This study aims to investigate the associations of autistic traits and attention-deficit/hyperactivity disorder (ADHD) traits with internet addiction (IA) in general adolescents, and to examine the mediating roles of resilience and coping styles. A cross-sectional design was employed, involving 3003 middle school students. Data collection utilized the Autism Spectrum Screening Questionnaire (ASSQ), Swanson, Nolan, and Pelham-IV Rating Scale (SNAP-IV), the Resilience Scale for Chinese Adolescents (RSCA), the Simplified Coping Style Questionnaire (SCSQ), and the Revised Chinese Internet Addiction Scale (CIAS-R). Participants were divided into internet addiction (IA) and non-addiction groups based on the CIAS-R cutoff score of 53, with group differences analyzed via independent samples t-tests/Mann-Whitney U tests. Spearman correlation analysis was conducted to explore variable associations. Structural equation modeling (SEM) was constructed to test mediating effects, with the Bootstrap method (5000 resamplings) used for pathway validation. The IA group exhibited significantly higher scores on the ASSQ, SNAP-IV, and negative coping, along with lower scores on the RSCA and positive coping (p < 0.05). Significant correlations were observed among all variables (p < 0.01). Internal resilience, negative coping, and the “resilience → negative coping” serial pathway mediated the associations between ASSQ, SNAP-IV, and CIAS-R. External resilience uniquely mediated the relationship between SNAP-IV and CIAS-R. Resilience and coping styles mediate autistic traits, ADHD traits, and IA. Moreover, the associative pathways of these two traits differ. These findings provide preliminary insights into the psychological mechanisms underlying the associations between autistic traits, ADHD traits and IA in adolescents.

Depression and non-alcoholic fatty liver disease (NAFLD) are increasingly recognized as interconnected disorders, yet the causal mechanisms linking them remain unclear. Using univariable and multivariable Mendelian randomization (MR), we demonstrated that depression causally increased the risk of NAFLD (P = 8.473 × 10-8, OR = 1.944, 95% CI: 1.524 to 2.479), independent of major metabolic confounders. Mediation analysis further identified the gut microbial genus Phascolarctobacterium as a partial mediator of this effect (P = 0.0328, β = 0.145, 95% CI: 0.0119 to 0.278), with a mediated proportion of 21.818%. By integrating genetic mapping, transcriptomic profiling, and machine learning, we identified MICAL2 as a central hub gene linking depression-associated genetic variation to NAFLD. Furthermore, single-cell analysis revealed MICAL2-associated gene signatures are linked to macrophage dysfunction in NAFLD. Besides, molecular docking and dynamics simulations suggested that sanguinarine might target MICAL2 with stable binding affinity, highlighting a potential therapeutic avenue. Finally, experimental validation confirmed MICAL2 overexpression in liver tissues of NAFLD mouse models. Together, our findings support a mechanistic framework in which depression promotes NAFLD through a microbiota-mediated pathway converging on MICAL2 and macrophage dysfunction. These findings might have implications for risk stratification and early intervention of depression-induced NAFLD patients and offer novel insights into the brain-gut-liver interactions.

IntroductionThis study examined changes in regional homogeneity (ReHo) following Social Skills Training (SST) and their association with improvements in social deficits in individuals with autism spectrum disorder (ASD).Methods44 adolescents and adults with ASD (aged 12-30) were recruited, 38 participants (20 in training group, 18 in control group, matched for sex, age, and IQ) were retained after quality control of MRI data. The training group underwent magnetic resonance imaging (MRI) scans and assessments of Aberrant Behavior Checklist (ABC) and Social Responsiveness Scale (SRS) before and after a 14-week SST program, while the control group completed the same MRI scans and assessments at the same time point but did not receive SST.ResultsResting-state functional MRI analyses revealed significant group × condition interactions in five social brain regions, including the right medial frontal gyrus, right insula, and left medial superior frontal gyrus. At the endpoint of SST, the training group showed reduced ReHo in these regions alongside significant decreases in scores of ABC total, social withdrawal factor, SRS total, social awareness, social cognition, social communication factors. The control group, in contrast, showed only limited improvements on specific subscales, while the training group demonstrated a broader pattern of behavioral gains. We also found an exploratory association between the decrease in ReHo of the right medial frontal gyrus and the reduction in the ABC total score in training group.DiscussionThese findings indicate that SST may modulate local functional connectivity within the social brain networks, and these connectivity changes may correlate with observed behavioral improvements.

