Emerging role of MAP kinase pathways as therapeutic targets in COPD
Bibliographic record
Abstract
Studies examining the cellular mechanisms of inflammation and protease production in the lung tissue and airways of COPD patients have shed light on the important role of kinase-based signaling cascades. These pathways can be activated by environmental stimuli such as tobacco smoke, and by endogenous signals such as cytokines, growth factors, and inflammation-derived oxidants. The three most widely characterized cascades are those directed by the classical mitogen activated protein (MAP) kinase (ERK1/2), stress activated protein kinase/c-Jun N-terminal protein kinase, and p38 enzymes. These phosphorylation cascades transmit and amplify extracellular, receptor-mediated signals through the cytoplasm of the cell to activate nuclear transcription factors which bind and induce expression of target genes. The result is tight control of diverse cellular events, and rapid responses to external stimuli. However, recent research suggests that constitutive or aberrant activation of MAP kinases contributes to several COPD-associated phenotypes, including mucus overproduction and secretion, inflammation, cytokine expression, apoptosis, T cell activation, matrix metalloproteinase production, and fibrosis. This review explores the biological functions of the MAP kinase pathways in the pathogenesis of COPD, their activation by cigarette smoke, and discusses the potential role of MAP kinase inhibitors in COPD therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".