OBJECTIVES/GOALS: In a familial case where 10 of 17 members inherited EA/LVNC in an autosomal dominant pattern, we discovered a novel, damaging missense variant in the gene KLHL26 that segregates with disease and comprises an altered electrostatic surface profile, likely decoupling the CUL3-interactome. We hypothesize that this KLHL26 variant is etiologic of EA/LVNC. METHODS/STUDY POPULATION: We differentiated a family trio (a heart-healthy daughter and EA/LVNC-affected mother and daughter) of induced pluripotent stem cells into cardiomyocytes (iPSC-CMs) in a blinded manner on three iPSC clones per subject. Using flow cytometry, immunofluorescence, and biomechanical, electrophysiological, and automated contraction methods, we investigated iPSC-CM differentiation efficiency between D10-20, contractility analysis and cell cycle regulation at D20, and sarcomere organization at D60. We further conducted differential analyses following label-free protein and RNA-Seq quantification at D20. Via CRISPR-Cas9 gene editing, we plan to characterize KLHL26 variant-specific iPSC-CM alterations and connect findings to discoveries from patient-specific studies. RESULTS/ANTICIPATED RESULTS: All iPSC lines differentiated into CMs with an increased percentage of cTnT+ cells in the affected daughter line. In comparison to the unaffected, affected iPSC-CMs had fewer contractions per minute and altered calcium transients, mainly a higher amount of total calcium release, faster rate of rise and faster rate of fall. The affected daughter line further had shorter shortening and relaxation times, higher proliferation, lower apoptosis, and a smaller cell surface area per cardiac nucleus. The affected mother line trended in a similar direction to the affected daughter line. There were no gross differences in sarcomere organization between the lines. We also discovered differential expression of candidate proteins such as kinase VRK1 and collagen COL5A1 from proteomic profiling. DISCUSSION/SIGNIFICANCE: These discoveries suggest that EA/LVNC characteristics or pathogenesis may result from decreased contractile ability, altered calcium transients, and cell cycle dysregulation. Through the KLHL26 variant correction and introduction in the daughter lines, we will build upon this understanding to inform exploration of critical clinical targets.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.