Mouse models to evaluate the function of genes associated with allergic airway disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: In recent years, considerable effort has been invested in developing mouse models of allergic airway disease, as a means of evaluating the role of select genes in its pathophysiology. Here, we review the principal models used in this field, including models of allergic asthma and hypersensitivity pneumonitis. As an example of how these models can reveal novel functional roles for genes, we review our work showing a role for the stem-cell-associated gene, Cd34. Through this example, we illustrate the genetic and immunological strategies available in the field to better understand allergic airway inflammation. RECENT FINDINGS: CD34 was found to play an important role in the development of two different models of allergic disease, that is, Th2-driven allergic asthma and Th17-driven hypersensitivity pneumonitis. Using a combination of genetically modified mice as well as cell transfers and chimeric mice, we showed that CD34 is important for the efficient trafficking of hematopoietic subsets into and out of the lung, including mast cells, eosinophils and dendritic cells. SUMMARY: The currently available array of mutant mice and animal models of allergic disease now offers an opportunity to make profound insights into these diseases and provide preclinical models for the development of therapeutics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".