Objective:To investigate the alterations in the topological properties of gray matter and white matter dynamic and static functional brain networks in patients with major depressive disorder (MDD) and bipolar depression (BDD) using graph theory analysis, and to evaluate the potential of their combination as biomarkers for differential diagnosis between unipolar and bipolar depression.Methods:From March 2021 to April 2024, inpatients were recruited from the Department of Psychosomatic Medicine, Zhongda Hospital, Southeast University, including 132 patients with MDD, 84 patients with BDD, and 91 healthy controls (HCs). Resting-state structural and functional MRI data were collected, and dynamic and static functional brain networks of gray matter and white matter were constructed. Graph theory analysis was applied to calculate global and nodal network properties, differences in topological attributes among the three groups were compared by One-way analysis of covariance, and Turkey′s post hoc test was used for further pairwise comparison. The network topology attribute indicators with statistically significant inter-group differences were selected using the Least Absolute Shrinkage and Selection Operator regression (LASSO) for feature classification. The diagnostic performance of combined gray and white matter network features for distinguishing MDD from BDD was assessed using receiver operating characteristic (ROC) curves and a random forest model.Results:In the analysis of the static gray matter functional network, both MDD and BDD patients showed abnormal local topological properties. Compared with HCs, the MDD group exhibited abnormal betweenness centrality (BC) in the left inferior frontal gyrus, left precuneus, left ventromedial occipital cortex, right ventromedial occipital cortex, and right anterior thalamus ( t=-3.95-3.62, all P<0.05). The degree centrality (DC) of the left and right anterior thalamus was also abnormal in the MDD group ( t=3.78,4.14, both P<0.001), as was the nodal efficiency (Ne) of the left precuneus and bilateral anterior thalamus ( t=2.37, 3.61, 3.82, all P<0.05). Compared with HCs, the BDD group showed abnormalities in DC and Ne of the left precuneus ( t=-2.76, P=0.014; t=-3.01, P=0.007). In the analysis of the dynamic white matter functional network, both MDD and BDD patients demonstrated abnormal temporal variability of local topological properties. Compared with HCs, the MDD and BDD groups showed reduced BC temporal variability in the left superior corona radiata ( t=-2.39, P=0.047; t=-4.28, P<0.001), and there were significant differences in DC temporal variability in the right posterior limb of the internal capsule and lentiform nucleus ( t=2.65, P=0.021; t=3.49, P=0.001) in MDD group compared with HCs and BBD. The differential diagnosis model combining gray and white matter dynamic and static network topological features achieved an area under the ROC curve of 0.80. Conclusion:Both MDD and BDD exhibit altered topological properties in static gray matter functional networks and dynamic white matter functional networks. The combination of these features may aid in the differential diagnosis of MDD and BDD.

Objective:To investigate the alterations in the topological properties of gray matter and white matter dynamic and static functional brain networks in patients with major depressive disorder (MDD) and bipolar depression (BDD) using graph theory analysis, and to evaluate the potential of their combination as biomarkers for differential diagnosis between unipolar and bipolar depression.Methods:From March 2021 to April 2024, inpatients were recruited from the Department of Psychosomatic Medicine, Zhongda Hospital, Southeast University, including 132 patients with MDD, 84 patients with BDD, and 91 healthy controls (HCs). Resting-state structural and functional MRI data were collected, and dynamic and static functional brain networks of gray matter and white matter were constructed. Graph theory analysis was applied to calculate global and nodal network properties, differences in topological attributes among the three groups were compared by One-way analysis of covariance, and Turkey′s post hoc test was used for further pairwise comparison. The network topology attribute indicators with statistically significant inter-group differences were selected using the Least Absolute Shrinkage and Selection Operator regression (LASSO) for feature classification. The diagnostic performance of combined gray and white matter network features for distinguishing MDD from BDD was assessed using receiver operating characteristic (ROC) curves and a random forest model.Results:In the analysis of the static gray matter functional network, both MDD and BDD patients showed abnormal local topological properties. Compared with HCs, the MDD group exhibited abnormal betweenness centrality (BC) in the left inferior frontal gyrus, left precuneus, left ventromedial occipital cortex, right ventromedial occipital cortex, and right anterior thalamus ( t=-3.95-3.62, all P<0.05). The degree centrality (DC) of the left and right anterior thalamus was also abnormal in the MDD group ( t=3.78,4.14, both P<0.001), as was the nodal efficiency (Ne) of the left precuneus and bilateral anterior thalamus ( t=2.37, 3.61, 3.82, all P<0.05). Compared with HCs, the BDD group showed abnormalities in DC and Ne of the left precuneus ( t=-2.76, P=0.014; t=-3.01, P=0.007). In the analysis of the dynamic white matter functional network, both MDD and BDD patients demonstrated abnormal temporal variability of local topological properties. Compared with HCs, the MDD and BDD groups showed reduced BC temporal variability in the left superior corona radiata ( t=-2.39, P=0.047; t=-4.28, P<0.001), and there were significant differences in DC temporal variability in the right posterior limb of the internal capsule and lentiform nucleus ( t=2.65, P=0.021; t=3.49, P=0.001) in MDD group compared with HCs and BBD. The differential diagnosis model combining gray and white matter dynamic and static network topological features achieved an area under the ROC curve of 0.80. Conclusion:Both MDD and BDD exhibit altered topological properties in static gray matter functional networks and dynamic white matter functional networks. The combination of these features may aid in the differential diagnosis of MDD and BDD.

Three patients diagnosed with COVID-19 were all young women in their thirties who have suffered from Internet violence in their personal life after hospitalization. They showed significant emotional distress such as, depression state, acute stress disorder, and dissociative disorder. The current study adopts short-term, individualized and comprehensive psychological interventions, including psychological support, encouragement, listening, safety confirmation, catharsis, psychological suggestion, and stimulation of internal potential to treat patients. The third case was provided with psychological interventions combined with antipsychotic treatment. After timely psychological interventions all three patients achieved sound results.

Three patients diagnosed with COVID-19 were all young women in their thirties who have suffered from Internet violence in their personal life after hospitalization. They showed significant emotional distress such as, depression state, acute stress disorder, and dissociative disorder. The current study adopts short-term, individualized and comprehensive psychological interventions, including psychological support, encouragement, listening, safety confirmation, catharsis, psychological suggestion, and stimulation of internal potential to treat patients. The third case was provided with psychological interventions combined with antipsychotic treatment. After timely psychological interventions all three patients achieved sound results.

Objective To investigate the promoting effect of individualized intervention on social function rehabilitation in patients with schizophrenia. Methods Total of 200 hospitalized patients with schizophrenia in a tertiary psychiatrichospital were selected as the research object and were randomly assigned to the study group ( n=100) and the control group ( n=100) . Patients in control group were treated with routine treatment and nursing, whilepatients in study group were given individualized intervention combined with routine treatment and nursing. Brief psychiatric rating scale ( BPRS) was used to assess the severity of the psychotic symptoms.Insight and treatment attitude questionnaire ( ITAQ) was used to assess the treatment compliance of patients. Activity of daily living scale (ADL) and personal and social performance scale(PSP) were used to assess their social function. Then, we compared the results of two groups that before and after the intervention. Results Before the intervention, there was no significant difference in BPRS, ITAQ and ADL scores between two groups ( P>0.05) . The PSP scores of the study group were lower than those of the control group ( P<0.05) . After the intervention, the ITAQ and PSP scores of two groups were significantly higher than those before the intervention, and the BPRS and ADL scores were significantly lower than those before the intervention ( P<0.05) . After the intervention, there was no significant difference in BPRS and ITAQ scores between two groups ( P>0. 05) . The ADL scores of the study group were significantly lower than those of the control group, and the PSP scores were significantly higher than those of the control group (P<0.05).Conclusions Personalized intervention enhances the patient′s self-care ability, daily activities ability and social competence, and promotes the recovery of social function.