Homology of homologous knotted proteins.

Quantification and classification of protein structures, such as knotted proteins, often requires noise-free and complete data. Here, we develop a mathematical pipeline that systematically analyses protein structures. We showcase this geometric framework on proteins forming open-ended trefoil knots, and we demonstrate that the mathematical tool, persistent homology, faithfully represents their structural homology. This topological pipeline identifies important geometric features of protein entanglement and clusters the space of trefoil proteins according to their depth. Persistence landscapes quantify the topological difference between a family of knotted and unknotted proteins in the same structural homology class. This difference is localized and interpreted geometrically with recent advancements in systematic computation of homology generators. The topological and geometric quantification we find is robust to noisy input data, which demonstrates the potential of this approach in contexts where standard knot theoretic tools fail.

Upload and Review of Insulin Pump and Glucose Sensor Data by Adults with Type 1 Diabetes: A Clinic Audit.

Devices have facilitated improvement in glycemia in individuals with type 1 diabetes mellitus (T1DM), but self-management remains key. It is unclear whether people review their device data before clinic appointment. We assessed this by a survey. T1DM adults using glucose sensors and/or insulin pumps attending an Australian public hospital (diabetes clinics >4 months) were prospectively surveyed. The percentage who uploaded and reviewed their data was determined and their interest in education facilitating understanding of their device data was assessed. Of 138 adults (100% participation rate), 79% uploaded and 32% reviewed their device data before their clinic appointments. Individuals using pumps with sensors were most likely to review their data. Median HbA1c levels were lower in those who did versus did not review their device data (50.8 vs. 61.8 mmol/mol, P = 0.0001). Most (89%) were interested in education. Although diabetes technology has improved glycemia in T1DM, the benefits may be maximized through device-specific education programs enhancing self-management.