Epithelial-mesenchymal transition (EMT) changes in patients with LAM and IPF
Bibliographic record
Abstract
<bold>Introduction/Aim:</bold> IPF is an irreversible fibrotic disease. Lymphangioleiomyomatosis (LAM) is a rare lung disease characterised by the abnormal proliferation of mesenchymal smooth muscle-like cells, leading to the formation of multiple lung cysts. EMT has been identified as a key mechanism driving fibrotic changes in COPD. Here, we aim to evaluate EMT activity in IPF (n=13) and LAM (n=6) compared to normal controls (NC, n=12). <bold>Method:</bold> Resected small airway (SA) tissue were stained for EMT markers – E-cadherin, N-cadherin, vimentin and S100A4. Biomarkers’ expression was quantified in the epithelial layer and parenchymal region using Image-Pro Plus 7.0 software. <bold>Results:</bold> Thickened epithelium was observed in IPF and LAM compared to NC. Compared to NC, E-cadherin expression was reduced in IPF (p<0.05), while N-cadherin expression was significantly increased in IPF (p<0.05) and LAM (p<0.001); vimentin expression was significantly increased in the epithelium and reticular basement membrane (Rbm) of IPF and LAM (p<0.01), while S100A4 expression was higher in the epithelium (p<0.01). Interestingly, S100A4 expression in the Rbm was lower in IPF and LAM compared to NC, potentially reflecting the presence of more mature myofibroblast, where S100A4 expression is lost. Furthermore, vimentin and S100A4 expression in type 2 pneumocytes within the lung parenchymal were significantly increased in IPF and LAM compared to NC. <bold>Conclusion:</bold> The observed SA remodelling, along with the differential expression of EMT markers, suggest active EMT in IPF and LAM patients. Further investigation into the correlations between EMT markers and lung function parameters may provide deeper insights into the pathogenesis of IPF and LAM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".