Mesoporous Zr MOFs regulated by linear ligand replacement strategy to achieve single Ru(bpy) molecule encapsulation for ratio ECL detection of miRNA-21.

Rational optimization of the pore size and topology of porous nanocarriers is crucial for improving the loading amount of luminophore and enhancing electrochemiluminescence (ECL) performance. In this study, an equimolar linear ligand replacement strategy was employed to synthesize novel mesoporous metal-organic frameworks (MOFs) for encapsulating Ru(bpy) (Ru@Zr MOFs) under room temperature without an acid modulator. Ingenious ligand substitution allows precise control of pore size, enabling encapsulation at the single-molecule level within mesoporous cages.

Promising Therapeutic Targets for Intracranial Aneurysms: A Systematic druggable genome-wide Mendelian Randomization.

Background: Intracranial aneurysm (IA), known as pathological dilation of cerebral arteries,commonly occurring at bifurcating arteries,carries a high risk of severe morbidity and mortality if left untreated.Although the treatment and early diagnosis have significantly improved,the complex pathophysiological process of IA formation presents significant challenges in the development of targeted therapies.Efficient disease-modifying therapies for IA are not yet available.

Dual-Mode Hybrid Discharge Plasma-Activated Injectable Hydrosol for Enhanced Immunotherapeutic Cancer Therapy.

Although cold atmospheric plasma is a promising therapeutic technique for tumor immunotherapy via reactive oxygen and nitrogen species (RONS), the challenges associated with the generation and delivery of these RONS hamper clinical adoption. Herein, a dual-mode hybrid discharge plasma-activated sodium alginate hydrosols (PAH) is proposed to enhance the antitumor immune response. Gaseous highly reactive RONS are generated by dual-mode hybrid plasma produced by mixed O and NO modes, which are converted into aqueous RONS in PAH via gas-liquid reactions between plasma and hydrosols.

AI-driven and Traditional Radiomic Model for Predicting Muscle Invasion in Bladder Cancer via Multi-parametric Imaging: A Systematic Review and Meta-analysis.

Rationale And Objectives: This study systematically evaluates the diagnostic performance of artificial intelligence (AI)-driven and conventional radiomics models in detecting muscle-invasive bladder cancer (MIBC) through meta-analytical approaches. Furthermore, it investigates their potential synergistic value with the Vesical Imaging-Reporting and Data System (VI-RADS) and assesses clinical translation prospects.

Methods: This study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.