Lung Myeloid Dendritic Cells Coordinately Induce T <sub>H</sub> 1 and T <sub>H</sub> 17 Responses in Human Emphysema
Bibliographic record
Abstract
Exposure to tobacco smoke activates innate and adaptive immune responses that in long-term smokers have been linked to diseases of the lungs, cardiovascular system, joints, and other organs. The destruction of lung tissue that underlies smoking-induced emphysema has been associated with T helper 1 cells that recognize the matrix protein elastin. Factors that result in the development of such autoreactive T cells in smokers remain unknown but are crucial for further understanding the pathogenesis of systemic inflammatory diseases in smokers. Here, we show that lung myeloid dendritic cells were sufficient to induce T helper 1 and T helper 17 responses in CD4 T cells. T helper 1 and 17 cells are invariably present in lungs from patients with emphysema but not in lungs from normal individuals. Interleukin-17A, a canonical T helper 17 cytokine, enhanced secretion of CCL20, a chemoattractant for dendritic cells, and matrix metalloproteinase 12, a potent elastolytic proteinase, from lung macrophages. Thus, although diverse lung factors potentially contribute to T helper effector differentiation in vivo, lung myeloid dendritic cells direct the generation of pathogenic T cells and support a feedback mechanism that sustains both inflammatory cell recruitment and lung destruction. This mechanism may underlie disease in other elastin-rich organs and tissues.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".