Hemopoietic Progenitor Cells and Hemopoietic Factors: Potential Targets for Treatment of Allergic Inflammatory Diseases
Bibliographic record
Abstract
Eosinophilic infiltration is a cardinal feature of allergic inflammation; based upon its biological actions, the eosinophil has assumed the role as the principal inflammatory cell in asthma. In assessing the mechanisms by which eosinophils are recruited to sites of inflammation, a sizeable body of evidence exists supporting the proposal that expansion of hemopoietic compartments in the bone marrow stimulates an increased turnover and traffic of mature eosinophils to the site of allergic inflammation. In addition, recent findings point to the possible egress and traffic of primitive progenitor cells to the site of inflammation where in-situ differentiation may provide a continued supply of pro-inflammatory cells. In the present article, we will review the evidence for these findings, and discuss the rationale for targeting hemopoiesis and migrational pathways of hemopoietic cells in the treatment of allergic disease. In this context, we will discuss the effect of corticosteroid treatment on hemopoietic mechanisms; the effects of therapies that inhibit the actions of cysteinyl leukotrienes (CysLTs); the effects of in vivo blockade of the eosinophil-active cytokine, interleukin (IL)-5; and, the effects of antihistamines on hemopoiesis. In addition, we will address the potential role that small molecular weight chemokine receptor antagonists may play in modulating progenitor cell trafficking to tissue sites of inflammation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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; both teacher heads agree on what is shown here.
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".