1. Amjad MM, Javed H, Azeem MZ, Anwer T, Khan BW, Khattak MH, Khan UZ, Zahoor MA, Tabassum Z, Ehsan M, Sidra H, Ahmad H, Nazir S, Khan K. Efficacy of transcranial direct current stimulation in children and adolescents with autism spectrum disorder: A systematic review and meta-analysis. Brain Res. 2025: 150114.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication, repetitive behaviors, and loss of interests. Despite the use of conventional treatment such as medication and behavioral therapy, many children and adolescents still experience significant functional impairments. Recent advances in noninvasive brain stimulation have raised the interest of transcranial direct current stimulation (tDCS) in addressing core symptoms of ASD. METHODS: A comprehensive literature search of databases PubMed, Cochrane Library, and Google Scholar for relevant studies was conducted until March 28, 2025. A total of 1,443 records were identified. After duplicate removal and application of inclusion and exclusion criteria, 11 studies contributed to the Meta-analyses, while 28 studies were eligible for the systematic review. RESULTS: In addressing clinical outcomes, tDCS yielded significant improvement in social communication, the pooled data from 4 studies showed significant improvement in social communication (SMD =  - 0.66, 95 % CI [-0.94, -0.39] and p < 0.00001), social awareness was also improved with tDCS (SMD = -0.60; 95 % CI [-1.12, -0.07] and p = 0.03) however, language skill showed no significant improvement (SMD = -0.11; 95 % CI [-0.44, 0.21] and p = 0.50). Moreover, tDCS also showed enhancement in restrictive repetitive behaviors (SMD = -0.60, 95 % CI [-0.85, -0.34] and p < 0.00001). In addition, tDCS generated robust improvements in behavioral symptoms and regulations (SMD = -0.65; 95 % CI [-0.98, -0.32] and p < 0.001). Finally, for overall symptom severity reduction in ASD by tDCS, assessed by SRS score, exhibited statistical improvements (SMD = -0.64; 95 % CI [-0.89, -0.39] and p < 0.00001). However, the pooled analysis of 5 studies assessing ATEC score demonstrated no statistically significant difference (SMD = -0.61; 95 % CI [-1.34, 0.11] and p = 0.10) with high heterogeneity (p = 0.0006, I2 = 80 %). To overcome heterogeneity, we performed a sensitivity analysis, which made the result significant (SMD = -0.95; 95 % CI [-1.41, -0.49] and p < 0.0001) with low heterogeneity (p = 0.16, I2 = 42 %). CONCLUSION: tDCS appears to be a promising noninvasive therapy for improving social and behavioral symptoms of ASD. However, large-scale, multi-center RCTs with standardized protocols and longer follow-up durations are essential to determine optimal stimulation parameters and to identify which patients will benefit the most from it.

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2. Bhamidimarri PM, Alhosani K, Cai H, Al-Ali H, Abukhaled YM, Tawamie H, Abdelaziz S, Fawaz M, Kashir J, Sajjad Y, Mohiyiddeen L, Fakih M, Hamdan H. Review on the role of hippocampus in autism spectrum disorder: Recent insights into neuropathology, genetics, and emerging therapeutic strategies. Neurobiol Dis. 2025; 218: 107227.

The hippocampus, central to learning, memory, and social behavior, is increasingly implicated in the pathophysiology of autism spectrum disorder (ASD). Structural and functional disruptions in this region contribute to core ASD traits through impaired neurogenesis, abnormal dendritic morphology, excitatory/inhibitory imbalance, and altered connectivity with large-scale brain networks. Neuroimaging studies revealed changes in hippocampal volume, subfield-specific anomalies in the CA1 and dentate gyrus, and reduced functional connectivity within these regions. Genetic mutations in Shank3, Syngap1, Fmr1, and Nlgn3 disrupt synaptic plasticity and social memory circuits, while epigenetic alterations and environmental exposures further impair regulatory processes. Neuroinflammation exacerbates ASD pathology through microglial activation and cytokine release. Collectively, current evidence positions hippocampal dysfunction as central to ASD, emphasizing its relevance as both a biomarker and a therapeutic target to improve clinical outcomes.

