Specialized Pro-Resolving Lipid Mediators in Pulmonary Diseases: Molecular and Therapeutic Implications
Bibliographic record
Abstract
Inflammatory lung diseases (ILDs) represent a global public health crisis characterized by escalating prevalence, significant morbidity, and substantial mortality. In response to the complex immunopathogenic mechanisms driving these conditions, novel pharmacological strategies targeting resolution pathways have emerged throughout the discovery of specialized pro-resolving lipid mediator (SPM; resolvins, maresins, and protectins) dysregulation across the ILD spectra, positioning these endogenous molecules as promising therapeutic candidates for modulating maladaptive inflammation and promoting tissue repair. Over the past decade, this paradigm has catalyzed extensive translational research into SPM-based interventions as precision therapeutics for respiratory inflammation. In asthma, they reduce mucus hypersecretion, bronchial hyperreactivity, and airway inflammation, with prenatal SPM exposure potentially lowering offspring disease risk. In COPD, SPMs attenuate amyloid A-driven inflammation, normalizing cytokine/chemokine imbalances and oxidative stress and mitigating COVID-19-associated cytokine storm, enhancing survival. This review synthesizes SPMs' pharmacotherapeutic mechanisms in ILDs and evaluates current preclinical and clinical evidence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".