This two-arm, assessor-blinded, randomized controlled trial investigated the effect of a 16-week Executive Function Training Course (EFTC) based on the principles of ABA for preschool children with ASD. Seventy-two children aged 3–6 years were randomly allocated to the intervention group (EFTC + treatment as usual, TAU) or control group (TAU). Executive function (EF) served as the primary outcome, evaluated using both performance-based tasks and parent-report rating scales. Secondary outcomes included core autism symptoms, emotional-behavioral comorbidities, developmental progress, and parental stress. Linear mixed model analysis revealed significant group × time interactions for total EF [F (1, 67.94) = 9.712, p = 0.003], inhibition [F (1, 66.97) = 5.916, p = 0.018], and working memory [F (1, 67.15) = 6.173, p = 0.015] measured by the task-based EF assessment. No significant differences were observed in parent-reported EF or other secondary outcomes. These findings provide empirical evidence for the effectiveness of EFTC on EF in preschool children with ASD. More studies are needed to explore the effects of EFTC in ecological contexts, as well as on broader symptomatology and development, and long-term effects on EF in preschool children with ASD. Trial registration: The trial is registered in the Chinese Clinical Trial Registry, ChiCTR2400091585 (2024.10.30), https://www.chictr.org.cn/bin/project/edit?pid=249048.

Depression is a leading contributor to morbidity and disability among children and adolescents. Cognitive behavioural therapy (CBT) is a guideline-recommended first-line treatment, but access remains constrained by therapist supply, distance, and stigma. Smartphone-delivered Internet-based CBT (iCBT) has emerged as a scalable adjunct for adult populations, yet rigorous regulatory-grade evidence in Chinese paediatric and adolescent samples remains limited. This protocol describes a trial to determine whether a smartphone-delivered CBT-based digital therapeutic is superior to a matched health-education placebo in reducing depressive symptoms in Chinese children and adolescents with Major Depressive Disorder (MDD), and to characterize its safety. This is a prospective, multicenter, double-blind, placebo-controlled superiority trial at four tertiary-A hospitals in mainland China. Eligible children and adolescents aged 8–17 years meeting DSM-5 criteria for current MDD without psychotic features and scoring above 30 on the Children’s Depression Rating Scale–Revised (CDRS-R) at screening will be randomized 1:1 to an investigational smartphone-delivered CBT-based digital therapeutic (Model WL-PD) or to a visually matched health-education placebo. Both arms receive eight weeks of structured content; participants with moderate-to-severe severity (CDRS-R ≥ 57) additionally receive open-label fluoxetine under weight-banded dosing. The primary efficacy endpoint is the change in CDRS-R total score from baseline to Week 8. Secondary endpoints include CDRS-R change at Weeks 1, 2, 3, 4, and 6; response and remission rates; Clinical Global Impression scores; the Children’s Depression Inventory; the Conners’ Parent Symptom Questionnaire; and a Week-8 device-performance evaluation. Safety endpoints include adverse-event, serious adverse-event, and device-defect incidence. The planned sample of 214 participants (107 per arm) is powered at 80% to detect a between-arm difference of 4.6 CDRS-R points (assumed control SD = 10.7) with a one-sided α of 0.025 and 20% inflation for attrition. The primary analysis is an analysis of covariance on the Full Analysis Set adjusting for baseline CDRS-R; superiority is declared if the lower bound of the two-sided 95% confidence interval excludes zero, with a mixed model for repeated measures as a sensitivity analysis. The trial was prospectively registered and opened to enrolment in March 2026; recruitment is ongoing, with a planned close in December 2026. The last enrolled participant’s Week-8 visit is expected in the first quarter of 2027, and the primary analysis is anticipated within the following calendar year. The blinded, multicentre design and the integration of guideline-concordant pharmacotherapy where indicated address two persistent gaps in the paediatric digital therapeutics literature: methodologically rigorous control conditions and pragmatic alignment with real-world prescribing. The trial will contribute registration-grade randomized evidence for a smartphone-delivered digital therapeutic in paediatric MDD. Chinese Clinical Trial Registry, ChiCTR2600120453 (prospectively registered on 16 March 2026). Protocol version V1.1, 26 January 2026 (sponsor identifier BJWL-202512).

