Optimising immunisations for children with needle phobia and/or developmental disorders: a retrospective audit to inform policy and practice in Australia.

Integrating EEG microstate dynamics in a stacked ensemble for neurodiagnostic ASD assessment.

The oral-gut-brain axis is a path connecting the gastrointestinal tract and the central nervous system (CNS). The gut microbiota influences the immune system, metabolism, and nerve cells through the production of neurotransmitters and microbial metabolites that can cross the blood-brain barrier (BBB). The interplay between neuroinflammation and altered oral and gut microbiota is a bidirectional complex path modulated by inflammatory mediators. Recent studies suggest a potential role for Toll-like receptor (TLR) signaling pathways in the induction of neuroinflammation via the oral-gut-brain axis. As neuroinflammation is one of the key elements in the pathophysiology of neurodegenerative and neuropsychiatric disorders, this review was conducted to reflect on the pathophysiological pathways and clinical evidence on the role of TLR and inflammasome signaling pathways via oral-gut-brain axis in neurodegenerative diseases such as cognitive impairment, Alzheimer's disease, Multiple sclerosis, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis, and psychiatric disorders such as major depressive disorder, anxiety disorders, schizophrenia, bipolar disorders, and Autism spectrum disorders. Because the contributing factors have not been fully understood yet, further studies could help provide novel therapeutic opportunities.

Excessive electronic media use in early childhood is a potential risk factor for autism spectrum disorder (ASD), though evidence is inconclusive. This study examines screen exposure's relationship with ASD incidence and severity in Bangladeshi children. A hospital-based case-control study at the National Institute of Neurosciences and Hospital, Dhaka, Bangladesh from July 1 2022 to June 30 2023, enrolled 260 participants (130 with ASD per DSM-5 criteria and 130 age-matched controls). Data were collected via structured caregiver interviews on children's screen exposure (including any exposure in the first year, initial exposure age, daily duration, hours during the first year and maternal screen use). ASD severity was assessed using the Autism Diagnostic Observation Schedule (ADOS). Group differences were evaluated using t-tests and χ² tests and correlations between exposure variables and severity were examined using Pearson's coefficients. Eighty percent of ASD cases were exposed to screens in their first year, compared with 46.2% of controls (p<0.001). Mean daily screen time was 6.26±2.37 hours for cases and 1.72±1.29 hours for controls (p<0.001). Children with ASD began exposure earlier (13.68±8.21 vs. 18.09±5.42 months, p<0.001). Screen duration and infant hours showed significant positive correlations with ADOS severity scores (r ≈ 0.30, p<0.001), while age at first exposure correlated negatively (r = - 0.31, p<0.001). Early, prolonged screen exposure was significantly associated with ASD diagnosis and symptom severity. Though causality is not established, these findings emphasize delaying screen introduction and promoting interactive play during early development.

Maternal digit ratio (2D:4D), autistic traits, and autism spectrum disorder in offspring: A case-control study.

What do the records say: Autism spectrum disorder and higher education.

Global research consistently identifies significant disparities in the diagnosis of Autism Spectrum Disorder (ASD), strongly associated with family socioeconomic status and geographic location. However, such data from low-resource settings like Bangladesh is critically lacking. This case-control study aimed to characterize the socioeconomic and geographic profiles of children clinically diagnosed with ASD at a major tertiary centre in Bangladesh. The study was conducted at Department of Pediatrics, Mymensingh Medical College & Hospital, Bangladesh; Institute of Pediatric Neurodisorder and Autism (IPNA), BMU; Institute of Child and Mother Health (ICMH), Dhaka, Bangladesh from June 2021 to May 2022, enrolling 25 children with ASD and 25 typically developing controls aged 3-16 years. Data on key demographic indicators, including parental education, family income, place of birth and residence characteristics, were collected through parental interviews. Statistical analyses revealed profound disparities. Children with ASD were significantly more likely to come from families with higher parental education (Fathers: 80.0% vs. 16.0%; Mothers: 76.0% vs. 12.0%), higher monthly family income (92.0% vs. 44.0%) and an urban birthplace (80.0% vs. 32.0%). Furthermore, residence near a high-traffic road was a strongly associated environmental factor (92.0% vs. 44.0%). These findings highlight significant inequities in the pathway to an ASD diagnosis in Bangladesh, which are likely driven by differential access to specialized healthcare, varying levels of parental awareness and the urban concentration of diagnostic services rather than causal risk factors. The results underscore an urgent public health imperative: to develop and implement equitable strategies that enhance ASD awareness, decentralize diagnostic capabilities and ensure that all children in Bangladesh, irrespective of their socioeconomic background or place of residence, have an equal opportunity for timely identification and support.

