Visium

Mouse brain

GSM9817881

Interactive viewer H&E ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9817881_A_brain_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM9817881_A_brain_hires_image': DataArray[cyx] (3, 2000, 686)
│     └── 'GSM9817881_A_brain_lowres_image': DataArray[cyx] (3, 600, 206)
├── Shapes
│     └── 'GSM9817881_A_brain': GeoDataFrame shape: (2373, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2373, 19465)
with coordinate systems:
    ▸ 'GSM9817881_A_brain', with elements:
        GSM9817881_A_brain_full_image (Images), GSM9817881_A_brain_hires_image (Images), GSM9817881_A_brain_lowres_image (Images), GSM9817881_A_brain (Shapes)
    ▸ 'GSM9817881_A_brain_downscaled_hires', with elements:
        GSM9817881_A_brain_hires_image (Images), GSM9817881_A_brain (Shapes)
    ▸ 'GSM9817881_A_brain_downscaled_lowres', with elements:
        GSM9817881_A_brain_lowres_image (Images), GSM9817881_A_brain (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("hJsUy7aOMpwZsyz2")   # 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/hJsUy7aOMpwZsyz2

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid hJsUy7aOMpwZsyz2

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["hJsUy7aOMpwZsyz20001"])[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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Part of collection

Pericyte KATP Channel Hyperactivity Redistributes Cortical Blood Flow in a CADASIL Mouse Model→

8 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: brain
Modality: RNA
Chemistry: Visium CytAssist v2
Resolution: 686 × 2,000 px
mpp: 12.860 µm/px
Size: 41 MB
Sample ID: GSM9817881
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