Objective This study aimed to examine age-related alterations in the topological properties of whole-brain white matter fiber networks in children and adolescents with autism spectrum disorder (ASD). Methods We conducted a cross-sectional analysis involving 146 individuals with ASD and 98 typically developing (TD) participants, aged 6–18 years. All ASD participants met DSM-5 diagnostic criteria. Diffusion tensor imaging (DTI) data were processed using DPABI to construct structural connectivity matrices. Graph theory-based global and nodal network properties were analyzed. General linear models were applied to assess the main effects of age and group, as well as age × group interactions. For effects that reached statistical significance, correlation plots were generated to visualize the relationship between imaging metrics and age. Results (1) In connectivity matrices, 1,032, 99, and 76 edges exhibited significant main effects of age, group, and age × group interaction, respectively (P < 0.05). After FDR correction, 116 edges remained significant for the main effects of age (P < 0.05). (2) For global properties, Eglob and Lp showed significant main effects of age (P < 0.05), while no significant group or interaction effects were observed (P > 0.05). (3) For nodal properties, 70, 44, and 39 brain regions exhibited significant main effects of age, group, and interaction, respectively (P < 0.05), though none survived FDR correction. Limitations: Key limitations include a modest sample size, imperfect sex and IQ matching between groups, and the cross-sectional design which precludes longitudinal inference. The age range was restricted to 6–18 years, excluding earlier and adult development. Some results did not withstand multiple comparison correction, warranting cautious interpretation. Conclusions White matter network topology undergoes dynamic development throughout school age and adolescence in both ASD and TD individuals, with potential group differences in specific regional connectivity and nodal properties.

Background To explore the relationship between autistic traits (AT), emotional symptoms, and adverse life events among adolescents in the Chinese general population, and examine whether resilience mediates autistic traits and emotional symptoms, as well as adverse life events. Methods 5666 current middle school students were enrolled to assess autistic traits using the Autism Spectrum Screening Questionnaire (ASSQ), emotional symptoms using the Child Depression Inventory (CDI) and the Screen for Child Anxiety Related Emotional Disorders (SCARED), adverse life events using the Adolescent Self-Rating Life Events Check-List (ALSEC), and resilience using the Resilience Scale for Chinese Adolescent (RSCA). Spearman correlations and linear regression analyses were used to explore the relationship between the scores of ASSQ, SCARED, CDI, and ASLEC. The Bootstrap percentile confidence method was used to analyze the potential mediating role of resilience. Results There were significant positive correlations between the ASSQ total score and its three subscales, including Social Interaction (ASSQ-SI), Communication Problems (ASSQ-CP), and Restricted and Repetitive Behaviors (ASSQ-RRB), and the scores of CDI, SCARED, and ASLEC; ASSQ-SI and ASSQ-RRB were significant positive predictors of the CDI, SCARED, and ASLEC; ASSQ-SI had a significant positive predictive effect on the four subscales of the ASLEC (Relationships Pressure, Academic Pressure, Being Punished, Loss, and Adaption Problem); RSCA (individual power and supportive power) mediated the ASSQ and CDI, SCARED, and ALSEC. Conclusion Significant relationships exist between autistic traits and emotional symptoms and adverse life events in Chinese general population adolescents, and resilience mediates the autistic traits and emotional symptoms and adverse life events.