Atypical neural synchronization in the temporal gyrus during face processing in children with autism spectrum disorder.

Monoallelic and biallelic KDM5A variants identified in patients with autism spectrum disorder.

Auditory brainstem responses in an animal model of autism spectrum disorder: Audiograms, sex differences and maturation changes.

To evaluate the therapeutic effects of exercise interventions in children and adolescents with autism spectrum disorder (ASD) using an umbrella meta-analysis. We systematically searched Embase, CINAHL, the Cochrane Library, Web of Science, PubMed, SinoMed, CNKI, Wanfang, and VIP for systematic reviews and meta-analyses of exercise-based interventions in ASD. Two reviewers independently assessed methodological quality and extracted data. We included 20 systematic reviews and meta-analyses comprising 14,245 participants. Exercise interventions were associated with enhanced social skills (SMD=0.52; 95% CI 0.28-0.76; P<0.001), improvements in repetitive stereotyped behaviors (SMD=0.49; 95% CI 0.29-0.69; P<0.001), and improved motor skills (SMD=1.16; 95% CI 0.64-1.68; P<0.001) in individuals with ASD. Exercise interventions are associated with improvements in social skills, repetitive stereotyped behaviors, and motor skills in children and adolescents with ASD. However, the overall certainty of evidence is low, and substantial heterogeneity and moderate-to-high overlap across meta-analyses warrant cautious interpretation. Exercise may represent a scalable, low-cost neuromodulatory adjunct within neurodevelopmental rehabilitation; future high-quality trials with long-term follow-up and clearly defined intensity and dose-response relationships are needed.

Sphingosine-1-phosphate drives astrocyte pyroptosis via activation of NLRC4 inflammasome in autism spectrum disorder.

In today's society, autism spectrum disorder (ASD) is a common neurological disorder that affects a person's behavior and communication. Hence, an early ASD prediction is essential for improving the lifecycle of ASD patients. Recently, many works have been deployed for diagnosing ASD using the electroencephalogram (EEG) and magnetic resonance imaging (MRI). But they are inefficient owing to the irrelevant noises and misclassification outcomes. Hence, a well-ordered logistic regression with scaled function-based deep learning neural network (LRSF-DLNN)-based ASD prediction using EEG and functional MRI (fMRI) is proposed. Initially, the inputs, like the EEG signal and fMRI image of the eye, are gathered and then subjected to the preprocessing phase. Here, for performing noise removal of EEG, the cosine-based Butterworth filter (CBF) approach is established. Similarly, the fMRI undergoes slice time correction and a GF filter-based smoothing process. Then, the preprocessed EEG is decomposed by utilizing weighted penalty factor-centric variational mode decomposition (WPFVMD), and the process of alpha and theta band estimation is performed on the basis of single-scale time dependent-based event-related spectral perturbation (SSTD-ERSP). Likewise, the features are extracted from both the decomposed EEG and smoothed fMRI. Next, the extracted features are given for feature selection (FS) utilizing distance functional green anaconda optimization (DFGAO). Lastly, the optimal features are given to the LRSF-DLNN classifier, which efficiently predicts ASD. Hence, the evaluation outcomes exposed that the proposed technique achieved better performance with a higher accuracy (98.8%) than other prevailing models.

