Autism

Heterophily-Aware Spectral GCN for Population-Level Brain Disorder Prediction.

Integrating resting-state functional magnetic resonance imaging (rs-fMRI) and phenotypic data is a promising way to build a comprehensive population graph for the prediction of brain disorders using graph neural networks (GNNs). However, existing GNN-based methods face two limitations: the complexity of relationships between subjects poses challenges in constructing a well-defined population graph...

Threat discrimination of real-world social interactions in schizotypal traits.

Threat detection is compromised across the schizophrenia spectrum, often revealed by paranoia and delusions. Threat difficulties extend to nonclinical populations with liability toward schizophrenia. A key source of these difficulties may be due to hyper-sensitivity to social stressors in real-world environments. In a large, nonclinical sample (N = 161), we measured the influence of social context...

Artificial intelligence-based classification of Spitz tumors.

Spitz tumors are diagnostically challenging due to overlap in atypical histological features with conventional melanomas. We investigated to what exte...

DoBSeqWF: a framework for sensitive detection of individual genetic variation in pooled sequencing data.

Population screening for rare genetic diseases has the potential to increase early diagnosis and treatment, but the high cost of next-generation seque...

Predicting fine motor deficit in autism by measuring brain activities and characterizing motor impairments.

Motor impairments affect approximately 86.9% of children with Autism Spectrum Disorder (ASD), often persisting into adolescence and increasing the ris...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offering advantages over CAR-T therapy, including reduc...

Genetic structure analysis of a Northwest Chinese population using a self-developed DIP system and machine learning for forensic ancestry inference.

This study investigates forensic ancestry inference in admixed populations using a self-developed 60-DIP panel, analyzing Kyrgyz samples from Northwes...

Gross motor performance of infants with an at-home wearable measurement and the Alberta Infant Motor Scale: A concurrent validity study.

AIM: To evaluate the concurrent validity of assessing infants' gross motor performance with an at-home wearable measurement versus the Alberta Infant ...

Update on pharmacogenomic approaches in the treatment of autism spectrum disorders.

Advances and applications in tumor organoid research Harnessing human tumor organoids for cancer modeling and precision therapy.

Human tumor organoids represent a paradigm shift in cancer modeling, overcoming critical limitations of conventional systems by faithfully recapitulat...

Genetic risk in Alzheimer's disease.

Alzheimer's disease (AD) has a strong genetic predisposition. Genome-wide association studies have identified multiple risk loci, yet many non-coding ...

Neuroprognostication via Radiomics and Machine Learning Following Neonatal Hypoxic-Ischemic Insult.

OBJECTIVE: To produce objective predictions of neurodevelopmental outcomes after perinatal hypoxic-ischemic insult for the full spectrum of severity o...

Neuroimaging-derived brain age as a new promising biomarker in mental disorders.

Mental disorders are frequently associated with accelerated brain aging, yet the diagnostic and classificatory utility of brain age remains uncertain....

Early Maturation of Heart Rate Variability in Very Preterm Infants Depends on Neonatal Factors and Is Associated With Neurodevelopmental Risk.

AIM: This study investigated central autonomic network maturation deviations using a previously defined machine learning model set to estimate a funct...

A Multimodal Dataset for Neurophysiological and AI Applications.

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivit...

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-assessment tools identify only a fraction of women wh...

Establishment of insulin resistance-related ten-gene signature in endometrial cancer and identification of ACTL8 as a prognostic and immunological biomarker.

BACKGROUND: Endometrial cancer (EC) is a common gynecological tumor. Insulin resistance (IR) increases the risk of EC. However, the common molecular b...

Comparative analysis of BORIS, Ethovision, DeepLabCut, and SimBA for quantifying autism spectrum disorder-like behaviors in the valproic acid mouse model.

Preclinical research often relies on animal observation and subsequent behavioral analysis to study brain function; however, traditional methods are c...

Integrating environmental factors and genetic variants in machine learning to assess occupational noise impact on health.

Noise-induced hearing loss (NIHL) is a complex disorder arising from the interplay between noise, as well as contributions from other environmental an...

Unsupervised Disentanglement of Brain Heterogeneity for Identifying Subtypes of Alzheimer's Disease.

Neuroanatomical heterogeneity in Alzheimer's disease (AD) hinders precision diagnosis and treatment, as distinct brain phenotypes may correspond to di...