Abstract:Objective To explore the clinical application of functional near-infrared spectroscopy （fNIRS） in distinguishing patients with generalized anxiety disorder（ GAD） alone from those GAD comorbid with attention deficit hyperactivity disorder（ ADHD）. Methods From October 2023 to May 2024， 34 adult patients with GAD alone were recruited as a control group， and 35 adult patients with GAD comorbid with ADHD were recruited as a study group from the outpatient and inpatient departments of the Second People's Hospital of Guizhou Province. The Adult ADHD Self-Report Scale（ ASRS） was used to assess participants' attention deficit and hyperactivity/impulsivity symptoms， while the Generalized Anxiety Disorder-7（ GAD 7） was employed to evaluate anxiety symptoms. FNIRS based on the 1-BACK task was used to detect changes in oxy-hemoglobin（ Oxy-Hb） concentration in the prefrontal cortex（ PFC） of both groups. Results The scores of the ASRS attention deficit subscale， hyperactivity subscale， and GAD-7 in study group were higher than those in control group， and the differences were statistically significant（ all P＜0.05）. Behavioral data indicated that there were no statistically significant differences in reaction time and accuracy between the two groups during the 1-BACK task（ all P＞0.05）. During the 1-BACK task， compared with control group， patients in study group exhibited statistically enhanced activation in multiple regions of PFC ［false discovery rate（FDR）- corrected P ＜ 0.05］， including the triangular inferior frontal gyrus（ channels 7，8，9）， middle frontal gyrus（ channels 15， 43）， dorsolateral superior frontal gyrus（ channels 16， 17）， and precentral gyrus（ channel 11）. However， when conducting a rank ANCOVA analysis with GAD-7 scores as a covariate to control for anxiety severity， all previously observed between-group channel differences were found to be statistically insignificant（ all P ＞ 0.05）. Additionally， the effect of GAD-7 as a covariate did not reach statistical significance across all channels （all FDR-corrected P ＞ 0.05）. Conclusions The severity of anxiety may serve as a key mediating variable influencing prefrontal cortical activation. When utilizing fNIRS to distinguish between GAD alone and GAD comorbid with ADHD， careful control of this confounding factor is essential.

Abstract:Correlation and gender differences between metacognition function and anhedonia in patients with stable schizophrenia

Abstract:Objective To explore the characteristics of serum IL-18 levels in first-episode drugnaive adolescent schizophrenia（ FEDNAS） patients and their correlation with clinical symptoms， so as to assess the potential of IL-18 to predict disease risk. Methods This study was a cross-sectional study. From September 2021 to June 2024， 99 patients with FEDNAS were recruited at the Fourth People's Hospital of Lianyungang， Kangda College of Nanjing Medical University to form the patient group. Concurrently，40 healthy controls matched for age and gender， assessed as having no history of psychiatric disorders， were recruited locally to form the control group. Serum IL-18 concentrations were measured in all subjects. The Positive and Negative Symptom Scale（ PANSS） was used to assess patients' clinical symptoms. The correlation between IL-18 levels and the symptom severity and duration of schizophrenia was analyzed. t-test， χ2 test， analysis of covariance， and Pearson/Spearman correlation analysis were used to evaluate betweengroup differences and variable correlations. Multiple linear regression was used to analyze the correlation between IL-18 and cognitive symptoms. Relative risk was calculated using modified Poisson regression， and attributable fractions and population attributable fractions were also computed. Results Eleven patients（ 11.11%，11/99） in patient group had a family history of mental illness. The total PANSS score of the patient was（ 80.65±15.85）. The serum IL-18 concentration in patient group（ 157.85±55.39） pg/ml was statistically lower than that in control group（ 194.07±62.57） pg/ml（ F=12.952，P ＜ 0.001， Cohen's d=0.63）. The level of IL-18 in FEDNAS patients was negatively correlated with PANSS cognitive factor score（ r= -0.357， P ＜ 0.001）， and positively correlated with disease duration（ rs=0.235，P=0.019）， with statistical differences. The IL-18 level in patients with a disease course of ＜ 2 years was statistically lower than that in control group（ F=7.905，P=0.001）. Based on the results of univariate analysis， all participants' IL-18 levels were divided into a high-expression group（ above the 67% quantile） and a low-expression group（ below the 67% quantile） according to the 67% quantile. Modified Poisson regression analysis revealed that low IL- 18 expression was statistically associated with the risk of FEDNAS［ RR=0.989， 95%CI（ 0.986，0.991）， P ＜ 0.001］. The attributable fraction（ AF） calculations indicated that low IL-18 expression reduced the individual risk of disease onset by approximately 1.11%， with a population attributable fraction（ PAF） of -0.74%. Conclusions Serum IL-18 levels in FEDNAS patients are lower than those in healthy controls， exhibiting a negative correlation with cognitive symptoms and showing pronounced changes in the early disease stage（ ＜2 years）. This suggests that decreased IL-18 levels may reflect an immune response pattern specific to the early disease stage and participate in the pathological process of cognitive impairment in FEDNAS.

