Gob-5 Is Not Essential for Mucus Overproduction in Preclinical Murine Models of Allergic Asthma
Bibliographic record
Abstract
Overexpression of Gob-5 has previously been linked to goblet cell metaplasia and mucin overproduction in both in vitro and in vivo model systems. In this study, Gob-5 knockout mice were generated and their phenotype was evaluated in two established preclinical models of allergic asthma. We sought to determine whether the Gob-5-null animals could produce less mucus in response to allergic challenge, and whether this would have any impact on reducing goblet cell metaplasia and airway inflammation. We found that in the absence of a proinflammatory stimulus we could not detect an overt phenotypic difference between age and sex-matched knockout and wild-type animals. Allergic challenge with ovalbumin or intranasal administration of interleukin-13 produced a robust allergic response that was similar regardless of genotype. In addition, siRNA-mediated knockdown of CLCA-1 in cultured lung epithelial cells failed to reduce mucin expression in vitro. Thus, in contrast to previously published reports, our findings show that Gob-5 expression is not essential for mucin overproduction in vitro or in murine models of allergic asthma. Furthermore, we have also exploited the use of gene expression array analysis to investigate the possibility that a compensatory mechanism, involving other genes, may act to override the requirement for Gob-5-mediated mucus overproduction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".