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Avrahami, A.

Publications and source records attributed to Avrahami, A..

2 recordsLinked to original sources

Gold Electron Microscopy Grids with Anisotropic Foil Geometry Enable On-Grid Contact Guidance

All-gold electron microscopy (EM) grids reduce beam-induced motion relative to conventional holey carbon supports and provide biocompatible substrates for cellular cryo-EM. However, placing customizable all-gold grid fabrication in the hands of researchers requires accessible processes based on standard microfabrication tools. We report a wafer-scale process using microfabrication techniques available in most academic cleanrooms such as lift-off metallization, electroplating, and sacrificial layer release to fabricate 594 all-gold grids per 4-inch wafer without individual grid handling. A numerical electroplating model provides a quantitative framework to relate gold deposition, grid-bar thickness, and tilt-compatible grid geometry. We show that oval 2 {micro}m x 6 {micro}m foil holes bias on-grid actin organization by substrate geometry alone, without chemical micropatterning. The EM grids supported a 2.15 [A] apoferritin single-particle reconstruction on a 200 kV cryo-TEM and are compatible with protein micropatterning and cell culture. This platform establishes an accessible route to programmable, application-specific all-gold cryo-EM supports that couple high-resolution structural imaging with engineered control of cellular organization.

Cell Biology↗

Machine Learning Identifies Common Risk Variants and Implicates Abnormal Vision Physiology in ASD

Genomic technology advancements have facilitated associations between genetic variants and disease risk. Rare deleterious variants can independently induce disease, while common variants collectively enhance susceptibility with minimal individual effects. The nuanced nature of common variant consequences attenuates their identification. Autism spectrum disorders (ASD) are hereditary neurodevelopmental disorders. Atypical eye-gaze responses frequently occur in ASD; however, this phenotype has been overlooked in genetic studies. Using WizWhy, an interpretable machine learning tool, to analyze the Autism Sequencing Consortium (ASC) data, 210 common variants across 177 genes were associated with ASD risk. This association is supported by significant overlap with the SFARI gene database and relevant gene ontologies. Individuals with a higher variant burden are at increased ASD risk. Notably, 52 genes were linked to abnormal eye physiology, underscoring the role of this pathway in ASD etiology. Focusing on specific hub genes as potential pharmacological targets may benefit patients with ASD.

genetics↗