Autism spectrum disorder (ASD) is a genetically complex neurodevelopmental condition with a high heritability. However, genomic studies of ASD have been underrepresented in East Asian populations, and the molecular yield in ASD cohorts remains modest. Here, we present a whole-genome sequencing analysis of 3109 samples across 1033 Chinese ASD families. By examining a wide spectrum of genetic variation, we identified rare ASD-associated variants in 19.2% of affected individuals, providing a population-specific view of the genetic architecture of ASD. We identify significant enrichment of de novo variants in probands, nominate or strengthen candidate risk genes (e.g., NCL, SPPL3, ADGRB1, SLC9A3, KIF1B) through mutational burden, evolutionary constraint, recurrent missense site, and functional assays, and implicate convergent pathways including protein palmitoylation. By integrating over 40,000 ASD cases across unpublished and published global cohorts, we identify 245 ASD risk genes, including 45 with limited prior evidence and 32 with no prior association. Single-cell transcriptomic profiling of the developing human cortex reveals that ASD risk genes exhibit widespread yet heterogeneous expression across all major cell types, with peak expression in excitatory neurons, particularly intratelencephalic neurons, and enriched expression in microglia (e.g., C1QC, CARD11, SNX13, MEF2C, FOXP2, TCF12, MED13L), suggesting convergent involvement of both synaptic and neuroimmune mechanisms. Together, our findings expand the ASD genetic landscape and suggest convergent pathogenic axes involving transcriptional regulation, synaptic signaling and plasticity, and neuroimmune interactions. This work supports the development of inclusive diagnostic strategies and provides a foundation for mechanistic and intervention exploration in ASD.

Epigenetic dysregulation plays an essential role in autism spectrum disorder (ASD), but the parent-of-origin effects (POEs) of DNA methylation remain unknown. Here, we applied PacBio HiFi sequencing with haplotype-phased methylation profiling in 124 individuals (31 ASD quartets) to systematically dissect POE-dependent methylation. Comparative analysis of phased methylomes between probands and unaffected siblings identified 114 paternal- and 106 maternal-specific differential methylated cytosines (DMCs), 45 and 46 differential methylated regions (DMRs), and 2425 and 2693 methylation outliers (MOs), respectively. These POE methylation alterations were enriched in ASD-relevant gene categories but exhibited distinct genomic distributions and functional pathways between parental haplotypes. Furthermore, genome-wide parent-of-origin DMR analysis identified 443 allele-specific methylation (ASM) regions, from which we detected 34 differential expression ASMs and 62 ASM outliers, showing pronounced enrichment within PWS/AS locus and ASD-associated genes. Collectively, this study provides a comprehensive evidence of pervasive POE-dependent methylation imbalance and aberrant ASM at imprinting regions underlying ASD pathogenesis, offering insights into epigenetic mechanisms of complex neurodevelopmental disorders.

Owing to the influence of genetic and environmental factors, complex associations exist between autistic traits in children with autism spectrum disorder (ASD) and their parents. However, little is known about the structure or the temporal stability of these familial associations, particularly from a network perspective. This study used network analysis to examine the interrelationships and longitudinal stability of autistic traits, as measured by the Social Responsiveness Scale, Second Edition (SRS-2), in 1294 ASD family trios at baseline and in 193 mother–child pairs at follow-up. Objective eye-tracking technology was employed to support the findings. Network analysis revealed that social communication was the most central domain across all family members. Parents and children were primarily associated through the dimension of restricted interests and repetitive behaviors (RRBs), and this pattern was supported by eye-tracking data. Comparisons between the baseline and follow-up networks revealed no significant changes in global strength, structure, or centrality, suggesting overall network stability over time. These findings contribute to a deeper understanding of the familial transmission of autistic traits and may offer insights for future etiological and intervention research on ASD.