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3. Cao D, Ni L, Qi Q, Zhou L, Wang J, Li Y, Zhang W, Wei J, Luo Y, Wang Y, Zhang F, Li S. Free Water Corrected Diffusion Magnetic Resonance Imaging Reveals Microstructural Alterations in Corpus Callosum Subregions of Preschool Children With Autism. Hum Brain Mapp. 2025; 46(18): e70435.

Autism spectrum disorder (ASD) is associated with white matter microstructural abnormalities, particularly in the corpus callosum (CC). This study employed free water corrected diffusion magnetic resonance imaging (fwc-dMRI) to investigate CC subregion-specific microstructural alterations in preschool children with ASD, which mitigates partial volume effects from extracellular free water. Sixty-one ASD children (6.03 ± 1.08 years) and 62 typically developing (TD) controls (6.49 ± 1.45 years) were enrolled in this study. In the ASD group, the symptom severity was assessed by the Autism Behavior Checklist (ABC). Fwc-dMRI technique, a bi-tensor tractography method, was used to investigate the white matter microstructure, which models free water and brain tissues through isotropic and anisotropic tensors to eliminate the partial volume effects caused by extracellular free water. The CC was segmented into seven subregions automatically according to its alignment to the cortex by a robust machine learning approach based on an anatomically curated white matter atlas. Fwc-dMRI-derived metrics were extracted for each CC subregion. Then we compared diffusion metrics between the two groups, and the correlation between the fractional anisotropy tissue (FA(t)) and the scores of the ABC scale was analyzed in ASD. Significant group differences were localized to CC6 (temporal lobe projections), showing reduced FA(t) (t = -3.251, p < 0.01) and elevated radial diffusivity tissue (t = 3.632, p < 0.01), and CC1 (orbital lobe projections), exhibiting decreased free water (t = -3.068, p < 0.05). FA(t) in CC2-5 negatively correlated with ABC scores (r = -0.36 to -0.52, p < 0.01), linking frontoparietal connectivity to the symptom severity of ASD. Fwc-dMRI identified distinct microstructural disruptions in CC subregions, implicating dysmyelination in temporal pathways (CC6) and abnormal axonal development in frontal projections (CC1). These findings highlight fwc-dMRI's potential for early ASD diagnosis and intervention monitoring. Free water corrected diffusion magnetic resonance imaging localized microstructural abnormalities in the corpus callosum subregions of preschooler with Autism spectrum disorder (ASD). The microstructural damage of the corpus callosum is related to the severity of symptoms in ASD. eng.

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4. Carter Leno V, Begum-Ali J, Goodwin A, Mason L, Pasco G, Narvekar N, Pickles A, Charman T, Johnson MH, Jones EJH. Cortical markers of excitation/inhibition balance are associated with sensory responsivity from infancy in longitudinal cohorts enriched for autism and ADHD. Transl Psychiatry. 2025.

