The small heat‐shock protein <i>α</i><scp>B</scp>‐crystallin is essential for the nuclear localization of Smad4: impact on pulmonary fibrosis
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by the proliferation of myofibroblasts and the accumulation of extracellular matrix (ECM) in the lungs. TGF-β1 is the major profibrotic cytokine involved in IPF and is responsible for myofibroblast proliferation and differentiation and ECM synthesis. αB-crystallin is constitutively expressed in the lungs and is inducible by stress, acts as a chaperone and is known to play a role in cell cytoskeleton architecture homeostasis. The role of αB-crystallin in fibrogenesis remains unknown. The principal signalling pathway involved in this process is the Smad-dependent pathway. We demonstrate here that αB-crystallin is strongly expressed in fibrotic lung tissue from IPF patients and in vivo rodent models of pulmonary fibrosis. We also show that αB-crystallin-deficient mice are protected from bleomycin-induced fibrosis. Similar protection from fibrosis was observed in αB-crystallin KO mice after transient adenoviral-mediated over-expression of IL-1β or TGF-β1. We show in vitro in primary epithelial cells and fibroblasts that αB-crystallin increases the nuclear localization of Smad4, thereby enhancing the TGF-β1-Smad pathway and the consequent activation of TGF-β1 downstream genes. αB-crystallin over-expression disrupts Smad4 mono-ubiquitination by interacting with its E3-ubiquitin ligase, TIF1γ, thus limiting its nuclear export. Conversely, in the absence of αB-crystallin, TIF1γ can freely interact with Smad4. Consequently, Smad4 mono-ubiquitination and nuclear export are favoured and thus TGF-β1-Smad4 pro-fibrotic activity is inhibited. This study demonstrates that αB-crystallin may be a key target for the development of specific drugs in the treatment of IPF or other fibrotic diseases.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".