Collections / Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain
Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain
After intracranial hemorrhages, heme is released from cell-free hemoglobin. This red blood cell toxin may drive secondary brain injury at the hematoma-brain interface. This study aimed to generate a spatially resolved map of the transcriptome-wide gene expression changes in the heme-exposed brain and define the potential therapeutic activity of the heme-binding protein hemopexin.
Datasets7
Size~291 MB
AssayVisium
Samplemouse · brain
KindComparison
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse182127")
cohort.members # the 7 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/") Python · lamindb
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-gse182127")
coll.ordered_artifacts.to_dataframe() # the 7 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse182127 --dest data/ Licenses: 7 NCBI GEO policy
Member datasets · 7
Cite this collection
doi.org/10.1016/j.freeradbiomed.2021.11.011 ↗ BibTeX
@article{Buzzi_2022,
title = {Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain},
volume = {179},
ISSN = {0891-5849},
url = {http://dx.doi.org/10.1016/j.freeradbiomed.2021.11.011},
DOI = {10.1016/j.freeradbiomed.2021.11.011},
journal = {Free Radical Biology and Medicine},
publisher = {Elsevier BV},
author = {Buzzi, Raphael M. and Akeret, Kevin and Schwendinger, Nina and Klohs, Jan and Vallelian, Florence and Hugelshofer, Michael and Schaer, Dominik J.},
year = {2022},
month = Feb,
pages = {277–287}
}