Social skills training (SST) has demonstrated efficacy in improving social deficits in individuals with autism spectrum disorder (ASD), but the underlying neural mechanisms remain unclear. This study investigated alterations in whole-brain white matter network topology after SST in ASD individuals and explored potential correlation with improvements in social interaction deficits. 38 ASD patients aged 12 - 30 years were recruited, including 19 who completed magnetic resonance imaging (MRI) scans and social responsiveness scale (SRS) assessments at both baseline and the endpoint of a 14-week SST (training group) and 19 age-, sex-, and IQ-matched patients who underwent MRI scans and SRS assessment at the same time points but did not receive SST (control group). White matter connectivity matrices were constructed using diffusion tensor imaging (DTI), and graph theory analysis was used to assess global and nodal network properties. Paired t-tests and independent-samples t-tests were used for within- and between-group comparisons, respectively. Pearson's partial correlation was used to examine associations between network changes and SRS scores changes. After SST, four edges showed significant changes in white matter connectivity (FDR-corrected), with three increased and one decreased in the training group. Changes in nodal betweenness were also observed. While SRS scores significantly decreased in the training group, no significant correlations were found between neuroimaging changes and behavioral improvements, possibly due to the limited sample size. These findings suggest that SST may reshape white matter network, offering insights into its neural mechanisms and informing novel ASD intervention strategies.

Tic disorders are neurodevelopmental conditions that manifest in childhood or adolescence and can significantly impact the quality of life of affected children and their families to varying degrees. Integrated traditional Chinese and Western medicine treatment strategies have demonstrated more pronounced efficacy and better safety profiles. However, there is currently no standardized clinical expert consensus on this approach. To address this, the National Administration of Traditional Chinese Medicine initiated a project, and the China Association of Chinese Medicine assembled a team of authoritative domestic experts to develop this expert consensus, aiming to provide practical and feasible integrated treatment strategies for clinical practice. This consensus identified clinical issues through research, conducted literature reviews, and established evidence based on systematic evaluations. Expert surveys, two rounds of Delphi questionnaires, and expert consensus meetings were conducted to formulate a series of recommendations. We established a multidisciplinary consensus development panel. Based on systematic literature reviews, Delphi questionnaires, and consensus meetings, ten clinical issues were identified. Ultimately, a series of recommendations were developed, considering the balance of benefits and risks, the certainty of evidence, clinical feasibility, accessibility, and clinical acceptability. These recommendations comprehensively address key issues in the field of integrated traditional Chinese and Western medicine treatment, including indications for the use of Chinese or Western medicine alone or in combination, specific treatment protocols, methods for dose reduction and discontinuation, evaluation intervals, and the management of adverse reactions.

In daily conversations, people integrate multimodal cues from faces and adapt their gaze patterns to enhance comprehension according to the situation. Here we used eye-tracking to explore whether autistic individuals can adjust their face-viewing patterns flexibly when speech audio and visual information are asynchronous, with a primary focus on preschool-aged children. Participants from preschool cohort, including 72 autistic and 57 non-autistic individuals aged 3–6 years, watched videos of an actress speaking in either temporal synchrony or asynchrony conditions. We analyzed participants’ attention to the face, particularly the mouth, in both conditions. Full-sample data (ages 3–17 years, N = 228) are reported in supplementary materials for broader developmental context. We analyzed participants’ attention to the face, particularly the mouth, in both conditions. We discovered that both groups looked more at the face in asynchrony conditions and more at the mouth in synchrony conditions, suggesting they can detect speech audio-visual synchrony (AVS) and adjust their face-viewing patterns accordingly. Additionally, we found that the autistic group looked less at the face than the non-autistic group in both conditions. Our findings suggest that, like non-autistic individuals, autistic individuals are sensitive to speech AVS and can adjust their gaze patterns accordingly. However, these abilities may be hindered by their reduced face-looking time, resulting in less efficient and flexible integration of speech AVS, potentially impeding language development. These results provide novel insights for interventions in language development.

