Macrophage plasticity and glucose metabolism: the role of immunometabolism in pulmonary arterial hypertension
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it