Transcriptional Changes of Blood Eosinophils after Methacholine Inhalation Challenge in Asthmatics
Bibliographic record
Abstract
BACKGROUND: Methacholine challenge is commonly used within the asthma diagnostic algorithm. Methacholine challenge has recently been shown to induce airway remodelling in asthma via bronchoconstriction, without additional airway inflammation. We evaluated the effect of methacholine-induced bronchoconstriction on the peripheral whole-blood transcriptome. METHODS: Fourteen males with adult-onset, occupational asthma, 26-77 years of age, underwent methacholine inhalation challenges. The concentration of methacholine eliciting a ≥20% fall in FEV1 (PC20) was determined. Blood was collected immediately prior to and two hours after challenge. Complete blood counts and leukocyte differentials were obtained. Transcriptome analysis was performed using Affymetrix GeneChip(®) Human Gene 1.0 ST arrays. Data were analyzed using robust LIMMA and SAM. The cell-specific Significance Analysis of Microarrays (csSAM) algorithm was used to deconvolute the gene expression data according to cell type. RESULTS: Microarray pathway analysis indicated that inflammatory processes were differentially affected. CsSAM identified 1,559 transcripts differentially expressed (all down-regulated) between pre- and post-methacholine in eosinophils at a false discovery cutoff of 10%. Notable changes included the GOLGA5 and METTL2B genes and the protein ubiquitination and CCR3 pathways. CONCLUSIONS: We demonstrated significant changes in the peripheral blood eosinophil-specific transcriptome of asthmatics two hours after methacholine challenge. CCR3 and protein ubiquitination pathways are both significantly down-regulated.
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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) | 0.000 | 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) | 0.000 | 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".