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Nucleoside-modified messenger RNA (mRNA) vaccines elicit protective antibodies through their ability to promote T follicular helper (Tfh) cell differentiation. The lipid nanoparticles (LNPs) of mRNA vaccines possess intrinsic adjuvant activity. However, the extent to which nucleoside-modified mRNA is sensed and contributes to Tfh cell responses remains undetermined.
VLPs are nanoparticles formed by the self-assembly of viral structural proteins that mimic viral particles. VLPs do not contain genetic material, therefore they cannot replicate and are not infectious. This significantly enhances their safety compared to attenuated live vaccines or recombinant viral vectors, as unlike viral vector vaccines, they do not synthesize additional copies of immunogens.
Focal segmental glomerulosclerosis (FSGS) is a common glomerular lesion characterized by primary podocyte injury. Multiple genetic risk factors have been reported to be associated with the occurrence of FSGS. However, whether epigenetic factors, particularly N6-methyladenosine (m6A) modification, are involved in the pathogenesis of FSGS remains unclear.
Base editors enable precise conversion of single nucleotides without causing DNA double-strand breaks. This new generation of gene editing technology can theoretically correct most known pathogenic single-base mutations in humans, showing tremendous potential for treating genetic diseases.
Antibody-drug conjugate (ADC) target selection is a core aspect of drug design that directly impacts efficacy and safety. Current strategies emphasize achieving a balance between innovation and risk control, primarily focusing on two paths: optimization of established targets and exploration of new targets.
The homologous recombination (HR) pathway repairs DNA damage, such as double-strand breaks (DSBs), by copying sequence information from a homologous donor DNA template (typically the sister chromatid) to the damaged site. During HR in mammals, the RAD51 (radiation-sensitive protein 51) recombinase forms a nucleoprotein filament around the resected single-stranded DNA (ssDNA) generated during DSB end processing at the DSB site, known as the presynaptic filament. Subsequently, the presynaptic filament scans the genome for a suitable homologous DNA donor through a process called homology search. However, how this homology search occurs in the context of the three-dimensional (3D) genome remains largely unexplored.
In a new study, scientists from the Max Planck Institute for Evolutionary Anthropology analyzed the effects of over 2,000 clinically approved drugs on DNA repair and CRISPR genome editing outcomes. They discovered compounds that could be used to improve genome editing, molecules that can selectively kill cultured cancer cells, and further identified two proteins with novel functions in DNA repair.
During the global COVID-19 pandemic, mRNA vaccines gained worldwide recognition for their high efficiency and safety, showcasing the tremendous potential of mRNA technology. However, the applications of mRNA extend far beyond vaccines. In treating complex diseases like cancer, precisely delivering drugs to diseased cells while avoiding damage to healthy tissues has long been a major challenge in the medical field. Currently, although technologies like lipid nanoparticles (LNP) are widely used for mRNA delivery, their targeting capabilities remain limited, often leading to drug accumulation in non-target organs like the liver, causing potential side effects.
If breast cancer poses a significant threat to women's health, then triple-negative breast cancer (TNBC) is the most cunning and stubborn type among them. It grows rapidly, is prone to early metastasis, and more problematically, it lacks estrogen receptors, progesterone receptors, and HER2 protein-these three targets are the "sights" for many effective anti-cancer drugs. Therefore, TNBC has limited treatment options, chemotherapy remains the primary approach, and it easily develops drug resistance, often returning more aggressively after recurrence.
Artificial intelligence (AI) is driving advancements in genome editing, from predictive modeling to generative design. Emerging generative AI tools such as RFdiffusion, AlphaFold 3, and ESM now facilitate the de novo design of linkers, inhibitors, and enzymes. Recently, a commentary article titled "Expansion of artificial intelligence for genome editing" published in Nature Structural & Molecular Biology reviewed the recent work by Lu et al., who utilized AI to improve the precision of mitochondrial cytosine base editors.
