Objective:This study aimed to develop and compare machine learning (ML) models for predicting depressive symptoms in adolescents, based on teacher-reported textual descriptions of student behaviors. Methods:Participants were 441 adolescents from Tianjin, China. Their teachers provided written reports on behavioral or emotional concerns, while the students completed the Patient Health Questionnaire-9 (PHQ-9). Text data from reports were processed using Term Frequency-Inverse Document Frequency (TF-IDF). Four ML models-Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Least Absolute Shrinkage and Selection Operator (LASSO)-were trained and evaluated using a 80/20 data split and 5-fold cross-validation. Results:PHQ-9 screening identified 71.7% (n = 316) of adolescents with clinically significant depressive symptoms (score ≥10). The Random Forest (RF) model demonstrated superior performance, achieving a recall of 0.97, accuracy of 0.91, precision of 0.92, and F1-score of 0.92. SVM and XGBoost also showed good performance, while LASSO was the weakest. The analysis demonstrated that teacher reports could identify depressive symptoms with up to 97% recall. Conclusion:Machine learning, particularly Random Forest, can effectively predict adolescent depressive symptoms from teacher-reported text. This approach offers a practical and efficient tool for early identification in school settings, facilitating timely intervention.

Background: Many studies have explored anhedonia-related functional connectivity (FC), but the findings remain inconsistent. There is a gap in identifying a consistent anhedonia-related damage network and applying it to TMS treatment. Methods: We systematically reviewed studies on anhedonia-related functional connectivity and identified anhedonia-related brain damage locations. Using a novel functional connectivity network mapping approach applied to a large normative connectome dataset, we mapped these damage locations to anhedonia-related damage networks. Subsequently, transcriptomic analysis was conducted to uncover underlying molecular mechanisms. Additionally, we investigated the application of the anhedonia-related damage network in transcranial magnetic stimulation (TMS) treatment, focusing on changes in FC within this network following TMS treatment and its association with anhedonia improvement, as well as predicting TMS treatment efficacy based on baseline FC within the anhedonia-related damage network. Results: A total of eight experiments from seven studies using the nucleus accumbens (NAc) as the seed were eligible for functional connectivity network mapping analysis. This study identified an anhedonia-related damage network, primarily characterized by disrupted functional connectivity between the NAc and the default mode network. Transcriptomic analysis revealed gene enrichment associated with synaptic signaling, neuronal development, ion transport, and actin cytoskeleton regulation. TMS treatment increased NAc functional connectivity within the anhedonia-related damage network in the response group, with these changes correlating with improvements in anhedonia. Furthermore, baseline NAc FC within this network demonstrated predictive potential for TMS treatment efficacy. Conclusion: The anhedonia-related damage network was identified, emphasizing its underlying mechanisms and predictive value for TMS in treating anhedonia. ### Competing Interest Statement The authors have declared no competing interest.

Premature mortality in schizophrenia is associated with comorbidity with metabolic syndrome (MetS). In China, existing studies have reported inconsistent findings regarding the prevalence of MetS among patients with schizophrenia, with limited nationally representative epidemiological data. This meta-analysis aimed to (1) determine the pooled prevalence of MetS in a Chinese population with schizophrenia and (2) systematically evaluate subgroup disparities across demographic, clinical, and treatment-related variables. The PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform, VIP Journal Integration Platform, and China Biology Medicine databases were searched for cross-sectional studies on the prevalence of MetS in China, without any search restrictions. Subgroup analyses were performed according to first-episode status, sex, age group, marital status, educational level, illness duration, body mass index (BMI), smoking history, alcohol-use history, family history of schizophrenia/diabetes/hypertension, and medication history. We included 73 studies with a total sample size of 34,655 patients with schizophrenia, including 10,944 patients with MetS. The pooled analysis revealed a combined prevalence of schizophrenia and MetS in China of 31.4

