Regional Differences in the Ghrelin-Growth Hormone Secretagogue Receptor Signalling System in Human Heart Disease
Bibliographic record
Abstract
Background The hormone ghrelin and its receptor, the growth hormone secretagogue receptor (GHSR) are expressed in myocardium. GHSR binding activates signalling pathways coupled to cardiomyocyte survival and contractility. These properties have made the ghrelin-GHSR axis a candidate for a biomarker of cardiac function. The dynamics of ghrelin-GHSR are altered significantly in late stages of heart failure (HF) and cardiomyopathy, when left ventricular (LV) function is failing. We examined the relationship of GHSR with ghrelin in cardiac tissue from patients with valvular disease with no detectable changes in LV function. Methods Biopsy samples from the left ventricle and left atrium were obtained from 25 patients with valvular disease (of whom 13 also had coronary artery disease) and preserved LV ejection fraction, and compared to control samples obtained via autopsy. Using quantitative confocal fluorescence microscopy, levels of GHSR were determined using [Dpr 3 (n-octanoyl),Lys 19 (sulfo-Cy5)]ghrelin(1-19), and immunofluorescence determined ghrelin, the heart failure marker natriuretic peptide type-B (BNP), and contractility marker sarcoplasmic reticulum ATPase pump (SERCA2a). Results A positive correlation between GHSR and ghrelin was apparent in only diseased tissue. Ghrelin and BNP significantly correlated in the left ventricle and strongly colocalized to the same intracellular compartment in diseased and control tissue. GHSR, ghrelin, and BNP all strongly and significantly correlated with SERCA2a in the left ventricle of diseased tissue only. Conclusions Our results suggest that the dynamics of the myocardial ghrelin-GHSR axis is altered in cardiovascular disease in the absence of measurable changes in heart function, and might accompany a regional shift in endocrine programming.
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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".