Primary Amenorrhea in a 15-Year-Old Girl Leading to the Diagnosis of Bardet-Biedl Syndrome: A Case Report.

This case report highlights the clinical complexity of Bardet-Biedl syndrome, a rare autosomal recessive disorder, emphasizing reproductive anomalies to aid in diagnosis and management. It underscores the importance of thorough assessment and advocates for genetic testing to optimize care, despite current financial, and laboratory constraints.

Advanced AI and ML frameworks for transforming drug discovery and optimization: With innovative insights in polypharmacology, drug repurposing, combination therapy and nanomedicine.

Artificial Intelligence (AI) and Machine Learning (ML) are transforming drug discovery by overcoming traditional challenges like high costs, time-consuming, and frequent failures. AI-driven approaches streamline key phases, including target identification, lead optimization, de novo drug design, and drug repurposing. Frameworks such as deep neural networks (DNNs), convolutional neural networks (CNNs), and deep reinforcement learning (DRL) models have shown promise in identifying drug targets, optimizing delivery systems, and accelerating drug repurposing.

Dynamic contrast-enhanced magnetic resonance lymphangiography: a simple algorithm for image interpretation.

Dynamic contrast-enhanced magnetic resonance lymphangiography is a high-resolution imaging technique that has emerged as the preferred method for evaluating lymphatic anatomy and flow dynamics due to its precise anatomical detail. The lymphatic system has a complex anatomical distribution, and variability is common among individuals with cardiac abnormalities, particularly congenital heart disease. Lymphatic imaging has recently been revolutionized by the introduction of MR lymphangiography.

Graphene nanosheets decorated with heterostructured ruthenium sulfide as catalyst for enhanced hydrogen evolution reaction.

In present findings, a simple pyrolysis technique was applied to decorate S and N doped graphene with RuS2-CoO nanoparticles synthesizing a heterostructured nanocomposite RuS2-CoO@SNG. XPS results demonstrate the elemental composition of these nanomaterials with the hint of metal-metal charge transfer phenomenon likely due to heterostructure composition. These modifications led to a significant active surface area resulting in elevated electrocatalytic performance.