Sex-specific alterations in pulmonary metabolic, xenobiotic and lipid signalling pathways after e-cigarette aerosol exposure during adolescence in mice
Bibliographic record
Abstract
BACKGROUND: E-cigarette use is now prevalent among adolescents and young adults, raising concerns over potential adverse long-term health effects. Although it is hypothesised that e-cigarettes promote inflammation, studies have yielded conflicting evidence. Our previous work showed that JUUL, a popular e-cigarette brand, elicited minimal lung inflammation but induced significant molecular changes in adult C57BL/6 mice. METHODS: Now, we have profiled immunological and proteomic changes in the lungs of adolescent male and female BALB/c and C57BL/6 mice exposed to a flavoured JUUL aerosol containing 18 mg/mL of nicotine for 14 consecutive days. We evaluated changes in the immune composition by flow cytometry, gene expression levels by reverse transcription-quantitative PCR and assessed the proteomic profile of the lungs and bronchoalveolar lavage (BAL) by tandem mass tag-labelled mass spectroscopy. RESULTS: While there were few significant changes in the immune composition of the lungs, proteomic analysis revealed that JUUL exposure caused significant sex-dependent and strain-dependent differences in lung and BAL proteins that are implicated in metabolic pathways, including those related to lipids and atherosclerosis, as well as pathways related to immune function and response to xenobiotics. Notably, these changes were more pronounced in male mice. CONCLUSIONS: These findings raise the possibility that vaping dysregulates numerous biological responses in lungs that may affect disease risk, disproportionally impacting males and raising significant concerns for the future health of male youth who currently vape.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
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".