The CCR3 Receptor Is Involved in Eosinophil Differentiation and Is Up-Regulated by Th2 Cytokines in CD34+ Progenitor Cells
Bibliographic record
Abstract
The involvement of chemokines in eosinophil recruitment during inflammation and allergic reactions is well established. However, a functional role for chemokines in eosinophil differentiation has not been investigated. Using in situ RT-PCR, immunostaining, and flow cytometric analysis, we report that human CD34+ cord blood progenitor cells contain CCR3 mRNA and protein. Activation of CD34+ progenitor cells under conditions that promote Th2 type differentiation up-regulated surface expression of the CCR3. In contrast, activation with IL-12 and IFN-gamma resulted in a significant decrease in the expression of CCR3. Eotaxin induced Ca2+ mobilization in CD34+ progenitor cells, which could explain the in vitro and in vivo chemotactic responsiveness to eotaxin. We also found that eotaxin induced the differentiation of eosinophils from cord blood CD34+ progenitor cells. The largest number of mature eosinophils was found in cultures containing eotaxin and IL-5. The addition of neutralizing anti-IL-3, anti-IL-5, and anti-GM-CSF Abs to culture medium demonstrated that the differentiation of eosinophils in the presence of eotaxin was IL-3-, IL-5-, and GM-CSF-independent. These results could explain how CD34+ progenitor cells accumulate and persist in the airways and peripheral blood of patients with asthma and highlight an alternative mechanism by which blood and tissue eosinophilia might occur in the absence of IL-5.
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) | 0.002 | 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".