Glucagon and a glucagon‐GLP‐1 dual‐agonist increases cardiac performance with different metabolic effects in insulin‐resistant hearts
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The prevalence of heart disease continues to rise, particularly in subjects with insulin resistance (IR), and improved therapies for these patients is an important challenge. In this study we evaluated cardiac function and energy metabolism in IR JCR:LA-cp rat hearts before and after treatment with an inotropic compound (glucagon), a glucagon-like peptide-1 (GLP-1) receptor agonist (ZP131) or a glucagon-GLP-1 dual-agonist (ZP2495). EXPERIMENTAL APPROACH: Hearts from IR and lean JCR:LA rats were isolated and perfused in the working heart mode for measurement of cardiac function and metabolism before and after addition of vehicle, glucagon, ZP131 or ZP2495. Subsequently, cardiac levels of nucleotides and short-chain CoA esters were measured by HPLC. KEY RESULTS: Hearts from IR rats showed decreased rates of glycolysis and glucose oxidation, plus increased palmitate oxidation rates, although cardiac function and energy state (measured by ATP/AMP ratios) was normal compared with control rats. Glucagon increased glucose oxidation and glycolytic rates in control and IR hearts, but the increase was not enough to avoid AMP and ADP accumulation in IR hearts. ZP131 had no significant metabolic or functional effects in either IR or control hearts. In contrast, ZP2495 increased glucose oxidation and glycolytic rates in IR hearts to a similar extent to that of glucagon but with no concomitant accumulation of AMP or ADP. CONCLUSION AND IMPLICATIONS: Whereas glucagon compromised the energetic state of IR hearts, glucagon-GLP-1 dual-agonist ZP2495 appeared to preserve it. Therefore, a glucagon-GLP-1 dual-agonist may be beneficial compared with glucagon alone in the treatment of severe heart failure or cardiogenic shock in subjects with IR.
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 | 0.000 | 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".