Macrophage plasticity and glucose metabolism: the role of immunometabolism in pulmonary arterial hypertension
Bibliographic record
Abstract
Pulmonary arterial hypertension (PAH) is a syndrome characterized by a mean pulmonary artery pressure >20 mmHg and elevated pulmonary vascular resistance >2 Wood Units in the absence of left heart disease, chronic lung disease or hypoxia, and chronic thromboembolic disease. PAH is an obliterative pulmonary arteriopathy that leads to morbidity and mortality, often due to right ventricular failure (RVF). Emerging evidence from preclinical research, using chemical inhibition or genetic depletion of inflammatory mediators, reveals a role for inflammation in the adverse pulmonary vascular remodelling in PAH. More recently, studies have also identified inflammation of the right ventricle (RV) as a potential contributor to RV decompensation and failure. While inflammation contributes to the pathogenesis of PAH, no approved PH-targeted therapies specifically target inflammation. Macrophages are myeloid cells that play a critical role in inflammation and PAH. Their cellular plasticity enables the acquisition of tissue-specific phenotypes and functions that may promote either resolution or exacerbation of inflammatory signalling. Macrophage plasticity in PAH is poorly understood. We examine how alterations in glucose metabolism, particularly the uncoupling of glycolysis from glucose oxidation-a notable feature of PAH observed in various cell populations-impact macrophage polarization and the inflammatory phenotype associated with PAH. The study of immune cell metabolism, known as immunometabolism, is an emerging field that has yet to be explored in PAH. Improving understanding of the inflammatory mechanisms in PAH, particularly novel pathways related to macrophage immunometabolism, may identify new targets for anti-inflammatory therapies for PAH.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".