OBJECTIVES:Self-injury behavior is a prevalent mental health problem among adolescents. Childhood maltreatment is closely associated with the development of alexithymia, impulsivity, and self-injury behavior in adolescents and young adults with mental disorders; however, the underlying mechanisms remain unclear. This study aims to classify psychiatric patients aged 12 to 24 years into psychological subtypes based on alexithymic and impulsive traits, to explore differences in self-injury behavior among these subtypes, and to examine whether different forms of childhood maltreatment are associated with specific psychological subtypes, thereby providing evidence for clinical intervention and prognosis improvement. METHODS:Clinical data of adolescents and young adults with mental disorders treated between 2021 and 2022 were retrospectively collected. Principal component analysis (PCA) was performed using 6 dimensions derived from the Toronto Alexithymia Scale (TAS)-20 and the Barratt Impulsiveness Scale (BIS)-11, including difficulty identifying feelings (DIF), difficulty describing feelings (DDF), externally oriented thinking (EOT), attentional impulsiveness, motor impulsivity, and non-planning impulsivity. Principal components with eigenvalues (λ) ≥1 were retained, and their scores were subjected to 2-step cluster analysis for automatic subtype classification. Differences among the subtypes were compared with respect to demographic characteristics, clinical features, and self-injury behavior-related characteristics. Multivariate Logistic regression models were subsequently used to examine associations between the identified psychological subtypes and different forms of childhood maltreatment. RESULTS:A total of 634 adolescents and young adults with mental disorders were included, among whom 459 (72.4%) had a history of self-injury behavior. The diagnostic distribution comprised depressive disorders (n=295, 46.5%), bipolar disorder (n=136, 21.5%), anxiety disorders (n=61, 9.6%), schizophrenia (n=14, 2.2%), and other disorders (n=128, 20.2%), including personality disorders, obsessive-compulsive disorder, post-traumatic stress disorder, somatoform disorders, and eating disorders. PCA reduced the 6 dimensions related to alexithymia and impulsivity into 2 independent principal components (Z1 and Z2). Based on individual scores on Z1 and Z2, 2-step cluster analysis automatically classified participants into 3 clusters (K1, K2, and K3). The psychological characteristics of the K1 group were characterized by high motor impulsivity accompanied by marked difficulties in identifying and expressing emotions. The K2 group exhibited relatively low levels of impulsivity and alexithymia. The K3 group was characterized by high attentional impulsivity, high non-planning impulsivity, and externally oriented thinking. No significant differences were observed among the 3 groups in the distribution of primary psychiatric diagnoses (P>0.05). Comparisons of self-injury behavior-related characteristics showed that the K2 group had significantly lower rates of self-injury, lower self-injury frequency, lower self-injury addiction scores, and lower self-injury motivation scores than the other 2 groups (all P<0.05). No significant differences were found between the K1 and K3 groups in self-injury prevalence, self-injury addiction scores, and external emotion regulation motives (P>0.05). However, the K1 group scored significantly higher than the K3 group on the motivational dimensions of social influence, internal emotion regulation, and sensation seeking, while exhibiting a lower frequency of self-injury behavior (P<0.05) in the last year. Multivariable Logistic regression analysis revealed that childhood emotional abuse may be a risk factor for developing the K1 psychological subtype; childhood physical abuse may be a risk factor for developing both K1 and K3 psychological subtypes; and childhood emotional neglect was associated with the development of K1 and K2 psychological subtypes. CONCLUSIONS:Adolescents and young adults with mental disorders can be classified into 3 distinct psychological subtypes based on alexithymia and impulsive traits. These subtypes differ in the prevalence and motivational characteristics of self-injury behavior, independent of clinical diagnosis. Furthermore, the development of different psychological subtypes may be associated with exposure to different forms of childhood maltreatment. These findings suggest that providing targeted emotional regulation and impulse-control interventions for adolescents exposed to specific childhood adversities may help reduce the occurrence and frequency of self-injury behavior.

