OBJECTIVE: Autistic adolescents commonly experience sleep-related difficulties and prior studies have sought to separately examine physiological and family-level predictors of their sleep quality. The current study aimed to conceptually replicate and extend to an adolescent sample a prior study that found respiratory sinus arrhythmia was associated with sleep quality in autistic children. In addition, the current study also examined whether the quality of the family environment was associated with sleep quality in autistic adolescents.
METHODS: The sample consisted of 107 autistic adolescents who completed a baseline measure of respiratory sinus arrhythmia and then watched a video of their parents engaged in a discussion about a topic of disagreement while their respiratory sinus arrhythmia reactivity was measured. Adolescents also completed questionnaires measuring their sleep quality and family environment.
RESULTS: In regression models, adolescents\' physiological functioning was not a significant predictor of their sleep quality; however, adolescents living in poorer quality family environments reported worse sleep quality after controlling for their physiological functioning. The interaction between physiological functioning and the family environment predicting sleep quality was non-significant.
CONCLUSIONS: Although the current study did not conceptually replicate prior work, the findings highlight the importance of the family environment for adolescents\' sleep. Implications and future directions are discussed.

UNASSIGNED: Over the past few decades, there has been growing concern about the concurrent trends of increasing Autism Spectrum Disorder (ASD) prevalence and declining sperm quality. These trends represent significant public health challenges that warrant thorough investigation of their underlying causes and implications.
UNASSIGNED: The primary objectives of this study are to analyze trends in ASD prevalence and sperm quality parameters from 2000 to 2024, assess the statistical significance and effect size of these trends, explore potential correlations between ASD prevalence and sperm quality parameters, and identify significant predictors among sperm quality parameters that influence ASD prevalence.
UNASSIGNED: This study employed a longitudinal approach using multiple regression, time series analysis, ANOVA, Principal Component Analysis (PCA), hierarchical clustering, logistic regression, and cross-correlation analysis. Data on ASD prevalence were sourced from the CDC Autism and Developmental Disabilities Monitoring Network, while sperm quality data were collected from various published studies.
UNASSIGNED: The findings reveal significant negative associations between ASD prevalence and sperm quality parameters such as sperm concentration and motility, suggesting that better sperm quality is linked to lower ASD rates. Conversely, parameters like sperm DNA fragmentation (SDF), volume of ejaculate, pH level, and semen viscosity show positive associations with ASD prevalence, indicating higher values in these parameters correlate with higher ASD rates.
UNASSIGNED: The study highlights the importance of maintaining reproductive health to potentially mitigate ASD risk and calls for further research to elucidate the underlying mechanisms driving these trends. These findings support the hypothesis that reproductive health factors play a crucial role in ASD etiology and suggest potential biological markers for assessing ASD risk.

Autism Spectrum Disorder (ASD) is a neurological disorder that influences a person\'s comprehension and way of behaving. It is a lifetime disability that cannot be completely treated using any therapy up to date. Nevertheless, in time identification and continuous therapies have a huge effect on autism patients. The existing models took a long time to confirm the diagnosis process and also, it is highly complex to differentiate autism from various developmental disorders. To facilitate early diagnosis by providing timely intervention, saving healthcare costs and reducing stress for the family in the long run, this research introduces an affordable and straightforward diagnostic model to detect ASD using EEG and deep learning models. Here, a hybrid deep learning model called Cascade deep maxout fuzzy network (Cascade DMFN) is proposed to identify ASD and it is achieved by the integration of Deep Maxout Network (DMN) and hybrid cascade neuro-fuzzy. Moreover, hybrid similarity measures like Canberra distance and Kumar-hassebrook is employed to conduct the feature selection technique. Also, the EEG dataset and BCIAUT_P300 dataset are used for analyzing the designed Cascade DMFN for detecting Autism Spectrum Disorder. The designed Cascade DMFN has outperformed other classical models by yielding a high accuracy of 0.930, Negative Predictive Value (NPV) of 0.919, Positive Predictive Value (PPV) of 0.923, True Negative Rate (TNR) of 0.926, and True Positive Rate (TPR) of 0.934.

Pica is known to the medical community as an eating disorder in which individuals may ingest non-food items due to a nutritional deficiency and cause unintentional physical harm to themselves. This article discusses the cases of children with pica in addition to other comorbidities such as trichotillomania, depression, autism, and anxiety. Both patients were trialed on typical first-line treatments to address pica symptoms, including antidepressants, psychotherapy, and neurology consults, which were ineffective in treating pica symptoms. The introduction of naltrexone resulted in significant improvements, including decreased pica symptoms and improvements in depression, anxiety, and overall behaviors. These effects of naltrexone were further bolstered by the effects that occurred when both patients discontinued naltrexone for some time.

The aim of this study is to identify autism spectrum disorder (ASD) and attention-deficit-hyperactivity disorder (ADHD) traits in adolescents who experience psychotic-like experiences (PLEs), often ignored in clinical practice but widely prevalent in the general population. A total of 57 adolescents and young adults (aged between 16 and 24 years old) were recruited consecutively in the outpatient services. A total of 37 were females (64.9%), 18 were males (31.6%), and two participants (3.5%) were non-binary or gender non-conforming, with a mean age at referral of 18.26 ± 2.06. To investigate these symptoms, three sets of standardized questionnaires were used, as follows: the Autism Spectrum Quotient-short form (AQ-10), the Community Assessment of Psychic Experiences (CAPE-42), and the Adult ADHD Self-Report Scale (ASRS). We found significant associations between the ASRS and AQ-10 total scores and all CAPE scales. The model which explained the highest variance was CAPE Score\'s Total Frequency score (p < 0.001). Our findings underline the importance of investigating the presence of subthreshold ASD and ADHD symptoms in clinical populations, particularly in the period of adolescence and young adulthood, to promptly identify the presence of PLEs and, thus, prevent the onset of a frank psychotic disorder, particularly in the presence of a comorbid psychopathological condition, leading to better diagnosis and treatment for individuals with two or more of these conditions.

It is the current consensus amongst the psychiatric community that children undergoing evaluation for developmental delays and/or autism spectrum disorder (ASD) should be offered genetic testing early in the diagnostic process. Identifying genetic abnormalities can provide insight into patient prognosis and may reveal other medical complications that could arise throughout a patient\'s life. Despite these recognized benefits, genetic testing is often delayed or not offered and therefore deprives families of valuable knowledge about their child\'s future health outcomes. We present a case of a six-year-old patient who presented to our child and adolescent psychiatry office for behavioral concerns. She had received an ASD diagnosis years prior to presentation, but for unknown reasons, genetic testing had never been pursued. Genetic testing was obtained in our office, and the results revealed three different mutations that were linked to ASD and various other medical complications including epilepsy. With this knowledge, the patient\'s family gained important insight into their child\'s prognosis. This case highlights the necessity for adopting a point-of-care testing (POCT) model when evaluating children with developmental delays and/or ASD. Through this model, genetic testing would be offered to families during the initial visit for these patients. This would help streamline this process and allow for more widespread detection of genetic disorders linked to ASD and coexisting medical sequelae. Having this knowledge would empower families with a better understanding of their child\'s condition and would allow families to work together with providers to determine the best possible treatment plan.

This study had two aims. First, we aimed to investigate the prevalence of ACB, PCB, and oral habits among a group of Albanian children with ASD compared with a group of children without ASD. Second, we aimed to identify the associations of ASD with ACB, PCB, and oral habits. The sample inlcuded 125 children with ASD (91 males, 34 females) from 2 special schools for children with disabilities and 2 daily residential centers in Tirana. The control group included 125 children without ASD. The relationships between categorical variables were evaluated via the chi-square test. To identify the potential risk factors for ASD, we performed binary logistic regression. No statistically significant differences were found for CB or oral habits between the primary and adolescent dentition stages. A comparison of children with ASD with CB and oral habits revealed a significant difference in the prevalence of PCB. Binary logistic regression revealed that ACB, PCB and oral habits were not associated with ASD. CB was more prevalent among children with ASD in the primary and mixed dentition stages. Oral habits were more prevalent in the mixed and adolescent dentition stages. However, ASD is not a risk factor for CB or other oral habits.

Accumulating evidence proves that children with autism have gastrointestinal problems. However, a significant difference in gut microbiota (GM) exists between autistic and non-autistic children. These changes in the GM may stem from several factors. Recently, researchers focused on nutritional factors, especially vitamin deficiency. Thus, our systematic review investigates the connections among autism, GM alterations, and vitamin A deficiency (VAD), by analyzing studies sourced from PubMed and Embase databases spanning from 2010 to 2022. Adhering to PRISMA guidelines, we meticulously selected 19 pertinent studies that established links between autism and GM changes or between autism and VAD. Our findings uniformly point to significant alterations in the GM of individuals with autism, indicating these changes as promising biomarkers for the disorder. Despite the consistent association of GM alterations with autism, our analysis revealed no notable differences in GM composition between individuals with autism and those experiencing VAD. This suggests that VAD, especially when encountered early in life, might play a role in the onset of autism. Furthermore, our review underscores a distinct correlation between reduced levels of retinoic acid in children with autism, a disparity that could relate to the severity of autism symptoms. The implications of our findings are twofold: they not only reinforce the significance of GM alterations as potential diagnostic markers but also spotlight the critical need for further research into nutritional interventions. Specifically, vitamin A supplementation emerges as a promising avenue for alleviating autism symptoms, warranting deeper investigation into its therapeutic potential.

Autism is a neurodevelopmental disorder that manifests in individuals during childhood and has enduring consequences for their social interactions and communication. The prediction of Autism Spectrum Disorder (ASD) in individuals based on the differences in brain networks and activities have been studied extensively in the recent past, however, with lower accuracies. Therefore in this research, identification at the early stage through computer-aided algorithms to differentiate between ASD and TD patients is proposed. In order to identify features, a Multi-Layer Perceptron (MLP) model is developed which utilizes logistic regression on characteristics extracted from connectivity matrices of subjects derived from fMRI images. The features that significantly contribute to the classification of individuals as having Autism Spectrum Disorder (ASD) or typically developing (TD) are identified by the logistic regression model. To enhance emphasis on essential attributes, an AND operation is integrated. This involves selecting features demonstrating statistical significance across diverse logistic regression analyses conducted on various random distributions. The iterative approach contributes to a comprehensive understanding of relevant features for accurate classification. By implementing this methodology, the estimation of feature importance became more dependable, and the potential for overfitting is moderated through the evaluation of model performance on various subsets of data. It is observed from the experimentation that the highly correlated Left Lateral Occipital Cortex and Right Lateral Occipital Cortex ROIs are only found in ASD. Also, it is noticed that the highly correlated Left Cerebellum Tonsil and Right Cerebellum Tonsil are only found in TD participants. Among the MLP classifier, a recall of 82.61 % is achieved followed by Logistic Regression with an accuracy of 72.46 %. MLP also stands out with a commendable accuracy of 83.57 % and AUC of 0.978.

BACKGROUND:  Caring for a child with autism spectrum disorder (ASD) is a challenging and stressful task, especially in countries with limited resources. Additional research is necessary, considering the increasing prevalence of children with ASD, to gain increased knowledge of the complex difficulties faced by caregivers of ASD children and to offer insights into the coping strategies and support networks that parents utilise.
OBJECTIVE:  The objective of this study was to explore and describe the experiences and coping mechanisms of caregivers of children with ASD in Dr Kenneth Kaunda district, North West province, South Africa.
METHODS:  Qualitative explorative, contextual and descriptive design with purposive sampling technique and semi-structured interviews were conducted. Data were analysed following the six steps of reflexive thematic analysis.
RESULTS:  Two themes were identified: Caregivers\' experiences in raising a child with autism, and caregivers\' coping in raising a child with autism.
CONCLUSIONS:  The research established caregivers\' experiences and coping mechanisms in raising a child with ASD and the effects on different aspects of their lives including emotional, social and financial aspects, which contribute negatively to their holistic well-being. These impediments warrant the establishment of emotional support groups, empowerment of caregivers and awareness-raising through campaigns to educate the family and the community on the diverse challenges.Contribution: The findings of this study contribute to a deeper understanding of the multifaceted challenges faced by caregivers of children with ASD and provide insights into the support systems and coping mechanisms employed by these caregivers within the socio-ecological context.