The leishmaniases are globally important parasitic diseases for which no human vaccines are currently available. To facilitate vaccine development, we conducted an open label observational study to establish a controlled human infection model of sand fly-transmitted cutaneous leishmaniasis caused by L. major. Between 24th January and 12th August 2022, we exposed 14 (8F, 6M) participants to infected sand flies. The primary objective was to demonstrate effectiveness (attack rate) and safety (absence of CL lesion at 12 months), whereas secondary and exploratory objectives included rate of lesion development, parasite load and analysis of local immune responses using immunohistology and spatial transcriptomics. We estimated a take rate for CL development of 64% (9/14) based on all participants, increasing to 82% (9/11) if only participants with confirmed bites are included. Lesion development was terminated by therapeutic biopsy in 10 participants with confirmed bites. 30% (3/10) had either one (2/10) or two (1/10) lesion recurrences between 4-8 months after biopsy that were treated successfully with cryotherapy. No severe or serious adverse events were recorded, but scarring was evident as expected. All participants were lesion-free at long-term (>12 month) follow up. We provide the first comprehensive map of immune cell distribution and cytokine/chemokine expression in human CL lesions, revealing discrete immune niches. This controlled human infection model offers opportunities for rapid vaccine candidate selection and a greater understanding of immune-mediated protection and pathology.
from sddb import Catalog
cohort = Catalog().collection("geo-gse263298")
cohort.members # the 12 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="geo-gse263298")
coll.ordered_artifacts.to_dataframe() # the 12 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 geo-gse263298 --dest data/Licenses: 12 NCBI GEO policy
No linked publication found — please cite the data source.