Search Results (1,175)

Prader–Willi (PWS) and Angelman (AS) syndromes were the first examples in humans with errors in genomic imprinting, usually from de novo 15q11-q13 deletions of different parent origin (paternal in PWS and maternal in AS). Dozens of genes and transcripts are found in the 15q11-q13 region, and may play a role in PWS, specifically paternally expressed SNURF-SNRPN and MAGEL2 genes, while AS is due to the maternally expressed UBE3A gene. These three causative genes, including their encoding proteins, were targeted. This review article summarizes and illustrates the current understanding and cause of both PWS and AS using strategies to include the literature sources of key words and searchable web-based programs with databases for integrated gene and protein interactions, biological processes, and molecular mechanisms available for the two imprinting disorders. The SNURF-SNRPN gene is key in developing complex spliceosomal snRNP assemblies required for mRNA processing, cellular events, splicing, and binding required for detailed protein production and variation, neurodevelopment, immunodeficiency, and cell migration. The MAGEL2 gene is involved with the regulation of retrograde transport and promotion of endosomal assembly, oxytocin and reproduction, as well as circadian rhythm, transcriptional activity control, and appetite. The UBE3A gene encodes a key enzyme for the ubiquitin protein degradation system, apoptosis, tumor suppression, cell adhesion, and targeting proteins for degradation, autophagy, signaling pathways, and circadian rhythm. PWS is characterized early with infantile hypotonia, a poor suck, and failure to thrive with hypogenitalism/hypogonadism. Later, growth and other hormone deficiencies, developmental delays, and behavioral problems are noted with hyperphagia and morbid obesity, if not externally controlled. AS is characterized by seizures, lack of speech, severe learning disabilities, inappropriate laughter, and ataxia. This review captures the clinical presentation, natural history, causes with genetics, mechanisms, and description of established laboratory testing for genetic confirmation of each disorder. Three separate searchable web-based programs and databases that included information from the updated literature and other sources were used to identify and examine integrated genetic findings with predicted gene and protein interactions, molecular mechanisms and functions, biological processes, pathways, and gene-disease associations for candidate or causative genes per disorder. The natural history, review of pathophysiology, clinical presentation, genetics, and genetic-phenotypic findings were described along with computational biology, molecular mechanisms, genetic testing approaches, and status for each disorder, management and treatment options, clinical trial experiences, and future strategies. Conclusions and limitations were discussed to improve understanding, clinical care, genetics, diagnostic protocols, therapeutic agents, and genetic counseling for those with these genomic imprinting disorders. Full article

People with developmental disabilities, who represent about 2% of the global population, encounter diverse functional and cognitive challenges that adversely impact their navigation and accessibility experiences in the built environments. Historically, accessibility standards predominantly focused on physical barriers, with less attention given to sensory and cognitive barriers. This multipart study delves into barriers faced by individuals with intellectual/developmental disabilities in the built environment. The first part reviews the state of existing literature on developmental disabilities. The second part captures insights from individuals with intellectual/developmental disabilities as they navigate various public buildings. The final part synthesizes the collected information, including lessons learned from autism-friendly architectural and other design requirements, to assess the current state of development of the Canadian accessibility standard, CSA/ASC B651:23, in meeting the needs of people with developmental disabilities. The study culminates in recommendations aimed at enhancing the accessibility standard for the built environment, specifically in addressing sensory and cognitive barriers faced by people with developmental disabilities. Full article

Students with learning disabilities (LD) often struggle to develop deep, transferable conceptual understanding in mathematics due to cognitive and processing challenges, underscoring the relevance of instruction grounded in strong teacher pedagogical content knowledge (PCK). This issue is critical given widening post-pandemic achievement gaps and increased expectations for conceptual understanding in inclusive classrooms. Although many studies document effective mathematics interventions for students with LD, relatively few examine how teachers’ PCK functions in these classrooms. In contrast, general education research highlights the importance of PCK for conceptual learning. This manuscript bridges these studies by examining how insights from broader PCK research may inform instruction for students with LD. This manuscript presents a practice-based conceptual synthesis of research on mathematics teachers’ PCK, integrating findings from special education and mathematics intervention literature with classroom vignettes and practitioner examples. The synthesis highlights how core PCK components—content knowledge, understanding of student thinking and misconceptions, and instructional strategies—may support early conceptual understanding in students with LD, emphasizing multiple representations, error analysis, and routines that promote generalization through distributed practice. Implications for practice, professional development, and future research are discussed, offering practice-informed pathways to support inclusive mathematics instruction for students with LD. Full article

