Search Results (208)

Pathogenic variants in the MAP1B gene have been associated with neurological impairment, including intellectual disability, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, brain malformations, cognitive hearing loss, short stature, and dysmorphic features. However, few cases with detailed clinical characterization have been reported. We describe a 12-year-old boy carrying a loss-of-function MAP1B variant, presenting with severe elimination disorders despite normal intelligence. He was referred to the genetics service due to persistent elimination issues, including daytime urinary incontinence, nocturnal enuresis, and fecal incontinence. He had normal motor and cognitive development, with an IQ of 99; however, he also presented with ADHD, short stature, microcephaly, and myopia. Brain MRI revealed bilaterial subependymal periventricular nodular heterotopia (PVNH). Audiometry showed normal bilateral hearing. Testing fragile X syndrome (FXS) and karyotype analyses yielded normal results. Whole exome sequencing (WES) revealed a nonsense pathogenic variant in MAP1B (c.895 C>T; p.Arg299*). No other family members showed a similar phenotype; however, a great-uncle and a great-aunt had a history of nocturnal enuresis until age 10. The patient’s deceased mother had short stature and psychiatric disorders, and a history of consanguinity was reported on the maternal side. This case broadens the phenotypic spectrum associated with MAP1B syndrome, suggesting that elimination disorder, frequently reported in FXS, should also be evaluated in MAP1B pathogenic variant carriers. In addition, the presence of short stature also appears to be part of the syndrome. Full article

Background: Electronic waste (e-waste) recycling in informal settings like Agbogbloshie in Accra, Ghana, releases toxic metals into the environment, posing serious health risks to nearby residents, particularly children. This study assessed the body burdens of lead (Pb), manganese (Mn), cadmium (Cd), chromium (Cr), nickel (Ni), and arsenic (As) and their association with cognitive function in schoolchildren living within 1 km of the Agbogbloshie site. Method: A cross-sectional study involving 56 pupils collected demographic data and blood and urine samples and administered the Wechsler Intelligence Scale for Children—Fourth Edition (WISC-IV). Blood was tested for Pb and Mn and urine for Cd, Cr, Ni, and As. Associations between metal levels and cognitive outcomes were examined using regression analyses, adjusting for confounders. Result: Children showed elevated metal levels, with mean blood Pb of 60.43 µg/L and urinary s of 21.50 µg/L. Symptoms of cognitive dysfunction were common: 75% reported confusion, 67.9% poor memory, and 66% poor concentration. Urinary Cr levels were significantly associated with lower Full-Scale IQ (β = −18.42, p < 0.05) and increased difficulty in decision-making (OR = 0.1, p < 0.05). Conclusion: These findings underscore the neurodevelopmental risks of heavy metal exposure from e-waste in low- and middle-income countries and call for urgent public health interventions and policy actions. Full article

The study’s aim was to evaluate electroretinographic (ERG) alterations in Fragile X syndrome (FXS), FMR1 premutation carriers, and controls, and to explore correlations with peripheral blood FMRP expression levels and behavioral outcomes. ERG recordings were obtained using a handheld device across three stimulus protocols in 43 premutation carriers, 39 individuals with FXS, and 23 controls. Peripheral blood FMRP expression levels were quantified using TR-FRET (Time-Resolved Fluorescence Resonance Energy Transfer). Correlations were assessed with cognitive and behavioral measures including IQ (Intelligence Quotient), ABC_FX (Aberrant Behavior Checklist for Fragile X Syndrome), SNAP-IV (Swanson, Nolan, and Pelham Teacher and Parent Rating Scale), SEQ (Sensory Experiences Questionnaire), ADAMS (Anxiety, Depression, and Mood Scale), and the Vineland III Adaptive Behavior Scale standard score. Significant group differences were observed in multiple ERG parameters, particularly in 2 Hz b-wave amplitude (p = 0.0081), 2 Hz b-wave time to peak (p = 0.0164), 28.3 Hz flash combined amplitude (p = 0.0139), 3.4 Hz red/blue flash b-wave amplitude (p = 0.0026), and PhNR amplitude (p = 0.0026), indicating both outer and inner retinal dysfunction in FXS and premutation groups. Despite high test–retest reliability for ERG (ICC range = 0.71–0.92) and FMRP (ICC = 0.70), no correlation was found between ERG metrics and FMRP or behavioral measures. However, FMRP levels strongly correlated with IQ (ρ = 0.69, p < 0.0001) and inversely with behavioral impairment [ABC_FX (ρ = −0.47, p = 0.0041), SNAP-IV (ρ = −0.48, p = 0.0039), SEQ (ρ = −0.43, p = 0.0146), and the Vineland III standard score (ρ = 0.56, p = 0.0019)]. ERG reveals distinct retinal functional abnormalities in FMR1-related conditions but does not correlate with peripheral FMRP expression levels, highlighting the need for multimodal biomarkers integrating radiological, physiological, behavioral, and molecular measures. Full article

