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Clinicians form initial impressions about a childs diagnosis based on behavioral features, but research has not yet identified specific behaviors to guide initial diagnostic impressions. Participants were toddlers (N = 55, mean age 22.9 months) from a multi-site early detection study, referred for concern for ASD due to screening or parent/provider concern. Within 5 min of meeting a child, clinicians noted ASD or non-ASD impression, confidence in impression, and behaviors that informed their impression. These clinicians also determined final diagnoses for each child. When a childs final diagnosis was ASD (n = 35), senior clinicians formed an initial impression of ASD in 22 cases (63%) but missed 13 cases (37%). When final diagnosis was non-ASD (n = 20), senior clinicians made an initial impression of non-ASD in all cases (100%). Results were similar among junior clinicians. Senior and junior clinicians used the same behaviors to form accurate impressions of ASD and non-ASD: social reciprocity, nonverbal communication, and eye contact. Senior clinicians additionally used focus of attention when forming accurate impressions of ASD and non-ASD; junior clinicians used this behavior only when forming accurate non-ASD impressions. Clinicians initial impressions of ASD are very likely to be consistent with final diagnoses, but initial impressions of non-ASD need follow-up. Toddlers who show all four atypical behaviors (social reciprocity, nonverbal communication, eye contact, and focus of attention) might receive expedited ASD diagnoses. However, presence of apparently typical behaviors should not rule out ASD; for some children a longer evaluation is necessary to allow for more opportunities to observe subtle social behavior.

Hospital inpatient care relies on constant monitoring and reliable real-time data. Continuous improvement, adaptability, and state-of-the-art technologies are critical for ongoing efficiency, productivity, and readiness growth. When appropriately used, technologies, such as blockchain and IoT-enabled devices, can change the practice of medicine and ensure that it is performed based on correct assumptions and reliable data. The proposed electronic health record (EHR) can obtain context information from beacons, change the user interface of medical devices according to their location, and provide a more user-friendly interface for medical devices. The data generated, which are associated with the location of the beacons and devices, were stored in Hyperledger Fabric, a permissioned distributed ledger technology. Overall, by prompting and adjusting the user interface to context- and location-specific information while ensuring the immutability and value of the data, this solution targets a decrease in medical errors and an increase in the efficiency in healthcare inpatient care by improving user experience and ease of access to data for health professionals. Moreover, given auditing, accountability, and governance needs, it must ensure when, if, and by whom the data are accessed. [ABSTRACT FROM AUTHOR]

The social validity of autism behavioral intervention has been questioned. Naturalistic Developmental Behavioral Interventions (NDBIs) attempt to address some concerns, but it is unclear whether autistic people consider NDBIs socially valid. Social validity of an NDBI, Pivotal Response Treatment (PRT), was investigated through autistic adults commenting on videos of autistic children receiving PRT. Qualitative coding of responses generated three themes: respect for individuals; assessment of intervention implementation; and socioemotional considerations. Although video brevity limits the scope of the present studys conclusions, participants highlighted PRT components that appeared socially valid (e.g., reinforcing attempts, following the childs lead) and aspects appearing invalid (e.g., overemphasis on spoken language). Therefore, adjustments appear necessary for PRT to be fully acceptable to the autistic community.

Pervasive computing, or ubiquitous computing, is rapidly increasing in capacity and capabilities. With the Internet of Things (IoT) becoming an integral part of daily life and the growing availability of edge computing resources, automation guided by data is advancing applications in healthcare, manufacturing, automotive, and other areas. It's natural that pervasive computing will intersect with artificial intelligence (AI) and cybersecurity. AI can improve detection, prediction, and anticipative responses to human needs, while cybersecurity addresses topics like misuse prevention, ethics, policies, and governance. This issue features seven articles on these intersections, including four AI articles exploring natural language processing and computer vision, and three cybersecurity articles covering cryptography, medical devices, and maritime security.

Abstract This research addresses the accuracy issues in IoT-based human activity recognition (HAR) applications, essential for health monitoring, elderly care, gait analysis, security, and Industry 5.0. This study uses 12 machine learning approaches, split equally between support vector machine (SVM) and k-nearest neighbor (k-NN) models. Data from 102 individuals, aged 18–43, were used to train and test these models. The researchers aimed to detect twelve daily activities, such as sitting, walking, and cycling. Results showed k-NN models achieved slightly higher accuracy (97.08%) compared to SVM models (95.88%), though SVM had faster processing times. The improved machine learning approaches proved effective in accurately classifying daily activities, with k-NN models outperforming SVM models marginally. The paper provides significant contributions to the field of HAR by enhancing the performance of SVM and k-NN classifiers, optimizing them for higher accuracy and faster processing. Through robust testing with samples of real-world data, the study provides a detailed comparative analysis that highlights strengths and weaknesses of each classifier model, specifically within IoT-based systems. This work not only advances the theoretical understanding and practical applications of HAR systems in areas, such as healthcare and industrial automation, but also sets the stage for future research that could explore hybrid models or further enhancements, consequently improving the efficiency and functionality of IoT devices based on activity recognition.

