Apparent desensitization of the effects of sigma receptor ligand haloperidol in isolated rat and guinea pig hearts after chronic treatmentThis article is one of a selection of papers published in a special issue on Advances in Cardiovascular Research.
Bibliographic record
Abstract
The supposed role of cardiac sigma receptors is fine tuning of contractility. Sigma receptors affect several ionic channels and hence their signaling is reflected by the electrophysiological properties of the heart. Numerous ligands of sigma receptors are known to prolong the QT interval and therefore cause a variety of arrhythmias, including severe ones. The effects of the prototypical sigma ligand haloperidol have been studied extensively in humans as well as in various animal models, primarily after acute administration. We examined the incidence of arrhythmias, changes in heart rate, and prolongation of QT interval in isolated Langendorff-perfused rat and guinea pig hearts after they were exposed to nanomolar concentrations of haloperidol. Hearts from both untreated (acute) and pretreated (chronic) animals were investigated. While QT prolongation and arrhythmias due to haloperidol administration were observed in untreated rat and guinea pig hearts, arrhythmias were completely prevented in both species of chronically treated animals. In treated guinea pigs, the results were generally less convincing. Since the hearts were exposed to nanomolar concentration of haloperidol, we conclude that our data may be explained by desensitization of sigma 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".