Achieving sustainable economic growth requires a careful balance between public debt accumulation and the macroeconomic stability necessary for long-term development. While public debt can support growth through productive public investment, excessive debt may crowd out private investment, raise borrowing costs, and undermine financial stability, ultimately threatening economic sustainability. In this context, the quality of institutions plays a pivotal moderating role by fostering responsible debt management and ensuring that debt-financed investments contribute to sustainable development. In this context, this study investigates the relationship between public debt and economic growth, with a focus on the moderating role of institutional quality (IQ). Utilizing an unbalanced panel of 115 countries over the period from 1996 to 2021, this study tests the hypothesis that robust institutional frameworks mitigate the negative impact of public debt on economic growth. To address potential endogeneity, this study employs the dynamic system Generalized Method of Moments (GMM) estimation technique. The results reveal that, although the direct effect of public debt on economic growth is negative, the interaction between public debt and IQ yields a positive influence. Furthermore, the results indicate the presence of a threshold beyond which public debt begins to exert a beneficial effect on economic growth, whereas its impact remains adverse below this threshold. These findings underscore the critical importance of sound debt management strategies and institutional development for policymakers, suggesting that effective government governance is essential to harnessing the potential positive effects of public debt on economic growth. Full article

Background/Objectives: Children with above-average cognitive functioning often present complex developmental profiles, combining high cognitive potential with heterogeneous socio-emotional and learning trajectories. Although the cognitive and behavioral characteristics of giftedness have been widely studied in Anglophone countries, evidence remains limited in Southern Europe. This study aimed to investigate the cognitive, academic, and emotional–behavioral profiles of Italian children and adolescents with above-average cognitive functioning, using an inclusive, dimensional approach (IQ > 114). Methods: We analyzed a cross-sectional sample of 331 children and adolescents (ages 2.11–16.5 years), referred for clinical cognitive or behavioral evaluations. Participants were assessed using the WPPSI-III or WISC-IV for cognitive functioning, the MT battery for academic achievement, and the Child Behavior Checklist (CBCL) for emotional and behavioral symptoms. Comparative and correlational analyses were performed across age, gender, and functional domains. A correction for multiple testing was applied using the Benjamini–Hochberg procedure. Results: Gifted participants showed strong verbal comprehension (mean VCI: preschoolers = 118; school-aged = 121) and relative weaknesses in working memory (WM = 106) and processing speed (PS = 109). Males outperformed females in perceptual reasoning (PR = 121 vs. 118; p = 0.032), while females scored higher in processing speed (112 vs. 106; p = 0.021). Difficulties in writing and arithmetic were observed in 47.3% and 41.8% of school-aged participants, respectively. Subclinical internalizing problems were common in preschool and school-aged groups (mean CBCL T = 56.2–56.7). Working memory negatively correlated with total behavioral problems (r = −0.13, p = 0.046). Conclusions: These findings confirm the heterogeneity of gifted profiles and underscore the need for personalized educational and psychological interventions to support both strengths and vulnerabilities in gifted children. Caution is warranted when interpreting these associations, given their modest effect sizes and the exploratory nature of the study. Full article

