A Novel B220+ NK Cell Progenitor Found in the Murine Lung with Potent in Vitro NK Potential Gives Rise to Mature NK Cells with Distinct NK Cell-Surface Receptor Expression
Bibliographic record
Abstract
Abstract Natural Killer (NK) cells are important effector cells in innate immunity, and play a vital role in antiviral defense, tumor surveillance and modulation of the adaptive immune response. NK cells were originally believed to arise from a lin−NK1.1−CD122+ bone marrow (BM) progenitor. However, recent findings have identified NK progenitors (NKP) and distinct NK differentiation pathways in the thymus, lymph node, spleen and liver. The physiological role of these extra-BM developmental pathways remains to be determined. We hypothesized that these alternative pathways on NK development would have an impact on the generation of the phenotypic heterogeneity observed in cell-surface receptor expression and functional NK cell subsets. Here, we demonstrate the identification of a small population of cells in the lung of C57Bl/6 mice (0.02% of lung leukocytes) that have a lin−NK1.1−CD122+B220+ cell surface phenotype. These cells also show potent in vitro NK cell activity when cultured on OP-9 stromal cells with IL-7, mSCF, Flt3L and IL-15, as well as in vivo NK cell potential upon adoptive transplant into RAG-2−/− IL2Rγ−/− and NOD/SCID IL2Rγ−/− hosts. Mature NK cells (CD3−NK1.1+) derived in vitro from conventional BM NKP and lung B220+ NKP were characterized for cell-surface receptor expression after 16–18 days (figure 1, mean with SEM). Clear differences in activating and inhibitory NK cell-surface marker expression were observed between NK cells derived in vitro from conventional BM NKP and lung B220+ NKP (Ly49D p<0.05, Ly49G2 p<0.05, NKG2A/C/E p<0.05). These findings suggest that B220+ NKP may generate phenotypically and functionally distinct NK cell types. Figure 1: Cell-surface receptor expression on in vitro derived NK cells Figure 1:. Cell-surface receptor expression on in vitro derived NK cells
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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 | 0.001 |
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".