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Animal Models

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Gigapixel Imaging With a Novel Multi-Camera Array Microscope

Thomson et al., eLife. 2022.

https://www.doi.org/10.7554/eLife.74988

The dynamics of living organisms are organized across many spatial scales. The investigators created assembled a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution, large field-of-view recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, they computationally generated gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This system allows the team to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales (e.g., larval zebrafish, fruit flies, slime mold). Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms. Supported by ORIP (R44OD024879), NIEHS, NCI, and NIBIB.

Promoting Validation and Cross-Phylogenetic Integration in Model Organism Research

Cheng et al., Disease Models & Mechanisms. 2022.

https://www.doi.org/10.1242/dmm.049600

Model organisms are essential for biomedical research and therapeutic development, but translation of such research to the clinic is low. The authors summarized discussions from an NIH virtual workshop series, titled “Validation of Animal Models and Tools for Biomedical Research,” held from 2020 to 2021. They described challenges and opportunities for developing and integrating tools and resources and provided suggestions for improving the rigor, validation, reproducibility, and translatability of model organism research. Supported by ORIP (R01OD011116, R24OD031447, R03OD030597, R24OD018559, R24OD017870, R24OD026591, R24OD022005, U42OD026645, U42OD012210, U54OD030165, UM1OD023221, P51OD011107), NIAMS, NIDDK, NIGMS, NHGRI, and NINDS.