<i>In vivo</i>and<i>in vitro</i>assessment of cardiac β-adrenergic receptors in larval zebrafish (<i>Danio rerio</i>)
Bibliographic record
Abstract
β-Adrenergic receptors (βARs) are crucial for maintaining the rate and force of cardiac muscle contraction in vertebrates. Zebrafish (Danio rerio) have one β1AR gene and two β2AR genes (β2aAR and β2bAR). We examined the roles of these receptors in larval zebrafish in vivo by assessing the impact of translational gene knockdown on cardiac function. Zebrafish larvae lacking β1AR expression by morpholino knockdown displayed lower heart rates than control fish, whereas larvae deficient in both β2aAR and β2bAR expression exhibited significantly higher heart rates than controls. These results suggested a potential inhibitory role for one or both β2AR genes. By using cultured HEK293 cells transfected with zebrafish βARs, we demonstrated that stimulation with adrenaline or procaterol (a β2AR agonist) resulted in an increase in intracellular cAMP levels in cells expressing any of the three zebrafish βARs. In comparison with its human βAR counterpart, zebrafish β2aAR expressed in HEK293 cells appeared to exhibit a unique binding affinity profile for adrenergic ligands. Specifically, zebrafish β2aAR had a high binding affinity for phenylephrine, a classical α-adrenergic receptor agonist. The zebrafish receptors also had distinct ligand binding affinities for adrenergic agonists when compared with human βARs in culture, with zebrafish β2aAR being distinct from human β2AR and zebrafish β2bAR. Overall, this study provides insight into the function and evolution of both fish and mammalian β-adrenergic receptors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".