Abstract Backgroud This study aims to explore the relationships between self-esteem, resilience, social distress, and social avoidance among college students. It also examines the mediating roles of resilience and social distress in the relationship between self-esteem and social avoidance. Methods A convenience cluster sampling method was used to select all first-year students from a university in Yinchuan, Ningxia. Data were collected through an online survey administered via the WENJUANXING platform, which included a general information questionnaire, the Self-Esteem Scale, the Psychological Resilience Scale, and the Social Avoidance and Distress Scale. A total of 2513 first-year students completed the survey. SPSS 26.0 software was used to analyze the correlation between self-esteem, resilience, social distress and social avoidance, and the mediation model was tested by Mplus8. Results Self-esteem, resilience were negatively correlated with social distress scores (r = -0.411, p < 0.01; r =-0.387, p < 0.01, respectively). Self-esteem and resilience were negatively correlated with social avoidance scores (r = -0.437, p < 0.01; r = -0.379, p < 0.01, respectively). Social distress and social avoidance scores were positively correlated (r = 0.778, p < 0.01). Resilience partially mediated the association between self-esteem and social avoidance(β = -0.02, p < 0.01), with a mediation rate of 5.01%. Social distress partially mediated the associations between self-esteem and social avoidance(β = -0.203, p < 0.01) with a mediation rate of 50.87%. Resilience and social distress together (β = -0.06, p < 0.01) formed a mediating chain between self-esteem and social avoidance, with a mediation rate of 15.03%. Conclusions Self-esteem was negatively associated with social avoidance. Resilience and social distress were found to mediate the association partially.

Pathological anxiety is one of the most common mental health problems in adolescents. It is well documented that working memory, a core cognitive function, is often impaired in individuals with anxiety disorders. However, the computational mechanisms underlying these deficits in adolescents with anxiety disorder remain elusive. We used the classic delay-estimation visual working memory (VWM) task to assess the performance of adolescents with anxiety disorders (N = 39) and healthy controls (N = 41). Using a computational psychiatry approach, we tested 14 computational models established in basic research of VWM. Model comparison results identified the variable precision model as the best-fitting model for both groups, suggesting that the two groups share a qualitatively similar VWM process in completing the task. Subsequent analyses of the parameter estimates pointed to atypically reduced memory resources as the primary determinant of impaired VWM performance in adolescents with anxiety disorder. Crucially, the estimated memory resources in the anxious group predicted the severity of anxiety symptoms. Our results demonstrate that the reduced memory sources are the key factor mediating working memory deficits in adolescents with anxiety disorders, and this factor may also serve as a potential behavioral marker for future clinical interventions.

Aripiprazole is the most frequently recommended antipsychotic for the treatment of tics in children and adolescents with Tourette’s disorder (TD). However, to date, a randomized controlled trial for aripiprazole oral solution has not been conducted despite being widely preferred by children. Therefore, we examined whether aripiprazole oral solution is effective for treating tics. All patients received a flexible dose of aripiprazole oral solution (1 mg/mL, range: 2–20 mg) with a starting dose of 2 mg. The target dose for patients weighing < 50 kg was 2, 5, and 10 mg/day, and that for patients weighing ≥ 50 kg was 5, 10, 15, and 20 mg/day. The primary efficacy endpoint was the mean change in the Yale Global Tic Severity Scale-total tic score (YGTSS-TTS) from baseline to week 8. Of the 121 patients enrolled, 59 patients (96.7

In cognitive neuroscience, there is an increasing interest in identifying and understanding the synchronization of distinct neural oscillations with different frequencies that might support dynamic communication within the brain. This study explored the cross-frequency phase-amplitude coupling brain network characteristics of resting-state electroencephalograms between 30 children with attention-deficit/hyperactivity disorder (ADHD) and 30 age-matched typically developing children. Compared with control group, children with ADHD show increased coupling intensity and altered distribution patterns of dominant paired channels, especially in the δ-γH, θ-γH, α-γH, βL-γH, and βH-γH coupling networks. Regarding graph theory properties, the characteristic path length, the mean clustering coefficient, the global efficiency, and the mean local efficiency significant difference in many cross-frequency coupling networks, especially in the δ-γH, θ-γH, α-γH, βL-γH, and βH-γH coupling networks. The area under the receiver operating characteristic curve (AUC) in low-frequency coupling with a high-gamma frequency was larger than that in coupling with low-gamma frequency (AUC values of δ-γL, θ-γL, α-γL, βL-γL, βH-γL, δ-γH, θ-γH, α-γH, βL-γH, and βH-γH were 0.794, 0.722, 0.666, 0.570, 0.881, 0.992, 0.998, 0.998, 0.989, and 0.974, respectively). These findings demonstrate altered coupling intensity and disrupted topological organization of coupling networks, support the altered brain network theory in children with ADHD. The coupling intensity and graph theory properties of low-frequency coupling with high-gamma frequency were promising resting-state electroencephalogram biomarkers of ADHD in children.

