Diastolic Dysfunction with Normal Ejection Fraction and Reduced Heart Rate in Mice Expressing Human Growth Hormone and Displaying Signs of Growth Hormone Insufficiency
Bibliographic record
Abstract
Growth hormone (GH) signaling is essential for heart development. Both GH deficiency and excess raise cardiovascular risk. Human (h) and mouse (m) GH differ structurally and functionally: hGH binds both the GH receptor (GHR) and prolactin receptor (PRLR), whereas mGH binds only GHR; thus, there is the potential for differential effects. We generated transgenic (hGH-TG) mice that produce pituitary hGH in response to hypothalamic signaling. These mice grow at the same rate as mGH-expressing wild-type (mGH-WT) mice but are smaller and have higher body fat. Echocardiography was used here to compare hGH-TG and mGH-WT mouse hearts. Male hGH-TG mice show a 48% lower left ventricular mass, 36% lower stroke volume, and 48% reduced cardiac output, resembling GH deficiency. Diastolic dysfunction, restrictive ventricular filling, and lower heart rate are suggested in hGH-TG mice. No significant differences in ejection fraction or fractional shortening were observed, even after high-fat diet (HFD) stress. HFD did not affect RNA markers of cardiac damage, although a possible association between B-type natriuretic peptide RNA levels and heart rate was detected. These observations suggest that diastolic dysfunction related to hGH and/or low GH might be offset by a lower heart rate, while structural changes precede functional effects.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".