Objective To explore the difference of serum inflammatory factors in patients with first episode schizo-phrenia,patients with relapse episode schizophrenia and healthy people,and the correlation between serum inflam-matory factors with negative symptoms in patients with schizophrenia,so as to provide reference for clinical inter-vention.Methods A total of 86 patients with first episode schizophrenia(first episode group),80 patients with re-lapse episode schizophrenia(relapse episode group)and 82 healthy people(control group)were included in the study.The difference of serum inflammatory factors among the three groups and the correlation between serum inflammatory factors with negative symptoms were analyzed.Results There were significant differences in serum interleukin(IL)-1β and IL-16 levels among the three groups(P<0.05).The analysis and comparison between the two groups showed that the serum IL-1β in first episode group was significantly higher than that in relapse episode group and control group(P<0.05),serum IL-16 in first episode group and relapse episode group was significantly higher than that in control group(P<0.05).Serum IL-1β was negatively correlated with PANSS general psycho-pathological scale factor score in first episode group(P<0.05),and serum IL-16 was positively correlated with PANSS negative symptom scale factor score in relapse episode group(P<0.05).IL-16 level might be an inde-pendent risk factor affecting the onset of first episode group and relapse episode group(P<0.05).Conclusion There are differences in serum levels of IL-1β and IL-16 between patients with schizophrenia and healthy people.Serum IL-16 levels in patients with relapse episode schizophrenia are associated with negative symptoms.IL-16 lev-el may be an independent risk factor for schizophrenia.

Objective:To predict suicidal behaviors in patients with bipolar disorder by constructing a machine learning model based on random forest and backpropagation neural network, and provide clinical decision support for the prevention and intervention of patient suicide.Methods:From January 2020 to August 2023, 1 005 patients with bipolar disorder were enrolled.The general clinical data and social dysfunction, anxiety, depression scores of all patients were collected.The random forest algorithm was applied for feature selection, and backpropagation neural network model was constructed for evaluating the model's fitting effect and predictive performance.Results:There were statistically significant differences in sociodemographic characteristics and physiological and psychological factors among the suicide attempt group ( n=293), suicide ideation group ( n=332) and non-suicidal group ( n=380) of patients with bipolar disorder( P<0.05).Using the random forest algorithm identified six main predictive variables: educational level, age, free triiodothyronine (FT3), cognitive impairment, hopelessness and psychogenic anxiety.The developed backpropagation neural network model achieved a precision rate of 79.3%, a recall rate of 79.6%, an F1 score of 79.4%, and an AUC of 0.89 on the test set, indicating that the model predictive performance has high accuracy and discriminative power. Conclusion:This study developed a machine learning model for predicting suicide in patients with bipolar disorder, which possesses high accuracy and discriminative ability, providing a decision-making basis for the prevention and intervention of suicidal behaviors in patients with bipolar disorder.

Objective:To predict suicidal behaviors in patients with bipolar disorder by constructing a machine learning model based on random forest and backpropagation neural network, and provide clinical decision support for the prevention and intervention of patient suicide.Methods:From January 2020 to August 2023, 1 005 patients with bipolar disorder were enrolled.The general clinical data and social dysfunction, anxiety, depression scores of all patients were collected.The random forest algorithm was applied for feature selection, and backpropagation neural network model was constructed for evaluating the model's fitting effect and predictive performance.Results:There were statistically significant differences in sociodemographic characteristics and physiological and psychological factors among the suicide attempt group ( n=293), suicide ideation group ( n=332) and non-suicidal group ( n=380) of patients with bipolar disorder( P<0.05).Using the random forest algorithm identified six main predictive variables: educational level, age, free triiodothyronine (FT3), cognitive impairment, hopelessness and psychogenic anxiety.The developed backpropagation neural network model achieved a precision rate of 79.3%, a recall rate of 79.6%, an F1 score of 79.4%, and an AUC of 0.89 on the test set, indicating that the model predictive performance has high accuracy and discriminative power. Conclusion:This study developed a machine learning model for predicting suicide in patients with bipolar disorder, which possesses high accuracy and discriminative ability, providing a decision-making basis for the prevention and intervention of suicidal behaviors in patients with bipolar disorder.

