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Comparing brain connectivity between chimpanzees and humans is a means of understanding human cognition and evolution. To address the scarcity of chimpanzee neuroimaging data, we introduce a high-quality MRI resource that reveals previously unseen anatomical details, offering valuable insights into human brain evolution.
uiPSF is a toolbox to measure point spread functions based on inverse modeling that improves single-molecule localization microscopy (SMLM) localization and microscope characterization, and that works for many microscopy technologies.
An experimental method to study how cells sense and react to external mechanical forces combines controlled mechanical stimulation using nanopipettes with fluorescence imaging of membrane tension. This approach facilitates the study of mechanosensitive ion channels and the propagation of cell membrane tension.
Spatial transcriptomics and mRNA splicing measurements encode rich spatiotemporal information for cell states and their transitions. We present a multiscale dynamical system method for reconstructing cell-state-specific dynamics and spatial state transitions. This theory-based approach reconciles short-timescale local tensor streamlines between cells with long-timescale transition paths that connect cell attractors.
Pebblescout navigates vast, rapidly growing nucleotide content in resources by providing indexing and search capabilities. We used Pebblescout to index a metagenomic subset of Sequence Read Archive and seven other resources into databases spanning over 3.7 petabases and searchable interactively at a pilot website using queries as short as 42 bases.
We developed a two-pronged strategy to functionally probe the enormous repertoire of noncoding DNA within genomes. Our approach markedly improved signal-to-noise ratio and successfully intersected single-cell genomics with reporter assays. The result delivers a multiplex and highly quantitative readout of regulatory sequences’ activity in dynamic and multicellular systems.
Combining post-translational modification site-centric base editing with phenotypic screens uncovers the function of phosphorylation sites in high throughput, enabling the study of expansive signaling networks at a speed comparable to that of functional genomics.
This Perspective discusses the potential of protein structure-prediction models for exploring the structural landscape and specificity of TCR–pMHC interactions.
We created DELiVR, a deep-learning pipeline for 3D brain-cell mapping that is trained with virtual reality-generated reference annotations. It can be deployed via the user-friendly interface of the open-source software Fiji, which makes the analysis of large-scale 3D brain images widely accessible to scientists without computational expertise.
Several research groups are making it easier for other neuroscientists to analyze large datasets by providing tools that can be accessed and used from anywhere in the world.
Cell segmentation currently involves the use of various bespoke algorithms designed for specific cell types, tissues, staining methods and microscopy technologies. We present a universal algorithm that can segment all kinds of microscopy images and cell types across diverse imaging protocols.
RoboEM, an artificial intelligence (AI)-based flight agent, automatically steers through three-dimensional electron microscopy (3D-EM) images of brain tissue to follow neurites. RoboEM substantially improves state-of-the-art automated reconstructions, eliminating manual proofreading needs in complex connectomic analysis problems and paving the way for high-throughput, cost-effective, large-scale mapping of neuronal networks — connectomes.
The exceptionally photostable green fluorescent protein StayGold has been monomerized in different laboratories, which has generated three unique monomeric variants that will enable new imaging applications.
New condenser aperture designs form square or rectangular beams that match the camera dimensions, which efficiently expands the data acquisition area in cryogenic electron microscopy.
Diploid assembly is a difficult task that requires several types of genomic sequencing data, including — but not limited to — HiFi reads and parental sequences. Hypo-assembler, an assembly algorithm, uses high quality solid k-mers extracted from Illumina data alongside Nanopore reads to produce a high-quality diploid assembly using only Nanopore and Illumina data.
We developed a high-content profiling method named vibrational painting (VIBRANT) for single-cell drug response measurements, combining vibrational imaging, multiplexed vibrational probes and machine learning. VIBRANT showed high performance in predicting drug mechanisms of action, discovering novel compounds and assessing drug combinations, demonstrating great promise for phenotypic drug discovery.
We introduce a biomimetic antigen-presenting system that uses hexapod heterostructures for specific T cell recognition at the single-molecule and single-cell levels. The system enables high-resolution T cell activation, uses magnetic forces to increase immune responses, and offers flexible and precise identification of antigen-specific T cell receptors, aiding the study of T cell recognition and immune cell mechanics.