Autoantibodies against cardiac β<sub>1</sub>-adrenoceptor do not affect the low-affinity state β<sub>1</sub>-adrenoceptor-mediated inotropy in rat cardiomyocytes
Bibliographic record
Abstract
Circulating autoantibodies directed against the 2nd extracellular loop (EL-2) of β(1)-adrenoceptors (β(1)-AABs) have been detected in the serum of patients with various cardiovascular pathologies. β(1)-AABs induce agonistic, positive inotropic effects via β(1)-adrenoceptors (β(1)ARs). In the mammalian heart, β(1)-AR can exist in 2 distinct activated configurations (the so-called high- and low-affinity states). The aim of the present study was to investigate whether the action of β(1)-AAB is dependent on the affinity state of β(1)AR in isolated ventricular cardiomyocytes of adult Wistar rats. Immunoglobulin G (IgG) containing β(1)-AAB obtained from animals immunized with a peptide corresponding to the EL-2 of human β(1)-AR, caused a dose-dependent increase in cell shortening. Isoproterenol-induced inotropy was significantly reduced in cardiomyocytes that had been preincubated with IgG containing β(1)-AAB and in cardiomyocytes isolated from immunized rats. The negative effects of preincubation with IgG containing β(1)-AAB on the response to isoproterenol was inhibited in the presence of bisoprolol. CGP 12177A and pindolol-induced inotropy was not affected by IgG preincubation or immunization. No detectable inotropic effect of cell shortening was obtained with IgG containing β(1)-AAB in the presence of propranolol and 3-isobutyl-1-methylxanthine. The present study demonstrates that β(1)-AABs have no agonist/antagonist-like effects upon low-affinity state β(1)-ARs. This result indicates that β(1)-AABs recognize and stabilize the high-affinity state, but are unable to stabilize and (or) induce the low-affinity state receptor.
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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 | 0.001 |
| 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".