Chronological attenuation of <scp>NPRA</scp>/<scp>PKG</scp>/<scp>AMPK</scp> signaling promotes vascular aging and elevates blood pressure
Bibliographic record
Abstract
Abstract Hypertension is common in elderly population. We designed to search comprehensively for genes that are chronologically shifted in their expressions and to define their contributions to vascular aging and hypertension. RNA sequencing was conducted to search for senescence‐shifted transcripts in human umbilical vein endothelial cells (HUVECs). Small interfering RNA (siRNA), small‐molecule drugs, CRISPR/Cas9 techniques, and imaging were used to determine genes' function and contributions to age‐related phenotypes of the endothelial cell and blood vessel. Of 25 genes enriched in the term of “regulation of blood pressure,” NPRA was changed most significantly. The decreased NPRA expression was replicated in aortas of aged mice. The knockdown of NPRA promoted HUVEC senescence and it decreased expressions of protein kinase cGMP‐dependent 1 (PKG), sirtuin 1 (SIRT1), and endothelial nitric oxide synthase (eNOS). Suppression of NPRA also decreased the phosphorylation of AMP‐activated protein kinase (AMPK) as well as the ratio of oxidized nicotinamide adenine dinucleotide (NAD+)/reduced nicotinamide adenine dinucleotide (NADH) but increased the production of reactive oxygen species (ROS). 8‐Br‐cGMP (analog of cGMP), or AICAR (AMPK activator), counteracted the observed changes in HUVECs. The Npr1+/− mice presented an elevated systolic blood pressure and their vessels became insensitive to endothelial‐dependent vasodilators. Further, vessels from Npr1+/− mice increased Cdkn1a but decreased eNos expressions. These phenotypes were rescued by intravenously administrated 8‐Br‐cGMP and viral overexpression of human PKG, respectively. In conclusion, we demonstrate NPRA/PKG/AMPK as a novel and critical signaling axis in the modulation of endothelial cell senescence, vascular aging, and hypertension.
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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) | 0.002 | 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".