Toll‐like receptor‐mediated eosinophil–basophil differentiation: autocrine signalling by granulocyte–macrophage colony‐stimulating factor in cord blood haematopoietic progenitors
Bibliographic record
Abstract
Eosinophils are multi-functional leucocytes that play a role in inflammatory processes including allergy and infection. Although bone marrow (BM) inflammatory cells are the main source of eosinophil-basophil (Eo/B) differentiation-inducing cytokines, a recent role has been demonstrated for cytokine induction through Toll-like receptor (TLR)-mediated signalling in BM progenitors. Having previously demonstrated that cord blood (CB) progenitors induce Eo/B colony-forming units (CFU) after lipopolysaccharide (LPS) stimulation, we sought to investigate the intracellular mechanisms by which LPS induces Eo/B differentiation. Freshly isolated CD34-enriched human CB cells were stimulated with LPS (and/or pharmacological inhibitors) and assessed for alterations in haematopoietic cytokine receptor expression and signalling pathways by flow cytometry, Eo/B CFU in methylcellulose cultures, and cytokine secretion using Luminex assays. The LPS stimulation resulted in a significant increase in granulocyte-macrophage colony-stimulating factor (GM-CSF)-responsive, as opposed to interleukin-5-responsive, Eo/B CFU, which also correlated with significant increases in CD34(+) cell GM-CSFRα expression. Functionally, CB CD34(+) cells secrete abundant amounts of GM-CSF following LPS stimulation, via a p38 mitogen-activated protein kinase (MAPK)-dependent mechanism; this secretion was responsible for Eo/B CFU formation ex vivo, as shown by antibody blockade. We show for the first time that LPS stimulation of CB progenitor cells results in autocrine activation of p38 MAPK-dependent GM-CSF secretion facilitating Eo/B differentiation ex vivo. This work provides evidence that early life exposure to products of bacterial agents can modulate Eo/B differentiation, representing a novel mechanism by which progenitor cells can respond to microbial stimuli and so affect immune and inflammatory responses.
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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) | 0.001 | 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".