How Does the Brain Talk to the Arteries and Heart?
Bibliographic record
Abstract
In many hypertension (Htn) models, myogenic tone (MT) in isolated small arteries is increased. MT is regulated mainly by Ca 2+ transporters. Arterial transporter expression is “reprogrammed” in many Htn models: e.g., Na/Ca exchanger (NCX) and SR Ca 2+ pumps (SERCA2) are increased; this enhances constriction and MT. In heart failure (HF), cardiac Ca 2+ transporter “reprogramming” impairs contraction: e.g., NCX1 is increased, and SERCA2 expression or function is reduced. Do these cardiovascular (CV) changes in Htn and HF have a common trigger ? The brain RAAS is activated in both Htn and HF. Central Ang II infusion increases BP, circulating endogenous ouabain (EO), and arterial NCX and SERCA2 expression; brain RAAS blockade prevents all effects (Hamlyn et al., PloS one 9 : e108916, 2014). Here we induced Htn in rats (mean BP = 124 vs C ontrol = 99 mm Hg) and mice (139 vs C = 110 mm Hg) with sc low dose Ang II (150‐350 ng/kg/min) and a high (2‐6%) salt diet. Also, in mice, coronary artery ligation caused ~45% LV myocardial infarction (MI) and HF: a 38±4% fall in LV ejection fraction at 8 wks post‐MI. In both Htn and HF , plasma EO increased (1.31‐2.59 nM vs C = 0.07‐0.53 nM) as did expression of arterial NCX (1.7‐1.8xC) and SERCA2 (2.0‐2.3xC) and cardiac NCX (1.7‐1.9xC), but cardiac SERCA2 expression declined (0.58‐0.74xC). In vitro 48‐72 hr treatment with 50‐100 nM ouabain, but not digoxin, increased NCX and SERCA2 protein in primary cultured arterial myocytes (published), and NCX (1.3‐1.7xC) in cardiomyocytes. Conclusion plasma EO is the signal from the brain that triggers Ca 2+ transporter reprogramming in both Htn and HF. The novel slow brain RAAS‐plasma EO‐CV system modifies responses to the rapid RAAS‐activated sympathetic nerve pathway, and both modulate CV function in Htn and HF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".