ABSTRACT
Type I interferonopathies are a broad category of conditions associated with increased type I interferon gene expression and include monogenic autoinflammatory diseases and non-Mendelian autoimmune diseases such as dermatomyositis and systemic lupus erythematosus. While a wide range of clinical presentations among type I interferonopathies exists, these conditions often share several clinical manifestations and implications for treatment. Presenting symptoms may mimic non-Mendelian autoimmune diseases, including vasculitis and systemic lupus erythematosus, leading to delayed or missed diagnosis. This review aims to raise awareness about the varied presentations of monogenic interferonopathies to provide early recognition and appropriate treatment to prevent irreversible damage and improve quality of life and outcomes in this unique patient population.
ABSTRACT
The dynamics of cardiac fibrillation can be described by the number, the trajectory, the stability, and the lifespan of phase singularities (PSs). Accurate PS tracking is straightforward in simple uniform tissues but becomes more challenging as fibrosis, structural heterogeneity, and strong anisotropy are combined. In this paper, we derive a mathematical formulation for PS tracking in two-dimensional reaction-diffusion models. The method simultaneously tracks wavefronts and PS based on activation maps at full spatiotemporal resolution. PS tracking is formulated as a linear assignment problem solved by the Hungarian algorithm. The cost matrix incorporates information about distances between PS, chirality, and wavefronts. A graph of PS trajectories is generated to represent the creations and annihilations of PS pairs. Structure-preserving graph transformations are applied to provide a simplified description at longer observation time scales. The approach is validated in 180 simulations of fibrillation in four different types of substrates featuring, respectively, wavebreaks, ionic heterogeneities, fibrosis, and breakthrough patterns. The time step of PS tracking is studied in the range from 0.1 to 10 ms. The results show the benefits of improving time resolution from 1 to 0.1 ms. The tracking error rate decreases by an order of magnitude because the occurrence of simultaneous events becomes less likely. As observed on PS survival curves, the graph-based analysis facilitates the identification of macroscopically stable rotors despite wavefront fragmentation by fibrosis.