Abstract:Objective To explore the severity of hyperhomocysteinemia（ HHcy） among latelife schizophrenia（ LLS） and to analyze its risk factors. Methods A retrospective study was conducted on 380 LLS and HHcy who were hospitalized at Nanjing Youan Hospital from January 1， 2024 to January 1， 2025. Demographic data， past medical history， medication， biochemical tests， and scale scores were collected by reviewing patient case records. Patients were categorized into three groups based on HHcy severity： mild group （Hcy10-＜15 μmol/L， n=156）， moderate group（ Hcy15-≤30 μmol/L， n=167）， and severe group（ Hcy＞30 μmol/L， n=57）. Univariate analysis was performed to analyze the general information of the three groups of patients. The variables with statistically significant differences（ P＜0.05） and variance inflation factor ＜5 in univariate analysis were included in the multivariate Logistic regression model to further analyze the risk factors influencing the severity of HHcy in elderly patients with schizophrenia. Results Univariate analysis revealed statistically significant differences among the three groups of patients in age， gender， weight， body mass index， triglycerides， total cholesterol， apolipoprotein B， uric acid， and cystatin C（ all P＜0.05）. Multivariate Logistic regression analysis showed that， using mild group as a reference increasing age［ OR=1.04， 95%CI（ 1.00， 1.09）， P＜0.05］， increased body mass index［ OR=1.18， 95%CI（ 1.10， 1.27）， P＜0.01］， elevated total cholesterol ［OR=1.47， 95%CI（ 1.10， 1.95）， P＜0.01］， elevated cystatin C［ OR=6.37， 95%CI（ 2.00， 20.27）， P＜0.01］ were risk factors for progression from mild to moderate severity， while female sex［ OR=0.54， 95%CI（ 0.32， 0.93）， P＜ 0.05］ was a protective factor. While using moderate group as a reference， Elevated total cholesterol ［OR=5.99， 95%CI（ 3.53， 10.18）， P ＜ 0.01］ and elevated cystatin C［ OR=14.30， 95%CI（ 2.44， 83.76）， P＜0.01］ were risk factors for moderate to severe progression， while female sex［ OR=0.24， 95%CI（ 0.09， 0.67）， P ＜ 0.01］ was a protective factor. Conclusions This study indicates that LLS exhibit a high prevalence of HHcy， with its severity influenced by multiple factors. Male gender， advanced age， elevated body mass index， total cholesterol， and cystatin C are independent risk factors， and the impact of total cholesterol intensifies with increasing disease severity.

