Antifouling Immunomodulatory Copolymer Architectures That Inhibit the Fibrosis of Implants.

Immune reactions to medical implants often lead to encapsulation by fibrotic tissue and impaired device function. This process is thought to initiate by protein adsorption, which enables immune cells to attach and mount an inflammatory response. Previously, several antifibrotic materials have been either designed to reduce protein adsorption or discovered via high-throughput screens (HTS) to favorably regulate inflammation.

Artificial intelligence-guided design of lipid nanoparticles for pulmonary gene therapy.

Ionizable lipids are a key component of lipid nanoparticles, the leading nonviral messenger RNA delivery technology. Here, to advance the identification of ionizable lipids beyond current methods, which rely on experimental screening and/or rational design, we introduce lipid optimization using neural networks, a deep-learning strategy for ionizable lipid design. We created a dataset of >9,000 lipid nanoparticle activity measurements and used it to train a directed message-passing neural network for prediction of nucleic acid delivery with diverse lipid structures.

Identifying Patients with Heart Failure Eligible for Guideline-Directed Medical Therapy.

A majority of patients with heart failure (HF) do not receive adequate medical therapy as recommended by clinical guidelines. One major obstacle encountered by population health management (PHM) programs to improve medication usage is the substantial burden placed on clinical staff who must manually sift through electronic health records (EHRs) to ascertain patients' eligibility for the guidelines. As a potential solution, the study team developed a rule-based system (RBS) that automatically parses the EHR for identifying patients with HF who may be eligible for guideline-directed therapy.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.