Mass Cytometry Phenotyping of Human Granulocytes Reveals Novel Basophil Functional Heterogeneity
Bibliographic record
Abstract
Basophils, the rarest granulocyte, play critical roles in parasite- and allergen-induced inflammation. We applied mass cytometry (CyTOF) to simultaneously asses 44 proteins to phenotype and functionally characterize neutrophils, eosinophils, and basophils from 19 healthy donors. There was minimal heterogeneity seen in eosinophils and neutrophils, but data-driven analyses revealed four unique subpopulations within phenotypically basophilic granulocytes (PBG; CD45 + HLA-DR − CD123 + ). Through CyTOF and fluorescence-activated cell sorting (FACS), we classified these four PBG subpopulations as (I) CD16 low FcεRI high CD244 high (88.5 ± 1.2%), (II) CD16 high FcεRI high CD244 high (9.1 ± 0.4%), (III) CD16 low FcεRI low CD244 low (2.3 ± 1.3), and (IV) CD16 high FcεRI low CD244 low (0.4 ± 0.1%). Prospective isolation confirmed basophilic-morphology of PBG I–III, but neutrophilic-morphology of PBG IV. Functional interrogation via IgE-crosslinking or IL-3 stimulation demonstrated that PBG I–II had significant increases in CD203c expression, whereas PBG III–IV remained unchanged compared with media-alone conditions. Thus, PBG III–IV could serve roles in non-IgE-mediated immunity. Our findings offer new perspectives in human basophil heterogeneity and the varying functional potential of these new subsets in health and disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".