Cardiomyocyte glucagon receptor signaling modulates outcomes in mice with experimental myocardial infarction
Bibliographic record
Abstract
OBJECTIVE: Glucagon is a hormone with metabolic actions that maintains normoglycemia during the fasting state. Strategies enabling either inhibition or activation of glucagon receptor (Gcgr) signaling are being explored for the treatment of diabetes or obesity. However, the cardiovascular consequences of manipulating glucagon action are poorly understood. METHODS: We assessed infarct size and the following outcomes following left anterior descending (LAD) coronary artery ligation; cardiac gene and protein expression, acylcarnitine profiles, and cardiomyocyte survival in normoglycemic non-obese wildtype mice, and in newly generated mice with selective inactivation of the cardiomyocyte Gcgr. Complementary experiments analyzed Gcgr signaling and cell survival in cardiomyocyte cultures and cell lines, in the presence or absence of exogenous glucagon. RESULTS: Exogenous glucagon administration directly impaired recovery of ventricular pressure in ischemic mouse hearts ex vivo, and increased mortality from myocardial infarction after LAD coronary artery ligation in mice in a p38 MAPK-dependent manner. In contrast, cardiomyocyte-specific reduction of glucagon action in adult Gcgr (CM-/-) mice significantly improved survival, and reduced hypertrophy and infarct size following myocardial infarction. Metabolic profiling of hearts from Gcgr (CM-/-) mice revealed a marked reduction in long chain acylcarnitines in both aerobic and ischemic hearts, and following high fat feeding, consistent with an essential role for Gcgr signaling in the control of cardiac fatty acid utilization. CONCLUSIONS: Activation or reduction of cardiac Gcgr signaling in the ischemic heart produces substantial cardiac phenotypes, findings with implications for therapeutic strategies designed to augment or inhibit Gcgr signaling for the treatment of metabolic disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".