Objectives: The primary objective of this study was to determine whether motor disorders are significantly more prevalent in children with Autism Spectrum Disorder (ASD) without co-occurring genetic or neurological conditions compared to neurotypical children. Another aim was to explore the applicability of the MABC-2 test for assessing motor skills in a Polish cohort of children with ASD. Additionally, this study sought to develop a basic framework for motor skill assessment in children with autism. Methods: This study included 166 Caucasian children, both sexes, aged 5–12 years, without intellectual disability (IQ ≥ 70), without concomitant genetic or neurological disorders, particularly epilepsy or cerebral palsy. The study group consisted of children with ASD (n = 71), and the control group consisted of neurotypical children (n = 95). The participants were assessed with the Movement Assessment Battery for Children–second edition (MABC-2), MABC-2 checklist and the Developmental Coordination Disorder Questionnaire (DCDQ), used as a reference point. Results: The children with ASD obtained significantly lower MABC-2 test results in all subtests in comparison with the control group. The children with suspected or diagnosed coordination disorders were characterized by a significantly greater number of co-occurring non-motor factors than the other participants of this study. MABC-2 test showed greater consistency with DCDQ than with the MABC-2 questionnaire. Conclusions: Children with ASD present a lower level of manual dexterity and balance and greater difficulties in performing tasks, including throwing and catching, in comparison with neurotypical children. The MABC-2 test with the MABC-2 checklist and DCDQ questionnaire constitute a complementary diagnostic tool. Full article

Background: Advanced hybrid closed-loop (AHCL) systems have improved the glycemic control in type 1 diabetes (T1D). While time in range (TIR) (70–180 mg/dL) is the standard metric, time in tight range (TITR) (70–140 mg/dL) offers a stricter assessment. Real-world comparisons using the TITR are limited. This study compared the TIR and TITR metrics between the MiniMed™ 780G and Tandem Control-IQ™ in adults with T1D. Methods: This retrospective, single-center study included 42 propensity-score-matched adults with T1D (28 MM780G users and 14 Tandem Control-IQ users), each with ≥3 months of AHCL system use. Glycemic metrics from continuous glucose monitoring (CGM) were analyzed over a 14-day period. Comparisons between groups were conducted using Mann–Whitney U tests, adjusted linear regression, and linear mixed-effects models accounting for repeated measures. Results: At three months, the MM780G users achieved significantly higher TITR (60.1% ± 12 vs. 49.5% ± 9.3; p = 0.005) and TIR (83.7% ± 7.6 vs. 72.1% ± 7.5; p < 0.001) values, along with lower glucose variability, compared to these values in the Tandem Control-IQ users. The linear regression model confirmed that the MM780G was independently associated with a higher TITR (β = 14.2; p = 0.005). Mixed-effects modeling for the TIR showed a significant interaction between timepoint and device type (β = 4.81; p = 0.006), favoring the MM780G. Conclusions: In this real-world analysis, both AHCL systems improved glycemic control, but the MiniMed 780G could be associated with a superior performance in achieving tighter glucose targets without increasing hypoglycemia. TITR may serve as a valuable complementary metric alongside TIR in evaluating AHCL systems’ effectiveness. However, these findings should be interpreted cautiously due to limitations such as the retrospective design, small sample size, potential residual confounding, and lack of standardization in the device settings. Further studies are warranted to confirm these results and assess their generalizability. Full article

