Fibroblasts in Hypoxic Conditions Mimic Laryngotracheal Stenosis
Bibliographic record
Abstract
Objective To elucidate the role of hypoxia and inflammatory pathways in the pathogenesis of iatrogenic laryngotracheal stenosis (iLTS). Study Design (1) Examination of mucosal surface gene expression in human iLTS. (2) In vitro comparison of normal and scar laryngotracheal fibroblasts under normoxic and hypoxic conditions. Setting Tertiary care hospital in a research university (2012‐2016). Subjects and Methods Brush biopsies were obtained from normal laryngotracheal tissue and scar in iLTS patients; gene expression was compared. Fibroblasts were isolated from normal and scarred trachea and grown in vitro in either a 1% O 2 or normoxic environment. Cell growth and gene and protein expression were compared. Statistical analysis utilized a multilevel mixed effects model. Results Expression of IL‐6 (fold change = 2.8, P <. 01), myofibroblast marker αSMA (fold change = 3.0, P =. 01), and MMP13 (fold change = 5.4, P =. 02) was significantly increased in scar biopsy samples as compared to normal. Under hypoxic conditions in vitro, normal laryngotracheal fibroblasts proliferated significantly faster (n = 8, P <. 01 each day). Expression of IL‐6 (n = 8, fold change = 2.6, P <. 01) increased significantly after 12 hours under hypoxia. Expression of αSMA (n = 8, fold change= 2.0, P =. 03), COL1 (n = 8, fold change = 1.1, P =. 03), and MMP13 (n = 8, fold change = 1.6, P =. 01) increased significantly after 48 hours under hypoxia. Scar fibroblasts also proliferated significantly faster under hypoxic conditions but did not display the same expression profile. Conclusion Human iLTS scar has a myofibroblast phenotype. Under hypoxic conditions in vitro, normal laryngotracheal fibroblasts can transdifferentiate into a similar phenotype. These changes may be mediated by IL‐6, a fibrosis‐related cytokine.
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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) | 0.000 | 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".