There is increasing evidence supporting the effectiveness of the Early Start Denver Model (ESDM) for children on the autism spectrum. However, substantial variability in response to the ESDM has been reported across participants. We examined the plausible yet untested hypothesis that variations in the fidelity level of therapists delivering the intervention contribute to variability in childrens response to the ESDM. Videotaped sessions (n = 40) of toddlers on the autism spectrum who received the ESDM from trained therapists were coded to obtain measures of therapist fidelity and childrens learning in response to the therapists instruction. Variations in overall fidelity, along with variations in most items included in the ESDM fidelity checklist, contributed to the childrens learning response during the sessions.

This research paper deals with risk management in various evolutionary computing environments i.e. big data, Internet of things, pervasive and artificially intelligent environments. The presented research helps in identification and management of security risks for the evolutionary environments. A smart vendor has been utilized to implement the software benchmarking. The paper has implemented security risk management in projects related to big data as many vulnerabilities exist in the same. An intelligent vendor has been employed or application framework detection and identification of severity levels of security vulnerabilities. The software is scanned by the smart vendor not only to quantify the severity levels but also to provide the possible solutions. This work also emphasizes on analysis of various risks in Internet of things, pervasive, big data and AI environments. Various application metrics are collected to benchmark the software against application business drivers, kind of technology it uses for improving the quantitative performance of the software. [ABSTRACT FROM AUTHOR]

This study uses factor mixture modelling of the Short Sensory Profile (SSP) at two time points to describe subgroups of young autistic and typically-developing children. This approach allows separate SSP subscales to influence overall SSP performance differentially across subgroups. Three subgroups were described, one including almost all typically-developing participants plus many autistic participants. SSP performance of a second, largely-autistic subgroup was predominantly shaped by a subscale indexing behaviours of low energy/weakness. Finally, the third subgroup, again largely autistic, contained participants with low (or more "atypical") SSP scores across most subscales. In this subgroup, autistic participants exhibited large P1 amplitudes to loud sounds. Autistic participants in subgroups with more atypical SSP scores had higher anxiety and more sleep disturbances.

People spend a significant amount of time daily in the driving seat and some health complexity is possible to happen like heart-related problems, and stroke. Driver's health conditions may also be attributed to fatigue, drowsiness, or stress levels when driving on the road. Drivers' health is important to make sure that they are vigilant when they are driving on the road. A driver-centered pervasive application is proposed to monitor a driver's heart rate while driving. The input will be acquired from the interaction between the driver and embedded sensors at the steering wheel, which is tied to a Bluetooth link with an Android smartphone. The driver can view his historical data easily in tabular or graph form with selected filters using the application since the sensor data are transferred to a real-time database for storage and analysis. The application is coupled with the tool to demonstrate an opportunity as an aftermarket service for vehicles that are not equipped with this technology. [ABSTRACT FROM AUTHOR]

In this study, we investigate the impact of game-based learning on children's digital literacy in processing and acquiring information, focusing on the generation of digital natives who excel in responding to multimedia information. Utilizing data mining and the PRISMA Protocol, we conducted a systematic review based on the keywords 'Game-based learning on children’s digital literacy.' Data from the years 2017 to 2019, extracted from Sagepub and Emerald databases, reveal strong empirical support for the enhancement of children's digital literacy, particularly through game-based learning interventions, as evidenced by a significant effect size of 0.66. This translates to children becoming better at deciphering visual cues, understanding audio narratives, and critically evaluating the information presented in a variety of multimedia formats. Furthermore, game-based learning fosters critical thinking and problem-solving skills, keeping children engaged and motivated to learn in this dynamic digital landscape.