The placenta is often described as the “window to the brain” due to its crucial role in fetal neurological development. In this study, we investigated a family where the older male offspring exhibited severe neurodevelopmental and mild motor coordination disorders. His brother displayed emotional and behavioral dysregulation along with mild motor coordination disorders. The father was asymptomatic, while the mother and daughter showed mild learning disabilities. Whole exome sequencing (WES) identified a disruptive X-linked pathogenic variant, c.1088_1089del p.Asp363GlyfsTer2, within the calpain-6 (CAPN6) gene. We have submitted this variant to the ClinVar database (RCV005234146.2). The variant was found in hemizygous condition in the affected male offspring and in heterozygous condition in both the mother and daughter. As predicted, the variant undergoes nonsense-mediated mRNA decay (NMD), preventing the translation of the CAPN6 gene into a functional protein. CAPN6 is a critical gene predominantly expressed in placental and trophoblast tissues. Although its function is not well characterized, CAPN6 is also expressed in several regions of the developing brain. Recent studies have shown that genetic variants in CAPN6 significantly influence vascular endothelial growth factor (VEGF) activity, thereby affecting angiogenesis and the blood supply essential for fetal growth and development. Although CAPN6 lacks an MIM phenotype code, we hypothesize that it might be enumerated as a novel candidate gene contributing to neurodevelopmental disorders. Functional studies are imperative to elucidate the role of CAPN6 in placental function and its potential implications for neurodevelopmental processes. This work aims to inspire further research into the role of CAPN6 in placental biology and its relevance to neurodevelopmental disorders. Full article

Integrating people with hearing disabilities into schools is one of the biggest problems that Latin American societies face. Mexican Sign Language (MSL) is the main language and culture of the deaf community in Mexico. However, its use in formal education is still limited by structural inequalities, a lack of qualified interpreters, and a lack of technology that can support personalized instruction. This study outlines the conceptualization and development of a mobile application designed as an adaptive assistive technology for learning MSL, utilizing a combination of computer vision techniques, deep learning algorithms, and personalized pedagogical interaction. The suggested system uses convolutional neural networks (CNNs) and pose-estimation models to recognize hand gestures in real time with 95.7% accuracy. It then gives the learner instant feedback by changing the difficulty level. A dynamic learning engine automatically changes the level of difficulty based on how well the learner is doing, which helps them learn signs and phrases over time. The Scrum agile methodology was used during the development process. This meant that educators, linguists, and members of the deaf community all worked together to design the product. Early tests show that sign recognition accuracy and indicators of user engagement and motivation show favorable performance and are at appropriate levels. This proposal aims to enhance inclusive digital ecosystems and foster linguistic equity in Mexican education through scalable, mobile, and culturally relevant technologies, in addition to its technical contributions. Full article

Women with intellectual disabilities (IDs) face persistent health inequities, particularly in preventive services such as breast cancer screening, where participation rates remain disproportionately low. These disparities contribute to higher mortality and poorer survivorship outcomes, often linked to later-stage diagnoses. To better understand these challenges and inform the development of inclusive screening programs, this qualitative study conducted in Austria explored barriers, facilitators, and needs related to breast cancer screening from the dual perspectives of 17 women with mild-to-moderate IDs aged 45 and older and 10 caregivers. Semi-structured focus groups and interviews were analyzed thematically within a constructivist framework, integrating perspectives from both groups. Barriers included social taboos around sexuality, psychological distress, exclusion through standardized procedures, and unclear responsibility among stakeholders. Facilitators involved person-centered communication, accessible information, emotional and practical support, and familiar healthcare environments. Women with IDs expressed a strong desire for education, autonomy, and inclusion, while caregivers played a pivotal role in enabling access. These findings demonstrate that low screening participation among women with IDs is driven by systemic and organizational barriers rather than lack of health awareness or willingness to participate. Without structurally inclusive design, organized screening programs risk perpetuating preventable inequities in early detection. Embedding accessibility, clear accountability, and person-centered communication as standard features of breast cancer screening is therefore a public health priority to reduce avoidable late-stage diagnoses and narrow survival disparities for women with IDs. Full article

Objectives: We aimed to develop expert-informed recommendations for colleges and universities to support students with celiac disease (CeD) managing a gluten-free (GF) diet. Methods: A multidisciplinary panel of 40 stakeholders, including physicians, dietitians, a disability rights attorney, university staff, and students, was convened by the Celiac Disease Foundation to create expert-based and experience-informed recommendations. Over a 6-month period, the group conducted literature reviews, stakeholder interviews, and expert consensus discussions to identify common barriers and accommodations aligned with federal disability law. The expert panel collaboratively developed and revised an initial set of recommendations. Two rounds of structured voting were held during which panelists provided feedback to refine content and ensure clarity. All final recommendations were adopted with at least 90% of panelists voting in support. Results: The panel identified 24 accommodations across four domains: academics, housing, dining, and campus life. Academic recommendations include flexibility for illness-related absences, support for remote learning, and classroom modifications. Housing recommendations emphasize access to priority placement, appropriate appliances, and proximity to safe dining. Dining accommodations address GF food availability, ingredient transparency, staff training, and meal plan flexibility. Campus life recommendations ensure full participation in athletics, study abroad, social events, and internships, with supports for psychosocial well-being. Conclusions: This manuscript presents the first expert-informed recommendations focused specifically on the needs of college students with CeD. These recommendations are intended to support institutions as they develop strategies to enhance access to GF food, quality of life, educational supports, and student experience for those living with this chronic autoimmune condition. Full article

Stroke is a leading cause of death and long-term disability worldwide, with ischemic stroke accounting for approximately 62.4% of all cases. This condition often results in persistent motor dysfunction, significantly reducing patients’ productivity. The effectiveness of rehabilitation therapy is crucial for post-stroke motor recovery. However, limited access to rehabilitation services particularly in low- and middle-income countries remains a major barrier due to a shortage of experienced professionals. This challenge also affects home-based rehabilitation, an alternative to conventional therapy, which primarily relies on standard evaluation methods that are heavily dependent on expert interpretation. Electromyography (EMG) offers an objective and alternative approach to assessing muscle activity during stroke therapy in home environments. Recent advancements in deep learning (DL) have opened new avenues for automating the classification of EMG data, enabling differentiation between post-stroke patients and healthy individuals. This study introduces a novel methodology for transforming EMG signals into time–frequency representation (TFR) spectrograms, which serve as input for a convolutional neural network (CNN) model. The proposed Tri-CCNN model achieved the highest classification accuracy of 93.33%, outperforming both the Shallow CNN and the classic LeNet-5 architecture. Furthermore, an in-depth analysis of spectrogram amplitude distributions revealed distinct patterns in stroke patients, demonstrating the method’s potential for objective stroke assessment. These findings suggest that the proposed approach could serve as an effective tool for enhancing stroke classification and rehabilitation procedures, with significant implications for automating rehabilitation monitoring in home-based rehabilitation (HBR) settings. Full article

From the perspective of educational inclusion proposed by Booth and Ainscow, the transformation of school systems revolves around three key dimensions: presence, participation and learning. These dimensions constitute the axes of the so-called Inclusion Index and allow for a holistic analysis of the barriers that limit equity and inclusion in school contexts. Based on this theoretical framework, this study aims to systematically map the barriers documented in recent academic literature (2000–2025) that affect these dimensions at the primary and compulsory secondary education levels, with a special focus on intersectional variables that amplify inequalities (gender, migration, disability, mental health, among others). Full article

The transition from secondary to post-secondary levels has been seen as challenging and significant among adolescents, in particular adolescents with disabilities (ADWs). Given the increasing trend of students with disabilities pursuing higher education under the integrated education policy, it is unclear whether these students can receive appropriate support to enhance their learning and career exploration. This study investigated the experiences of ADWs during this transition. A group of 40 adolescents took part individually in a 1 h semi-structured interview. The interview data was analyzed with reference to five levels using an ecological model from microsystem, mesosystem, exosystem, macrosystem and chronosystem. Facilitating factors at each level were extracted, e.g., adequate use of assistive technologies helping them overcome their perceived limitations caused by disabilities, and accommodation in learning and assessments also helped unleash their potentials. However, difficulties were also identified, e.g., poor interaction with academic peers, issues with disability disclosure, and schools’ rigid arrangements. The results from this study corroborate the different systems as suggested by the ecological model and also align with the different components of the taxonomy of transition: (a) student-focused development and planning; (b) family involvement and support; and (c) the importance of interagency collaboration. It was recommended that a supporting network should be established between secondary schools and post-secondary institutions to enhance a smooth transition across different education sectors. Full article

Pain catastrophizing (PC) and hopelessness are increasingly recognized as central determinants of pain severity, disability, and treatment response in individuals with rheumatic and immune-mediated diseases. Traditionally conceptualized as secondary emotional reactions to pain, these cognitive-affective constructs instead represent active mechanisms that shape symptom perception, behavioral responses, and long-term outcomes. In this review, we synthesize evidence across neurobiological, psychological, and clinical domains to elucidate the pathways linking PC and hopelessness to maladaptive coping, kinesiophobia, and functional decline. Early life stress, trauma, and maladaptive cognitive schemas emerge as upstream vulnerability factors that prime heightened emotional reactivity and reduced prefrontal regulatory control, facilitating amplified pain signaling and fear-based avoidance behaviors. Avoidance and inactivity foster physical deconditioning, fatigue, and higher perceived disability, creating a vicious circle that sustains distress and poor quality of life. Moreover, inactivity-related metabolic dysfunction and weight gain may contribute to low-grade inflammation, particularly in conditions such as psoriatic arthritis, thereby intersecting with biological disease pathways. Importantly, these psychological processes identify a distinct patient subgroup for whom further escalation of immunosuppressive therapy provides limited benefit. Instead, integrated psychological approaches—including cognitive behavioral therapy, acceptance and commitment therapy, and coping-skills training—demonstrate meaningful effects on catastrophizing, agency, and functional recovery. We emphasize the need for routine screening to detect patients with maladaptive cognitive–emotional profiles and propose a stratified care model prioritizing targeted psychological interventions alongside standard rheumatologic therapy. Future research should refine phenotyping strategies, clarify neuroimmune links, and develop scalable intervention models to break the avoidance cycle and improve patient-centered outcomes. Full article

Intracranial Hemorrhage (ICH) remains a critical life-threatening condition where timely and accurate diagnosis using non-contrast Computed Tomography (CT) scans is vital to reduce mortality and long-term disability. Deep learning methods have shown strong potential for automated hemorrhage detection, yet most existing approaches lack confidence quantification and clinical interpretability, which limits their adoption in high-stakes care. This study presents X-HEM, an explainable hemorrhage ensemble model for reliable detection of Intracranial Hemorrhage (ICH) on non-contrast head CT scans. The aim is to improve diagnostic accuracy, interpretability, and confidence for real-time clinical decision support. X-HEM integrates three convolutional backbones (VGG16, ResNet50, DenseNet121) through soft voting. Bayesian uncertainty is estimated using Monte Carlo Dropout, while Grad-CAM++ and SHAP provide spatial and global interpretability. Training and validation were conducted on the RSNA ICH dataset, with external testing on CQ500. The model achieved AUCs of 0.96 (RSNA) and 0.94 (CQ500), demonstrated well-calibrated confidence (low Brier/ECE), and provided explanations that aligned with radiologist-marked regions. The integration of ensemble learning, Bayesian uncertainty, and dual explainability enables X-HEM to deliver confidence-aware, interpretable ICH predictions suitable for clinical use. Full article

