Excess Protein O-GlcNAcylation Links Metabolic Derangements to Right Ventricular Dysfunction in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
-acetylglucosamine, which, when added to serines or threonines, modulates protein function through protein O-GlcNAcylation. Glutamine-fructose-6-phosphate amidotransferase (GFAT) regulates HBP flux, and AMP-kinase phosphorylation of GFAT blunts GFAT activity and O-GlcNAcylation. While numerous studies demonstrate increased right ventricle (RV) glucose uptake in pulmonary arterial hypertension (PAH), the relationship between O-GlcNAcylation and RV function in PAH is unexplored. Therefore, we examined how colchicine-mediated AMP-kinase activation altered HBP intermediates, O-GlcNAcylation, mitochondrial function, and RV function in pulmonary artery-banded (PAB) and monocrotaline (MCT) rats. AMPK activation induced GFAT phosphorylation and reduced HBP intermediates and O-GlcNAcylation in MCT but not PAB rats. Reduced O-GlcNAcylation partially restored the RV metabolic signature and improved RV function in MCT rats. Proteomics revealed elevated expression of O-GlcNAcylated mitochondrial proteins in MCT RVs, which fractionation studies corroborated. Seahorse micropolarimetry analysis of H9c2 cardiomyocytes demonstrated colchicine improved mitochondrial function and reduced O-GlcNAcylation. Presence of diabetes in PAH, a condition of excess O-GlcNAcylation, reduced RV contractility when compared to nondiabetics. Furthermore, there was an inverse relationship between RV contractility and HgbA1C. Finally, RV biopsy specimens from PAH patients displayed increased O-GlcNAcylation. Thus, excess O-GlcNAcylation may contribute to metabolic derangements and RV dysfunction in 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".