{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T10:57:22Z","timestamp":1783508242535,"version":"3.55.0"},"reference-count":74,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["bpspubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["British J Pharmacology"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Background and Purpose<\/jats:title>\n                    <jats:p>Myocardial fibrosis (MF), a hallmark of structural cardiac remodelling, drives disease progression across most forms of heart failure and plays a central role in heart failure with preserved ejection fraction (HFpEF). Despite its clinical relevance, effective treatments remain scarce. In preclinical models, current methods for quantifying MF fail to capture its regional heterogeneity, limiting reliable assessment of novel anti\u2010fibrotic compounds. This study aimed to develop a whole\u2010heart imaging and deep learning (DL)\u2010based quantification pipeline for MF, and to validate its utility by evaluating the efficacy of a glucagon\u2010like peptide\u20101 receptor (GLP\u20101R) agonist in a mouse model of HFpEF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Experimental Approach<\/jats:title>\n                    <jats:p>\n                      By utilising fluorescent collagen\u2010labelling dye, tissue clearing and three\u2010dimensional light sheet fluorescence microscopy (3D LSFM), we developed a high\u2010throughput imaging platform for MF. We established a DL framework to quantify interstitial, perivascular and replacement fibrosis, as well as hypertrophy, in 17 left ventricular (LV) segments. The antifibrotic efficacy of the GLP\u20101R agonist semaglutide was evaluated in the\n                      <jats:italic>db\/db<\/jats:italic>\n                      UNx\u2010ReninAAV mouse model, which exhibits diabetes, kidney failure, obesity and hypertension.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Results<\/jats:title>\n                    <jats:p>Whole\u2010heart 3D LSFM, combined with DL, enabled micrometre\u2010resolution mapping of MF in rodents. Using this approach, we observed that interstitial collagen content increases proportionally with cardiac hypertrophy. Chronic treatment with semaglutide reduced LV hypertrophy and perivascular fibrosis but did not affect the extent of replacement fibrosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions and Implications<\/jats:title>\n                    <jats:p>The established 3D imaging and quantification approach provides a powerful tool for evaluating the therapeutic efficacy of antifibrotic compounds and studying the pathological mechanisms underlying cardiovascular diseases.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bph.70217","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T04:10:29Z","timestamp":1761106229000},"page":"1030-1047","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Deep learning\u2010enhanced 3D imaging unveils semaglutide impact on cardiac 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