{'fraction_non_alphanumeric': 0.022905364677516575, 'fraction_numerical': 0.0, 'mean_word_length': 6.793427230046948, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Quantification of Multicellular Organization, Junction Integrity, and Substrate Features in Collective Cell Migration

Abstract Quantitative analysis of multicellular organization, cell–cell junction integrity, and substrate properties is essential to understand the mechanisms underlying collective cell migration. However, spatially and temporally defining these properties is difficult within collectively migrating cell groups due to challenges in accurate cell segmentation within the monolayer. In this paper, we present Matlab®-based algorithms to spatially quantify multicellular organization (migration distance, interface roughness, and cell alignment, area, and morphology), cell–cell junction integrity, and substrate features in confocal microscopy images of two-dimensional collectively migrating endothelial monolayers. We used novel techniques, including measuring the migrating front roughness using a parametric curve formulation, automatically binning cells to obtain data as a function of distance from the migrating front, using iterative morphological closings to fully define cell boundaries, quantifying β-catenin localization as a measure of cell–cell junction integrity, and skeletonizing fibronectin to determine fiber length and orientation. These algorithms are widely accessible, as they use common fluorescent markers and Matlab® functions, and provide high-throughput critical feature quantification within collectively migrating cell groups. These image analysis algorithms can help standardize feature quantification among different experimental techniques, cell types, and research groups studying collective cell migration.