Activation of the Prolyl Hydroxylase Oxygen-sensor Results in Induction of GLUT1, Heme Oxygenase-1, and Nitric-oxide Synthase Proteins and Confers Protection from Metabolic Inhibition to Cardiomyocytes
Bibliographic record
Abstract
Recently an oxygen-sensing/transducing mechanism has been identified as a family of O2-dependent prolyl hydroxylase domain-containing enzymes (PHD). In normoxia, PHD hydroxylates a specific proline residue that directs the degradation of constitutively synthesized hypoxia-inducible factor-1alpha. During hypoxia, the cessation of hydroxylation of this proline results in less degradation and thus increases hypoxia-inducible factor-1alpha protein levels. In this study we have examined the consequences of activating the PHD oxygen-sensing pathway in cultured neonatal myocytes using ethyl-3,4 dihydroxybenzoate and dimethyloxalylglycine, inhibitors that, similar to hypoxia, inhibit this family of O2-dependent PHD enzymes. Increased glucose uptake and enhanced glycolytic metabolism are classical cellular responses to hypoxia. Ethyl-3,4 dihydroxybenzoate treatment of cardiomyocyte cultures for 24 h increased [3H]deoxy-4-glucose uptake concurrent with an induction of GLUT1 protein. In addition, ethyl-3,4 dihydroxybenzoate, dimethyloxalylglycine, and hypoxia treatments were found to induce protein levels of nitricoxide synthase-2 and heme oxygenase-1, two important cardioregulatory proteins whose expression in response to hypoxic conditions is poorly understood. In conjunction with these changes in gene expression, activation of the PHD oxygen-sensing mechanism was found to preserve myocyte viability in the face of metabolic inhibition with cyanide and 2-deoxyglucose. These results point to a key role for the PHD pathway in the phenotypic changes that are observed in a hypoxic myocyte and may suggest a strategy to pharmacologically induce protection in heart.
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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 | 0.000 |
| 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".