Inhibition of nonexocytotic norepinephrine release by desipramine reduces myocardial infarction size
Bibliographic record
Abstract
During myocardial ischemia, a substantial accumulation of norepinephrine occurs in the ischemic zone due to a local nonexocytotic release of norepinephrine. Norepinephrine release is driven by the neuronal monoamine transporter (NET), which reverses its usual transmembrane transport direction. We investigated whether this local accumulation of norepinephrine contributes to irreversible myocardial injury in an in vivo model of myocardial infarction. Male, anaesthetized Wistar rats were subjected to 30 min coronary occlusion and subsequent 120 min reperfusion. Five minutes prior to coronary occlusion, the NET inhibitor desipramine was administered intravenously. Infarct size (IS) was determined by TTC-staining and was related to the area at risk (AAR). The influence of desipramine on cardiac norepinephrine release was investigated in isolated perfused hearts with 30 min of regional ischemia. Norepinephrine was measured in the effluent from the hearts by HPLC and electrochemical detection. Desipramine (0.1-0.8 mg/kg) dose-dependently reduced infarct size (IS/AAR) from 0.54 to 0.21 and suppressed postischemic norepinephrine release from 245 to 108 pg/mL. In summary, the data indicate that nonexocytotic release of norepinephrine in myocardial ischemia exaggerates acute ischemic damage, because suppression of ischemia-induced release of norepinephrine by the tricyclic antidepressant desipramine effectively reduces infarct size in an in vivo model of myocardial ischemia.
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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 | 0.000 |
| 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".