{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T04:32:59Z","timestamp":1785731579855,"version":"3.56.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:00:00Z","timestamp":1782172800000},"content-version":"vor","delay-in-days":173,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Spatial transcriptomics maps tissue architecture at high resolution, but spot-level maps are difficult to compare across sections, whereas whole-section averages obscure regional organization. We developed region-aware bridge modeling to aggregate interpretable biological program features into compact mesoscale summaries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Using public colorectal cancer and breast cancer 10x Genomics high-definition Visium sections, we constructed epithelial-like, fibroblast, smooth or myoepithelial, and extracellular matrix bridge features from cell-state indicators, curated gene-program scores, and quality-control summaries. Median-quadrant aggregation produced an eight-region design matrix. Within-section validation showed non-random mesoscale heterogeneity: region-label shuffling reduced the overall mean absolute pairwise regional difference from 0.298 to 0.0020 in colorectal cancer and from 0.328 to 0.0024 in breast cancer, with empirical upper-tail probability values of 0.0002 for both analyses across 5000 permutations. Shifted and rotated partitions changed the overall heterogeneity metric by less than 10%. Exploratory ridge modeling identified fibroblast as the only non-target predictor in the extracellular matrix model, and Bayesian sensitivity analysis supported a positive fibroblast-extracellular matrix association. Supplementary lung, prostate, and ovarian cancer sections supported workflow applicability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Code and processed outputs are available through GitHub and Zenodo under 10.5281\/zenodo.19801620.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioadv\/vbag176","type":"journal-article","created":{"date-parts":[[2026,6,22]],"date-time":"2026-06-22T11:25:19Z","timestamp":1782127519000},"source":"Crossref","is-referenced-by-count":1,"title":["Region-aware bridge modeling enables interpretable mesoscale representation of spatial transcriptomic tissue sections"],"prefix":"10.1093","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9397-3324","authenticated-orcid":false,"given":"Seung-Hwan","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Biology, Fisher College , Boston, 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