Biosignature for airway inflammation in a house dust mite-challenged murine model of allergic asthma
Bibliographic record
Abstract
House dust mite (HDM) challenge is commonly used in murine models of allergic asthma for preclinical pathophysiological studies. However, few studies define objective readouts or biomarkers in this model. In this study we characterized immune responses and defined molecular markers that are specifically altered after HDM challenge. In this murine model, we used repeated HDM challenge for two weeks which induced hallmarks of allergic asthma seen in humans, including airway hyper-responsiveness (AHR) and elevated levels of circulating total and HDM-specific IgE and IgG1. Kinetic studies showed that at least 24 h after last HDM challenge results in significant AHR along with eosinophil infiltration in the lungs. Histologic assessment of lung revealed increased epithelial thickness and goblet cell hyperplasia, in the absence of airway wall collagen deposition, suggesting ongoing tissue repair concomitant with acute allergic lung inflammation. Thus, this model may be suitable to delineate airway inflammation processes that precede airway remodeling and development of fixed airway obstruction. We observed that a panel of cytokines e.g. IFN-γ, IL-1β, IL-4, IL-5, IL-6, KC, TNF-α, IL-13, IL-33, MDC and TARC were elevated in lung tissue and bronchoalveolar fluid, indicating local lung inflammation. However, levels of these cytokines remained unchanged in serum, reflecting lack of systemic inflammation in this model. Based on these findings, we further monitored the expression of 84 selected genes in lung tissues by quantitative real-time PCR array, and identified 31 mRNAs that were significantly up-regulated in lung tissue from HDM-challenged mice. These included genes associated with human asthma (e.g. clca3, ear11, il-13, il-13ra2, il-10, il-21, arg1 and chia1) and leukocyte recruitment in the lungs (e.g. ccl11, ccl12 and ccl24). This study describes a biosignature to enable broad and systematic interrogation of molecular mechanisms and intervention strategies for airway inflammation pertinent to allergic asthma that precedes and possibly potentiates airway remodeling and fibrosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.002 |
| 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".