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Visium

Mouse brain

GSM9817882

silver Interactive viewer H&E cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1 ✓ Verified publication
Mouse brain preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM9817882_B_brain_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM9817882_B_brain_hires_image': DataArray[cyx] (3, 2000, 640)
│     └── 'GSM9817882_B_brain_lowres_image': DataArray[cyx] (3, 600, 192)
├── Shapes
│     └── 'GSM9817882_B_brain': GeoDataFrame shape: (2077, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2077, 19465)
with coordinate systems:
    ▸ 'GSM9817882_B_brain', with elements:
        GSM9817882_B_brain_full_image (Images), GSM9817882_B_brain_hires_image (Images), GSM9817882_B_brain_lowres_image (Images), GSM9817882_B_brain (Shapes)
    ▸ 'GSM9817882_B_brain_downscaled_hires', with elements:
        GSM9817882_B_brain_hires_image (Images), GSM9817882_B_brain (Shapes)
    ▸ 'GSM9817882_B_brain_downscaled_lowres', with elements:
        GSM9817882_B_brain_lowres_image (Images), GSM9817882_B_brain (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("tBjlMDBKXA4aQaEw")   # 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/tBjlMDBKXA4aQaEw

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid tBjlMDBKXA4aQaEw
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["tBjlMDBKXA4aQaEw0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
Visium
Organism
mouse
Tissue
brain
Condition
cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 1
Modality
RNA
Observations
2,077
Tier
silver
Chemistry
Visium CytAssist v2
Resolution
640 × 2,000 px
mpp
9.355 µm/px
Size
28 MB
Sample ID
GSM9817882
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