Code Repositories
Here you will find links to the code repositories for some of the publications by researchers at Simpson Querrey Lung Institute for Translational Science (SQLIFTS).
General
Successful Clinical Response In Pneumonia Therapy (SCRIPT)
- NU SCRIPT Study on GitHub
Division of Pulmonary and Critical Care
- NU Pulmonary on GitHub
Specific Publications
Grant RA, Morales-Nebreda L, Markov NS, et al. Circuits between infected macrophages and T cells in SARS-CoV-2 pneumonia. Nature. 2021; 590(7847):635-641.
- NUPulmonary / 2020_Grant on GitHub
Stoeger T, et al. Aging is associated with a systemic length-associated transcriptome imbalance. Nature Aging. 2022; 2(12):1191-1206.
Gao CA, Markov NS, Stoeger T, et al. Machine learning links unresolving secondary pneumonia to mortality in patients with severe pneumonia, including COVID-19. Journal of Clinical Investigation. 2203; 133(12):e170682.
- NUSCRIPT / CarpeDiem on GitHub
Grant RA, Poor TA, et al. Prolonged exposure to lung-derived cytokines is associated with activation of microglia in patients with COVID-19. JCI Insight. 2024; 9(8):e178859.
- NUPulmonary / 2023_Grant_Poor on GitHub
Bailey JI, Puritz CH, Senkow KJ, et al. Profibrotic monocyte-derived alveolar macrophages are expanded in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19. Nature Immunology. 2024. doi: 10.1038/s41590-024-01975-x. Online ahead of print.
- / Bailey_Puritz_Senkow_RPRA_2024 on GitHub
Markov NS, et al. Distinctive evolution of alveolar T cell responses is associated with clinical outcomes in unvaccinated patients with SARS-CoV-2 pneumonia. Nature Immunology. 2024; 25(9):1607-1622.
- / 2024_Markov_Ren_Senkow on GitHub
Fenske SW, Peltekian A, et al. Developing and validating a machine learning model to predict successful next-day extubation in the ICU (preprint).