Innate Immune Processes Are Sufficient for Driving Cigarette Smoke–Induced Inflammation in Mice
Bibliographic record
Abstract
The objective of this study was to characterize the impact of cigarette smoke exposure on lung immune and inflammatory processes. BALB/c and C57BL/6 mice were exposed to cigarette smoke for 4 days (acute) or at least 5 weeks (prolonged). Both mouse strains manifested an inflammatory response after acute smoke exposure, characterized by an influx of neutrophils and mononuclear cells. Multiplex analysis revealed a greater than twofold increase of the cytokines IL-1alpha, -5, -6, and -18, as well as the chemokines monocyte chemotactic protein-1 and -3, macrophage inflammatory protein-1alpha, -beta, and -gamma, -2, -3beta, macrophage defined chemokine, granulocyte chemotactic protein-2, and interferon-gamma-inducible protein-10. In BALB/c mice, neutrophilia persisted after prolonged exposure, whereas C57BL/6 showed evidence of attenuated neutrophilia both in the bronchoalveolar lavage and the lungs. In both mouse strains, cigarette smoke exposure was associated with an expansion of mature (CD11c(hi)/major histocompatibility complex class II(hi)) myeloid dendritic cells; we observed no changes in plasmacytoid dendritic cells. Lymphocytes in the lungs displayed an activated phenotype that persisted for CD4 T cells only after prolonged exposure. In BALB/c mice, T cells acquired T helper (Th) 1 and Th2 effector function after 5 weeks of smoke exposure, whereas, in C57BL/6 mice, neither Th1 nor Th2 cells were detected. In both mouse strains, cigarette smoke exposure led to an accumulation of FoxP3+ T regulatory cells in the lungs. Studies in RAG1 knockout mice suggest that these regulatory cells may participate in controlling smoke-induced inflammation. Acute and prolonged cigarette smoke exposure was associated with inflammation, activation of the adaptive immune system, and expansion of T regulatory cells in the lungs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".