Inflammatory gene regulation by Cdc42 in airway epithelial cells
Why this work is in the frame
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Bibliographic record
Abstract
Cytokine release from airway epithelial cells is a key immunological process that coordinates an immune response in the lungs. We propose that the Rho GTPase, Cdc42, regulates both transcription and trafficking of cytokines, ultimately affecting the essential process of cytokine release and subsequent inflammation in the lungs. Here, we examined the pro-inflammatory transcriptional profile that occurs in bronchial epithelial cells (BEAS-2B) in response to TNF-α using RNA-Seq and differential gene expression analysis. To interrogate the role of Cdc42 in inflammatory gene expression, we used a pharmacological inhibitor of Cdc42, ML141, and determined changes in the transcriptomic profile induced by Cdc42 inhibition. Our results indicated that Cdc42 inhibition with ML141 resulted in a unique inflammatory phenotype concomitant with increased gene expression of ER stress genes, Golgi membrane and vesicle transport genes. To further interrogate the inflammatory pathways regulated by Cdc42, we made BEAS-2B knockdown strains for the signaling targets TRIB3, DUSP5, SESN2 and BMP4, which showed high differential expression in response to Cdc42 inhibition. Depletion of DUSP5 and TRIB3 reduced the pro-inflammatory response triggered by Cdc42 inhibition as shown by a reduction in cytokine transcript levels. Depletion of SESN2 and BMP4 did not affect cytokine transcript level, however, Golgi fragmentation was reduced. These results provide further evidence that in airway epithelial cells, Cdc42 is part of a signaling network that controls inflammatory gene expression and secretion by regulating Golgi integrity. Summary sentence:We define the Cdc42-regulated gene networks for inflammatory signaling in airway epithelial cells which includes regulation of ER stress response and vesicle trafficking pathways.
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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 it