Abstract:Objective To conduct a scoping review on risk prediction models for violent aggression behavior in patients with schizophrenia spectrum disorders， so as to inform future research and clinical decisionmaking. Methods Risk prediction models for violent aggression behavior in patients with schizophrenia spectrum disorders were systematically searched in 9 Chinese and English databases， including Chinese Biomedical Literature Data， China National Knowledge Infrastructure， VIP， WanFang Data， PubMed， Cochrane Library， CINAHL， Embase， and Web of Science. The search period was from January 1， 2014 to July 6， 2024. Data on modeling methods， validation and presentation formats， predictors， and predictive performance were extracted， and standardized reporting was conducted. Results A total of 18 articles were included， and the sample size of model construction ranged from 57 to 1 426. The incidence of violent aggression behavior in patients with schizophrenia spectrum disorders was from 24% to 79.70%. Logistic regression and various machine learning algorithm models were employed， with supervised machine learning method demonstrating the best performance in predicting such behavior. Common predictors included history of violent aggression behavior， negative symptoms， history of antipsychotic medication use， age， hospital stay， educational level and adherence. Conclusions Existing predictive models demonstrate some effectiveness in forecasting violent aggression behavior among individuals with schizophrenia spectrum disorders. In the context of artificial intelligence， multimodal clinical prediction models should be utilized to conduct accurate risk assessments of such behaviors and optimize the key influencing factors contributing to their occurrence， and thereby providing a basis for early clinical intervention decisions.

Abstract:Schizophrenia results from the interaction of environmental， individual， genetic， and immune factors， and is also associated with epigenetic modifications. Toxoplasma gondii is a widely distributed obligate intracellular parasite in nature. Approximately one-third of the global population has been infected with Toxoplasma gondii， but most cases are inapparent infections， with an infection rate of about 8% in China. Metaanalysis， ecological studies， and large-scale observational research indicate an association between Toxoplasma gondii infection and an increased risk of schizophrenia. However， as the pathogenesis of schizophrenia remains unclear， research into the impact of Toxoplasma gondii infection on schizophrenia has become a hot topic. Current mechanistic studies primarily focus on neuroinflammation and alterations in neurotransmitter systems， though definitive conclusions have yet to be reached. This review aims to systematically present research progress on the impact of Toxoplasma gondii infection on schizophrenia from epidemiological， immunological， and genetic perspectives， providing a reference for the early diagnosis of Toxoplasma gondii infection in patients with schizophrenia.

Abstract:Objective To explore the changes in hypothalamic-pituitary-thyroid（ HPT） axis hormones and inflammatory factor levels in non-suicidal self-injury（ NSSI） adolescents， and investigate the risk relationship with NSSI in adolescents. Methods A total of 62 depressive disorder adolescents who visited the Outpatient Department of Inner Mongolia Mental Health Center from March 2024 to May 2025 were selected as research subjects. Patients were divided into a depression-only group（ n=19） and a depression-with-NSSI group （n=43） based on the presence of NSSI. Levels of HPT axis hormones and inflammatory factors were measured by collecting blood samples from the elbow vein. A binary Logistic regression model was used to construct a risk prediction model for adolescent NSSI based on HPT axis and inflammatory factors， and a receiver operating characteristic（ ROC） curve was plotted. The predictive performance of the diagnostic model was evaluated using the area under the curve（ AUC）， optimal cutoff value， sensitivity and specificity. Results Compared with depression-only group， depression-with-NSSI group exhibited decreased thyroid-stimulating hormone（ TSH） levels［ （1.50±0.79） vs.（ 2.41±1.40）； t=3.267， P=0.002］， and increased neutrophil-to-lymphocyte ratio （NLR） levels［ （2.29±1.29） vs.（ 1.39±0.44）； t=-2.942， P=0.005］， with statistically significant differences. Binary Logistic regression analysis revealed that decreased TSH［ OR=0.415， 95%CI（ 0.212， 0.813）， P=0.010］ and increased NLR［ OR=16.941， 95%CI（ 1.586， 180.996）， P=0.019］ were statistically associated with an increased risk of adolescent NSSI. ROC curve analysis revealed that the AUC for predicting adolescent NSSI risk were 0.690 for TSH and 0.715 for NLR， with a combined AUC of 0.794（ P＜0.05）. Conclusions Both TSH and the inflammatory factor NLR are independent predictors of NSSI in adolescents， and have predictive effects on the risk of NSSI in adolescents.

Abstract:Objective To investigate the clinical characteristics and associated factors of suicide risk and anxiety symptoms in late-life depression（ LLD） patients at the acute phase. Methods A cross-sectional observational study was conducted to analyze data of 117 LLD patients accompanied by suicide risk and anxiety symptoms hospitalized at Beijing Anding Hospital affiliated with Capital Medical University between July 2021 and May 2022. This study collected patients' general information， clinical characteristics， cognitive function， five thyroid function parameters， adrenocorticotropic hormone， cortisol， total cholesterol， triglycerides， highdensity lipoprotein cholesterol， low-density lipoprotein cholesterol， and sex hormone levels. Hamilton Anxiety Rating Scale（ HAMA）， Hamilton Depression Rating Scale-24（ HAMD-24）， and Montreal Cognitive Assessment （MoCA） were used to evaluate anxiety， depressive symptoms， and cognitive function. According to the total score of HAMA， patients were divided into mild anxiety group（ HAMA score 14-＜21， n=47） and moderate to severe anxiety group（ HAMA score≥21， n=70）. Clinical symptoms， cognitive function， and endocrine hormone levels were compared between the two groups. Logistic regression was used to analyze risk factors for moderate-tosevere anxiety symptoms. Results Compared with patients with mild anxiety， those with moderate to severe anxiety had a higher proportion of married individuals［ 84.29%（59/70） vs. 68.09%（32/47），χ2=4.270］ and a higher proportion of prior history of traumatic brain injury［ 22.86%（16/70） vs. 6.38%（3/47）， χ2=5.611］， higher scores on the HAMD anxiety/ somatization factor［ 9.00（ 7.00，11.00） vs. 8.00（ 6.00，9.00）， Z=-3.259］， and sleep disturbance factor［ 6.00（ 4.75，7.25） vs. 6.00（ 3.00，6.00）， Z=-2.182］， and higher total HAMD-24 scores ［30.00（ 27.00，37.25） vs. 27.00（ 24.00，30.00），Z=-4.058］， and higher scores on the HAMA psychotic anxiety factor［ 14.00（ 12.75， 17.00） vs. 11.00（ 10.00，12.00）， Z=-6.687］ and somatic anxiety factor［ 17.00（ 15.00， 20.00） vs. 13.00（ 12.00，14.00），Z=-6.352］， and lower MoCA total scores［ （17.51±4.80） vs.（ 20.10±4.67） t=2.249］， and all differences were statistically significant（ all P＜0.05）. Logistic regression analysis revealed that the anxiety/somatization factor was a statistically significant risk factor of moderate-to-severe anxiety in LLD patients with suicide risk［ OR=1.636，95%CI（ 1.030，2.599），P=0.037］. Conclusions Among LLD patients with suicide risk and anxiety symptoms at the acute phase， those with moderate to severe anxiety are often married， have a history of traumatic brain injury， have severe depressive symptoms， and low cognitive function. The anxiety/somatization factor is a risk factor for moderate to severe anxiety symptoms.

Abstract:Claudin 5（ CLDN5） is a key structural component of intercellular tight junction proteins and has been identified as one of the most important intercellular tight junction proteins in the blood-cerebrospinal fluid barrier. Numerous studies have demonstrated that blood-cerebrospinal fluid barrier dysfunction is an important mechanism in the occurrence and progression of depressive disorder. CLDN5， one of the most important intercellular tight junction proteins in the blood-cerebrospinal fluid barrier， has also received much attention. This paper reviews the relationship between CLDN5 gene and the occurrence and treatment of depressive disorder， aiming to provide a reference for future research.

Abstract:Repetitive transcranial magnetic stimulation（ rTMS） is a widely used non-invasive neuromodulation method for the treatment of depressive disorders. Ineffective rTMS imposes significant financial and psychological burdens on patients with depressive disorders， hence the urgent need for reliable predictive biomarkers to predict clinical efficacy. This paper summarizes and discusses the electrophysiological and imaging biomarkers for predicting the efficacy of rTMS for depressive disorders， aiming to provide theoretical support to guide clinical practice in the treatment of depressive disorders.

Abstract: