TRIM33 prevents pulmonary fibrosis by impairing TGF-β1 signalling
Bibliographic record
Abstract
Background Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterised by myofibroblast proliferation and abnormal extracellular matrix accumulation in the lungs. Transforming growth factor (TGF)-β1 initiates key profibrotic signalling involving the SMAD pathway and the small heat shock protein B5 (HSPB5). Tripartite motif-containing 33 (TRIM33) has been reported to negatively regulate TGF-β/SMAD signalling, but its role in fibrogenesis remains unknown. The objective of this study was to elucidate the role of TRIM33 in IPF. Methods TRIM33 expression was assessed in the lungs of IPF patients and rodent fibrosis models. Bone marrow-derived macrophages (BMDM), primary lung fibroblasts and 3D lung tissue slices were isolated from Trim33 -floxed mice and cultured with TGF-β1 or bleomycin (BLM). Trim33 expression was then suppressed by adenovirus Cre recombinase (AdCre). Pulmonary fibrosis was evaluated in haematopoietic-specific Trim33 knockout mice and in Trim33 -floxed mice that received AdCre and BLM intratracheally. Results TRIM33 was overexpressed in alveolar macrophages and fibroblasts in IPF patients and rodent fibrotic lungs. Trim33 inhibition in BMDM increased TGF-β1 secretion upon BLM treatment. Haematopoietic-specific Trim33 knockout sensitised mice to BLM-induced fibrosis. In primary lung fibroblasts and 3D lung tissue slices, Trim33 deficiency increased expression of genes downstream of TGF-β1. In mice, AdCre- Trim33 inhibition worsened BLM-induced fibrosis. In vitro , HSPB5 was able to bind directly to TRIM33, thereby diminishing its protein level and TRIM33/SMAD4 interaction. Conclusion Our results demonstrate a key role of TRIM33 as a negative regulator of lung fibrosis. Since TRIM33 directly associates with HSPB5, which impairs its activity, inhibitors of TRIM33/HSPB5 interaction may be of interest in the treatment of IPF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
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 teacher head, 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".