Neuronal cholinergic signaling constrains norepinephrine activity in the heart
Bibliographic record
Abstract
It is well known that cholinergic hypofunction contributes to cardiac pathology, yet, the mechanisms involved remain unclear. Our previous study has shown that genetically engineered model of cholinergic deficit, the vesicular acetylcholine transporter knockdown homozygous (VAChT KDHOM) mice, exhibit pathological cardiac remodeling and a gradual increase in cardiac mass with aging. Given that an increase in cardiac mass is often caused by adrenergic hyperactivity, we hypothesized that VAChT KDHOM mice might have an increase in cardiac norepinephrine (NE) levels. We thus investigated the temporal changes in NE content in the heart from 3-, 6-, and 12-mo-old VAChT mutants. Interestingly, mice with cholinergic hypofunction showed a gradual elevation in cardiac NE content, which was already increased at 6 mo of age. Consistent with this finding, 6-mo-old VAChT KDHOM mice showed enhanced sympathetic activity and a greater abundance of tyrosine hydroxylase positive sympathetic nerves in the heart. VAChT mutants exhibited an increase in peak calcium transient, and mitochondrial oxidative stress in cardiomyocytes along with enhanced G protein-coupled receptor kinase 5 (GRK5) and nuclear factor of activated T-cells (NFAT) staining in the heart. These are known targets of adrenergic signaling in the cell. Moreover, vagotomized-mice displayed an increase in cardiac NE content confirming the data obtained in VAChT KDHOM mice. Establishing a causal relationship between acetylcholine and NE, VAChT KDHOM mice treated with pyridostigmine, a cholinesterase inhibitor, showed reduced cardiac NE content, rescuing the phenotype. Our findings unveil a yet unrecognized role of cholinergic signaling as a modulator of cardiac NE, providing novel insights into the mechanisms that drive autonomic imbalance.
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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".