Background/Objectives: Knee osteoarthritis (KOA) is a prevalent disorder affecting both older adults and younger individuals, leading to compromised joint function and mobility. Early and accurate detection is critical for effective intervention, as treatment options become increasingly limited as the disease progresses. Traditional diagnostic methods rely heavily on the expertise of physicians and are susceptible to errors. The demand for utilizing deep learning models in order to automate and improve the accuracy of KOA image classification has been increasing. In this research, a unique deep learning model is presented that employs autoencoders as the primary mechanism for feature extraction, providing a robust solution for KOA classification. Methods: The proposed model differentiates between KOA-positive and KOA-negative images and categorizes the disease into its primary severity levels. Levels of severity range from “healthy knees” (0) to “severe KOA” (4). Symptoms range from typical joint structures to significant joint damage, such as bone spur growth, joint space narrowing, and bone deformation. Two experiments were conducted using different datasets to validate the efficacy of the proposed model. Results: The first experiment used the autoencoder for feature extraction and classification, which reported an accuracy of 96.68%. Another experiment using autoencoders for feature extraction and Extreme Learning Machines for actual classification resulted in an even higher accuracy value of 98.6%. To test the generalizability of the Knee-DNS system, we utilized the Butterfly iQ+ IoT device for image acquisition and Google Colab’s cloud computing services for data processing. Conclusions: This work represents a pioneering application of autoencoder-based deep learning models in the domain of KOA classification, achieving remarkable accuracy and robustness. Full article

The Draw-A-Person Intellectual Ability test for children, adolescents, and adults is a widely used tool in psychology for assessing intellectual ability. This test relies on human drawings for initial raw scoring, with the subsequent conversion of data into IQ ranges through manual procedures. However, this manual scoring and IQ assessment process can be time-consuming, particularly for busy psychologists dealing with a high caseload of children and adolescents. Presently, DAP-IQ screening continues to be a manual endeavor conducted by psychologists. The primary objective of our research is to streamline the IQ screening process for psychologists by leveraging deep learning algorithms. In this study, we utilized the DAP-IQ manual to derive IQ measurements and categorized the entire dataset into seven distinct classes: Very Superior, Superior, High Average, Average, Below Average, Significantly Impaired, and Mildly Impaired. The dataset for IQ screening was sourced from primary to high school students aged from 8 to 17, comprising over 1100 sketches, which were subsequently manually classified under the DAP-IQ manual. Subsequently, the manual classified dataset was converted into digital images. To develop the artificial intelligence-based models, various deep learning algorithms were employed, including Convolutional Neural Network (CNN) and state-of-the-art CNN (Transfer Learning) models such as Mobile-Net, Xception, InceptionResNetV2, and InceptionV3. The Mobile-Net model demonstrated remarkable performance, achieving a classification accuracy of 98.68%, surpassing the capabilities of existing methodologies. This research represents a significant step towards expediting and enhancing the IQ screening for psychologists working with diverse age groups. Full article

Background: Objective evaluation of the swimming start is crucial for sprint performance improvement. Traditional visual assessment of its phases—reaction, take-off, flight, and underwater glide—lacks precision. This study addresses the need for more integrated and accessible biomechanical tools by validating IQ LAB software (Version 250319), which is embedded in the SwimPro system and enables immediate video-based motion analysis without external processing. Existing tools like Dartfish (ProSuite 4.0) require separate video handling and licensing, whereas IQ LAB offers a built-in, streamlined solution suitable for applied environments. Methods: We evaluated the concurrent validity of the IQ LAB software, a desktop 2D motion analysis tool, using Dartfish (ProSuite 4.0) as the gold standard. The reliability was assessed using intrarater temporal stability and interrater agreement, considering selected kinematic parameters related to the swimming kick start (to 5 m). A sample of 13 competitive male swimmers (age 17.2 ± 1.1 years) was analyzed across two sessions. Concurrent validity was assessed by comparing IQ LAB outputs to those from Dartfish software in the sagittal plane. Intrarater reliability was measured using a test–retest design across two sessions spaced 7 days apart. Interrater reliability involved two independent raters analyzing the same video data using IQ LAB. Results: IQ LAB and Dartfish kinematic parameters demonstrated strong agreement (Pearson r ≥ 0.95), with no significant systematic differences. The intrarater and interrater reliability were excellent (ICC ≥ 0.94, 95% CI included). The test–retest reliability of the selected parameters across seasons also showed excellent reproducibility (ICC ≥ 0.93). Conclusions: IQ LAB software provides a valid and reliable 2D kinematic assessment of the swimming kick start, offering a practical and accessible tool for coaches and researchers. This study introduces a novel validated software solution for biomechanical analysis in swimming starts. Full article