Autism and ADHD are characterised by atypical sensory responsivity, and this may be driven by alterations in the balance of cortical excitation to inhibition (E/I). Studies early in development are required to establish when sensory responsivity differences emerge and whether they predict later neurodevelopmental condition outcomes. We utilised data from a prospective longitudinal cohort of infants with and without a family history (FH) of autism and/or ADHD (N = 151; 55% male, 83% white). We extracted electroencephalography (EEG) metrics of E/I balance at 5, 10 and 14 months; the aperiodic exponent of the slope of the power spectrum (‘1/f’). Models estimated latent growth curves of parent-reported hyper and hypo-responsivity between 10 – 36 months. Analyses tested associations between developmental trajectories of FH, sensory responsivity, parent-rated neurodevelopmental traits at 3 years and E/I balance. We coded and entered binary variables indexing FH-autism and FH-ADHD in the same model, which allowed us to test for effects of one form of FH whilst adjusting for the impact of the other. Results showed that FH-autism was associated with greater increases in parent-reported hyper-responsivity between 10-36 months (over and above the effects of FH-ADHD), and in univariate models for hyper-responsivity only, the intercept and the slope of hyper-responsivity were positively associated with both autistic and ADHD traits at age 3 years. However, in joint models which included hypo-responsivity, associations between hyper-responsivity and autistic and ADHD traits became non-significant. In these joint models, FH-ADHD was associated with steeper increases in hypo-responsivity (over and above the effects of FH-autism). Higher hypo-responsivity at 10-month baseline was associated with both autistic and ADHD traits at 3 years. A steeper slope of hypo-responsivity predicted ADHD traits at 3 years. Males displayed higher baseline hypo-responsivity. Aperiodic exponent values at 5 and 10, but not 14 months, were associated with hyper-responsivity. Results suggest a dissociation in the type of sensory responsivity associated with a family history of autism as compared to a family of ADHD, and that hypo-responsivity in infancy may be an indicator of later autism and ADHD outcomes. However, better measurement of each domain is required to draw strong conclusions as many hypo-responsivity items overlapped with autistic and ADHD traits. Alterations in E/I balance may contribute to early differences in sensory responsivity but further research is required to determine the directionality of effects.

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5. Chen W, Wang X, Zhu R, Gao W, Tao L, Yang R, Wei Q, Zhang Y, Gong Y, Zhong H, Huang L, Zhu X, Yang Y, Zhang L, Wan L, Yang G, Li Y, Jiao N, Wang J, Qin H, Zhu L. Integrative multi-omics reveals microbial genomic variants driving altered host-microbe interactions in autism spectrum disorder. Cell Rep Med. 2025: 102516.

Emerging evidence links the gut microbiome to autism spectrum disorder (ASD), yet the role of microbial genomic variation remains underexplored. We generated a large-scale metagenomic and metabolomic dataset from over 1,100 children, integrating public datasets, to characterize ASD-associated microbial changes. We identified 35 species, 213 genes, 28 pathways, and 99 metabolites, alongside 1,369 single-nucleotide variants, 233 insertions/deletions, and 195 structural variants with differential abundance. Profiling of microbial genomic variation revealed 33 species and 196 enzymes lacking abundance differences, yet exhibiting significant sequence variation. Integrated analysis of microbial variants and metabolites uncovered 357 neurological associations, with mediation analysis showing that several metabolites link microbial variants to the ASD phenotype. Importantly, diagnostic models incorporating microbial variant and/or metabolite features achieved superior performance and generalizability. Our findings highlight microbial genomic variation as a critical, previously overlooked dimension of ASD-associated dysbiosis, offering valuable insights for diagnosis and mechanistic studies.

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6. Damiao J, Damiao G, Polanco J, Lockwood M, Quinn J. Ethnographic Perspectives of Unreliable, Minimal and Non-Speaking Autism Associated With Apraxia. OTJR (Thorofare N J). 2025: 15394492251397894.

Individuals with unreliable, minimal, or non-speaking autism face significant challenges in expressing themselves. Historically, these communication difficulties have been attributed to cognitive deficits, however, emerging research suggests that apraxia, may be a primary barrier to effective communication. This study aims to explore the role of apraxia affecting speech, and how society views and supports communication. This auto-ethnographic study is informed by the lived experiences of three minimally speaking autistic individuals, highlighting the disconnect between cognitive capacity and expressive speech. The analysis resulted in the following themes: (a) apraxia as a global motor impairment and (b) disconnecting apraxia from intellectual function. This research underscores the need for adaptive communication strategies and inclusive policies that recognize intelligence and cognitive capabilities beyond verbal outputs. A shift toward understanding the impact of apraxia on communication within this population will foster more equitable access to education, health care, and social participation. Understanding How Movement Difficulties (Apraxia) Affect Communication in Non-Speaking AutismMany autistic people who speak very little, or whose speech is unreliable, are often misunderstood. In the past, these communication challenges were thought to reflect low intelligence. However, new evidence shows that a motor planning condition called apraxia may be a major reason why speech does not match what a person is capable of thinking or understanding. In this study, three autistic individuals shared their lived experiences through writing. Their stories revealed two key insights: (a) apraxia affects more than just speech—it can influence many kinds of movement and (b) difficulties with speech do not mean a lack of intelligence. These findings call for a shift in how society, educators, and health care providers view and support communication. By recognizing that motor challenges, rather than intellectual limits, often explain reduced speech, we can design better supports, create fairer opportunities in schools and health care, and promote true inclusion for autistic people. eng.

