Structural Cell-Derived Cytokines in Allergic Inflammation
Bibliographic record
Abstract
Based on observations of fluctuations in progenitors for inflammatory cells during allergic responses, we have proposed that a primary determinant of allergic inflammation involves microenvironmental influences on hemopoietic cell differentiation and phenotype; in addition, as a corollary of this, inflammatory cell burden is proposed as an important indicator of the severity and pattern of the inflammatory process in allergy. The studies outlined here focus on the effects of epithelial-cell- and fibroblast-derived cytokines on granulocytic and monocytic cell differentiation and activation in models involving allergic reactions in the upper and lower airways. Pure cultures of nasal or bronchial epithelial cells or fibroblasts are observed to give rise to cytokines important in inducing the differentiation of basophils, eosinophils, neutrophils and monocyte/macrophages. Gene expression, production and secretion of granulocyte/macrophage-colony-stimulating factor, interleukin-6 (IL-6) and IL-8 can be demonstrated in vitro and in vivo. Up-regulation of gene expression and production of these cytokines, which are important in inducing basophil, eosinophil and neutrophil/macrophage differentiation in several assays, is seen with IL-1 and the neuropeptide substance P; conversely, inhibition of cytokine production by structural cells is observed after pretreatment with corticosteroids in vitro, paralleling in vivo effects. Other modulatory effects also examined include: antiallergic compounds, which may affect posttranscriptional events in cytokine production, and heavy metal ions, which can also induce changes in gene expression. Structural-cell-derived extracellular matrices appear also to be important both in mast cell differentiation and in macrophage cytokine gene expression, both of which potentially feedback upon chronic allergic inflammatory processes, leading to their perpetuation.(ABSTRACT TRUNCATED AT 250 WORDS)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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; a candidate call from one teacher head, 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".