The present study was conducted with the objective of investigating long-term outcomes in individuals diagnosed with autism spectrum disorder (ASD) during childhood. The investigation focused on current symptom severity and social functioning, and it examined the role of parental psychological well-being, empathy and parent-child relationships. A total of 64 subjects who had previously been diagnosed with ASD were the subject of a re-evaluation 7 years after their initial diagnosis. Participants were divided into two groups: those who retained their ASD diagnosis (n = 53) and those who no longer met diagnostic criteria (n = 11). The clinical assessments comprised CARS, ABC, SRS and ASSP for participants and BSI, FAST, EQ and PCRS for their parents. Multiple linear regression and correlation analyses were used to examine associations between autism symptom severity, social skills and parental variables. Greater autism severity was associated with lower social skills, reduced parental empathy and higher parental psychopathology. Parental empathy (EQ) and the positive dimension of the parent-child relationship (PCRS) were significantly higher in the loss of ASD group. Parental empathy (EQ) and child social functioning (ASSP) positively predicted the quality of the parent-child relationship (PCRS). Higher parental psychiatric symptoms (BSI) and lower child social functioning significantly predicted greater autism severity (CARS). The severity of autism and an individual's social functioning are closely interlinked, with child characteristics having strong predictive power. Parental mental health and empathy have been shown to have a significant impact on the developmental outcomes and relational dynamics of their children.

Participation of children with autism spectrum disorder in everyday activities: self-reports and primary caregivers' proxy-reports.

A two-step temporal data augmentation and supervised learning framework for predicting autism diagnosis at 36 months in patients with tuberous sclerosis complex.

Sleep disorders are frequently reported in individuals with anorexia nervosa (AN). Autism spectrum disorder (ASD) is strongly associated with both anorexia nervosa and sleep disturbances. We study the possible influence of the association of ASD to AN to the development of sleep disorders. A retrospective cohort study design was used, including all patients followed for AN or ASD in the child and adolescent psychiatric unit at the Salvator hospital, Marseille, between January 2019 and January 2024. We had included 491 patients, mean age was 15.16years±3.11years. Sleep was assessed with the PSQI, ESS and ISI; autistic traits with the Autism-Spectrum Quotient (AQ). Sleep disorders were significantly more prevalent in the anorexia nervosa binge/purge subtype group than the Anorexia nervosa restrictive subtype or the ASD groups with pathological scores in the PSQI in 78% (p<10-3), ISI in 46.3% (p=0.035) and in the ESS in 58.5% (p=0.017). The prevalence of sleep disorders was significantly higher in AN patients having pathological AQ score. However, when controlling for confounding factors, this association was no more significant. Our findings were inconclusive in establishing a clear association between autistic traits and sleep disorders in individuals with anorexia nervosa. However, a potential influence cannot be ruled out.

CVAE-guided triage and modular classifiers for multimodal ASD detection.

This paper aimed to unravel the effects of Yizhi Kaiqiao formula combined with repetitive transcranial magnetic stimulation (rTMS) on neurocognitive function and social outcomes in preschool children with autism spectrum disorder (ASD). In this randomized controlled trial, 178 preschool children with ASD recruited between January 2022 and February 2024 were randomly assigned to a combined group (Yizhi Kaiqiao formula + rTMS) or an rTMS-only group (n = 89 each). Both groups received a 3-month intervention. Pre- and post-intervention, TCM and Western medicine symptom severity (TCM syndrome scores, ADOS-2, CARS), inflammatory indicators (IL-6, TNF-α), neurocognitive function (MMN amplitude and latency, DCCS), social ability (SRS), and quality of life (PedsQL 4.0) were compared. Adverse event incidence was also recorded. Nine children in the combined group and seven in the rTMS-only group dropped out, leaving 80 and 82 completers, respectively. Post-intervention, the combined group showed greater improvements than the rTMS-only group in symptoms (TCM, ADOS-2, CARS), neuroinflammation/oxidative stress (IL-6, TNF-α), neurocognition (MMN, DCCS), social ability (SRS), and quality of life (PedsQL 4.0) (p < 0.05). Adverse event rates were low and comparable between groups (3.75%vs. 1.22%, p > 0.05). On the basis of conventional treatment, compared with rTMS adjuvant therapy alone, Yizhi Kaiqiao formula combined with rTMS is a relatively effective strategy for enhancing behavioral rehabilitation adjuvant therapy. https://www.chictr.org.cn/index.html.

ASDnet: Classification model for individuals with autism spectrum disorder using facial grid-wise expressions features and dual-branch visual transformation