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7. Demirtaş Ş, Besalti M. The role of artificial intelligence interventions to improve eye contact for children with autism spectrum disorder: a systematic review. BMC Psychiatry. 2025.

BACKGROUND: Children with autism spectrum disorder (ASD) often struggle with eye contact during social interactions, a key aspect of effective communication. In recent years, various artificial intelligence (AI)-based interventions have been developed to support children with ASD. This study aims to systematically review the published literature on the AI-based interventions for improving eye contact. METHODS: The review adhered to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Two researchers searched six databases: Scopus, Web of Science, PubMed, APA PsycInfo, Education Source, and IEEE Xplore, which initially yielded 1663 records. After screening and eligibility assessment, 16 studies met all inclusion criteria. Data were extracted through a narrative synthesis focusing on key variables, including study characteristics (author, year, region, sample, design, setting, and duration), definitions and measurements of eye contact, AI tool, and technological modalities, findings including reported effectiveness, generalization and maintenance outcomes, as well as whether social validity was assessed in each study. Two researchers independently conducted data extraction, quality assessment, and risk-of-bias evaluation using the Joanna Briggs Institute (JBI) checklists and the Single-Case Experimental Design (SCED) scale. RESULTS: Included studies used a variety of AI-based tools. The most frequently used intervention modality was robotic systems, which were used in 12 studies, followed by wearable technologies (two studies), virtual reality (one), and game-based software (one). Preliminary findings suggest that AI technologies are often associated with increases in the frequency and duration of eye contact. Six studies (38%) assessed generalization of treatment effects, generally reporting positive outcomes, while seven studies (44%) assessed social validity. The research mostly utilized quantitative designs, including randomized controlled trials, repeated measure designs, single-subject research designs, and quasi-experimental designs. One qualitative case study and one case report were also identified. Methodological quality ratings ranged from moderate to high across study designs. CONCLUSION: This systematic review revealed that AI-based interventions are developing technology for improving eye contact behavior in children with ASD. Particularly, robotic systems provide promising evidence for improving eye-contact behaviors in children with ASD. However, the current evidence base remains limited due to small sample sizes and variations in the operational definitions of eye contact, measurement methods, and levels of AI sophistication. Data on generalization and social validity were also limited, highlighting the need for larger, methodologically rigorous studies to confirm these findings and assess their broader applicability. CLINICAL TRIAL NUMBER: This study did not involve clinical trials, and as such, there is no clinical trial number to report.

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8. Ismail M, Aananou S, Foguem C, Guinhouya KM, Dossou GT, Boudis F, Tchedre K, Vilhelm C, Guinhouya BC, Zitoun D. A systematic computational analysis of pharmacological options in neuroinflammatory-induced autism spectrum disorder in children: A potential for drug repositioning. J Biol Methods. 2025; 12(4): e99010079.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication and the presence of restricted or repetitive behaviors. Although its underlying pathophysiological mechanisms remain unclear, growing evidence indicates that neuroinflammation plays a significant role, especially in children. OBJECTIVE: This study aims to explore neuroinflammatory pathways in children aged 12 and under, with a focus on potential therapeutic opportunities through drug repositioning. METHODS: We conducted a systematic computational analysis using data from 27 studies and bioinformatics resources such as DrugBank and PubChem, identifying over 8,000 potential drug candidates from the initial 29 treatments retrieved from the literature. RESULTS: Key compounds such as cannabidiol, fluoxetine, and risperidone were highlighted for their broad therapeutic potential. In addition, emerging treatments, including cell-based therapies and dietary interventions, were explored. CONCLUSION: Our findings support drug repositioning as an effective strategy for developing new ASD treatments during critical developmental periods, emphasizing the need for further research to validate these pathways and the efficacy of innovative therapies.

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9. Kealhofer M, Brown R, Riley BP, Nguyen TH. Joint analysis of de novo mutations from autism spectrum disorder, schizophrenia, congenital heart disease, and other developmental disorders improves detection power and implicates shared molecular pathways and CNS processes. NAR Genom Bioinform. 2025; 7(4): lqaf162.

Rare exonic variant studies have previously implicated overlapping risk genes and pathways for autism spectrum disorder (ASD), severe, undiagnosed developmental disorders (UDDs), intellectual disability (ID), congenital heart disease (CHD), and schizophrenia (SCZ). Here, we use a two-trait Bayesian integrative analysis approach on 43 287 ASD, UDD/ID, CHD, and SCZ case trios to increase statistical power for gene discovery and to identify shared risk genes. At a posterior probability > 0.80, we identified 180 candidate risk genes for ASD, 315 for UDD/ID, 49 for CHD, and 47 for SCZ, including genes not previously reported, and also detected shared risk genes in pair-wise analyses. Gene set enrichment analysis of the ASD-UDD/ID, ASD-SCZ, and UDD/ID-SCZ shared risk genes overwhelmingly implicated gene sets associated with the synapse and epigenetic modification, while CHD-ASD shared risk genes were enriched in cell cycle phase transition gene sets, and CHD-UDD/ID shared risk genes implicated cardiac development. ASD-UDD/ID risk genes had elevated expression in interneurons and pyramidal cells, while ASD-UDD/ID and CHD-UDD/ID shared risk genes showed elevated connectivity in protein-protein interaction networks. Leveraging information across disorders with genetic overlap, both to increase power for candidate risk gene discovery and also as a method to elucidate shared genetic mechanisms.

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10. McAllister ML, McFayden T, Ravi S, Zwaigenbaum L, Schultz R, Estes A, Girault J, Shen M, Swanson MR. A Pause, Not a Stop: Language Regression in Toddlers at High Familial Likelihood of Autism. medRxiv. 2025.

Language development, a core pillar of social communication, has variable trajectories in autism that include a regression or loss of skills in roughly 20% of autistic individuals. Language regression is most frequently identified through parent report but can also be observed as a decrease in raw scores on a repeated language assessment (measure-defined). Later language outcomes after regression have been observed to be highly variable, but not lower than children without a language regression. The current study explores rates of parent-reported and measure-defined language regression in a large sample of infants at high familial likelihood of autism due to having an older autistic sibling. Among all participants at high familial likelihood for autism ( n =428), parent-reported regression was observed in 2.8% ( n =12) and was associated with 2.77 times higher odds of receiving an autism diagnosis. Measure-defined regression was observed in 8% ( n =36) and was associated with 1.21 times higher odds of autism diagnosis. These rates of regression are expectedly lower than estimates collected in autistic samples. Neither of these elevated odds was statistically significant and there was low concordance between these groups with only one participant present in both. Nearest-neighbor comparison samples of non-autistic infants at high and low likelihood for autism without language regression were selected to assess differences in language growth trajectories associated with regression. Infants with parent-reported language regression showed comparable language development to a matched high-likelihood sample while infants with measure-defined language regression showed slower overall language development than matched peers. Taken together, our results show that parent-report and direct measurement of regression capture unique aspects of child language development that may not be predictive of an autism diagnosis but may indicate delayed language growth in early toddlerhood. These language outcomes support previous findings of wide heterogeneity among those with regression and continued language growth after loss of skills. KEY POINTS: Language regression can be captured through parent-report or decrease in raw scores on repeated language assessment and is reported in approximately 20% of autistic toddlers.Most research on language regression uses retrospective report of regression in autistic children, but this study prospectively examines regression in toddlers at high familial likelihood for autism who do and do not receive later diagnoses.Parent-reported and measure-defined regression in this high-likelihood sample have low concordance indicating that these may be different events in language development.The presence of language regression was not associated with significantly higher odds of receiving an autism diagnosis.Children who exhibit language regression continue growing and developing language and those with parent-reported regression display comparable language skills to children without language regression at three years of age.