Purpose: The power of the Internet has impacted various industries, especially the healthcare industry. With the rapid population growth and advancement of various sensor technologies and smart devices, the demand for quality healthcare services has increased in the past few years. At the same time, Internet of Things (IoT) technology makes intelligent objects communicate with each other by connecting all the objects without human intervention. IoT facilitated services and technologies in healthcare to provide low-cost and efficient service delivery to patients and consumers. It reduces the patient's hospital stay time and efficient information exchange by providing cost-effective healthcare services. This systematic review analyzes different technologies, core applications, datasets, algorithms, challenges, and limitations of IoT in the healthcare sector. Methods: Database search is performed to review IoT healthcare-enabling technologies, algorithms, applications, and IoT-centric architectures. Search has been conducted over popular databases like Springer, Elsevier, and IEEE Xplore. We have downloaded around 544 research papers, out of which we have selected only 116 based on our interests. Results: We identified different challenges in healthcare IoT applications as security and privacy, scalability, high cost, energy efficiency, quality of service, network architecture, mobility, and interoperability. However, data security and privacy issues are significant challenges in the healthcare sector as they deal with patients' confidential information. Also, we proposed a novel architecture that covers most IoT healthcare requirements. IoT healthcare applications are also detailed. In addition, it reviews most of the healthcare datasets and the utilized algorithms. Conclusions: Based on the reviewed articles in this paper, it is has been concluded that IoT devices are beneficial in the healthcare applications, regardless of their limitations in terms of energy, processing, and storage. It is a promising technology that can save time and effort to the practitioners and doctors. Several architectures and technologies are discussed as well as the limitations, which enables researchers to tackle those limitations. However, the future of IoT healthcare holds immense potential for high-security enabled and pervasive applications. Analyzing vast healthcare data using deep learning techniques can play a vital role in extracting valuable insights. To leverage the power of deep learning, it is crucial to design a well-structured cloud architecture capable of implementing these techniques and predicting future trends. While researchers have proposed various frameworks for IoT healthcare, there remains a need to assess the feasibility and effectiveness of these proposed frameworks. Furthermore, it is essential to address the specific requirements and intricacies when designing detailed architectural patterns for healthcare applications. Overall, the future of IoT healthcare is expansive and offers exciting research opportunities for scholars and experts in the field. By embracing innovative technologies and addressing the specific needs of the healthcare industry, we can unlock the full potential of IoT in revolutionizing healthcare delivery and improving patient outcomes. [ABSTRACT FROM AUTHOR]

States in the United States differ in how they determine special education eligibility for autism services. Few states include an autism-specific diagnostic tool in their evaluation. In research, the Autism Diagnostic Observation Schedule (ADOS for first edition, ADOS-2 for second edition) is considered the gold-standard autism assessment. The purpose of this study was to estimate the proportion of children with an educational classification of autism who exceed the ADOS/ADOS-2 threshold for autism spectrum (concordance rate). Data were drawn from 4 school-based studies across 2 sites (Philadelphia, Pennsylvania, and San Diego, California). Participants comprised 627 children (2-12 years of age; 83% male) with an autism educational classification. Analyses included (a) calculating the concordance rate between educational and ADOS/ADOS-2 classifications and (b) estimating the associations between concordance and child's cognitive ability, study site, and ADOS/ADOS-2 administration year using logistic regression. More San Diego participants (97.5%, all assessed with the ADOS-2) met ADOS/ADOS-2 classification than did Philadelphia participants assessed with the ADOS-2 (92.2%) or ADOS (82.9%). Children assessed more recently were assessed with the ADOS-2; this group was more likely to meet ADOS/ADOS-2 classification than the group assessed longer ago with the ADOS. Children with higher IQ were less likely to meet ADOS/ADOS-2 classification. Most children with an educational classification of autism meet ADOS/ADOS-2 criteria, but results differ by site and by ADOS version and/or recency of assessment. Educational classification may be a reasonable but imperfect measure to include children in community-based trials.

To investigate the diversity, distribution, persistence, and prevalence of stress survival and resistance genes of Listeria monocytogenes clones dominating in food processing environments in Norway, genome sequences from 769 L. monocytogenes isolates from food industry environments, foods, and raw materials (512 of which were sequenced in the present study) were subjected to whole-genome multilocus sequence typing (wgMLST), single-nucleotide polymorphism (SNP), and comparative genomic analyses. The data set comprised isolates from nine meat and six salmon processing facilities in Norway collected over a period of three decades. The most prevalent clonal complex (CC) was CC121, found in 10 factories, followed by CC7, CC8, and CC9, found in 7 factories each. Overall, 72% of the isolates were classified as persistent, showing 20 or fewer wgMLST allelic differences toward an isolate found in the same factory in a different calendar year. Moreover, over half of the isolates (56%) showed this level of genetic similarity toward an isolate collected from a different food processing facility. These were designated as pervasive strains, defined as clusters with the same level of genetic similarity as persistent strains but isolated from different factories. The prevalence of genetic determinants associated with increased survival in food processing environments, including heavy metal and biocide resistance determinants, stress response genes, and inlA truncation mutations, showed a highly significant increase among pervasive isolates but not among persistent isolates. Furthermore, these genes were significantly more prevalent among the isolates from food processing environments compared to in isolates from natural and rural environments (n = 218) and clinical isolates (n = 111) from Norway. [ABSTRACT FROM AUTHOR]

