Indoor Rewilding of Laboratory Mice Recalibrates Pulmonary Mucosal Immunity and Mechanics
Bibliographic record
Abstract
ABSTRACT Laboratory mice raised under specific-pathogen-free (SPF) conditions experience restricted microbial and antigenic exposure, which favours an immature immune system and limits their translational value for respiratory research. While microbial enrichment in “dirty” mouse models restores immune maturation, its impact on integrated respiratory function and model transferability to human disease remains understudied. Here, we tested whether ecological exposure through indoor rewilding of SPF-reared mice could reshape immune complexity and recalibrate pulmonary physiology. Two-month-old female C57BL/6J mice were housed for three months under SPF or indoor-rewilding conditions and assessed for immune, mechanical, and systemic parameters. Rewilded mice exhibited expanded pulmonary immune subsets, increased dendritic-cell immune checkpoint, with TNF/IFN-γ activation coupled to regulatory IL-10 signaling. Despite sustained exposure, the alveolar-capillary barrier integrity was preserved. Functionally, respiratory oscillometry revealed improved pulmonary mechanics, including lower airway resistance, higher compliance, and reduced airway responsiveness to methacholine. Systemic cytokine analyses indicated compartmentalized pulmonary immune activation, maintaining an overall anti-inflammatory balance. Importantly, PRIA screening detected no reportable pathogens introduced during rewilding, while cecal shotgun metagenomics confirmed microbial enrichment. Together, these findings demonstrate that indoor rewilding reestablishes coordinated lung immune and mechanical homeostasis in SPF-reared mice, providing a safe and scalable model for studying human-like mucosal immunity and respiratory physiology with broad implications for preclinical respiratory research and therapeutic testing.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".