Neutrophil Subsets from Children with Malaria Exposure and Burkitt Lymphoma in Kenya
by Sharon Akinyi Okoth·Updated 6d ago
21.1 KB1files
Available on 1 platform
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Description
A prospective study profiling neutrophil subsets from children with different Plasmodium falciparum malaria exposure histories and children diagnosed with Burkitt lymphoma in Western Kenya, along with healthy malaria low-exposed Kenyan adults. Data was collected using multiparameter flow cytometry, characterizing neutrophils by expression of CD15, CD16, CD10, CD11b, CD182, CD184, and CD62L. The dataset, authored by Sharon Akinyi Okoth and last updated on 2026-06-01, is shared under a CC-BY-4.0 license.
Use Cases
Analyzing correlations between malaria exposure and frequencies of aged versus mature neutrophil subsets based on flow cytometry data.
Investigating the potential link between immature neutrophil expansion and Burkitt lymphoma tumorigenesis suggested by the study's findings.
Profiling immune cell phenotypes in pediatric populations from sub-Saharan Africa with different infectious disease histories.
Validating flow cytometry gating strategies for neutrophil subsets defined by CD15, CD16, CD10, CD11b, CD182, CD184, and CD62L markers.
Strengths
Includes data from a specific, clinically relevant cohort: children with malaria exposure and Burkitt lymphoma from Western Kenya.
Provides multiparameter flow cytometry data for seven specific surface markers (CD15, CD16, CD10, CD11b, CD182, CD184, CD62L).
Dataset is openly shared under a permissive CC-BY-4.0 license.
Limitations
The dataset is very small at 21.1 KB, indicating limited scope and likely a small sample size.
Row count and column-level documentation are unknown, requiring manual inspection after download to understand data structure.
Functional assay data is absent, as noted in the description, limiting direct mechanistic conclusions.
Provenance
Source
figshare, author Sharon Akinyi Okoth.
Collection Method
Prospective study using multiparameter flow cytometry.
Freshness
Last updated 2026-06-01 17:49:19.
Geography
Western Kenya.
Data is provided in XLSX format, requiring software capable of reading Excel files.