The endothelium in hypoxic pulmonary vasoconstriction
Bibliographic record
Abstract
Hypoxic pulmonary vasoconstriction (HPV) in combination with hypercapnic pulmonary vasoconstriction redistributes pulmonary blood flow from poorly aerated to better ventilated lung regions by an active process of local vasoconstriction. Impairment of HPV results in ventilation-perfusion mismatch and is commonly associated with various lung diseases including pneumonia, sepsis, or cystic fibrosis. Although several regulatory pathways have been identified, considerable knowledge gaps persist, and a unifying concept of the signaling pathways that underlie HPV and their impairment in lung diseases has not yet emerged. In the past, conceptual models of HPV have focused on pulmonary arterial smooth muscle cells (PASMC) acting as sensor and effector of hypoxia in the pulmonary vasculature. In contrast, the endothelium was considered a modulating bystander in this scenario. For an ideal design, however, the oxygen sensor in HPV should be located in the region of gas exchange, i.e., in the alveolar capillary network. This concept requires the retrograde propagation of the hypoxic signal along the endothelial layer of the vascular wall and subsequent contraction of PASMC in upstream arterioles that is elicited via temporospatially tightly controlled endothelial-smooth muscle cell crosstalk. The present review summarizes recent work that provides proof-of-principle for the existence and functional relevance of such signaling pathway in HPV that involves important roles for connexin 40, epoxyeicosatrienoic acids, sphingolipids, and cystic fibrosis transmembrane conductance regulator. Of translational relevance, implication of these molecules provides for novel mechanistic explanations for impaired ventilation/perfusion matching in patients with pneumonia, sepsis, cystic fibrosis, and presumably various other lung diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
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".