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11. Renne T, Benitière F, Poulain C, Dubuc A, Bourque VR, Huguet G, Nowakowski T, Jacquemont S. Genetic and Cortical Cell-Type Liability Architecture of Autism. bioRxiv. 2025.

Autism Spectrum Disorders (ASD) can result from rare genetic variants interfering with brain development. Whether their effects converge on specific cortical cell types remains unresolved. Previous studies have focused on a narrow set of high-confidence ASD (hcASD) genes, which were enriched in neuronal cell types during prenatal development. By contrast, studies of postnatal cerebral cortex have repeatedly associated ASD with transcriptional changes in both neurons and glia. To comprehensively map ASD genetic liability across cortical cell types, we conducted a functional genetic burden analysis with 124,416 individuals, including ASD probands and unaffected family members. We examined six classes of rare gene-disrupting variants aggregated across a complete spectrum of transcriptomic cell types of the human prefrontal cortex throughout development. We show that cellular liabilities in ASD delineate a broad and developmentally dynamic architecture. Likewise, we uncover high dependency on classes of variants with Loss-of-Function (LoF) and de novo linked to prenatal cells, while duplications, missense, and inherited variants increase liability through postnatal and glial cell types. Notably, inherited LoF variants uncover the contribution of microglia to ASD liability, also supported by transcriptomic evidence from postmortem ASD brains. Finally, we show that overall, variants disrupting genes differentially expressed in postmortem ASD brains significantly contribute to ASD liability, demonstrating convergence between disrupted transcriptomes and genetic liability. Together, our study offers an integrative, cell-type-aware framework for interpreting ASD risk genetics.

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12. Srivastava E, Ujjain S, Gandhi TK, Kumar S. CoarseFuse: Graph-Coarsening-Based Multi-Atlas Functional Connectivity Fusion for Autism Spectrum Disorder Diagnosis. IEEE J Biomed Health Inform. 2025; Pp.

Autism spectrum disorder (ASD) affects $\sim$1-2% of the population, yet reliable imaging biomarkers remain elusive. Resting-state fMRI (rs-fMRI) enables noninvasive mapping of large-scale connectivity, but single-atlas analyses miss multi-scale effects and many fusion methods trade interpretability for complexity. We present CoarseFuse, a subject-specific, graph-coarsening multi-atlas fusion framework that (i) builds a unified supra-graph from multiple parcellations with space+function cross-atlas affinities, (ii) performs a closed-form, correlation-informed Laplacian refinement with row-sum/PSD projection, and (iii) applies feature-aware local-variation coarsening (LVN) to obtain low-dimensional pseudo-atlases that retain ROI-level interpretability. On ABIDE I, CoarseFuse yields a balanced accuracy (BA) of 82.1% and F1 of 82.0% under stratified 5- fold cross-validation (multiple backbones), outperforming early/late fusion baselines; LVN reduces dimensionality by $\sim$73% (450$\rightarrow$120 nodes). A leave-one-site-out (17-site) evaluation demonstrates robustness to scanner/protocol variation ( macro BA $79.2\%\pm 4.1$; macro F1 $80.1\%\pm 3.9$). Ablations show that explicit cross-atlas edges improve BA by $\sim$1.4-1.5 points and closed-form refinement adds 0.6-0.9 points while improving spectral conditioning. The learned super-nodes align with canonical resting-state networks (e.g., default mode, salience), supporting biological interpretability. To our knowledge, this is the first closed-form Laplacian update tailored for multi-atlas rs-fMRI fusion. CoarseFuse advances rs-fMRI-based ASD diagnosis by combining accuracy, scalability, and transparent network-level insights.

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13. Tagavi DM, Puga S, Dick C, Dahiya AV, Bearss K, Locke J. Improving the Fit of Interventions for Autism in Schools: Lessons Learned Following Paraeducator Coaching on the RUBIES Program. J Educ Psychol Consult. 2025.

