Visium
Human mesenteric artery
GSM8881931
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8881931_ND_6_B_hires_image': DataArray[cyx] (3, 2000, 1747)
│ └── 'GSM8881931_ND_6_B_lowres_image': DataArray[cyx] (3, 600, 524)
├── Shapes
│ └── 'GSM8881931_ND_6_B': GeoDataFrame shape: (711, 2) (2D shapes)
└── Tables
└── 'table': AnnData (711, 36601)
with coordinate systems:
▸ 'GSM8881931_ND_6_B', with elements:
GSM8881931_ND_6_B_hires_image (Images), GSM8881931_ND_6_B_lowres_image (Images), GSM8881931_ND_6_B (Shapes)
▸ 'GSM8881931_ND_6_B_downscaled_hires', with elements:
GSM8881931_ND_6_B_hires_image (Images), GSM8881931_ND_6_B (Shapes)
▸ 'GSM8881931_ND_6_B_downscaled_lowres', with elements:
GSM8881931_ND_6_B_lowres_image (Images), GSM8881931_ND_6_B (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("jECz0WMr6QPUprOJ") # 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/jECz0WMr6QPUprOJ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid jECz0WMr6QPUprOJ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["jECz0WMr6QPUprOJ0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Mapping Endothelial-Macrophage Interactions in Diabetic Vasculature: Role of TREM2 in Vascular Inflammation and Ischemic Response [Spatial Transcriptomics]→ 10 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- mesenteric artery
- Modality
- RNA
- Observations
- 711
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 1,747 × 2,000 px
- mpp
- 4.080 µm/px
- Size
- 6.2 MB
- Sample ID
- GSM8881931
- License
- unknown
- Published
- Mar 20, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB