The iBEAT V2.0 is a robust, multisite-applicable, infant-tailored computational pipeline that uses deep learning to process and analyze infant brain magnetic resonance images. This protocol describes the usage and technique details of the iBEAT V2.0.

This protocol describes cfSNV, a user-friendly software package that comprehensively considers the unique properties of cell-free DNA for the sensitive detection of somatic mutations from blood samples.

In this Perspective, authors from the UK Consortium on Metabolic Phenotyping propose a ‘fit-for-purpose’, four-tiered framework to evaluate the reliability of targeted metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation.

A robust, mild and fast approach for the posttranslational, site-directed fluorination of protein sidechains, detectable via ¹⁹F-based magnetic resonance methods.

This protocol isolates large and small extracellular vesicles, as well as nonvesicular nanoparticles known as exomeres and supermeres, from cell-conditioned medium or human plasma via differential ultracentrifugation, filtration, concentration and high-resolution density-gradient fractionation.

The iBEAT V2.0 is a robust, multisite-applicable, infant-tailored computational pipeline that uses deep learning to process and analyze infant brain magnetic resonance images. This protocol describes the usage and technique details of the iBEAT V2.0.

The authors present a protocol for preparation—by dehydration and mounting—of whole human organs for imaging via X-ray hierarchical phase-contrast tomography, resulting in high-resolution images with a ratio of voxel size to organ diameter of 1:150,000.

EPAM-ia is a method based on flow cytometry for the simultaneous isolation and analysis of endothelial cells, pericytes, astrocytes and microglia from the neurovascular unit, a structure that critically regulates blood–brain barrier function.

The authors present a simple and cost-efficient approach for the covalent coupling of enzymes on solid supports or for the intermolecular cross-linking of enzymes.

This protocol describes cfSNV, a user-friendly software package that comprehensively considers the unique properties of cell-free DNA for the sensitive detection of somatic mutations from blood samples.

In many environmental or clinical settings, it is useful to detect and quantify analytes instantaneously in situ. This protocol describes how to develop metal–organic frameworks for selective, sensitive analysis by luminescence.

In this Perspective, authors from the UK Consortium on Metabolic Phenotyping propose a ‘fit-for-purpose’, four-tiered framework to evaluate the reliability of targeted metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation.

A robust, mild and fast approach for the posttranslational, site-directed fluorination of protein sidechains, detectable via ¹⁹F-based magnetic resonance methods.