Implementing evidence-based behavioral interventions in school settings presents various challenges, particularly for paraeducators who often have limited formal training in working with autistic students, let alone specific behavior management strategies for this population. This study examined paraeducator feedback on the RUBI in Educational Settings (RUBIES) intervention, an adapted evidence-based behavioral intervention for schools. Sixteen paraeducators who participated in a randomized controlled trial of RUBIES completed semi-structured interviews, providing insights into the program’s strengths and areas for improvement. Using the Framework for Reporting Adaptations and Modifications – Expanded (FRAME), feedback was categorized into (a) positive feedback and (b) adaptation suggestions in the areas of (a) content and (b) implementation and scale-up activities. Paraeducators found RUBIES content effective in reducing challenging behaviors and improving student engagement. However, implementation barriers such as scheduling constraints, difficulty accessing materials, and limited coordination with broader educational teams were identified. Recommendations included expanding staff training and integrating digital tools for real-time strategy use and data collection. Findings highlight the need for ongoing monitoring and iterative adaptation of RUBIES implementation strategies in collaboration with community partners to ensure its feasibility and sustainability in school settings. Future research should focus on refining RUBIES and assessing long-term outcomes to enhance the program’s impact on paraeducators and autistic students.

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14. Towler JR, Kannan C, Soupioni C, Castle E, Fletcher-Miles H, Childs M, Donnelley S, Reinert-Joensen T, Brooks D, Tree JJ. Facial expression recognition in the broader autism phenotype: What does alexithymia have to do with it?. Cognition. 2025; 270: 106407.

Emotion recognition difficulties are widely reported in autism, but the « alexithymia hypothesis » proposes that such deficits are driven by co-occurring alexithymic traits rather than autism itself. We tested this hypothesis in a large sample of 556 adults spanning the broader autism phenotype, using self-reported autistic traits (Autism Quotient, AQ), alexithymia (Toronto Alexithymia Scale, TAS-20), and multiple face processing tasks. All participants completed an emotional expression discrimination task; Subsample 1 (N = 231) additionally completed an expression labelling task and Raven’s matrices, while Subsample 2 (N = 325) completed the Cambridge Face Memory Test. Across correlational, regression, partial correlation, and mediation analyses, autistic traits-particularly social-communicative difficulties-were the strongest and most consistent predictors of poorer emotion recognition. In contrast, the core alexithymia facets of difficulty identifying and describing feelings did not contribute unique variance once autistic traits were controlled. Importantly, externally oriented thinking (EOT) emerged as the only alexithymia facet with independent predictive value, consistently associated with reduced accuracy across both emotional and identity face recognition tasks. This suggests that EOT reflects a broader domain-general attentional style that deprioritises reflective engagement with socially salient information. Group-based analyses further confirmed that high autistic trait groups showed significant recognition impairments regardless of alexithymia levels. These findings challenge the alexithymia hypothesis and highlight autistic traits as primary drivers of emotion recognition difficulties, with EOT adding an additional, qualitatively distinct influence. The results call for revised multivariate models of face and emotion processing that integrate autistic traits, attentional orientations, cognitive ability, and gender.

