Spatial Imaging Platform
Spatial Imaging Platform - Related Videos
08:52
Spatial Molecular Imaging of the Glycome Using Mass Spectrometry
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Cited by 1 •
2025
This protocol details the key steps to enable rigorous and reproducible measurement of both glycogen and N-linked glycans using mass spectrometry imaging.
11:54
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
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Cited by 8 •
2017
We demonstrate a microfluidic platform with an integrated surface electrode network that combines resistive pulse sensing (RPS) with code division multiple access (CDMA), to multiplex detection and sizing of particles in multiple microfluidic channels.
08:13
Spatial Memory Testing Using Mazes
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2023
Spatial learning and memory are neurological functions that allow us to remember important details associated with our environment. Scientists test this phenomenon in rodents using different types of mazes like Morris water maze, Radial water maze, and Barnes maze. By investigating spatial memory in rodents, neurobehavioral scientists can gain valuable understanding of how these processes are altered following brain damage in humans. Here, the neurobiology behind spatial memory is briefly...
10:16
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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2025
This article introduces a protocol for using DeepSpaceDB, a dynamic, interactive database for spatial transcriptomics, offering analysis workflows and examples to explore tissue organization and disease-related gene expression.
10:37
Spatial Separation of Molecular Conformers and Clusters
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Cited by 3 •
2014
We present a technique that allows the spatial separation of different conformers or clusters present in a molecular beam. An electrostatic deflector is used to separate species by their mass-to-dipole moment ratio, leading to the production of gas-phase ensembles of a single conformer or cluster stoichiometry.
FAQs
The connection comes from examining location together with biological activity. High-resolution microscopy shows where cells and structures are positioned, while spatially resolved molecular measurements can associate those positions with gene expression or other molecular features. Image analysis then relates these patterns to cellular behavior and tissue architecture, helping explain how spatial organization contributes to developmental function.
Intact tissue retains the relationships among neighboring cells, molecular features, and larger tissue structures. Those relationships are essential when development depends on changes in cell position, communication, and organization. By maintaining spatial context, the platform allows researchers to interpret molecular or cellular observations within the architecture of the developing specimen rather than viewing each feature in isolation.
Image analysis converts complex microscopy data into identifiable and mappable features across a specimen. It helps researchers examine the distribution of cells, molecules, or biological structures and relate those patterns to tissue organization. This analytical step is important because the platform does more than capture images: it connects visual information with questions about developmental patterning and function.
A typical workflow combines high-resolution microscopy with image analysis and, when included, spatially resolved molecular measurements. Microscopy supplies detailed structural information, while molecular measurements add location-specific biological information. Analysis brings these data types together so researchers can compare molecular features with cellular positions and tissue architecture while retaining the specimen’s spatial relationships.
In developmental biology, the platform can examine how cells change position, communicate, and organize into tissues as an embryo develops. These observations support studies of pattern formation and morphogenesis, where spatial arrangement is closely connected to tissue development. The resulting maps help relate cellular behavior and gene expression to the evolving architecture of embryonic tissues.
The same spatial approach extends beyond normal embryonic development to disease models and regenerative processes. Researchers can examine how cellular organization, molecular features, and tissue architecture are related in these settings. Preserving spatial context supports comparisons between biological states and helps investigate how changes in organization may accompany disease-related development or tissue regeneration.