Neurofeedback (NF) is a drug-free training intervention aimed at reducing symptoms of attention deficit/hyperactivity disorder (ADHD) by self-regulation of EEG rhythm features. It is worth exploring the effects on EEG rhythm characteristics and ADHD symptoms during training, as it can serve as crucial evidence of the efficacy and efficiency of NF training. Theta/beta NF training was performed by 21 children with ADHD, and EEG data were recorded during training. The average power of five EEG rhythmic features and the theta/beta ratio (TBR) were calculated using power spectrum analysis. The differences in therapeutic effects at each stage of NF training were assessed with the SWAN scale. Mean theta power calculated at Cz decreased significantly and relative beta power increased significantly during the last training compared to the first training period in children with ADHD. Moreover, TBR values decreased significantly at both Fz and Cz, which were highly suppressed in sessions 3 (approximately 36 trials) and 5 (approximately 60 trials) of the 5 stages. Mean gamma power at the last training increased significantly, as did the gamma activity in session 5 calculated at Cz during the training stage. The progressively increased SWAN scale values at each stage also showed the role of NF in the improvement of ADHD symptoms. This study shows that children with ADHD can self-regulate EEG rhythmic features and that ADHD symptoms are improved during NF. Changes in task-state EEG rhythmic power can be used as neurophysiological biomarkers of the efficacy and efficiency of NF training in ADHD.Funding Information: This work was supported by the National Natural Science Foundation of China (61175118 and 61977050) and Scientific Research Foundation of Tianjin Education Commission (2018KJ083).Declaration of Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Ethics Approval Statement: The entire experiment was performed voluntarily by the children and their guardians, and written informed consent was signed. The study was approved by the Ethics Committees of Tianjin Medical University on 4 January 2020., Study no: TMUHMEC202031.

This study aimed to investigate the factors that influenced the clinicians to adjust the paliperidone dose in the acute phase of schizophrenia. This was a post hoc study of an 8-week, open-label, single-arm multicenter trial which evaluated the efficacy, safety, and tolerability of flexible doses of paliperidone ER (3–12 mg/day) in patients with acutely exacerbated schizophrenia. Patients were divided into groups according to the dose at week 8 (3, 6, and 9–12 mg). The responder was defined as the reduction percentage in the Positive and Negative Syndrome Scale (PANSS) total score of ≥30%. According to the chi-squared automatic interaction detection algorithm, decision tree models predicting an increase in the dose of paliperidone ER were established. A decision tree, based on 4-week Marder positive factor, Clinical Global Impression (CGI), and BMI, was established to guide the dose adjustments of paliperidone ER in the acute phase of schizophrenia. The multivariable logistic regression analysis showed that lower age at onset, higher baseline PANSS positive subscale score, and lower baseline Personal and Social Performance Scale (PSP) score were significant predictors of increased dose in responders. Patients with young-onset age, severe baseline symptoms, and poor function are more likely to benefit from high dosage.

目的 研究注意力缺陷多动障碍(ADHD)儿童的格兰杰因果网络异常特征,分析二值化网络与权重网络拓扑属性差异.方法 采集22例ADHD儿童与14例健康儿童闭眼静息态脑电数据,使用定向传递函数构建因果连接矩阵,计算两组儿童二值化与权重网络的聚类系数与特征路径长度,并比较两组儿童优势导联对分布差异.结果 ADHD儿童聚类系数增加、特征路径长度降低,且权重网络差异更明显;两组儿童优势导联对都呈现自下而上的信息流模式,ADHD儿童优势导联对分布更加规则,优势导联对信息流主要流向F7、F8两个节点.结论 ADHD儿童脑网络存在异常密集连接和异常高速信息传递,脑网络模块化增强,集成能力减弱,脑网络趋向于规则网络.

