Regulation of the effects of TGF-beta 1 by activation of latent TGF-beta 1 and differential expression of TGF-beta receptors (Tbeta R-I and Tbeta R-II) in idiopathic pulmonary fibrosis
Bibliographic record
Abstract
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterised by subpleural fibrosis that progresses to involve all areas of the lung. The expression of transforming growth factor-beta1 (TGF-beta 1), a potent regulator of connective tissue synthesis, is increased in lung sections of patients with IPF. TGF-beta 1 is generally released in a biologically latent form (L-TGF-beta 1). Before being biologically active, TGF-beta must be converted to its active form and interact with both TGF-beta receptors type I and II (T beta R-I and T beta R-II). TGF-beta latency binding protein 1 (LTBP-1), which facilitates the release and activation of L-TGF-beta 1, is also important in the biology of TGF-beta 1. METHODS: Open lung biopsy samples from patients with IPF and normal controls were examined to localise T beta R-I, T beta R-II, and LTBP-1. Alveolar macrophages (AM) and bronchoalveolar lavage (BAL) fluid were examined using the CCL-64 bioassay to determine if TGF-beta is present in its active form in the lungs of patients with IPF. RESULTS: Immunoreactive L-TGF-beta 1 was present in all lung cells of patients with IPF except for fibroblasts in the subepithelial regions of honeycomb cysts. LTBP-1 was detected primarily in AM and epithelial cells lining honeycomb cysts in areas of advanced IPF. In normal lungs LTBP-1 immunoreactivity was observed in a few AM. AM from the upper and lower lobes of patients with IPF secreted 1.6 (0.6) fmol and 4.1 (1.9) fmol active TGF-beta, respectively, while AM from the lower lobes of control patients secreted no active TGF-beta (p< or =0.01 for TGF-beta in the conditioned media from AM obtained from the lower lobes of IPF patients v normal controls). The difference in percentage active TGF-beta secreted by AM from the lower lobes of patients with IPF and the lower lobes of control patients was significant (p< or =0.01), but the difference between the total TGF-beta secreted from these lobes was not significant. The difference in active TGF-beta in conditioned media of AM from the upper and lower lobes of patients with IPF was also not statistically significant. BAL fluid from the upper and lower lobes of patients with IPF contained 0.7 (0.2) fmol and 2.9 (1.2) fmol active TGF-beta, respectively (p< or =0.03). The percentage of active TGF-beta in the upper and lower lobes was 17.6 (1.0)% and 78.4 (1.6)%, respectively (p< or =0.03). In contrast, BAL fluid from control patients contained small amounts of L-TGF-beta. Using immunostaining, both T beta R-I and T beta R-II were present on all cells of normal lungs but T beta R-I was markedly reduced in most cells in areas of honeycomb cysts except for interstitial myofibroblasts in lungs of patients with IPF. TGF-beta 1 inhibits epithelial cell proliferation and a lack of T beta R-I expression by epithelial cells lining honeycomb cysts would facilitate repair of the alveoli by epithelial cell proliferation. However, the presence of both T beta Rs on fibroblasts is likely to result in a response to TGF-beta 1 for synthesis of connective tissue proteins. Our findings show that biologically active TGF-beta 1 is only present in the lungs of patients with IPF. In addition, the effects of TGF-beta 1 on cells may be further regulated by the expression of T beta Rs. CONCLUSION: Activation of L-TGF-beta 1 and the differential expression of T beta Rs may be important in the pathogenesis of remodelling and fibrosis in IPF.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".