BACKGROUND:Major depressive disorder (MDD) is diagnosed mainly through clinical interviews, highlighting a need for objective neurophysiological measures. Although P300 abnormalities have been well documented in adults with MDD, evidence in adolescents remains scarce. This study examined P300 alterations in adolescents with first-episode, drug-naïve MDD and evaluated its diagnostic potential. METHODS:A total of 182 adolescents with first-episode, drug-naïve MDD and 127 healthy controls (HCs) participated in the study. Electroencephalogram was recorded during a visual oddball task, and P300 amplitude and latency were extracted as features for support vector machine (SVM) classification between groups. RESULTS:Adolescents with MDD exhibited significantly reduced P300 amplitudes in response to both standard and target stimuli compared to HCs (all p < 0.05, Cohen's d = 0.263-1.139), with no group differences were observed in P300 latency (all p > 0.05). In the MDD group, P300 amplitude was negatively correlated with the Children's Depression Inventory scores (p < 0.001, r = -0.232 - -0.347). The SVM classifier based on P300 features achieved a maximum accuracy of 90.63%. LIMITATIONS:The proportion of females was significantly higher in the MDD group than in the HCs group. The performance of the SVM model has not yet been validated using an independent external dataset. CONCLUSION:Adolescents with MDD exhibit reduced P300 amplitudes, which were significantly associated with greater symptom severity. The SVM model demonstrated that P300 features effectively distinguish patients from HCs, underscoring their potential as objective neurophysiological measures for early identification and clinical assessment of adolescents MDD.

This study explored the interactions between emotional and behavioral symptoms in preschool children with autism spectrum disorder (ASD) and identified potential clinical subtypes based on these interrelationships. A total of 1886 preschool children with ASD and 285 age-matched typically developing (TD) children were assessed using the Child Behavior Checklist for ages 1.5-5. Symptom networks were estimated using the EBICglasso algorithm, and group differences were evaluated via network comparison tests. Subgroups within the ASD sample were identified using Individual Difference Symptom Networks (IDSN) with k-means clustering. The results revealed distinct network structures between the ASD and TD groups, with emotional reactivity demonstrating the highest centrality in the ASD network. Two distinct ASD subgroups (ASD-A and ASD-B) were identified, which showed significant differences from the TD group across all emotional and behavioral dimensionsin the CBCL 1.5-5. The subgroups differed significantly in overall network strength and specific edge connections, particularly between aggressive behavior and withdrawal problems. The findings indicate that emotional reactivity may play a central role in the symptom network of preschool children with ASD. The identification of two clinical subgroups with distinct symptom connectivity patterns provides valuable insights for developing more individualized and targeted intervention strategies. ASD-A subgroup points to the potential value of comprehensive early intervention programs, whereas ASD-B subgroup highlights the need for functional communication training and social engagement strategies.

BACKGROUND:Autism spectrum disorder (ASD) lacks rapid and effective interventions for its core social difficulties. The right temporoparietal junction (rTPJ), a critical hub for social cognition, together with gamma band abnormalities implicated in ASD, provides a promising neuromodulation target. METHODS:In this randomized, double-blind, sham-controlled trial, 47 children with ASD (39 male; mean [SD] age = 8.79 [2.71] years) were assigned to receive either 21 sessions of 40-Hz high-definition transcranial alternating current stimulation (tACS) targeting the rTPJ (3 sessions/day for 7 days) or sham stimulation, with assessments conducted at baseline, postintervention (week 1), and a 3-week follow-up (week 4). The primary outcome was change in Ohio State University Autism Rating Scale-DSM-5 (OARS-5) total scores. Secondary outcomes included the Aberrant Behavior Checklist-Second Edition, Social Responsiveness Scale-Second Edition, and Short Sensory Profile. Eye-tracking metrics during Frith-Happé animations were exploratory measures of theory of mind (ToM)-related social cognitive processing. RESULTS:The active group demonstrated significant improvements in OARS-5 total scores at week 1 (mean difference = -1.13, 95% CI [-1.78 to -0.47], p < .001) and week 4 (mean difference = -1.47, 95% CI [-2.20 to -0.74], p < .001). Improvements in selected behavioral and sensory domains were observed. Average fixation duration during ToM animations showed a significant group × time interaction. No serious adverse events occurred. CONCLUSIONS:These findings suggest that 40-Hz tACS targeting the rTPJ may be associated with rapid improvements in ASD symptom severity, particularly social functioning, in children with ASD, while being well tolerated. Clinical significance requires further evaluation.