BACKGROUND:Play is an indispensable and meaningful activity in children's daily life. Research has shown that autistic children often exhibit differences in play development. The core traits of autism, such as distinct patterns in social interaction and communication, focused interests, and repetitive behaviors, frequently manifest in their play. Therefore, play may serve as an insightful measure of these differences. Unlike previous studies focusing on play behaviors only, we explored other behaviors associated with autism during free play, and constructed a clinical prediction model for effectively screening autistic children. METHODS:Participants, including 123 autistic children and 123 neurotypical children aged 1-6 years, engaged in a 1.5-min free play with fixed toys, which was videotaped. A novel behavior-coding scheme was used to code these videos for 19 autistic behaviors, including play. The coding details of the 19 behaviors were then converted and expanded to 81 digital behavior indicators, including counts, duration, and proportion. RESULTS:The autistic children showed less functional play and imaginative play and reduced social communication and interactions, such as eye contact, facial expressions, and vocalizations, compared to the neurotypical children during free play. Furthermore, 5 behavioral indicators were selected for the prediction model through stepwise logistic regression, including 1 on socially oriented vocalizations and 4 on count and duration of functional play. The receiver operating characteristic (ROC) curve revealed a good prediction performance with an area under the curve (AUC) of 0.826, a sensitivity of 85.4%, and a specificity of 68.3%. CONCLUSION:Our findings highlight differences in play performance and social communication and interactions during free play among autistic children. Based on these findings, we constructed a good clinical prediction model, which might be a potential digital tool used by clinicians to effectively screen autistic children.

Background:Early-onset schizophrenia(EOS)and autism spectrum disorder(ASD)are two mental disorders with abnormal neurodevelopment and overlapping clinical symptoms.However,few prospective multi-center imaging studies explored their pathophysiological differences and similarities comprehensively. Methods:We utilized a large cohort of functional magnetic resonance imaging data with standardized scanning protocols from 594 participants(276 participants with high-functioning ASD,187 participants with EOS,and 131 normal controls(NCs))recruited at five centers.A comprehensive evaluation of anatomical and connectomic features,in-cluding cortical thickness,subcortical nuclei volume,functional connectivity,functional gradients,and network efficiency,was conducted,culminating in the construction of imaging-based neuro-profiles for individuals with EOS and ASD. Results:The derived neuro-profiles revealed that EOS is characterized by more pro-nounced reductions in cortical thickness and subcortical nuclei volumes.In contrast,ASD exhibited more pronounced abnormalities in connectomic attributes.The de-creased network functional connectivity and compressed functional gradients in ASD are likely to contribute to reduced network efficiency.Classifiers based on imaging profiles successfully distinguished individuals with EOS,ASD,and NCs with com-mendable performance in leave-site-out cross-validation(area under the operating characteristic curve(AUC)for ASD vs.NC:0.769,AUC for ASD vs.EOS:0.792,AUC for EOS vs.NC:0.854). Conclusion:The neuro-profiles revealed that EOS and ASD exhibit overlapping as well as unique imaging characteristics;however,EOS exhibits greater structural variation,while ASD presents with more subtle connectomic abnormalities.These findings offer valuable insights into the distinct neurobiological mechanisms of EOS and ASD and enhance the prospect of early diagnosis through objective imaging-based biomarkers.

