45 research outputs found
Intraocular Pressure Effects of Common Topical Steroids for Post-Cataract Inflammation: Are They All the Same?
Filtering Surgery in Owl Monkeys Treated with the Antimetabolite 5-Fluorouridine 5′-Monophosphate Entrapped in Multivesicular Liposomes
Utilization and cost-effectiveness of school and community center AED deployment models in Canadian cities
Comparative study on determination of fumagillin in fish by normal and reversed phase chromatography
Liposome-Encapsulated (S)-1-(3-Hydroxy-2-Phosphonylmethoxypropyl)cytosine for Long-Acting Therapy of Viral Retinitis
Intracellular bacteria engage a STING-TBK1-MVB12b pathway to enable paracrine cGAS-STING signalling
The innate immune system is crucial for eventual control of infections, but may also contribute to pathology. Listeria monocytogenes is an intracellular Gram-positive bacteria and a major cause of food-borne disease. However, important knowledge on the interactions between L. monocytogenes and the immune system is still missing. Here, we report that Listeria DNA is sorted into extracellular vesicles (EVs) in infected cells and delivered to bystander cells to stimulate the cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)-stimulator of interferon genes (STING) pathway. This was also observed during infections with Francisella tularensis and Legionella pneumophila. We identify the multivesicular body protein MVB12b as a target for TANK-binding kinase 1 phosphorylation, which is essential for the sorting of DNA into EVs and stimulation of bystander cells. EVs from Listeria-infected cells inhibited T-cell proliferation, and primed T cells for apoptosis. Collectively, we describe a pathway for EV-mediated delivery of foreign DNA to bystander cells, and suggest that intracellular bacteria exploit this pathway to impair antibacterial defence
2023 Roadmap on molecular modelling of electrochemical energy materials
New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as empowered by machine learning techniques can help us to understand, control and design electrochemical energy materials at atomistic precision. Therefore, this roadmap, which is a collection of authoritative opinions, serves as a gateway for both the experts and the beginners to have a quick overview of the current status and corresponding challenges in molecular modelling of electrochemical energy materials for batteries, supercapacitors, CO2 reduction reaction, and fuel cell applications