Objective: To determine if prenatal socioeconomic status (SES) is associated with childhood working memory (WM), we constructed a more precise, integrative measure of WM using variables from multiple tasks that may provide a more representative measure of WM. Study Design: We used data from a prospective birth cohort study in Mexico City, Mexico, with N = 515 children aged 6–9 years. Prenatal SES was measured using the Mexican Association of Marketing Research and Public Opinion Agencies (AMAI) index. We created a latent variable for nonverbal working memory using multiple tasks (Cambridge Neuropsychological Test Automated Battery spatial working memory, operant chamber Delayed Match to Sample and Incremental Repeated Acquisition). Structural equation models were used to assess associations between prenatal SES and nonverbal working memory, adjusting for child demographics (e.g., age and sex), prenatal exposures (e.g., exposures to lead, arsenic, and secondhand smoke), and family (current SES, maternal IQ) variables. Results: Children had a mean age of 6.6 years [SD 0.6], and 50.5% were boys. Using confirmatory factor analysis, we constructed a latent variable of nonverbal working memory, which was measurement invariant across child sex. Prenatal SES was associated with childhood nonverbal working memory (standardized factor loading = 0.17; p = 0.004). These associations were modified by child sex. Higher prenatal SES was significantly associated with higher childhood WM in females (standardized factor loading = 0.26; p = 0.002), but not in males. Conclusions: Prenatal socioeconomic status is a predictor of childhood working memory, but it may be a stronger predictor for girls compared with for boys. Full article

Persistent atrial fibrillation (AF), a prevalent cardiac arrhythmia, is primarily sustained by rotor-type reentries, with their localization crucial for successful ablation treatment. Fractionated atrial electrogram (EGM) signals have been associated with the tips of the rotors and are thus considered as ablation targets. However, the typical noise problems of physiological signals affect the results of EGM processing tools, and consequently the ablation outcome. This study proposes a data fusion framework based on the Joint Directors of Laboratories model with six levels and information quality (IQ) assessment for locating rotor tips from EGMs simulated in a two-dimensional model of human atrial tissue under AF conditions. Validation tests were conducted using a set of 13 IQ criteria and their corresponding metrics. First, EGMs were contaminated with different types of noise and artifacts (power-line interference, spikes, loss of samples, and loss of resolution) to assess tolerance. The signals were then preprocessed, and five statistical features (sample entropy, approximate entropy, Shannon entropy, mean amplitude, and standard deviation) were extracted to generate rotor location maps using a wavelet fusion technique. Fuzzy inference was applied for situation and risk assessment, followed by IQ mapping using a support vector machine by level. Finally, the IQ criteria were optimized through a particle swarm optimization algorithm. The proposed framework outperformed existing EGM-based rotor detection methods, demonstrating superior functionality and performance compared to existing EGM-based rotor detection methods. It achieved an accuracy of approximately 90%, with improvements of up to 10% through tuning and adjustments based on IQ variables, aligned with higher-level system requirements. The novelty of this approach lies in evaluating the IQ across signal-processing stages and optimizing it through data fusion to enhance rotor tip position estimation. This advancement could help specialists make more informed decisions in EGM acquisition and treatment application. Full article

