Role of dendritic cells in pulmonary fibrosis in mice
Bibliographic record
Abstract
Dendritic cells (DC) have been found to accumulate in lungs of patients with idiopathic pulmonary fibrosis, localized in lymphoid follicles together with activated T and B cells. However, their pathogenetic relevance in pulmonary fibrosis is poorly defined. We here found that mice exposed to adenoviral gene transfer of biologically active TGF-β1 (AdTGF-β1) to trigger pulmonary fibrosis responded with significantly increased accumulation particularly of CD11bpos DC, but also CD103pos DC in their lung tissue, compared to control mice. Gene expression profiling of sorted lung DC subsets from AdTGF-β1 versus control vector exposed mice revealed CD11b DC much more than CD103 DC to express markers of extracellular matrix (ECM) turnover such as MMP-2 and -7 as well as tissue inhibitors of MMPs, suggesting particularly lung CD11b DC to contribute to regulation of ECM deposition. Diphtheria toxin treatment of AdTGF-β1 exposed chimeric zDC+/DTR mice, leading to selective depletion of DCs while sparing macrophages, led to significantly reduced numbers of lung DC accompanied by progressive lung fibrosis in mice. Moreover, FMS-like tyrosine kinase-3 ligand (Flt3L) KO mice characterized by congenital lack of major lung DC subsets responded to AdTGF-β1 exposure with progressive lung fibrosis in the absence of lung DC accumulation, relative to WT mice. Together, the data show that i) pulmonary fibrosis is characterized by increased accumulation of DC subsets in lung tissue of mice, and that ii) selective depletion of lung DCs in diphtheria toxin-dependent and –independent model systems aggravates pulmonary fibrosis, thereby suggesting a regulatory role of lung DCs in pulmonary fibrogenesis.
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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) | 0.000 | 0.000 |
| 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 | 0.002 |
| 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".