BackgroundMaternal folic acid (FA) protects against developmental toxicity from certain environmental chemicals.ObjectiveWe examined combined exposures to maternal FA and pesticides in relation to autism spectrum disorder (ASD).MethodsParticipants were California children born from 2000-2007 who were enrolled in the Childhood Autism Risks from Genetics and the Environment (CHARGE) case-control study at age 2-5 y, were clinically confirmed to have ASD (n=296) or typical development (n=220), and had information on maternal supplemental FA and pesticide exposures. Maternal supplemental FA and household pesticide product use were retrospectively collected in telephone interviews from 2003-2011. High vs. low daily FA intake was dichotomized at 800μg (median). Mothers' addresses were linked to a statewide database of commercial applications to estimate agricultural pesticide exposure.ResultsHigh FA intake (≥800μg) during the first pregnancy month and no known pesticide exposure was the reference group for all analyses. Compared with this group, ASD was increased in association with

Immune abnormalities have been described in some individuals with autism spectrum disorders (ASDs) as well as their family members. However, few studies have directly investigated the role of prenatal cytokine and chemokine profiles on neurodevelopmental outcomes in humans. In the current study, we characterized mid-gestational serum profiles of 22 cytokines and chemokines in mothers of children with ASD (N=415), developmental delay (DD) without ASD (N=188), and general population (GP) controls (N=428) using a bead-based multiplex technology. The ASD group was further divided into those with intellectual disabilities (developmental/cognitive and adaptive composite score

This study reports on the initial validation of the Autism Symptom Interview (ASI), School-Age, a brief (15-20 min) phone interview derived from questions from the Autism Diagnostic Interview-Revised (ADI-R). The ASI, School-Age was administered by interviewers with minimal training to parents of children ages 5 to 12 who had all been previously identified with (or referred for assessment of) ASD or another neurodevelopmental disorder. Children then underwent a comprehensive assessment to determine a best-estimate clinical diagnosis of ASD (n = 159) or non-ASD (e.g. language disorder, intellectual disability, ADHD; n = 130). Clinicians who conducted the assessments were blind to ASI results. ROC analyses compared ASI scores to clinical diagnosis. Due to the small number of participants with non-ASD diagnoses who were classified as nonverbal (i.e. not yet using phrases on a daily basis), it was not possible to assess sensitivity and specificity of the nonverbal algorithm in this sample. The verbal algorithm yielded a sensitivity of 0.87 (95% CI = 0.81-0.92) and a specificity of 0.62 (95% CI = 0.53-0.70). When used in conjunction with the Autism Diagnostic Observation Schedule (ADOS), sensitivity and specificity were 0.82 (95% CI = 0.74-0.88) and 0.92 (95% CI = 0.86-0.96), respectively. Internal consistency and test-retest reliability were both excellent. Particularly for verbal school age children, the ASI may serve as a useful tool to more quickly ascertain or classify children with ASD for research or clinical triaging purposes. Additional data collection is underway to determine the utility of the ASI in children who are younger and/or nonverbal. Autism Res 2017, 10: 78-88. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

The Social Responsiveness Scale (SRS) is an autism rating scales in widespread use, with over 20 official foreign language translations. It has proven highly feasible for quantitative ascertainment of autistic social impairment in public health settings, however, little is known about the validity of the reinforcement in Asia populations or in references to DSM5. The current study aims to evaluate psychometric properties and cross-cultural aspects of the SRS-Korean version (K-SRS).The study subjects were ascertained from three samples: a general sample from 3 regular education elementary schools (n=790), a clinical sample (n=154) of 6-12-year-olds from four psychiatric clinics, and an epidemiological sample of children with ASD, diagnosed using both DSM IV PDD, DSM5 ASD and SCD criteria (n=151). Their parents completed the K-SRS and the Autism Spectrum Screening Questionnaire(ASSQ). Descriptive statistics, correlation analyses and principal components analysis (PCA) were performed on the total population. Mean total scores on the K-SRS differed significantly between the three samples. ASSQ scores were significantly correlated with the K-SRS T-scores. PCA suggested a one-factor solution for the total population.Our results indicate that the K-SRS exhibits adequate reliability and validity for measuring ASD symptoms in Korean children with DSM IV PDD and DSM5 ASD. Our findings further suggest that it is difficult to distinguish SCD from other child psychiatric conditions using the K-SRS.This is the first study to examine the relationship between the SRS subscales and DSM5-based clinical diagnoses. This study provides cross-cultural confirmation of the factor structure for ASD symptoms and traits measured by the SRS. Autism Res 2016, 9: 970-980. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies.