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15. Wang XN, Luo WW, Li HY, Zhang T. Application of neurobiofeedback therapy technology on social skills and emotion regulation in children with autism spectrum disorder. World J Psychiatry. 2025; 15(12): 111522.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by difficulties in social communication, restricted interests, and repetitive stereotyped behaviors. In recent years, the prevalence of ASD has continued to rise, with boys having a significantly higher incidence rate than girls. Children with ASD often have intellectual and language impairments, which seriously affect their social skills, emotional regulation, and daily life. Although traditional treatment methods have shown some effectiveness, they still have limitations in addressing social and emotional regulation. Neurobiofeedback therapy is a noninvasive, drug-free treatment method that helps individuals regulate physiological responses through feedback mechanisms, and it has shown potential in various psychological disorders and emotional regulation. However, there is limited research on the social skills and emotional regulation in children with ASD. Therefore, this study aims to explore the impact of neurobiofeedback technology on children with ASD through a retrospective cohort study, supplementing existing treatment methods and promoting a more comprehensive treatment of ASD. AIM: To investigate the effects of neurobiofeedback therapy on social skills and emotional regulation in children with ASD. METHODS: A retrospective study was conducted on 92 children with ASD who were admitted to our hospital from January 2023 to June 2024. According to their different treatment plans, they were divided into a conventional group (conventional rehabilitation treatment; n = 43) and a combined group (conventional rehabilitation treatment combined with neurobiofeedback therapy; n = 49). The general characteristics, Aberrant Behavior Checklist scores, Chinese version of the Psycho-Educational Profile, Third Edition scores, Social Responsiveness Scale scores, Emotion Regulation Checklist scores, Social Communication Questionnaire scores, and the incidence of adverse reactions were compared between groups. RESULTS: After intervention, the Aberrant Behavior Checklist and Social Responsiveness Scale scores of the combined group were lower than those of the conventional group. In contrast, scores on the Chinese version of the Psycho-Educational Profile, Third Edition, Emotion Regulation Checklist, and Social Communication Questionnaire were significantly higher in the combined group than in the conventional group (all P < 0.05). There was no significant difference in the incidence of adverse reactions between the two groups. CONCLUSION: Neurobiofeedback therapy can effectively improve clinical symptoms, emotional regulation, and social skills in children with ASD.

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16. Wang XX. Maternal factors contributing to variability in gut microbiota and gastrointestinal function in autism spectrum disorders. World J Psychiatry. 2025; 15(12): 109906.

Autism spectrum disorder is a mental neurodevelopmental condition characterized by social deficits and repetitive behavior, and its development is influenced by genetic and environmental factors. Furthermore, an important factor in etiology is the health status of the mother during pregnancy. Maternal health can critically affect the development of the offspring’s nervous system, including the central nervous system and enteric nervous system. Unfavorable maternal health can disrupt the normal development of the offspring’s nervous system in various ways, such as changes in microbiota composition. As one of the common comorbidities of autism spectrum disorder, no consistent conclusion has been drawn on how poor maternal health affects enteric nervous system and central nervous system development in offspring. From the perspective of maternal health, this review discusses how maternal status affects the gastrointestinal health of offspring and the development of mental systems to raise public awareness of maternal health and provide a new idea for eugenics and childbearing.

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17. Wenger BM, Chang X, Mentch FD, Chaiyachati BH, DeMauro SB, Hakonarson H. Polygenic risk for autism spectrum disorder based on four group comparison across term and preterm birth. Sci Rep. 2025.

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18. Zhao Y, Xiao Z, Chen Z, Song Y. A Comparative Network Analysis of Parenting Stress and Affiliate Stigma in Parents of Children With ASD and ADHD. Clin Psychol Psychother. 2025; 32(6): e70205.

Children with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) present behavioural problems that contribute to caregiver stress and stigma. While trait mindfulness is considered a protective factor, the underlying mechanisms buffering the distress may differ due to differences in children’s problem behaviours. This study used network analysis to compare the interplay of parenting stress, affiliate stigma, child problem behaviours and parental trait mindfulness in parents of children with ASD (n = 174) versus ADHD (n = 108). We constructed psychological network models and compared node centrality to identify core components and pathways in their psychological networks. Parenting stress and affiliate stigma were central but differently structured in both networks. The ASD network featured strong links between the child’s prosocial behaviour, the node ‘Difficult Child’ of parenting stress and ‘Cognitive Stigma’ of affiliate stigma. In contrast, the ADHD network was defined by links between the nodes ‘Cognitive Stigma’ and ‘Affective Stigma’ of affiliate stigma and the child’s prosocial behaviour. Trait mindfulness was negatively associated with parenting stress and affiliate stigma, suggesting transdiagnostic benefits. These findings reveal distinct distress mechanisms, suggesting that interventions for ASD families should target children’s social skills, while those for ADHD families should focus on managing parent-child behavioural cycles.

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