p38 MAPK signaling in chronic obstructive pulmonary disease pathogenesis and inhibitor therapeutics
Bibliographic record
Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by persistent respiratory symptoms and airflow limitation due to airway and/or alveolar remodeling. Although the abnormalities are primarily prompted by chronic exposure to inhaled irritants, maladjusted and self-reinforcing immune responses are significant contributors to the development and progression of the disease. The p38 isoforms are regarded as pivotal hub proteins that regulate immune and inflammatory responses in both healthy and disease states. As a result, their inhibition has been the subject of numerous recent studies exploring their therapeutic potential in COPD. MAIN BODY: We performed a systematic search based on the PRISMA guidelines to find relevant studies about P38 signaling in COPD patients. We searched the PubMed and Google Scholar databases and used "P38" AND "COPD" Mesh Terms. We applied the following inclusion criteria: (1) human, animal, ex vivo and in vitro studies; (2) original research articles; (3) published in English; and (4) focused on P38 signaling in COPD pathogenesis, progression, or treatment. We screened the titles and abstracts of the retrieved studies and assessed the full texts of the eligible studies for quality and relevance. We extracted the following data from each study: authors, year, country, sample size, study design, cell type, intervention, outcome, and main findings. We classified the studies according to the role of different cells and treatments in P38 signaling in COPD. CONCLUSION: While targeting p38 MAPK has demonstrated some therapeutic potential in COPD, its efficacy is limited. Nevertheless, combining p38 MAPK inhibitors with other anti-inflammatory steroids appears to be a promising treatment choice. Clinical trials testing various p38 MAPK inhibitors have produced mixed results, with some showing improvement in lung function and reduction in exacerbations in COPD patients. Despite these mixed results, research on p38 MAPK inhibitors is still a major area of study to develop new and more effective therapies for COPD. As our understanding of COPD evolves, we may gain a better understanding of how to utilize p38 MAPK inhibitors to treat this disease. Video Abstract.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".