The Fermi surface topology of the shape-memory alloy Ni0.62Al0.38 has been determined using Compton scattering. A large area of this Fermi surface can be made to nest with other areas by translation through a vector of ≈ 0.18 [1, 1, 0](2π/a), which correponds to the wavevector associated with martensitic precursor phenomena such as phonon softening and diffuse streaking in electron diffraction patterns. This observation is compelling evidence that these phenomena are driven by the enhanced electron-lattice coupling due to the Fermi surface nesting.
The existence of flat areas of a Fermi surface (FS), predicted by electronic structure calculations and used in models of both magnetically mediated and phonon-mediated Fulde-Ferrell-LarkinOvchinnikov superconducting states, is reported in the paramagnetic phase of the ferromagnetic superconductor ZrZn 2 using positron annihilation. The strongly mass-renormalized FS sheet, dominating the Fermi level density of states, is seen for the first time. The delocalization of the magnetization is studied using measured and calculated magnetic Compton profiles.
Anti‐transferrin receptor (TfR)‐based bispecific antibodies have shown promise for boosting antibody uptake in the brain. Nevertheless, there are limited data on the molecular properties, including affinity required for successful development of TfR‐based therapeutics. A complex nonmonotonic relationship exists between affinity of the anti‐TfR arm and brain uptake at therapeutically relevant doses. However, the quantitative nature of this relationship and its translatability to humans is heretofore unexplored. Therefore, we developed a mechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model for bispecific anti‐TfR/BACE1 antibodies that accounts for antibody‐TfR interactions at the blood‐brain barrier (BBB) as well as the pharmacodynamic (PD) effect of anti‐BACE1 arm. The calibrated model correctly predicted the optimal anti‐TfR affinity required to maximize brain exposure of therapeutic antibodies in the cynomolgus monkey and was scaled to predict the optimal affinity of anti‐TfR bispecifics in humans. Thus, this model provides a framework for testing critical translational predictions for anti‐TfR bispecific antibodies, including choice of candidate molecule for clinical development.
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