Autism

Network analysis of serotonin CNVs shows biological convergence from genetic heterogeneity and discriminates between autism and developmental delay.

Differentiating autism spectrum disorder (ASD) from developmental delay (DD) is critical for guiding early intervention, but overlapping features and shared biological mechanisms pose challenges. This study investigates whether copy number variations (CNVs) affecting serotonergic genes carry sufficient information to distinguish between these neurodevelopmental disorders (NDDs). Using network mapp...

Decoding variants of uncertain significance in systemic autoinflammatory diseases.

The development and implementation of genetic testing has revolutionized the diagnostic landscape of autoinflammatory diseases, leading to an exponential increase in the identification of disease-associated genetic variants. Yet a substantial proportion of these are considered variants of uncertain significance (VUS), complicating both diagnosis and therapeutic decision-making. This challenge is r...

Genetic algorithm-optimized machine learning approaches for EEG-based silent speech decoding.

The phases of human communication consist of speech perception, production, and imagination. The objective of this work is to understand and analyse t...

Recent Advances in Omics and Genetic Tools in Schistosome Research and Control.

Schistosomiasis is a neglected tropical disease posing a persistent threat to global health, particularly in endemic areas. Mass drug administration w...

Maternal obesity and the embryonic rewiring of feeding circuits: beyond the hypothalamus.

Maternal obesity disrupts fetal hypothalamic development by inducing structural changes in feeding circuits, such as reduced hypothalamic precursor pr...

An integrated machine learning and chemical space network approach for the design of potent epigenetic HDAC6 inhibitors for targeting neurological disorders.

Histone deacetylase 6 (HDAC6) is increasingly recognized as a key regulator of cytoskeletal dynamics and intracellular transport in both neurodevelopm...

Coformer: a deep learning-based framework for cross-environment and multi-year cotton phenotype prediction and interpretation.

Accurate prediction of key agronomic traits in cotton is crucial for advancing its genetic improvement and enabling breeding-by-design. However, when ...

Surface-based brain age index reflects hematological impacts on cognitive development in children with beta-thalassemia major.

Children with beta-thalassemia major (β-TM) are at risk of neurodevelopmental or cognitive impairment. In this study, we developed SurfGNN, a surface-...

The Evolution of Precision Anti-Doping From UGT2B17 Polymorphism Insights to Integrated Detection Frameworks.

Screening for endogenous anabolic-androgenic steroid abuse has long relied on the urinary testosterone/epitestosterone (T/E) ratio. However, this metr...

Advances in laboratory diagnostic studies of pheochromocytoma and paraganglioma.

Pheochromocytoma (PCC) and paraganglioma (PGL), collectively referred to as pheochromocytomas and paragangliomas (PPGLs), are rare neuroendocrine tumo...

Gated edge-node interaction graph convolutional network for ADHD classification.

Objective.Attention deficit hyperactivity disorder (ADHD) remains challenging to diagnose objectively and often relies on subjective clinical assessme...

Metagenomic polymorphic toxin effector and immunity profiling predicts microbiome development and disease-related dysbiosis.

Bacteria use antagonistic interbacterial weapons, such as polymorphic toxin secretion systems (TSS), to compete for niches in the human gut microbiome...

Understanding Blood-Injection-Injury Phobia: Do Not Miss the Point.

Needle and blood-injection-injury phobia is commonly encountered in the perioperative setting. It can significantly disrupt operating room throughput,...

Identification of Potential Biomarkers in ASD Integrating RNA Seq Data and Machine Learning Approaches.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, caused by various epigenetic and genetic factors. This has resulted in an unclear und...

Emerging frontiers in genome editing: From CRISPR to next-generation technologies.

Genome editing has revolutionized molecular biology. It offers precise modification of genetic material across diverse organisms. This review outlines...

Integrating temporal morphophysiological and genomic markers for precise classification of flowering time in cannabis.

Indigenous Cannabis sativa populations exhibit remarkable diversity in their flowering-time responses to photoperiod cues, reflecting adaptation to va...

Microscopic image enhancement for accurate sickle cell disease identification using intuitionistic fuzzy driven retinex.

Sickle cell disease (SCD) is a debilitating genetic blood disorder that must be identified and diagnosed early for effective treatment planning. Sever...

Pan-cancer analysis of single-cell profiles with polygenic signals reveals genetic influences on tumor immunity across cancers.

Inherited genetic variation can weaken the ability of the immune system to detect and eliminate malignant cells, limiting the effectiveness of cancer ...

Smartphone movement data can reliably predict smoking lapses and cravings to enable timely smoking cessation support.

Decades of research aiming to develop effective smoking interventions have identified triggers that contribute to failed quitting attempts including e...

A translational multimodal machine-learning prototype predicting valproate response in epilepsy treatment.

OBJECTIVE: Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a co...