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Laghaei, R.

Publications and source records attributed to Laghaei, R..

2 recordsLinked to original sources

COMPUTATIONAL STUDIES OF CARGO TRANSPORT THROUGH THE NUCLEAR PORE COMPLEX

Nuclear Pore Complexes (NPCs) are large protein complexes in eukaryotic cells that span the double-membrane of the nucleus and regulate bi-directional transport between nucleus and cytoplasm. T h e NPC core is lined by intrinsically disordered protein chains called nucleoporins (Nups) which form a selective barrier where large macromolecules (cargoes) need to bind to nuclear transport receptors (NTRs) such as Karyopherins (Kaps) to cross. Previous experimental results have suggested that not only Nups but Kaps, too, are important in the transport process of other NTRs/NTR-cargo complexes. In this work, we assess the role of Kaps in the transport of other NTRs (specifically, NTF2s) through the NPC, a process referred to as the "Kap-centric transport model". Here, using coarse-grained MD simulation we show that Kaps are able to direct NTF2s into the Nup meshwork, which leads to their increased flow. Our results also suggest that NTRs follow specific lanes inside the pore to maximize efficient transport.

biophysics↗

The Brain Image Library: A Community-Contributed Microscopy Resource for Neuroscientists

Advancements in microscopy techniques and computing technologies have enabled researchers to digitally reconstruct brains at micron scale. As a result, community efforts like the BRAIN Initiative Cell Census Network (BICCN) have generated thousands of whole-brain imaging datasets to trace neuronal circuitry and comprehensively map cell types. This data holds valuable information that extends beyond initial analyses, opening avenues for variation studies and robust classification of cell types in specific brain regions. However, the size and heterogeneity of these imaging data have historically made storage, sharing, and analysis difficult for individual investigators and impractical on a broad community scale. Here, we introduce the Brain Image Library (BIL), a public resource serving the neuroscience community that provides a persistent centralized repository for brain microscopy data. BIL currently holds thousands of brain datasets and provides an integrated analysis ecosystem, allowing for exploration, visualization, and data access without the need to download, thus encouraging scientific discovery and data reuse.

neuroscience↗