from sddb import Catalog
cohort = Catalog().collection("figshare-28394915")
cohort.members # the 6 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")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")
coll = db.Collection.get(key="figshare-28394915")
coll.ordered_artifacts.to_dataframe() # the 6 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]# sddb client: download every member .zarr into data/
sddb-cli download --collection figshare-28394915 --dest data/Licenses: 6 CC BY 4.0
To determine the cellular and molecular basis of Castleman Disease (CD), we analyze the spatial proteome and transcriptome from a discovery (n = 9 cases) and validation (n = 13 cases) cohort of Unicentric CD, idiopathic Multicentric CD, HHV8-associated MCD, and reactive lymph nodes. CD shows increased stromal cells that form unique microenvironments. Interaction of activated follicular dendritic cell (FDC) cytoplasmic meshworks with mantle-zone B cells is associated with B-cell activation and differentiation. CXCL13+ FDCs, PDGFRA + T-zone reticular cells (TRC), and ACTA2-positive perivascular reticular cells (PRC) were the predominant source of increased VEGF expression and IL-6 signaling. MCD is characterized by increased TRC while UCD shows increased B-reticular cells (BRC). VEGF expression by FDCs is associated with peri-follicular neovascularization. FDC, TRC and PRC of CD activates JAK-STAT, TGFβ, and MAPK pathways via specific ligand-receptor interactions. Here, we show that stromal-cell activation and associated B cell activation and differentiation, neovascularization and stromal remodeling underlie CD.
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