ObjectiveDelayed onset of independent walking is common in intellectual disability (ID). However, in children with autism spectrum disorders (ASD), delayed walking has not been reported as frequently, despite the high rate of concurrent ID in ASD. This study directly examined the relationship between delayed walking and severity of ID in children with ASD versus other non-ASD diagnoses.MethodParticipants were 1185 individuals (ASD, n = 903; non-ASD, n = 282) who received an assessment at age 4 to 12 years (6.89 ± 2.25) that yielded an estimate of nonverbal IQ (NVIQ) and retrospectively reported age of walking from the Autism Diagnostic Interview-Revised. The relationship between diagnostic group and delayed walking (defined as occurring at ≥16 months) as a function of NVIQ was explored using the Cox proportional hazards model.ResultsChildren with ASD were less likely to exhibit delayed walking than those with non-ASD diagnoses, and this difference was larger at lower levels of NVIQ (P = .002). For example, rates of delayed walking for ASD and non-ASD were 13% and 19%, respectively, in those with NVIQ >85 but 31% and 60% in children with NVIQ

Inflammation and asthma have both been reported in some children with autism spectrum disorder (ASD). To further assess this connection, peripheral immune cells isolated from young children with ASD and typically developing (TD) controls and the production of cytokines IL-17, -13, and -4 assessed following ex vivo mitogen stimulation. Notably, IL-17 production was significantly higher following stimulation in ASD children compared to controls. Moreover, IL-17 was increased in ASD children with co-morbid asthma compared to controls with the same condition. In conclusion, children with ASD exhibited a differential response to T cell stimulation with elevated IL-17 production compared to controls.

ImportanceMore than half of youth with autism spectrum disorders (ASDs) have sensory overresponsivity (SOR), an extreme negative reaction to sensory stimuli. However, little is known about the neurobiological basis of SOR, and there are few effective treatments. Understanding whether SOR is due to an initial heightened sensory response or to deficits in regulating emotional reactions to stimuli has important implications for intervention.ObjectiveTo determine differences in brain responses, habituation, and connectivity during exposure to mildly aversive sensory stimuli in youth with ASDs and SOR compared with youth with ASDs without SOR and compared with typically developing control subjects.Design, setting, and participantsFunctional magnetic resonance imaging was used to examine brain responses and habituation to mildly aversive auditory and tactile stimuli in 19 high-functioning youths with ASDs and 19 age- and IQ-matched, typically developing youths (age range, 9-17 years). Brain activity was related to parents' ratings of children's SOR symptoms. Functional connectivity between the amygdala and orbitofrontal cortex was compared between ASDs subgroups with and without SOR and typically developing controls without SOR. The study dates were March 2012 through February 2014.Main outcomes and measuresRelative increases in blood oxygen level-dependent signal response across the whole brain and within the amygdala during exposure to sensory stimuli compared with fixation, as well as correlation between blood oxygen level-dependent signal change in the amygdala and orbitofrontal cortex.ResultsThe mean age in both groups was 14 years and the majority in both groups (16 of 19 each) were male. Compared with neurotypical control participants, participants with ASDs displayed stronger activation in primary sensory cortices and the amygdala (P  1.70, P

Although the diagnosis of autism spectrum disorder (ASD) is based on behavioral signs and symptoms, the evaluation of a child with ASD has become increasingly focused on the identification of the genetic etiology of the disorder. In this review, we begin with a clinical overview of ASD, highlighting the heterogeneity of the disorder. We then discuss the genetics of ASD and present updated guidelines on genetic testing. We then consider the insights gained from the identification of both single gene disorders and rare variants, with regard to clinical phenomenology and potential treatment targets.

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.

The present study evaluated the ability of males with fragile X syndrome (FXS), nonsyndromic autism spectrum disorder (ASD), or typical development to learn new words by using as a cue to the intended referent an emotional reaction indicating a successful (excitement) or unsuccessful (disappointment) search for a novel object. Performance for all groups exceeded chance-levels in both search conditions. In the Successful Search condition, participants with nonsyndromic ASD performed similarly to participants with FXS after controlling for severity of ASD. In the Unsuccessful Search condition, participants with FXS performed significantly worse than participants with nonsyndromic ASD, after controlling for severity of ASD. Predictors of performance in both search conditions differed between the three groups. Theoretical and clinical implications are discussed.

Purpose of reviewThe heterogeneity in clinical presentation and outcome in neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD) autism spectrum disorder (ASD) necessitates the identification and validation of biomarkers that can guide diagnosis, predict developmental outcomes, and monitor treatment response. Electrophysiology holds both practical and theoretical advantages as a clinical biomarker in neurodevelopmental disorders, and considerable effort has been invested in the search for electroencephalography (EEG) biomarkers in ADHD and ASD.Recent findingsHere, we discuss the major themes in the evaluation of biomarkers and then review studies that have applied EEG to better inform diagnosis, focusing on the controversy surrounding the theta:beta ratio in ADHD; prediction of risk, highlighting recent studies of infants at high risk for ASD; and treatment monitoring, presenting new efforts in the redefinition of outcome measures in clinical trials of ASD treatment.SummaryWe conclude that insights gained from EEG studies will contribute significantly to a more mechanistic understanding of these disorders and to the development of biomarkers that can assist with diagnosis, prognosis, and intervention. There is a need, however, to utilize approaches that accommodate, rather than ignore, diagnostic heterogeneity and individual differences.

Individuals with autism demonstrate atypical and variable responses to social and emotional stimuli, perhaps reflecting heterogeneity of the disorder. The goal of this study was to determine whether unique profiles of psychophysiological responses to such stimuli could be identified in individuals diagnosed with autism spectrum disorder (ASD), with fragile X syndrome (FXS), and with comorbid autism and fragile X syndrome (ASD + FXS), and in typically developing (TYP) individuals. This study included 52 boys (ages 10-17): idiopathic ASD (n = 12), FXS (n = 12), comorbid ASD + FXS (n = 17), and TYP (n = 11). Physiological responses, including potentiated startle, electrodermal response, heart rate variability, and vagal tone, were collected concurrently while participants viewed emotionally evocative pictures of human faces or nonsocial images. Although some of these measures have been utilized separately for investigations on these diagnostic groups, they have not been considered together. Results using Kruskal-Wallis one-way analysis of variance by ranks indicate statistically significant differences in distributions of autonomic regulation responses between groups. The most notable differences were between the ASD group and both the FXS groups on measures of sympathetic activity, with FXS groups evincing increased activity. Also, both the ASD and ASD + FXS groups showed significantly decreased parasympathetic activity compared with FXS and TYP groups. In addition, the ASD + FXS group demonstrated a unique distribution of startle potentiation and arousal modulation. This study provides evidence that autonomic arousal and regulation profiles could be useful for distinguishing subgroups of autism and shed light on the variability underlying emotional responsivity.

ObjectiveAutism spectrum disorder is characterized by deficits in social function and the presence of repetitive and restrictive behaviors. Following a previous test of principle, the authors adopted a quantitative approach to discovering genes contributing to the broader autism phenotype by using social responsiveness as an endophenotype for autism spectrum disorder.MethodLinkage analyses using scores from the Social Responsiveness Scale were performed in 590 families from the Autism Genetic Resource Exchange, a largely multiplex autism spectrum disorder cohort. Regional and genomewide association analyses were performed to search for common variants contributing to social responsiveness.ResultsSocial Responsiveness Scale scores were unimodally distributed in male offspring from multiplex autism families, in contrast with a bimodal distribution observed in female offspring. In correlated analyses differing by Social Responsiveness Scale respondent, genomewide significant linkage for social responsiveness was identified at chr8p21.3 (multipoint LOD=4.11; teacher/parent scores) and chr8q24.22 (multipoint LOD=4.54; parent-only scores), respectively. Genomewide or linkage-directed association analyses did not detect common variants contributing to social responsiveness.ConclusionsThe sex-differential distributions of Social Responsiveness Scale scores in multiplex autism families likely reflect mechanisms contributing to the sex ratio for autism observed in the general population and form a quantitative signature of reduced penetrance of inherited liability to autism spectrum disorder among females. The identification of two strong loci for social responsiveness validates the endophenotype approach for the identification of genetic variants contributing to complex traits such as autism spectrum disorder. While causal mutations have yet to be identified, these findings are consistent with segregation of rare genetic variants influencing social responsiveness and underscore the increasingly recognized role of rare inherited variants in the genetic architecture of autism spectrum disorder.

Thyroid hormones are critical for normal brain development. This study examined autism spectrum disorders (ASD) and thyroid stimulating hormone (TSH) levels measured in mid-pregnancy maternal serum and infant blood after birth. Three groups of children born in Orange County, CA in 2000-2001 were identified: ASD (n = 78), developmental delay (n = 45), and general population controls (GP) (n = 149). Samples were retrieved from prenatal and newborn screening specimen archives. Adjusted logistic regression models showed inverse associations between ASD and log transformed TSH levels in maternal serum samples (ASD vs. GP: OR [95 % CI] 0.33 [0.12-0.91], Early Onset ASD vs. GP: 0.31 [0.10-0.98]). Results for thyroid levels in newborn blood samples were similar though not significant (ASD vs. GP: 0.61 [0.18-2.04]).

ObjectiveImpairments in learning are central to autism spectrum disorders. The authors investigated the cognitive and neural basis of these deficits in young adults with autism spectrum disorders using a well-characterized probabilistic reinforcement learning paradigm.MethodThe probabilistic selection task was implemented among matched participants with autism spectrum disorders (N=22) and with typical development (N=25), aged 18-40 years, using rapid event-related functional MRI. Participants were trained to choose the correct stimulus in high-probability (AB), medium-probability (CD), and low-probability (EF) pairs, presented with valid feedback 80%, 70%, and 60% of the time, respectively. Whole-brain voxel-wise and parametric modulator analyses examined early and late learning during the stimulus and feedback epochs of the task.ResultsThe groups exhibited comparable performance on medium- and low-probability pairs. Typically developing persons showed higher accuracy on the high-probability pair, better win-stay performance (selection of the previously rewarded stimulus on the next trial of that type), and more robust recruitment of the anterior and medial prefrontal cortex during the stimulus epoch, suggesting development of an intact reward-based working memory for recent stimulus values. Throughout the feedback epoch, individuals with autism spectrum disorders exhibited greater recruitment of the anterior cingulate and orbito-frontal cortices compared with individuals with typical development, indicating continuing trial-by-trial activity related to feedback processing.ConclusionsIndividuals with autism spectrum disorders exhibit learning deficits reflecting impaired ability to develop an effective reward-based working memory to guide stimulus selection. Instead, they continue to rely on trial-by-trial feedback processing to support learning dependent upon engagement of the anterior cingulate and orbito-frontal cortices.

ImportanceIncreasing evidence suggests that autism spectrum disorder (ASD) and many forms of developmental delay (DD) originate during fetal development. Preeclampsia may trigger aberrant neurodevelopment through placental, maternal, and fetal physiologic mechanisms.ObjectiveTo determine whether preeclampsia is associated with ASD and/or DD.Design, setting, and participantsThe Childhood Autism Risks from Genetics and the Environment (CHARGE) study is a population-based, case-control investigation of ASD and/or DD origins. Children from 20 California counties aged 24 to 60 months at the time of recruitment and living in catchment areas with a biological parent fluent in English or Spanish were enrolled from January 29, 2003, through April 7, 2011. Children with ASD (n = 517) and DD (n = 194) were recruited through the California Department of Developmental Services, the Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, and referrals. Controls with typical development (TD) (n = 350) were randomly selected from birth records and frequency matched on age, sex, and broad geographic region. Physicians diagnosing preeclampsia were masked to neurodevelopmental outcome, and those assessing neurodevelopmental function were masked to preeclampsia status.ExposuresPreeclampsia and placental insufficiency were self-reported and abstracted from medical records.Main outcomes and measuresThe Autism Diagnostic Observation Schedule and Autism Diagnostic Interview-Revised were used to confirm ASD, whereas children with DD and TD were confirmed by Mullen Scales of Early Learning and Vineland Adaptive Behavior Scales and were free of autistic symptoms. Hypotheses were formulated before data collection.ResultsChildren with ASD were twice as likely to have been exposed in utero to preeclampsia as controls with TD after adjustment for maternal educational level, parity, and prepregnancy obesity (adjusted odds ratio, 2.36; 95% CI, 1.18-4.68); risk increased with greater preeclampsia severity (test for trend, P = .02). Placental insufficiency appeared responsible for the increase in DD risk associated with severe preeclampsia (adjusted odds ratio, 5.49; 95% CI, 2.06-14.64).Conclusions and relevancePreeclampsia, particularly severe disease, is associated with ASD and DD. Faulty placentation manifests in the mother as preeclampsia with vascular damage, enhanced systemic inflammation, and insulin resistance; in the placenta as oxygen and nutrient transfer restriction and oxidative stress; and in the fetus as growth restriction and progressive hypoxemia. All are potential mechanisms for neurodevelopmental compromise.

Advances in genome-wide technology, coupled with the availability of large cohorts, are finally yielding a steady stream of autism spectrum disorder (ASD) genes carrying mutations of large effect. These findings represent important molecular clues, but at the same time present notable challenges to traditional strategies for moving from genes to neurobiology. A remarkable degree of genetic heterogeneity, the biological pleiotropy of ASD genes, and the tremendous complexity of the human brain are prompting the development of new strategies for translating genetic discoveries into therapeutic targets. Recent developments in systems biology approaches that 'contextualize' these genetic findings along spatial, temporal, and cellular axes of human brain development are beginning to bridge the gap between high-throughput gene discovery and testable pathophysiological hypotheses.