BACKGROUND:Minimally verbal children with autism are understudied and lack effective treatment options. Personalized continuous theta burst stimulation (cTBS) targeting the amygdala and its circuitry may be a potential therapeutic approach for this population. METHODS:In a double-blind randomized controlled trial, minimally verbal children with autism (ages 2-8 years) received 4 weeks of cTBS. An amygdala-optimized functional connectivity (AOFC) group (n = 23) received personalized stimulation targeting a left dorsolateral prefrontal cortex site functionally connected with the amygdala. A non-optimized (NO) control group (n = 21) received stimulation at a standard prefrontal site. We assessed changes in Autism Diagnostic Observation Schedule scores, amygdala volume, spontaneous neural activity, and FC. RESULTS:Personalized AOFC-guided cTBS improved social and communication skills with an effect size twice that of the NO group (Cohen's d = 0.55 vs. 0.24). The AOFC group showed greater reductions in amygdala volume, spontaneous neural activity, and hyperconnectivity. Network-level amygdala connectivity changes with default mode, frontoparietal, and dorsal attention networks were correlated with clinical improvements. Field mapping analysis revealed that greater electric field overlap between standard and optimized targets predicted better treatment outcomes. CONCLUSIONS:Personalized AOFC-guided cTBS enhanced social skills and communication in minimally verbal children with autism by modulating amygdala structure and connectivity. Changes in amygdala network connectivity predicted clinical improvements, suggesting a mechanistic link between neural circuit plasticity and behavioral outcomes. These findings demonstrate the potential of precision-targeted neuromodulation in addressing a critical gap in autism treatment for this understudied population.

Background: Non-suicidal self-injury (NSSI) is a significant public health concern among adolescents, particularly in psychiatric settings, where prevalence rates exceed those observed in the general community. Childhood maltreatment (CM) is a known risk factor for NSSI; however, the mechanisms linking CM to NSSI are not fully understood.Objective: This study explored the mediating roles of stressful life events (SLEs) and negative affect (depression and anxiety) in the relationship between CM and NSSI, grounded in the cumulative adversity theory.Methods: In this cross-sectional survey, 226 Chinese adolescents (Mage = 14.76, SD = 1.70) admitted to a psychiatric unit participated. Measures included the Childhood Trauma Questionnaire (CTQ-SF), the Adolescent Self-Rating Life Events Checklist (ASLEC), the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and the Ottawa Self-Injury Inventory Chinese Revised Edition (OSIC). Structural equation modelling (SEM) was used to analyze mediation pathways.Results: Stressful life events and negative affect fully mediated the relationship between childhood maltreatment and NSSI. Specifically, CM indirectly influenced NSSI severity through increased negative affect (β = 0.088, 95% CI: 0.014-0.186, p = .039) and through a sequential pathway involving both SLEs and negative affect (β = 0.137, 95% CI: 0.072-0.251, p = .002). However, the pathway from CM to NSSI via SLEs alone was not significant (β = -0.053, 95% CI: -0.267 to 0.093, p = .565).Conclusion: The findings align with cumulative adversity theory, suggesting that childhood maltreatment elevates NSSI risk by increasing emotional distress in response to subsequent stressful life events. Targeted interventions should focus on helping at-risk adolescents manage stress and strengthen emotional resilience.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant clinical heterogeneity. Sex-based differences are observed in the core symptoms of ASD. This study investigated the patterns and stability of restricted and repetitive behaviors (RRBs) among Chinese children with ASD. For cross-sectional comparisons, researchers recruited 1760 male and 350 female participants whose ages ranged from 4 to 17 years. The Social Responsiveness Scale-2 (SRS-2) was used to measure the core symptoms of ASD. Compared with males, females exhibited lower severity and incidence rates of RRB both overall and at the symptom level. Furthermore, multigroup confirmatory factor analyses demonstrated that sex-related differences did not significantly affect the conceptualization of RRBs. An online follow-up study involving a subset of participants (166 males and 41 females) revealed that RRB symptoms remained stable between the two visits for males; however, only specific symptoms were highly consistent over time for females. This study revealed potential sex-related differences in RRBs among Chinese individuals with ASD and revealed sex-dependent variations in symptom-level presentation patterns and stability. These findings may contribute to a better understanding of the mechanisms underlying sex-related differences and aid in the development of sex-specific diagnostic criteria.

BACKGROUND:Non-suicidal self-injury (NSSI) poses a significant mental health challenge among adolescents, necessitating accessible and effective interventions. While the development of technology offers new opportunities, higher costs remain a concern. In this context, digital psychological interventions such as text message intervention (SMS) present a convenient and low-cost delivery method that requires no face-to-face contact. However, the extent to which this method could function as a viable strategy remains underexplored. OBJECTIVE:To evaluate the effectiveness of an SMS intervention specifically developed for NSSI among adolescents when combined with treatment as usual (TAU), compared to TAU alone. METHODS:A randomized controlled trial (RCT) was conducted with 86 Chinese adolescents, randomly assigned to either the SMS intervention plus TAU or TAU alone. The SMS intervention, consisting of text messages addressing NSSI-related knowledge, distress tolerance skills, and emotion regulation strategies, was administered over 8 weeks. Assessments were conducted at baseline, 4 weeks, and 8 weeks. RESULTS:Participants in the intervention group showed a significant reduction in NSSI behavior at 4 weeks (RR = 0.43, p < .001), though this effect was not significant at 8 weeks (RR = 0.84, p = .265). No significant changes in NSSI ideation were observed at 4 weeks (RR = 0.87, p = .221) or 8 weeks (RR = 1.10, p = .437). Resistance to NSSI urges increased significantly at 8 weeks in the intervention group (RR = 1.93, p = .002), but not at 4 weeks (RR = 1.44, p = .063). Secondary outcomes showed no significant changes. CONCLUSIONS:The low cost, scalability, and accessibility of SMS interventions make them a potentially valuable complementary tool for supporting self-harm populations. However, further research is necessary to confirm their efficacy across diverse settings and to determine how best to integrate them with comprehensive treatment strategies.

Background: Adolescents hospitalised for non-suicidal self-injury (NSSI) represent a particularly severe subset within psychiatric care. The NSSI imposes significant challenges on parents, including lack of knowledge, ineffective coping strategies, and negative emotions, exacerbated by stigma. Parental empowerment is crucial for supporting adolescent recovery; however, current interventions often neglect parents. Single-session interventions (SSIs) may offer an accessible and promising approach to address this gap. Methods: This mixed-methods study assessed the short-term effects of project CSH-P: a mobile-based, self-guided SSI aimed at empowering parents of adolescents hospitalised for NSSI. 88 participants were randomly assigned to CSH-P (n = 46) or control group (n = 42). Online assessments measuring knowledge, attitudes, and stigma were administered at baseline, immediately post-intervention, and one week later. Additionally, semi-structured individual interviews were conducted with participants who received CSH-P post-intervention. Results: Compared to the control group, participants who received CSH-P showed significant improvements in NSSI-related knowledge (Cohen’s d = .42, p = .027) and more positive attitudes toward their adolescents (Cohen’s d = - .31, p = .047). Qualitative findings confirmed these results, with parents reporting highly positive engagement and perceived empowerment across cognitive, emotional, and behavioural dimensions. Furthermore, parents provided constructive feedback for further enhancing the intervention’s impact. Conclusions: Project CSH-P demonstrates the potential to enhance parental empowerment in managing adolescent self-injurious behaviours. Its brevity, low cost, and ease of dissemination make it a promising strategy for widely applicable prevention and treatment efforts. Future research should explore the long-term sustainability of these improvements and assess the broader impact on parenting practices and adolescent treatment outcomes.