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

Individuals with autism spectrum disorder have deficits in facial emotion recognition and white matter microstructural alterations. Nonetheless, most previous studies were confounded by different variables, such as psychiatric comorbidities and psychotropic medications used by ASD participants. Also, it remains unclear how exactly FER deficits are related to white matter microstructural alterations in ASD. Accordingly, we aimed to investigate the FER functions, white matter microstructure, and their relationship in drug-naive and comorbidity-free ASD individuals. 59 ASD individuals and 59 typically developed individuals were included, where 46 ASD and 50 TD individuals completed FER tasks. Covariance analysis showed scores were lower in both basic and complex FER tasks in the ASD group. Tract-Based Spatial Statistics showed FA values in widespread white matter fibers were lower in the ASD group than in the TD group, including forceps major and forceps minor of the corpus callosum, anterior thalamic radiation, corticospinal tract, cingulum, inferior frontal-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus. Moreover, in the TD group but not the ASD group, the performance in the complex FER task was negatively correlated with the FA value in some white matter fibers, including forceps major of the corpus callosum, ATR, CT, cingulum, IFOF, ILF, SLF. Our study suggests children with ASD may experience deficits in facial emotion recognition and exhibit alterations in white matter microstructure. More importantly, our study indicates that white matter microstructural alterations may be involved in FER deficits in children with ASD.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by increasing prevalence, diverse impairments, and unclear origins and mechanisms. To gain a better grasp of the origins of ASD, it is essential to identify the most distinctive structural brain abnormalities in individuals with ASD.MethodsA Multi-Stage Progressive Feature Refinement Approach was employed to identify the most pivotal structural magnetic resonance imaging (MRI) features that distinguish individuals with ASD from typically developing (TD) individuals. The study included 175 individuals with ASD and 69 TD individuals, all aged between 7 and 18 years, matched in terms of age and gender. Both cortical and subcortical features were integrated, with a particular focus on hippocampal subfields.ResultsOut of 317 features, 9 had the most significant impact on distinguishing ASD from TD individuals. These structural features, which include a specific hippocampal subfield, are closely related to the brain areas associated with the reward system.ConclusionStructural irregularities in the reward system may play a crucial role in the pathophysiology of ASD, and specific hippocampal subfields may also contribute uniquely, warranting further investigation.

Objective: The study involved 17 children with Autism Spectrum Disorder (ASD), 21 with ADHD, 30 with both (ASD + ADHD), and 28 typically developing children (TD).Methods: The amplitude of low-frequency fluctuations (ALFF) was measured as a regional brain function index. Intrinsic functional connectivity (iFC) was also analyzed using the region of interest (ROI) identified in ALFF analysis. Statistical analysis was done via one-way ANCOVA, Gaussian random field (GRF) theory, and post-hoc pair-wise comparisons.Results: The ASD + ADHD group showed increased ALFF in the left middle frontal gyrus (MFG.L) compared to the TD group. In terms of global brain function, the ASD group displayed underconnectivity in specific regions compared to the ASD + ADHD and TD groups.Conclusion: The findings contribute to understanding the neural mechanisms underlying ASD + ADHD.

Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.

Objective: Verbal fluency, the capacity to generate words from a designated category, predicts myriad cognitive and life outcomes. The study investigated verbal fluency in children with ADHD, autism spectrum disorder (ASD), and comorbid ADHD and ASD, to understand how ADHD- and ASD-related symptoms individually and jointly predict verbal fluency, and the underlying linguistic and cognitive substrates.Method: Thirty-three school-aged children with ADHD, 27 with ASD, 25 with comorbid ADHD and ASD, and 39 with typical development, were assessed for ADHD and ASD symptoms and completed a semantic verbal fluency task.Results: Findings indicated that ADHD and ASD symptoms, especially ADHD hyperactivity-impulsivity symptoms and language-related ASD symptoms, interactively predicted verbal fluency across diagnostic groups.Conclusion: The study implicated the potential cognitive and linguistic mechanisms underlying verbal fluency differences in ADHD and/or ASD, and clinical practices on enhancing verbal fluency in these clinical groups.

OBJECTIVE:The current study aimed to investigate the dynamic changes in brain glymphatic function during chemotherapy in breast cancer patients (BCP) and their correlation with cognitive function. MATERIALS AND METHODS:A total of 40 healthy female participants (control group) and 80 female BCP were included. Various cognitive assessment tools were used to evaluate cognitive function. Diffusion tensor imaging along the perivascular space was employed to measure brain glymphatic function. RESULTS:Following chemotherapy, BCP exhibited a significant decline in various cognitive scores. After chemotherapy, the along the perivascular space index, a parameter indicating brain glymphatic function, was slightly higher than that at baseline and the control group levels and was correlated with cognitive scores. CONCLUSION:This study unveiled a close relationship between the dynamic changes in brain glymphatic function after chemotherapy and cognitive function in BCP. Our findings contribute to a deeper understanding of the brain mechanisms underlying chemotherapy-related cognitive impairment and provide a theoretical basis for future interventions and treatments. In addition, they offer a new perspective for exploring the relationship between brain function and cognitive states.

Background Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level. Objective This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children. Methods A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets. Results Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets. Conclusions Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.