Monocyte Chemoattractant Protein (MCP)-4 Expression in the Airways of Patients with Asthma
Bibliographic record
Abstract
Chemokines are chemotactic cytokines that play an important role in recruiting leukocytes in allergic inflammation. Monocyte chemoacctractant protein (MCP)-4 is a CC chemokine with potent chemotactic activities for eosinophils, monocytes, T lymphocytes, and basophils and therefore represents a good candidate to participate in allergic reactions. To determine if MCP-4 plays a role in asthma, we have investigated the expression of MCP-4 messenger RNA (mRNA) and protein in the airways of patients with asthma and normal control subjects by in situ hybridization and immunohistochemistry. We found that MCP-4 mRNA and protein was significantly upregulated in the epithelium and submucosa of bronchial biopsies and in the bronchoalveolar lavage (BAL) cells of patients with asthma compared with normal control subjects (p < 0. 01). In addition, MCP-4 protein was significantly elevated in the BAL fluid of patients with atopic asthma when compared with normal control subjects (p < 0.01) and there was a significant correlation between MCP-4, eotaxin, and eosinophils. In support of our in situ findings demonstrating MCP-4 expression in epithelial cells and mononuclear cells in vivo, we have found that MCP-4 expression can be induced in these cells in vitro by tumor necrosis factor-alpha (TNF-alpha) and interleukin-1beta (IL-1beta). Interferon-gamma (IFN-gamma) acted synergistically with TNF-alpha and IL-1beta in the induction of mRNA MCP-4 mRNA expression in A549 cells, whereas the glucocorticoid dexamethasone diminished the cytokine-induced expression of MCP-4. Our findings demonstrate that MCP-4 is upregulated in the airways of patients with asthma and suggest that MCP-4 plays a role in the recruitment of eosinophils into the airways of patients with asthma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".