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A rapidly evolving toolbox is helping researchers to get a handle on the biological and functional diversity of these ubiquitous — but still somewhat enigmatic — cell-secreted nanoparticles
RS-FISH is a user-friendly software for accurate spot detection that is applicable to smFISH experiments, spatial transcriptomics, and spatial genomics. The approach enables fast spot detection in even very large volumetric datasets.
By modeling the probability of N6-methyladenosine (m6A) RNA modifications for individual reads from direct RNA sequencing, m6Anet achieves high classification accuracy and takes a step towards transcriptome-wide maps of m6A modifications at single-base, single-molecule resolution.
Multiplexing real-time single virus tracking with imaging paves the way for detailed information on virus–host interactions, offering a potential paradigm shift.
This work presents m6Anet, which implements a neural-network-based multiple instance learning model to detect m6A modifications from direct RNA sequencing data.
An improved version of the MS2-MCP system for imaging RNA dynamics involves tethering translation termination factors to tagged mRNAs to bypass destabilization caused by NMD machinery.
Hyperfolder yellow fluorescent protein (hfYFP) and its variants are fluorescent proteins with high chemical and thermal stability. They resist aggregation, withstand diverse chemical challenges and show promise in expansion and electron microscopies. The chloride resistance and uncanny stability in guanidinium of hfYFP enable fluorescence-guided protein purification under denaturing conditions.
Common cellular segmentation models based on machine learning perform suboptimally for test images that differ greatly from training images. Cellpose 2.0 allows biologists to quickly train state-of-the-art segmentation models on their own imaging data. This was previously only possible using large, annotated datasets and required expert machine learning knowledge.
Cellpose 2.0 improves cell segmentation by offering pretrained models that can be fine-tuned using a human-in-the-loop training pipeline and fewer than 1,000 user-annotated regions of interest.
This Resource presents and analyzes four datasets containing both gene expression and morphological profile data for cells subjected to hundreds to thousands of chemical or genetic perturbations and highlights their complementary nature.
The engineered hyperfolder YFP (hfYFP) and variants offer unprecedented chemical and thermal stability, making them versatile probes for microscopy as well as for challenging applications like correlative light and electron microscopy and expansion microscopy.
Researchers use electric fields to transfer RNA from a tissue sample onto a surface for subsequent fluorescence in situ hybridization-based profiling of transcriptomes at the single-cell level.
Harvester ants live in desert grasslands and eat seeds. Colonies manage water stress by regulating foraging using olfactory interactions between outgoing and returning foragers. A long-term study in New Mexico shows how this collective behavior is evolving in drought conditions.