Spinal muscular atrophy (SMA), a rare neuromuscular disorder, is the leading genetic cause of death in infants and toddlers. SMA is caused by the deletion or a loss of function mutation of the survival motor neuron 1 (SMN1) gene. In humans, a second closely related gene SMN2 exists; however it codes for a less stable SMN protein. In recent years, significant progress has been made toward disease modifying treatments for SMA by modulating SMN2 pre-mRNA splicing. Herein, we describe the discovery of LMI070/branaplam, a small molecule that stabilizes the interaction between the spliceosome and SMN2 pre-mRNA. Branaplam (1) originated from a high-throughput phenotypic screening hit, pyridazine 2, and evolved via multiparameter lead optimization. In a severe mouse SMA model, branaplam treatment increased full-length SMN RNA and protein levels, and extended survival. Currently, branaplam is in clinical studies for SMA.

Reflected P‐to‐P and P‐to‐S converted seismic waves in a two‐component elastic common‐source gather generated with a P‐wave source in a two‐dimensional model can be imaged by two independent scalar reverse‐time depth migrations. The inputs to migration are pure P‐ and S‐waves that are extracted by divergence and curl calculations during (shallow) extrapolation of the elastic data recorded at the earth’s surface. For both P‐to‐P and P‐to‐S converted reflected waves, the imaging time at each point is the P‐wave traveltime from the source to that point. The extracted P‐wave is reverse‐time extrapolated and imaged with a P‐velocity model, using a finite difference solution of the scalar wave equation. The extracted S‐wave is reverse‐time extrapolated and imaged similarly, but with an S‐velocity model. Converted S‐wave data requires a polarity correction prior to migration to ensure constructive interference between data from adjacent sources. Synthetic examples show that the algorithm gives satisfactory results for laterally inhomogeneous models.

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Using two independent, 3D scalar reverse-time depth migrations, we migrate the reflected P- and S-waves in a prestack 3D, three-component (3-C), elastic seismic data volume generated with a P-wave source in a 3D model and recorded at the top of the model. Reflected P- and S-waves are extracted by divergence (a scalar) and curl (a 3-C vector) calculations, respectively, during shallow downward extrapolation of the elastic seismic data. The imaging time for the migrations of both the reflected P- and P-S converted waves at each point is the one-way P-wave traveltime from the source to that point.The divergence (the extracted P-waves) is reverse-time extrapolated using a finite-difference solution of the 3D scalar wave equation in a 3D P-velocity modeland is imaged to obtain the migrated P-image. The curl (the extracted S-waves) is first converted into a scalar S-wavefield by taking the curl’s absolute value as the absolute value of the scalar S-wavefield and assigning a positive sign if the curl is counterclockwise relative to the source or a negative sign otherwise. This scalar S-wavefield is then reverse-time extrapolated using a finite-difference solution of the 3D scalar wave equation in a 3D S-velocity model, and it is imaged with the same one-way P-wave traveltime imaging condition as that used for the P-wave. This achieves S-wave polarity uniformity and ensures constructive S-wave interference between data from adjacent sources. The algorithm gives satisfactory results on synthetic examples for 3D laterally inhomogeneous models.