Importance:The prevalence of psychological distress among mothers of children with autism spectrum disorder (ASD) suggests a need for interventions that address parental mental health during the critical period after the child's autism diagnosis when parents are learning to navigate the complex system of autism services.Objective: To investigate whether a brief cognitive behavioral intervention, problem-solving education (PSE), decreases parenting stress and maternal depressive symptoms during the period immediately following a child's diagnosis of ASD.Design, Setting, and Participants: A randomized clinical trial compared 6 sessions of PSE with usual care. Settings included an autism clinic and 6 community-based early intervention programs that primarily serve low-income families. Participants were mothers of 122 young children (mean age, 34 months) who recently received a diagnosis of ASD. Among mothers assessed for eligibility, 17.0%declined participation. We report outcomes after 3 months of follow-up (immediate postdiagnosis period).INTERVENTIONS Problem-solving education is a brief, cognitive intervention delivered in six 30-minute individualized sessions by existing staff (early intervention programs) or research staff without formal mental health training (autism clinic).Main Outcomes and Measures: Primary outcomeswere parental stress and maternal depressive symptoms.RESULTS: Fifty-nine mothers were randomized to receive PSE and 63 to receive usual care. The follow-up rate was 91.0%. Most intervention mothers (78.0%) received the full PSE course. At the 3-month follow-up assessment, PSE mothers were significantly less likely than those serving as controls to have clinically significant parental stress (3.8% vs 29.3%; adjusted relative risk [aRR], 0.17; 95%CI, 0.04 to 0.65). For depressive symptoms, the risk reduction in clinically significant symptoms did not reach statistical significance (5.7%vs 22.4%; aRR, 0.33; 95%CI, 0.10 to 1.08); however, the reduction in mean depressive symptoms was statistically significant (Quick Inventory of Depressive Symptomatology score, 4.6 with PSE vs 6.9 with usual care; adjusted mean difference, -1.67; 95%CI, -3.17 to -0.18).Conclusions and Relevance: The positive effects of PSE in reducing parenting stress and depressive symptoms during the critical postdiagnosis period, when parents are asked to navigate a complex service delivery system, suggest that itmay have a place in clinical practice. Furtherwork will monitor these families for a total of 9 months to determine the trajectory of outcomes..

Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism spectrum disorder (ASD) using an event-related potential shape learning paradigm, and we examined the relation between visual statistical learning and cognitive function. Compared to typically developing (TD) controls, the ASD group as a whole showed reduced evidence of learning as defined by N1 (early visual discrimination) and P300 (attention to novelty) components. Upon further analysis, in the ASD group there was a positive correlation between N1 amplitude difference and non-verbal IQ, and a positive correlation between P300 amplitude difference and adaptive social function. Children with ASD and a high non-verbal IQ and high adaptive social function demonstrated a distinctive pattern of learning. This is the first study to identify electrophysiological markers of visual statistical learning in children with ASD. Through this work we have demonstrated heterogeneity in statistical learning in ASD that maps onto non-verbal cognition and adaptive social function.

Understanding the pathogenesis of neurodevelopmental disorders has proven to be challenging. Using autism spectrum disorder (ASD) as a paradigmatic neurodevelopmental disorder, this article reviews the existing literature on the etiological substrates of ASD and explores how genetic epidemiology approaches including gene-environment interactions (G×E) can play a role in identifying factors associated with ASD etiology. New genetic and bioinformatics strategies have yielded important clues to ASD genetic substrates. The next steps for understanding ASD pathogenesis require significant effort to focus on how genes and environment interact with one another in typical development and its perturbations. Along with larger sample sizes, future study designs should include sample ascertainment that is epidemiologic and population-based to capture the entire ASD spectrum with both categorical and dimensional phenotypic characterization; environmental measurements with accuracy, validity, and biomarkers; statistical methods to address population stratification, multiple comparisons, and G×E of rare variants; animal models to test hypotheses; and new methods to broaden the capacity to search for G×E, including genome-wide and environment-wide association studies, precise estimation of heritability using dense genetic markers, and consideration of G×E both as the disease cause and a disease course modifier. Although examination of G×E appears to be a daunting task, tremendous recent progress in gene discovery has opened new horizons for advancing our understanding of the role of G×E in the pathogenesis of ASD and ultimately identifying the causes, treatments, and even preventive measures for ASD and other neurodevelopmental disorders.

BackgroundThe relationship between behavioral problems and obesity in early childhood in Latinos is largely unknown.MethodsCross-sectional anthropometric and behavioral data of children at three years of age were gathered from a cohort of 174 children of Latina mothers at two San Francisco hospitals. Child behaviors were assessed using the preschool Child Behavior Checklist (CBCL/1½-5). Logistic regression was used to analyze the association between behavior and obesity.ResultsAt three years, 27.7% were obese. There were no associations between affective (OR = 1.89; 95% confidence interval [CI] 0.42-8.59), anxiety (OR = 1.86; 95% CI 0.53-6.47), pervasive developmental (OR = 0.42; 95% CI 0.13-1.36), attention deficit hyperactivity (OR = 0.58; 95% CI 0.12-2.76), or oppositional defiant (OR = 6.49; 95% CI 0.65-64.49) problems and obesity.ConclusionsThough psychological problems and obesity are associated among older children and adolescents, there was no association in Latino three-year olds in a low-income sample.