The GPx1-PTP1B-PP2A axis: A key determinant of airway inflammation and alveolar destruction
Bibliographic record
Abstract
Protein phosphatase 2A (PP2A) is a primary serine-threonine phosphatase that modulates inflammatory responses in asthma and COPD. Despite its importance, the mechanisms that regulate lung PP2A activity remain to be determined. The redox-sensitive enzyme protein tyrosine phosphatase 1B (PTP1B) activates PP2A by dephosphorylating the catalytic subunit of the protein at tyrosine 307. This study aimed to identify how the interaction between the intracellular antioxidant glutathione peroxidase-1 (GPx-1) and PTP1B impacted on lung PP2A activity and airway inflammation. Studies using gene silencing techniques in mouse lung or human small airway epithelial (SAE) cells determined that knocking down PTP1B expression blocked GPx-1’s activation of PP2A and negated the anti-inflammatory effects of GPx-1 protein in the lung. Similarly, the expression of human GPx-1 in transgenic mice significantly increased PP2A and PTP1B activities and prevented chronic cigarette smoke-induced airway inflammation and alveolar destruction. GPx-1 knockout mice, however, exhibited an exaggerated emphysema phenotype, correlating with a non-responsive PP2A pathway. Importantly, GPx-1-PTP1B-PP2A signaling becomes inactivated in advanced lung diseases. Indeed, PTP1B protein was oxidized in the lungs of advanced emphysema subjects and, unlike normal lung epithelial cells, cigarette smoke did not increase PTP1B activity within epithelial cells isolated from COPD subjects. These findings establish that the GPx-1-PTP1B-PP2A axis plays a critical role in countering the inflammatory and proteolytic responses that result in lung tissue destruction in response to cigarette smoke exposure.
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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 | 0.001 | 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 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".