10x Xenium
Mouse aorta
GSM8900775
silver Interactive viewer diabetes mellitus ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 64615, 48270), (1, 32307, 24135), (1, 16153, 12067), (1, 8076, 6033), (1, 4038, 3016)
│ └── 'morphology_mip': DataTree[cyx] (1, 64615, 48270), (1, 32307, 24135), (1, 16153, 12067), (1, 8076, 6033), (1, 4038, 3016)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (64615, 48270), (32307, 24135), (16153, 12067), (8076, 6033), (4038, 3016)
│ └── 'nucleus_labels': DataTree[yx] (64615, 48270), (32307, 24135), (16153, 12067), (8076, 6033), (4038, 3016)
├── Points
│ └── 'transcripts': DataFrame with shape: (7816814, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (17160, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (17160, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (17160, 1) (2D shapes)
└── Tables
└── 'table': AnnData (17160, 479)
with coordinate systems:
▸ 'global', with elements:
morphology_focus (Images), morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("hOwmW2Js4Sd4I2zU") # 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/hOwmW2Js4Sd4I2zU
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid hOwmW2Js4Sd4I2zU Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["hOwmW2Js4Sd4I2zU0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- aorta
- Condition
- diabetes mellitus
- Modality
- RNA
- Observations
- 17,160
- Transcripts
- 7,816,814
- Tier
- silver
- Chemistry
- Xenium v1
- Size
- 1.7 GB
- Sample ID
- GSM8900775
- License
- NCBI GEO policy
- Published
- Feb 6, 2026
Cite this dataset
doi.org/10.1161/atvbaha.125.324012 ↗ BibTeX
@article{Tanwar_2026,
title = {Single-Cell Multimodal Profiling Highlights Persistent Aortic Smooth Muscle Cell Changes in Diabetic Mice Despite Glycemic Control},
volume = {46},
ISSN = {1524-4636},
url = {http://dx.doi.org/10.1161/atvbaha.125.324012},
DOI = {10.1161/atvbaha.125.324012},
number = {3},
journal = {Arteriosclerosis, Thrombosis, and Vascular Biology},
publisher = {Ovid Technologies (Wolters Kluwer Health)},
author = {Tanwar, Vinay Singh and Malek, Vajir and Wang, Jingyi and Luo, Yingjun and Malhi, Naseeb Kaur and Zhang, Hongpan and Abdollahi, Maryam and Lanting, Linda and Senapati, Parijat and Das, Sadhan and Reddy, Marpadga A and Zang, Chongzhi and Miller, Clint L. and Chen, Zhen Bouman and Natarajan, Rama},
year = {2026},
month = Mar
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB