Regional Heterogeneity in Murine Lung Fibroblasts from Normal Mice or Mice Exposed Once to Cigarette Smoke
Bibliographic record
Abstract
Chronic obstructive lung disease (COPD) is characterized by matrix deposition in the small airways but matrix loss from the parenchyma, phenomena which must depend on the ability of local fibroblasts to produce matrix after smoke exposure. To investigate this idea, we exposed C57Bl/6 mice once to cigarette smoke or to air (control) and prepared primary cultures of lung fibroblasts by microdissecting large airways (trachea, LAF), medium size airways (major bronchi, MAF) and parenchyma (PF). Control PF showed the lowest rate of wound closure and wound closure was depressed in all lines by a single in vivo smoke exposure. Gene expression of matrix proteins differed considerably among the sites; decorin, which may sequester TGFβ, was markedly higher in PF. PF showed higher intrinsic ratios of pSmad2/Smad2. Smoke caused much greater increases in secreted and matrix deposited collagens 1 and 3 in PF than in LAF or MAF. Expression of Thy-1, a gene that suppresses myofibroblast differentiation, was increased by smoke in PF. We conclude that there is considerable regional heterogeneity in murine lung fibroblasts in terms of matrix production, either basally or after in vivo smoke exposure; that PF have lower ability to repair wounds and higher intrinsic TGFβ signaling; and that a single exposure to smoke produces lasting changes in the pattern of matrix production and wound repair, changes that may be mediated in part by smoke-induced release of TGFβ. However, PF still retain the ability to repair by producing new matrix after a single in vivo smoke exposure.
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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".