Background: Parental burnout is a state of extreme exhaustion that is detrimental to family life. There is some evidence, albeit limited, that children of exhausted parents are at risk of neglect or abuse. The children’s lived experience remains an underinvestigated issue. This qualitative and participatory study aimed to explore children’s and adolescents’ perceptions and experience of parental burnout, as well as the resources they identify as available to assist them. Methods: We interviewed 24 children of exhausted parents, including children typically developing (n = 17), children with illness/disability (n = 3), and children with learning/behavioral difficulties (n = 4). We used interactive data collection tools, adapted to the participants’ age. The interviews were followed by a participatory validation seminar. Results: We evidenced a high emotional burden experienced by children exposed to parental burden. The children conveyed feeling insecure about what happens, perceiving a mismatch between their own needs and those of their parents, and being afraid both of and for their parents. Conclusions: Our results call for an increased recognition of parental burnout as not only a personal or family problem, but a possibly important societal and public health concern, with implications for child prevention and health promotion. Full article

School leaders are central to addressing educational inequality by fostering inclusion and belonging within their school communities. In fast-growth educational environments where enrollment surges and demographic shifts outpace resource capacity, school leaders face complex challenges in developing inclusive structures and cultures for students with disabilities. In this qualitative case study, the authors examined how 18 principals across PreK-12 grade levels in three rapidly expanding Texas districts conceptualized and enacted inclusive leadership. Thematic analysis of semi-structured interviews and focus groups revealed that while principals believed all students are capable of learning, they defined inclusion philosophically but implemented pragmatically limited notions of inclusion shaped by their districts’ organizational structures and continuum of services approaches to special education. Findings illustrate that fast-growth contexts amplify tensions between compliance and care, as school leaders balance external accountability and resource constraints with efforts to cultivate school cultures grounded in empathy, relationships, safety, and belonging. The study presents a complicated picture of how principals navigate pragmatic constraints while pursuing inclusive practices for students receiving special education services. Inclusive educational leadership in fast-growth school environments is more likely to occur when leaders reframe inclusion not as placement, but as a shared commitment to recognizing every student’s capability within a responsive community. Full article

Infantile Epileptic Spasms Syndrome (IESS) is a devastating epileptic encephalopathy of infancy that carries a high risk of lifelong neurodevelopmental disability. Timely diagnosis is critical, as every week of delay in effective treatment is associated with worse cognitive outcomes. Although synchronized electroencephalogram (EEG) and surface electromyography (EMG) recordings capture both the electrophysiological and motor signatures of spasms, accurate automated detection remains challenging due to the non-stationary nature of the signals and the absence of physiologically plausible inter-modal fusion in current deep learning approaches. We introduce IESS-FusionNet, an end-to-end dual-stream framework specifically designed for accurate, real-time IESS detection from simultaneous EEG and EMG. Each modality is processed by a dedicated Unimodal Encoder that hierarchically integrates Continuous Wavelet Transform, Spatio-Temporal Convolution, and Bidirectional Mamba to efficiently extract frequency-specific, spatially structured, local and long-range temporal features within a compact module. A novel Cross Time-Mixing module, built upon the linear recurrent attention of the Receptance Weighted Key Value (RWKV) architecture, subsequently performs efficient, time-decaying, bidirectional cross-modal integration that explicitly respects the causal and physiological properties of cortico-muscular coupling during spasms. Evaluated on an in-house clinical dataset of synchronized EEG-EMG recordings from infants with confirmed IESS, IESS-FusionNet achieves 89.5% accuracy, 90.7% specificity, and 88.3% sensitivity, significantly outperforming recent unimodal and multimodal baselines. Comprehensive ablation studies validate the contribution of each component, while the proposed cross-modal fusion requires approximately 60% fewer parameters than equivalent quadratic cross-attention mechanisms, making it suitable for real-time clinical deployment. IESS-FusionNet delivers an accurate, computationally efficient solution with physiologically inspired cross-modal fusion for the automated detection of infantile epileptic spasms, offering promise for future clinical applications in reducing diagnostic delay. Full article