Are there ventricle-specific postnatal maturational differences in myocardial β-adrenoceptors?
Bibliographic record
Abstract
Newborn hearts have restricted functional reserve and variable responsiveness to inotropes that could be partly due to differences in myocardial beta-adrenoceptors (beta-AR). To clarify this issue, this study documented ventricle-specific changes in myocardial beta-AR density and affinity during postnatal maturation. In vivo left and right ventricle (LV and RV, respectively) biopsies were obtained from newborn (3-day-old, n = 11), immature (14-day-old, n = 7), and adult (n = 6) pigs. Total beta-AR density (B(max), fmol/g) and dissociation constant (K(d), pmol/L) were determined by radioligand binding with I125 iodocyanopindolol. Overall, beta-AR B(max) in the LV significantly decreased with maturation. Interestingly, newborn animal hearts (LV and RV) subdivided into 2 groups: an adult-like low K(d) group with low B(max) and a fetal-like high K(d) group with high B(max), which were significantly different from one another. The high K(d) newborn group also had significantly higher K(d) and B(max) than both immature and adult hearts. Newborns had similar Bmax but higher Kd in the LV than the RV, whereas immature and adult hearts did not have ventricular differences. During maturation, beta-AR density decreased, whereas LV beta-AR binding affinity increased. Variable beta-AR maturity was also identified immediately post partum, which could potentially explain the newborn heart's variable responsiveness to inotropes. The subset of newborn hearts with lower binding affinity (reduced responsiveness) could also contribute to the newborn heart's overall reduction in functional reserve.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".