Results 161 to 170 of about 602,475 (301)
RNA‑binding protein DAZAP1 promotes gastric cancer metastasis by enhancing NOTCH1 and JAG1 mRNA stability. [PDF]
Peng S +19 more
europepmc +1 more source
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley +12 more
wiley +1 more source
The METTL3-IGF2BP3 axis drives osteosarcoma progression by enhancing ID1 mRNA stability. [PDF]
Shu R +8 more
europepmc +1 more source
There is a significant need for biomaterials with well‐defined stability and bioactivity to support tissue regeneration. In this study, we developed a tunable microgel platform that enables the decoupling of stiffness from porosity, thereby promoting bone regeneration.
Silvia Pravato +9 more
wiley +1 more source
A new mechanism regulating microglial NLRP3 inflammasome: FMR1 mediates NLRP3 mRNA stability. [PDF]
Deng Q +11 more
europepmc +1 more source
Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim +4 more
wiley +1 more source
STC2 promotes anoikis resistance by modulating TGIF1 mRNA stability in colorectal cancer. [PDF]
Hu F, He Q, Ding Z, Cheng J, Lin J.
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
HELZ2 Regulates <i>Apob</i> mRNA Stability to Modulate Fatty Liver Disease and Atherosclerosis. [PDF]
Jiang Y, Zhang Z.
europepmc +1 more source

