The lung hematopoietic niche supports bone marrow-independent hematopoiesis and contributes to local eosinophil expansion during allergic inflammation.
Bibliographic record
Abstract
Abstract Bone marrow is classically viewed as the major source of differentiated leukocytes infiltrating tissues from circulation. Recent evidence shows that the lung can potentially function as a hematopoietic organ on its own. This is a novel concept and tissue factors driving in situ leukocyte production are not yet well understood. In naïve murine lungs, we detected a small population of Lin−CD34+c-Kit+ common myeloid progenitors (CMPs) by flow cytometry and single cell RNA-seq analysis. Males had 0.087±0.06% CMPs, while females had a larger population of 0.18±0.08%, out of CD45+ cells. In a 3 challenge in vivo ovalbumin model of allergic inflammation, we observed a six-fold expansion of CMPs in the lung tissue and the appearance of Siglec-F+CD34+IL-5Rα+ eosinophil progenitors (EoPs) (1.505±0.6% of CD45+). To illustrate the hematopoietic potential of the lung independent of bone marrow recruitment, we cultured naïve lung single cell suspensions ex vivo in presence of SCF, FLT3 and IL-5. This was sufficient to yield up to 20% mature eosinophils, which is comparable to tissue eosinophil levels in models of allergic inflammation. We further tested whether Tenascin-C (TNC), a known component of bone marrow hematopoiesis, may equally support the hematopoietic niche in the lung. TNC is a provisional matrix glycoprotein that strongly associates with epithelial remodeling and eosinophil accumulation in asthma. TNC−/− mice had a significant defect in CMP and EoP expansion in a murine model of asthma and ex vivo IL-5 lung cultures. Administration of recombinant TNC rescued normal lung eosinophilopoiesis. These results suggest the existence and significant potential of the lung hematopoietic niche to supply effector cells during inflammation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".