Impact of nose-only exposure system on pulmonary gene expression
Bibliographic record
Abstract
Nose-only exposure is used to study the distribution and toxicity of airborne contaminants. Restraint of animals in nose-only tubes causes stress, but the impact on pulmonary mRNA levels is unknown. Since stress and xenobiotics activate common pathways, we assessed whether nose-only exposure would alter expression of toxicologically relevant genes in the lungs. To identify candidate genes for further analysis, we first interrogated microarray data to examine time-dependent changes in gene expression in air-control animals from a nose-only inhalation study involving male wild-type C57BL/6 mice and transgenic tumor necrosis factor (TNF)-alpha over-expressing littermates. Comparison of transcript levels immediately and 24 h after a single 4-h nose-only exposure to air revealed differential expression of 280 genes (false discovery rate-adjusted, p < .05). Functional analysis revealed enrichment of immune response, apoptosis, and signalling terms, consistent with effects of restraint stress. We then selected a subset of target genes for comparison of naive animals and air-exposed animals from the inhalation study by real-time polymerase chain reaction (PCR). Expression of genes involved in stress (BNIP, sestrin-1, CDKN1A [p21], GADD45 gamma), glucocorticoid-response (GILZ, Sgk), and signal transduction (MAP3K6, C/EBP-delta) was increased as a result of nose-only exposure (p < .05). In contrast, proinflammatory factors (lymphotoxin-beta, chemokine receptor CXCR5) were decreased (p < .05). Immune gene responses observed in wild-type animals were reduced in animals with lung inflammation, indicating that pathological states can modify the response to nose-only exposure. Observed responses may warrant consideration in the evaluation of materials delivered by nose-only inhalation, and suggest that incorporation of naive animals into nose-only studies should be considered as a best practice.
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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) | 0.001 | 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 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".