IL-4 and IL-13 regulate TLR expression and eosinophil-basophil differentiation of cord blood CD34+ progenitor cells
Bibliographic record
Abstract
Intrauterine environmental exposures have been shown to influence neonatal immunity and subsequent allergic disease development [ 1 ]. We have previously shown that cord blood (CB) progenitor cells of high atopic risk infants have reduced toll-like receptor (TLR) expression and produce fewer lipopolysaccharide (LPS)-stimulated eosinophil-basophil (Eo/B) colonies, compared to low-atopic risk infants. In the present study, we investigated whether a surrogate ex vivo T H 2 milieu (i.e., either IL-4 or IL-13), could represent an underlying mechanism to explain our previous findings. CB CD34 cells from healthy donors were cultured with IL-4 or IL-13 (in combination with LPS) and assessed for TLR-2, TLR-4, and TLR-9 expression using flow cytometry, as well as Eo/B differentiation using methylcellulose cultures. Pharmacological inhibitors were added to the methylcellulose cultures to determine the effect of blocking IL-4 or IL-13 signalling in CB CD34 cells in relation to Eo/B colony forming unit (CFU) formation. Stimulation of CD34 cells with IL-4 or IL-13 trended to decreased expression of TLR-2 (p=0.063), whereas IL-4, but not IL-13, reduced Eo/B CFU formation in the presence of LPS. The latter was found to be dependent on IL-4Rα and not IL-13Rα1. Thus, the responsiveness of CB CD34 progenitor cells to LPS is differentially regulated by the T H 2 cytokines, IL-4 and IL-13, and may be related to TLR expression on these cells. Therefore, in utero interactions between placental-derived pro-allergic cytokines and neonatal progenitor cells influences CD34 phenotype and function, with implications for Eo/B-mediated inflammatory responses in early life.
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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 | 0.001 |
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".