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We developed fatigue-resistant hydrogel optical fibers through the controlled growth of polymeric nanocrystalline domains to enable light delivery to peripheral nerves during locomotion. The hydrogel fibers withstand locomotion strain across more than 30,000 fiber stretch cycles and enable the optogenetic inhibition of pain hypersensitivity in naturally behaving mice.
An engineered RNA A-to-I deaminase (rABE) offers low sequence bias, high activity and low background for REMORA (RNA-encoded molecular recording in adenosines) and enables improved molecular recording of RNA–protein interactions.
This work introduces microbial-enrichment methodology (MEM) that enables removal of host DNA in human intestinal biopsies and characterization of low-abundance microbial taxa down to 1%.
Here we developed synthetic transactivation domains (TADs) built from human mechanosensitive transcription factors (MTFs). By linking MTF TAD segments together, we engineered compact and potent multipartite transcriptional activation modules. We then harnessed these modules to create a CRISPR activation system, which we termed the dCas9 recruited enhanced activation module (CRISPR-DREAM).
By learning representations for both cells and various condition covariates, scPoli facilitates atlas-level integration and analysis of single-cell genomics datasets with improved interpretability.
OPUS-DSD is a neural network-based algorithm that reconstructs distinct conformations or continuous dynamics of the macromolecular structural landscape, starting from single-particle cryo-EM data.
The green alga Chlamydomonas reinhardtii is a useful reference organism for studying photosynthesis, cilia and the cell cycle. Like many other algae, it exhibits daily rhythms in gene expression and behavior that are in sync with the rising and setting of the sun.
Nature Methods is proud to publish our very first Registered Report in this issue. Here, we reflect on what we have learned since introducing this article type.
Tension-activated cell tagging (TaCT) is a new method that uses flow cytometry to sort mechanically active cells based on the forces generated by their surface adhesion receptors.
Science needs diversity, but barriers such as housing insecurity can hinder access to education and training. To lobby for change, students put their own experiences to work.
CryoREAD automatically builds DNA–RNA atomic structure from cryo-EM maps. Backbone accuracy is typically >85% and the method is applicable for maps with RNA-only, DNA-only and DNA–RNA–protein complex structures. CryoREAD uses deep learning to identify structure information and subsequently construct the 3D structure of nucleic acids.