Violent behavior, defined as the intentional threat, attempt, or act of causing verbal or physical harm to others, poses a serious threat to public safety and social stability. Traditional violence risk assessment methods, such as unstructured clinical judgment and structured professional judgment, often suffer from high subjectivity, low predictive accuracy, and limited adaptability to dynamic risk changes. In recent years, the rapid development of artificial intelligence (AI) has provided new avenues for addressing these challenges. By integrating machine learning, deep learning, and natural language processing techniques, AI enables early, individualized, and multimodal risk detection based on physiological signals, facial expressions, linguistic features, and behavioral data. This paper comprehensively reviews and synthesizes the main applications of artificial intelligence in violence risk assessment, including machine learning - based predictive modeling, natural language processing for risk prediction, aggression detection based on physiological data, and multidimensional data - driven prediction. It further provides an in-depth analysis of the challenges related to interpretability, algorithmic bias, data privacy, and the limitations of existing research. Finally, the paper discusses strategies for the responsible development of AI technologies, emphasizing the critical role of interdisciplinary collaboration and ethical frameworks in clinical and forensic practice.

IntroductionSulforaphane (SFN) has been found to alleviate complications linked with several diseases by regulating gut microbiota (GM), while the effect of GM on SFN for autism spectrum disorders (ASD) has not been studied. Therefore, this study aimed to investigate the relationship between the effects of SFN on childhood ASD and GM through animal model and human studies.MethodsWe evaluated the therapeutic effects of SFN on maternal immune activation (MIA) induced ASD-like rat model and pediatric autism patients using three-chamber social test and OSU Autism Rating Scale-DSM-IV (OARS-4), respectively, with parallel GM analysis using 16SrRNA sequencing.ResultsSFN significantly improved the sniffing times of ASD-like rats in the three-chamber test. For human participants, the average verbal or non-verbal communication (OSU-CO) scores of SFN group had changed significantly at the 12-wk endpoint. SFN was safe and no serious side effects after taking. GM changes were similar for both ASD-like rats and ASD patients, such as consistent changes in order Bacillales, family Staphylococcaceae and genus Staphylococcus. Although the gut microbiota composition was significantly altered in SFN-treated ASD-like rats, the alteration of GM was not evident in ASD patients after 12 weeks of SFN treatment. However, in the network analysis, we found 25 taxa correlated with rats' social behavior, 8 of which were associated with SFN treatment in ASD-like rats, For ASD patients, we found 35 GM abundance alterations correlated with improvements in ASD symptoms after SFN treatment. Moreover, family Pasteurellaceae and genus Haemophilus were found to be associated with SFN administration in the network analyses in both ASD-like rats and ASD patients.DiscussionThese findings suggest that SFN could provide a novel avenue for preventing and treating ASD, and its therapeutic effects might be related to gut microbiota.

Thalamocortical (TC) circuits are essential for sensory information processing. Clinical and preclinical studies of autism spectrum disorders (ASDs) have highlighted abnormal thalamic development and TC circuit dysfunction. However, mechanistic understanding of how TC dysfunction contributes to behavioral abnormalities in ASDs is limited. Here, our study on a Shank3 mouse model of ASD reveals TC neuron hyperexcitability with excessive burst firing and a temporal mismatch relationship with slow cortical rhythms during sleep. These TC electrophysiological alterations and the consequent sensory hypersensitivity and sleep fragmentation in Shank3 mutant mice are causally linked to HCN2 channelopathy. Restoring HCN2 function early in postnatal development via a viral approach or lamotrigine (LTG) ameliorates sensory and sleep problems. A retrospective case series also supports beneficial effects of LTG treatment on sensory behavior in ASD patients. Our study identifies a clinically relevant circuit mechanism and proposes a targeted molecular intervention for ASD-related behavioral impairments.