The purpose of this study was to evaluate the application of the minimum clinically important difference (MCID) concept to clinical results in Chinese patients with acutely exacerbated schizophrenia. The original study was an 8-week, open-label, single-arm, multicenter study of flexible doses of paliperidone-extended release (pali-ER) in Chinese patients with acutely exacerbated schizophrenia. This is a post hoc analysis to determine the MCID value of PANSS, PSP and evaluate the responsiveness of each outcome measurements in the acute phase of schizophrenia. The responsiveness of the four measurements (PANSS, PANSS reduction rate, PSP, CGI-S) was analyzed. Four hundred ninety nine patients completed the 8-week follow-up and were finally used for this post hoc analysis. The MCID calculated by different approaches varied from 14.02 to 31.50 for PANSS, 15.14 to 42.79% for PANSS reduction rate, and 7.62 to 13.13% for PSP. In addition, the improvement of the CGI-S owned the highest responsiveness of the four outcome measurements. The threshold value of MCID for schizophrenia patients was determined by choice of the assessment method to an extent. In addition, the CGI-S score appeared to be the most valid and responsive measure of effectiveness for the acute phase of schizophrenia when take the treatment satisfaction of patients as anchor.

Altered functional networks in attention deficit/hyperactivity disorder (ADHD) have been frequently reported, but effective connectivity has hardly been studied. Especially the differences of effective connectivity in children with ADHD after receiving neurofeedback (NF) training have been merely reported. Therefore, this study aimed to explore the effective networks of ADHD and the positive influence of NF on the effective networks. Electroencephalogram (EEG) data were recorded from 22 children with ADHD (including data from children pretraining and posttraining) and 15 age-matched healthy controls during an eyes-closed resting state. Phase transfer entropy (PTE) was used to construct the effective connectivity. The topological properties of networks and flow gain were measured separately in four bands (delta, theta, alpha, and beta). Results revealed the following: pretraining children with ADHD manifested a higher clustering coefficient and lower characteristic path length in the delta band than healthy controls; weakened anterior-to-posterior flow gain in the delta band, strengthened posterior-to-anterior flow gain in the alpha band and strengthened anterior-to-posterior flow gain in the beta band were observed in pretraining children with ADHD; The topological properties and flow gain in posttraining children with ADHD were close to those of healthy controls. Moreover, parent’s SWAN presented significant improvements of ADHD symptoms after NF. Our findings revealed that the effective connectivity of ADHD was altered and that NF could improve the brain function of ADHD. The present study provided the first evidence that children with ADHD differed from healthy children in phase-based effective connectivity and that NF could reduce the differences.

目的 从 theta-gamma相位幅度耦合因果脑网络角度探讨注意力缺陷/多动障碍(ADHD)儿童可能的神经电生理机制.方法 22例 ADHD儿童作为病例组,14例健康儿童作为对照.采集两组受试者静息态脑电,使用平均向量长度方法计算所有导联对间 theta节律相位对 gamma节律幅度的耦合值,分别构建两受试组的因果连接脑网络,使用非参数检验分析两受试组间的耦合差异.结果 ADHD组导联内的耦合强度减弱,Fpl 、Fp2导联内的耦合强度显著低于对照组(P<0.05).两组受试者导联内的耦合强度与其作为幅度导联被其他脑区耦合的平均强度具有极强的正相关关系(对照组 rs=0.863 , ADHD组 rs=O.787 ,均 P<0.001).对照组以左额区(Fpl 、F3)、右枕区(O2)被其他脑区耦合为主,而ADHD组则以枕区(O1 、O2)被其他脑区耦合为主.与对照组相比,ADHD组前额区 (Fpl 、Fp2)被其他多个脑区耦合的强度显著降低,同时还存在脑区内和脑区间耦合模式转变.结论 前额区为主的多个脑区内耦合减弱,前额区被其他脑区耦合减弱,被耦合中心部分转移等因果脑网络异常,以及相位幅度耦合模式的转变可能是ADHD儿童静息态脑电特有的神经电生理特征.