Foxi1 regulates multiple steps of mucociliary development and ionocyte specification through transcriptional and epigenetic mechanisms.

Foxi1 is a master regulator of ionocytes (ISCs / INCs) across species and organs. Two subtypes of ISCs exist, and both α- and β-ISCs regulate pH- and ion-homeostasis in epithelia. Gain and loss of FOXI1 function are associated with human diseases, including Pendred syndrome, male infertility, renal acidosis and cancers.

Temporal Notch signaling regulates mucociliary cell fates through Hes-mediated competitive de-repression.

Tissue functions are determined by the types and ratios of cells present, but little is known about self-organizing principles establishing correct cell type compositions. Mucociliary airway clearance relies on the correct balance between secretory and ciliated cells, which is regulated by Notch signaling across mucociliary systems. Using the airway-like epidermis, we investigate how cell fates depend on signaling, how signaling levels are controlled, and how Hes transcription factors regulate cell fates.

Data-driven prediction of COVID-19 cases in Germany for decision making.

Background: The COVID-19 pandemic has led to a high interest in mathematical models describing and predicting the diverse aspects and implications of the virus outbreak. Model results represent an important part of the information base for the decision process on different administrative levels. The Robert-Koch-Institute (RKI) initiated a project whose main goal is to predict COVID-19-specific occupation of beds in intensive care units: Steuerungs-Prognose von Intensivmedizinischen COVID-19 Kapazitäten (SPoCK).

[Forecasting models to guide intensive care COVID-19 capacities in Germany].

Background: Time-series forecasting models play a central role in guiding intensive care coronavirus disease 2019 (COVID-19) bed capacity in a pandemic. A key predictor of future intensive care unit (ICU) COVID-19 bed occupancy is the number of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in the general population, which in turn is highly associated with week-to-week variability, reporting delays, regional differences, number of unknown cases, time-dependent infection rates, vaccinations, SARS-CoV‑2 virus variants, and nonpharmaceutical containment measures. Furthermore, current and also future COVID ICU occupancy is significantly influenced by ICU discharge and mortality rates.