BackgroundThe use of pre- and perinatal risk factors as predictive factors may lower the age limit for reliable autism prediction. The objective of this study was to develop a clinical model based on these risk factors to predict autism.MethodsA stepwise logistic regression analysis was conducted to explore the relationships between 28 candidate risk factors and autism risk among 615 Han Chinese children with autism and 615 unrelated typically developing children. The significant factors were subsequently used to create a clinical risk score model. A chi-square automatic interaction detector (CHAID) decision tree was used to validate the selected predictors included in the model. The predictive performance of the model was evaluated by an independent cohort.ResultsFive factors (pregnancy influenza-like illness, pregnancy stressors, maternal allergic/autoimmune disease, cesarean section, and hypoxia) were found to be significantly associated with autism risk. A receiver operating characteristic (ROC) curve indicated that the risk score model had good discrimination ability for autism, with an area under the curve (AUC) of 0.711 (95% CI=0.679-0.744); in the external validation cohort, the model showed slightly worse but overall similar predictive performance. Further subgroup analysis indicated that a higher risk score was associated with more behavioral problems. The risk score also exhibited robustness in a subgroup analysis of patients with mild autism.ConclusionThis risk score model could lower the age limit for autism prediction with good discrimination performance, and it has unique advantages in clinical application.

Background: Major depressive disorders (MDD) and bipolar disorders (BD) are the most common psychiatric diagnoses of suicide attempts (SA) in adolescents. However, little is known regarding the differences in incidence and clinical -related features of SA between these two disorders. The study aims to examine the SA incidence and related factors in adolescents with MDD versus BD. Method: A retrospective survey was conducted in outpatients. SA incidence, demographic characteristics and substance use history were collected. Symptom Checklist -90 was used to measure the severity of symptoms. The Revised Chinese internet addiction scale and Barratt Impulsiveness Scale -11 were utilized to assess the presence of internet addiction and impulsiveness. The Childhood Trauma Questionnaire was used to measure childhood maltreatment subtypes. Results: 295 MDD and 205 BD adolescents were recruited. The incidence of SA for MDD and BD were 52.5 % and 56.4 %, respectively. BD adolescents who attempted suicide showed worse symptoms, higher rates of nicotine and alcohol use, higher motor and non -planning impulsivity, and a more childhood physical abuse proportion than MDD adolescents with SA. Physical abuse in childhood was found to be associated with SA in both disorders (OR = 1.998 for MDD; OR = 2.275 for BD), while higher anxiety (OR = 1.705), and alcohol use (OR = 2.094) were only associated with SA in MDD. Limitations: Retrospective, cross-sectional design cannot draw causality, and biases in self -report measurements cannot be ignored. Conclusions: The findings revealed some difference between BD and MDD for adolescents with SA, and it emphasize significance of prompt identification and exact distinction between BD and MDD in adolescents.

Sulforaphane has been reported to possibly improve core symptoms associated with autism spectrum disorders from mostly small size studies. Here we present results of a larger randomized clinical trial (N = 108) in China. There were no significant changes in caregiver rated scales between sulforaphane and placebo groups. However, clinician rated scales showed a significant improvement in the sulforaphane group, and one third of participants showed at least a 30% decrease in score by 12 weeks treatment. The effects of sulforaphane were seen across the full range of intelligence and greater in participants over 10 years. Sulforaphane was safe and well-tolerated even for young children. The inconsistent results between caregiver and clinician rated scales suggest more clinical trials are needed to confirm our findings.

Non-suicidal self-injury (NSSI) is an issue primarily of concern in adolescents and young adults. Recent literature suggests that persistent, repetitive, and uncontrollable NSSI can be conceptualized as a behavioral addiction. The study aimed to examine the prevalence of NSSI with addictive features and the association of this prevalence with demographic and clinical variables using a cross-sectional and case–control design. A total of 548 outpatients (12 to 22 years old) meeting the criteria for NSSI disorder of DSM-5 were enrolled and completed clinical interviews by 4 psychiatrists. NSSI with addictive features were determined by using a single-factor structure of addictive features items in the Ottawa self-injury inventory (OSI). Current suicidality, psychiatric diagnosis, the OSI, the revised Chinese Internet Addiction Scale, the Childhood Trauma Questionnaire, and the 20-item Toronto Alexithymia Scale were collected. Binary logistic regression analyses were used to explore associations between risk factors and NSSI with addictive features. This study was conducted from April 2021 to May 2022. The mean age of participants was 15.93 (SD = 2.56) years with 418 females (76.3