Myocardial infarctions (MI) affect 805,000 people per year in the United States. To mitigate the pathological effects of MI, we have developed and investigated pro-reparative decellularized extracellular matrix (ECM) hydrogels. However, no one has ever utilized single cell and spatially resolved transcriptomics to further probe how ECM can elicit pro-repair in an MI model. Thus, we utilize spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) to further delineate the regional and cell-specific bioactivity of decellularized ECM hydrogels. ECM hydrogel subacute treatment induced cardiac resident macrophage preservation, fibroblast activation, increased vasculature development, and a cardiomyocyte development program. Similar findings of cardiomyocyte and vasculature development, alongside fibroblast development was found for chronic treatment. Thus, we depict the pro-reparative nature of decellularized ECM hydrogels on cardiac cell types and elucidate previously undiscovered therapeutic pathways, further demonstrating ECM’s potential as an MI therapy.
from sddb import Catalog
cohort = Catalog().collection("geo-gse262430")
cohort.members # the 9 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse262430")
coll.ordered_artifacts.to_dataframe() # the 9 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse262430 --dest data/Licenses: 9 NCBI GEO policy
No linked publication found — please cite the data source.