Imbalance of Receptor-Regulated and Inhibitory Smads in Lung Fibroblasts from Bleomycin-Exposed Rats
Bibliographic record
Abstract
Transforming growth factor (TGF)-beta plays a central role in lung fibrosis, stimulating extracellular matrix deposition. Intracellular signaling of TGF-beta is mediated by Smad proteins. We questioned whether the expression and activation of Smads would be altered in lung fibroblasts from rats exposed to bleomycin, an agent used to provoke an experimental model of lung fibrosis. Fibroblasts were isolated from rat lungs 14 d after intratracheal instillation of bleomycin (BLF) or saline (NLF), and cell cultures established. Whole cell lysates were obtained at baseline, and after stimulation with TGF-beta1 (10 ng/ml). Western blot analysis was performed to measure levels of phosphorylated Smad3 (p-Smad3) and Smad7. Real-time PCR was used to determine changes in Smad7 mRNA after TGF-beta stimulation. We found increased baseline levels of p-Smad3 in BLF versus NLF (P < 0.05). In contrast, baseline levels of Smad7 were comparable. The ratio of stimulatory to inhibitory Smads was increased in BLF compared with NLF (P < 0.05). After stimulation with TGF-beta, levels of p-Smad3 were increased in both groups, with maximal responses at 30 min (P < 0.01). While Smad7 mRNA levels were significantly upregulated (at 1 h) after TGF-beta in both groups, the increase in Smad7 protein was significant in NLF only. We conclude there is sustained activation of Smad signaling in lung fibroblasts isolated from bleomycin-exposed rats, with an imbalance between the levels of p-Smad3 and Smad7. Insufficient levels of the inhibitory Smad7 at baseline, and inadequate response to TGF-beta, may contribute to the fibrotic phenotype characteristic of BLF.
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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 | 0.001 | 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) | 0.003 | 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".