A new approach to identifying patients with elevated risk for Fabry disease using a machine learning algorithm.

Background: Fabry disease (FD) is a rare genetic disorder characterized by glycosphingolipid accumulation and progressive damage across multiple organ systems. Due to its heterogeneous presentation, the condition is likely significantly underdiagnosed. Several approaches, including provider education efforts and newborn screening, have attempted to address underdiagnosis of FD across the age spectrum, with limited success.

Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis.

Objective: Disease activity measures, such as the Clinical Disease Activity Index (CDAI), are important tools for informing treatment decisions and monitoring patient outcomes in rheumatoid arthritis (RA). Yet, documentation of CDAI scores in electronic medical records and other real-world data sources is inconsistent, making it challenging to use these data for research. The purpose of this study was to validate a machine learning model to estimate CDAI scores for patients with RA using clinical notes.

Scaling of cytoskeletal organization with cell size in .

Spatially organized macromolecular complexes are essential for cell and tissue function, but the mechanisms that organize micron-scale structures within cells are not well understood. Microtubule-based structures such as mitotic spindles scale with cell size, but less is known about the scaling of actin structures within cells. Actin-rich denticle precursors cover the ventral surface of the embryo and larva and provide templates for cuticular structures involved in larval locomotion.

Combined deletion of cathepsin protease family members reveals compensatory mechanisms in cancer.

Proteases are important for regulating multiple tumorigenic processes, including angiogenesis, tumor growth, and invasion. Elevated protease expression is associated with poor patient prognosis across numerous tumor types. Several multigene protease families have been implicated in cancer, including cysteine cathepsins.