subjects during the emotional autobiographical memory task was collected by a 53-channel functional near-infrared spectroscopy imaging device. Results: The activation of the left dlPFC (ch13) in the pure depression group was significantly higher than in the pure anxiety group. The activation of the right dlPFC (ch48) was significantly higher under positive emotions than under negative emotions. The interaction between emotion valence and group was marginally significant, and the activation of the right dlPFC (ch41) in the pure depression group was significantly higher under positive emotion than in negative emotion. The activation of the pure depression group under positive emotions was significantly higher than that of the pure anxiety group. In comparison, the activation of the pure depression group under negative emotions was significantly lower than that of the healthy control group. The results of correlation analysis showed that the activation of the left dlPFC (ch13) was significantly negatively correlated with anxiety in positive emotions, but the activation of the right dlPFC (ch34, ch42) was significantly positively correlated with anxiety in positive and negative emotions. Conclusions: The right dlPFC was insensitive to positive emotions in college students with high-anxiety symptoms, whereas this region was insensitive to negative emotions in college students with high depressive symptoms, which might be one of the critical differences in the cognitive mechanisms of anxiety and depression. Furthermore, left and right dlPFC activation correlated differently with anxiety. The higher the anxiety level, the lower the activation on the left side, and the higher the activation on the right side. The results suggested that anxiety might reduce the function of the left dlPFC.

Introduction: The outbreak of the COVID-19 pandemic has disrupted people’s routine, bringing uncertainty and stress, leading to mental health issues. This situation is particularly acute among Chinese prospective graduates in higher education stage as they cannot predict the outcomes of their studies, graduation, and career development, and therefore experience career-related stress.Methods: This study included 4041 prospective graduates in higher education stage (using handy sampling) recruited in March 2020 as participants (M_Age = 22.56, SD = 1.865), utilizing a Sparse Gaussian Graphical Model for regularized partial correlation network analysis of depression symptoms (by PHQ-9), anxiety symptoms (by GAD-7), and career-related stress, which aims to explore the role of career-related stress in the symptom networks of depression and anxiety among prospective graduates in their final semester.Results: The results revealed that fatigue, sad mood, and psychomotor symptoms in depression, as well as uncontrollable worry and trouble relaxing in anxiety, were central symptoms in the network. Additionally, sad mood and guilt belonging to depressive symptoms, and feeling afraid, restlessness, and irritability belonging to anxiety symptoms, served as bridge symptoms connecting symptom communities. Specifically, guilt as a depressive symptom showed a strong association with employment stress in career-related stress. There were no significant differences in network structure and global strength based on participants’ gender. However, despite no significant differences in network structure, the global strength of prospective graduates from Wuhan was significantly lower than samples from non-Hubei provinces, possibly indicative of a Typhoon Eye Effect.Discussion: The findings of this study can inspire psychological professionals in higher education institutions to provide support for mental interventions and therapies for prospective graduates, and addressing career development issues.

Introduction: This study seeks to understand the reality and psychological difficulties faced by university graduates in Wuhan after the COVID-19 epidemic was controlled. Methods: A total of 6,417 graduate students were surveyed through an online questionnaire from late May to early June 2020. The questionnaire asked questions on depression, anxiety, insomnia, and suicidal behavior. In addition, self-administered epidemic-related questionnaires consisting of eight items were collected from university graduates. Results: Participants’ positive detection rates for depression, anxiety, insomnia, and suicidal behavior are 13.4%, 8.3%, 4.4%, and 12.1%, respectively. The three biggest challenges faced by graduates are future development, economic difficulties, and employment problems. Conclusion: The detectable rate of depression, anxiety, and insomnia is low, and the detectable rate of suicide symptoms should be given more attention. The biggest problem of this group is their future development, and what they want to solve the most is the economic difficulty.

Temporal rhythm (TR) is involved in the pathophysiology and treatment response of major depressive disorder (MDD). However, there have been few systematic studies on the relationship between TR-related genes (TRRGs) and MDD. This study aimed to develop a novel prognostic gene signature based on the TRRGs in MDD. We extracted expression information from the Gene Expression Omnibus (GEO) database and retrieved TRRGs from GeneCards. Expressed genes (TRRDEGs) were identified differentially, and their potential biological functions were analyzed. Subsequently, association analysis and receiver operating characteristic (ROC) curves were adopted for the TRRDEGs. Further, upstream transcription factor (TF)/miRNA and potential drugs targeting MDD were predicted. Finally, the CIBERSORT algorithm was used to estimate the proportions of immune cell subsets. We identified six TRRDEGs that were primarily involved in malaria, cardiac muscle contraction, and the calcium-signaling pathway. Four genes (CHGA, CCDC47, ACKR1, and FKBP11) with an AUC of >0.70 were considered TRRDEGs hub genes for ROC curve analysis. Outcomes showed that there were a higher ratio of T cells, gamma-delta T cells, monocytes, and neutrophils, and lower degrees of CD8+ T cells, and memory resting CD4+ T cells in TRRDEGs. Four new TRRDEG signatures with excellent diagnostic performance and a relationship with the immune microenvironment were identified.