Visium
Mouse cerebral blood vessel
GSM9817884
silver Interactive viewer H&E cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1 ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9817884_D_vessels_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM9817884_D_vessels_hires_image': DataArray[cyx] (3, 2000, 640)
│ └── 'GSM9817884_D_vessels_lowres_image': DataArray[cyx] (3, 600, 192)
├── Shapes
│ └── 'GSM9817884_D_vessels': GeoDataFrame shape: (632, 2) (2D shapes)
└── Tables
└── 'table': AnnData (632, 19465)
with coordinate systems:
▸ 'GSM9817884_D_vessels', with elements:
GSM9817884_D_vessels_full_image (Images), GSM9817884_D_vessels_hires_image (Images), GSM9817884_D_vessels_lowres_image (Images), GSM9817884_D_vessels (Shapes)
▸ 'GSM9817884_D_vessels_downscaled_hires', with elements:
GSM9817884_D_vessels_hires_image (Images), GSM9817884_D_vessels (Shapes)
▸ 'GSM9817884_D_vessels_downscaled_lowres', with elements:
GSM9817884_D_vessels_lowres_image (Images), GSM9817884_D_vessels (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("nMHfCk98MUZOFmix") # latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nMHfCk98MUZOFmix
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nMHfCk98MUZOFmix Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["nMHfCk98MUZOFmix0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Pericyte KATP Channel Hyperactivity Redistributes Cortical Blood Flow in a CADASIL Mouse Model→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- cerebral blood vessel
- Condition
- cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1
- Modality
- RNA
- Observations
- 632
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Resolution
- 640 × 2,000 px
- mpp
- 9.375 µm/px
- Size
- 25 MB
- Sample ID
- GSM9817884
- License
- CC BY 4.0
- Published
- Jun 22, 2026
Cite this dataset
doi.org/10.1038/s44161-026-00844-0 ↗ BibTeX
@article{Jeffrey_2026,
title = {Pericyte KATP channel hyperactivity redistributes cortical blood flow in a CADASIL mouse model},
volume = {5},
ISSN = {2731-0590},
url = {http://dx.doi.org/10.1038/s44161-026-00844-0},
DOI = {10.1038/s44161-026-00844-0},
number = {8},
journal = {Nature Cardiovascular Research},
publisher = {Springer Science and Business Media LLC},
author = {Jeffrey, Danielle A. and Prince, Eric W. and Khakpour, Niloufar and Ferris, Hannah R. and Peters, Colin H. and Seedorf, Gregory and Romero, Phinea Z. and Bueno Guerrero, Mayra and Russell, Abigail N. and Glodoski, Katherine and Futia, Gregory L. and Bonney, Stephanie K. and Thornton, Michael A. and Gibson, Emily A. and Proenza, Catherine and Garcia, Anastacia M. and Tsoukias, Nikolaos M. and Dabertrand, Fabrice},
year = {2026},
month = Aug,
pages = {725–743}
}Source: NCBI GEO ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB