Visium

Human placenta

GSM8252340

bronze Interactive viewer H&E preeclampsia Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8252340_PE_hires_image': DataArray[cyx] (3, 1591, 2000)
│     └── 'GSM8252340_PE_lowres_image': DataArray[cyx] (3, 477, 600)
├── Shapes
│     └── 'GSM8252340_PE': GeoDataFrame shape: (12410, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (12410, 18085)
with coordinate systems:
    ▸ 'GSM8252340_PE', with elements:
        GSM8252340_PE_hires_image (Images), GSM8252340_PE_lowres_image (Images), GSM8252340_PE (Shapes)
    ▸ 'GSM8252340_PE_downscaled_hires', with elements:
        GSM8252340_PE_hires_image (Images), GSM8252340_PE (Shapes)
    ▸ 'GSM8252340_PE_downscaled_lowres', with elements:
        GSM8252340_PE_lowres_image (Images), GSM8252340_PE (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("CBzxp4RKW17obiu70000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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")
artifact = db.Artifact.get("CBzxp4RKW17obiu7")   # stem uid: Lamin resolves it to the 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download CBzxp4RKW17obiu70000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/CBzxp4RKW17obiu7

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid CBzxp4RKW17obiu7

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Spatial transcriptome analysis for placental tissue of preeclampsia→

2 datasets · comparison

Metadata

Technology: Visium
Organism: human
Tissue: placenta
Condition: preeclampsia
Modality: RNA
Observations (spots): 12,410
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 2,000 × 1,591 px
mpp: 7.639 µm/px
Size: 273 MB
Sample ID: GSM8252340
License: NCBI GEO policy
Published: Nov 25, 2025

Cite this dataset

doi.org/10.1126/sciadv.aeb8806 ↗

BibTeX

@article{Matsuo_2026,
  title = {LIMCH1-enriched extracellular vesicles promote vascular permeability in early-onset preeclampsia},
  volume = {12},
  ISSN = {2375-2548},
  url = {http://dx.doi.org/10.1126/sciadv.aeb8806},
  DOI = {10.1126/sciadv.aeb8806},
  number = {5},
  journal = {Science Advances},
  publisher = {American Association for the Advancement of Science (AAAS)},
  author = {Matsuo, Seiko and Yokoi, Akira and Ushida, Takafumi and Yoshida, Kosuke and Suzuki, Hironori and Kitagawa, Masami and Asano-Inami, Eri and Yamada, Hiroaki and Miki, Rika and Tano, Sho and Imai, Kenji and Nagata, Ichiro and Kawaguchi, Shota and Yasui, Takao and Yamamoto, Yusuke and Kajiyama, Hiroaki and Kotani, Tomomi},
  year = {2026},
  month = Jan
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB