Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows.
View Article and Find Full Text PDFBackground: Diphtheria is a recurrent threat with endemic still occurs in many parts of the world. The standard of care is horse serum-derived diphtheria antitoxin (eDAT), which is in critical short supply globally. S315 is a fully human, monoclonal immunoglobulin G1 neutralizing antibody, specific to the receptor-binding domain of diphtheria toxin.
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