Objective : To explore the differences of serum inflammatory cytokines and tyrosine kinase with immunoglobulin and epidermal growth factor homology domains⁃2(Tie⁃2) levels between patients with first⁃episode schizophrenia and healthy people , and the correlation with clinical symptoms . Methods : A total of 168 participants were recruited , including 86 patients with first⁃episode schizophrenia (patient group) and 82 healthy people ( control group) . Demographic data , Positive and Negative Symptom Scale (PANSS) and Brief Psychiatric Rating Scale (PANSS) were collected at baseline . Serum inflammatory cytokines and Tie⁃2 levels were determined by MesoScale Discovery (MSD) . Results : Compared with the control group , the levels of serum interleukin (IL) Ⅳ1β and IL⁃4 in the patient group increased (P < 0. 05) , while the level of Tie⁃2 decreased (P < 0. 05) . IL⁃1β level in the patient group was positively correlated with the total score of BPRS , the score of BPRS hostility factor and the score of PANSS positive scale factor (P < 0. 05) . The positive score of PANSS and the total score of BPRS in the patient group had a positive effect on IL⁃1β level (P < 0. 05) . PANSS negative scale factor score , general psychopathological scale factor score and total score of PANSS in patient group also had positive effects on Tie⁃2 level (P < 0. 05) . IL⁃1β level in the patient group could effectively predict the severity of clinical symptoms in patients with first⁃episode schizophrenia at the critical level of 2 127. 076 pg/L , with specificity of 0. 675 and sensitivity of 0. 639 . The AUC of IL⁃1β and Tie⁃2 were 0. 836 1 and 0. 646 2 , respectively . Conclusion The levels of IL⁃1β , IL⁃4 and Tie⁃2 in patients with first⁃episode schizophrenia are different from those in healthy people . IL⁃1β levels in patients with first⁃episode schizophrenia are correlated with part of clinical symptoms . IL⁃1β and Tie⁃2 levels in the patient group may be influencing factors with high sensitivity and specificity in predicting the severity of clinical symptoms in patients with first⁃episode schizophrenia .

Objective:To explore the relationship between the childhood trauma and neruocognition in patients with schizophrenia.Methods:Sixty-two patients with schizophrenic were selected from Anhui mental health center, and sixty-three community health controls were selected. All subjects were assessed with the childhood trauma questionnaire (CTQ), Wisconsin card sorting Test (WCST), attention network test (ANT), verbal fluency test (VFT) and digit span test (DST). SPSS 17.0 was used for statistical analysis. t-test was used to compare the measurement data of normal distribution and Mann-Whitney U test was used to compare the measurement data of non-normal distribution. Spearman correlation analysis was used to analyze the relationship between CTQ score and cognitive function score. Results:Compared with health controls(34.00(30.00, 37.00), 6.00 (5.00, 7.00), 5.00(5.00, 5.00), 5.00(5.00, 5.00), 9.00(6.00, 11.00), 7.00(6.00, 10.00)), the total score of CTQ, subscores of emotional abuse, physical abuse, sexual abuse, emotional neglect and physical neglect in patients with schizophrenia were significantly increased (48.50(37.75, 57.00), 9.00(6.00, 12.25), 7.00(5.00, 9.25), 5.50(5.00, 7.25), 13.00 (9.00, 16.25), 11.00(8.00, 13.00)) ( Z=-4.781--6.724, all P<0.01). Compared with the control group, the number of WCST classification completed in the patient group was lower, while the number of wrong answers, continuous answers and persistent errors increased ( Z=-5.655--6.060, all P< 0.01). The correct rate of ant decreased, but the reaction time increased ( Z=-5.796, -6.094, all P< 0.01). VFT and DST scores were decreased ( Z=-3.492--8.499, both P< 0.01). In patients with schizophrenia, CTQ sexual abuse subscore were negatively correlated with completed categories scores ( r=-0.384) and positively correlated with total errors ( r=0.360), perseverative responses( r=0.394) and perseverative errors ( r=0.381) on WCST(all P<0.01). CTQ physical neglect scores were negatively correlated with the ANT correct ratio( r=-0.400) and conflict resolution( r=-0.417) (all P<0.01). CTQ emotional neglect scores were negatively correlated with VFT scores( r=-0.345) ( P<0.01). The significant associations remained after controlling for age, education and PANSS scores. Conclusion:Patients with schizophrenia experience more traumatic events in their early years and have extensive cognitive defects. The childhood trauma has negative effects on cognitive flexibility, attention, memory and speech function in patients with schizophrenia.However, the positive correlation between childhood trauma and executive conflict of attention network needs to be further verified and explored.

A 71﹣year﹣old male patient received venlafaxine hydrochloride sustained﹣release capsules 75 mg once daily orally for organic depressive disorder. On day 3 after medication,he developed mild gingival pain. The dose of venlafaxine hydrochloride sustained﹣release capsules was increased to 150 mg daily because of his condition. Three days later,his gingival pain aggravated significantly. Venlafaxine hydrochloride sustained﹣release capsules was stopped and oral care was given. On day 4 after the drug withdrawal,his gingival pain disappeared.

A 71﹣year﹣old male patient received venlafaxine hydrochloride sustained﹣release capsules 75 mg once daily orally for organic depressive disorder. On day 3 after medication,he developed mild gingival pain. The dose of venlafaxine hydrochloride sustained﹣release capsules was increased to 150 mg daily because of his condition. Three days later,his gingival pain aggravated significantly. Venlafaxine hydrochloride sustained﹣release capsules was stopped and oral care was given. On day 4 after the drug withdrawal,his gingival pain disappeared.