Background: The Automated Test of Embodied Cognition (ATEC) is a new system for measuring cognition in action that uses cognitively demanding physical tasks and motion capture technology. Rhythm is one of the domains assessed by the ATEC across a number of tasks and is a domain for which there is no broadly accepted neurocognitive measure. Method: Rhythm was assessed in a sample of 104 participants that included those at risk of cognitive decline and community controls. At-risk participants were also administered standard measures of executive functioning (EF), verbal list-learning, story memory, visual memory, and pre-morbid IQ. Results: The ATEC Rhythm Domain was found in the factor analysis with Varimax rotation to be loaded distinctly on the EF factor. ATEC Rhythm was significantly correlated with EF neurocognitive measures, and, in a Chi-square analysis, significantly differentiated the community control participants from those at risk for cognitive decline. ATEC Rhythm was significantly correlated with story memory and visual memory but not verbal list-learning. Age was negatively correlated with ATEC Rhythm, and women performed slightly better than men. ATEC Rhythm was also significantly correlated with the years of education and an estimate of pre-morbid IQ. Discussion: ATEC Rhythm was found to have discriminant and concurrent validity with EF measures and was significantly correlated with measures of story memory and visual memory, but not verbal list-learning. We speculate on rhythm’s relationship to story narrative and visual sequencing, and on rhythm’s relationship to cognitive reserve, as represented by education and the pre-morbid IQ estimate. Conclusions: The ATEC is a promising new measure that provides a systematic assessment of rhythm as a domain of embodied cognition. It may be useful in studies of neurodevelopment and neurocognitive decline, and it may be especially useful in assessing the effects of interventions that use physical activities, including dance and music therapies. Full article

Background: Embodied cognition is an emerging concept in cognitive science that emphasizes the integral role of perception, action, and bodily experience in shaping human thought and understanding. Recently, a new instrument has been developed called the Automated Test of Embodied Cognition (ATEC), which provides a comprehensive measure of eight domains of embodied cognition. Method: An embodied cognition in an alcohol use disorder (AUD) sample (N = 49) was assessed using ATEC, which employs cognitively demanding physical tasks, like an exercise video, to measure executive functions (EFs), memory, and other cognitive processes “in action”. Results: Embodied delayed recall was the most frequent impairment (84%), and EF impairments were also common. Among the EF domains, self-regulation was the most frequently impaired at 43%. Using the ATEC total score, 43% of the sample were rated as having a mild or greater level of overall impairment. Strong support for concurrent validity was found for ATEC EF and memory domains when correlated with neurocognitive assessments conceptually related to them. Significant categorical agreement (impaired/not impaired) was also found between neurocognitive testing and ATEC total score. Using the ATEC total score, younger age, higher education, and better premorbid IQ were found to be potential protective factors against cognitive decline. Conclusions: Findings support ATEC’s potential for future studies related to AUD and other disorders that may lead to cognitive decline. Embodied cognition may provide new insights into how AUD affects cognition and functioning and be useful to determine what interventions may improve recovery. Full article

Background/Objectives: Adolescence is a developmental stage characterized by profound physical and psychological transformations, often leading to vulnerabilities such as body dissatisfaction, identity challenges, and the use of maladaptive coping strategies. This often leads to body-related psychopathologies, including headaches, restrictive eating disorders, and non-suicidal self-injury (NSSI). The present study aimed to describe the typical functioning and features of these conditions and the differences between the three groups, and to identify the most effective assessment for predicting these conditions. Methods: Sixty adolescent patients (51 female; mean age = 15.34 ± 1.80) were divided into three groups: headaches, restrictive eating disorders, and NSSI, and assessed for differences in symptoms, cognitive performance, personality, functioning, and illness severity using semi-structured interviews, clinician-based scales, and performance-based tests like the Rorschach inkblot test, according to the Rorschach Performance Assessment System (R-PAS). Results: Individuals with headaches experienced more internalizing symptoms, had an average IQ, maintained some functioning areas, and had distorted patterns of self–other relationships with the tendency to project malevolent aspects onto others. Patients with restrictive eating disorders had high levels of depressive symptoms, above-average IQ scores, negative symptoms, moderate presence of obsessive–compulsive personality traits, disorganized thinking, and a tendency to interpret situations subjectively. Patients with NSSI showed the highest level of depressive symptoms and social anxiety symptoms, and a considerable presence of psychotic symptoms and perceptual distortions. Negative symptoms, borderline personality traits, and psychosis symptoms had the strongest predictivity. Conclusions: The study provides clinicians with relevant insights into the features of these conditions and highlights assessment strategies, tailored interventions, and enhanced outcomes for these vulnerable populations. Full article