The Protein Kinase TPL2 Is Essential for ERK1/ERK2 Activation and Cytokine Gene Expression in Airway Epithelial Cells Exposed to Pathogen-Associated Molecular Patterns (PAMPs)
Bibliographic record
Abstract
The epithelium forms a physical barrier important to the detection of pathogens. P. aeruginosa infections are frequently encountered in Cystic Fibrosis lungs, lead to ERK1/ERK2 activation and contribute to tissue destruction. We report here that in bronchial airway epithelial cells (BEAS-2B), diffusible material from P. aeruginosa and TLR2, TLR3 and TLR5 ligands activates ERK1/ERK2 via the protein kinase TPL2 and not the growth factor receptor EGFR. Activation of TPL2 by these agonists in airway epithelial cells requires the protein kinases TAK1 and IKKβ in accordance with the previously reported model of activation of TPL2 in macrophages. Inhibition of TPL2 activity with a pharmacological inhibitor (Compound 1) not only prevented ERK1/ERK2 activation but also decreased cytokine synthesis in response to pathogen-associated molecular patterns. These results suggest that inhibition of the protein kinase TPL2 is an attractive strategy to decrease inflammation in the lungs when it is not warranted.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".