Mitochondria in the Pulmonary Vasculature in Health and Disease: Oxygen‐Sensing, Metabolism, and Dynamics
Bibliographic record
Abstract
Abstract In lung vascular cells, mitochondria serve a canonical metabolic role, governing energy homeostasis. In addition, mitochondria exist in dynamic networks, which serve noncanonical functions, including regulation of redox signaling, cell cycle, apoptosis, and mitochondrial quality control. Mitochondria in pulmonary artery smooth muscle cells (PASMC) are oxygen sensors and initiate hypoxic pulmonary vasoconstriction. Acquired dysfunction of mitochondrial metabolism and dynamics contribute to a cancer‐like phenotype in pulmonary arterial hypertension (PAH). Acquired mitochondrial abnormalities, such as increased pyruvate dehydrogenase kinase (PDK) and pyruvate kinase muscle isoform 2 (PKM2) expression, which increase uncoupled glycolysis (the Warburg phenomenon), are implicated in PAH. Warburg metabolism sustains energy homeostasis by the inhibition of oxidative metabolism that reduces mitochondrial apoptosis, allowing unchecked cell accumulation. Warburg metabolism is initiated by the induction of a pseudohypoxic state, in which DNA methyltransferase (DNMT)‐mediated changes in redox signaling cause normoxic activation of HIF‐1α and increase PDK expression. Furthermore, mitochondrial division is coordinated with nuclear division through a process called mitotic fission. Increased mitotic fission in PAH, driven by increased fission and reduced fusion favors rapid cell cycle progression and apoptosis resistance. Downregulation of the mitochondrial calcium uniporter complex (MCUC) occurs in PAH and is one potential unifying mechanism linking Warburg metabolism and mitochondrial fission. Mitochondrial metabolic and dynamic disorders combine to promote the hyperproliferative, apoptosis‐resistant, phenotype in PAH PASMC, endothelial cells, and fibroblasts. Understanding the molecular mechanism regulating mitochondrial metabolism and dynamics has permitted identification of new biomarkers, nuclear and CT imaging modalities, and new therapeutic targets for PAH. © 2020 American Physiological Society. Compr Physiol 10:713‐765, 2020.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".