Mature neutrophils and a NF-κB-to-IFN transition determine the unifying disease recovery dynamics in COVID-19.

Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome.

Stabilizing human regulatory T cells for tolerance inducing immunotherapy.

Many autoimmune diseases develop as a consequence of an altered balance between autoreactive immune cells and suppressive FOXP3 Treg. Restoring this balance through amplification of Treg represents a promising strategy to treat disease. However, FOXP3 Treg might become unstable especially under certain inflammatory conditions, and might transform into proinflammatory cytokine-producing cells.