Rescue of amitriptyline-intoxicated hearts with nanosized vesicles
Bibliographic record
Abstract
OBJECTIVE: Amitriptyline, one of the most prescribed antidepressants, is reported to claim a large number of human lives due to drug overdose related cardiac arrest. Although amitriptyline poisoning has long been recognized as a frequent and serious fatality in the medical field, few efforts have been made to devise methods for treating its toxicity. To address this issue, phospholipid-based nanosized vesicles (spherulites) were employed to reverse the cardiotoxicity induced by amitriptyline in an isolated heart perfusion model. METHODS: The ability of spherulites to efficiently take up amitriptyline was first established in vitro in protein free and albumin-containing buffers. Vesicles bearing an internal pH of 3.0 or 7.4 were then infused into amitriptyline pre-intoxicated isolated rat hearts, and changes in coronary perfusion pressure (CPP), the first derivative of left ventricular pressure (dP/dt max) and heart rate were monitored. Control hearts received no vesicles. RESULTS: Based on the recoveries in CPP observed, the efficacies of the formulations were ranked as follows: control=pH 7.4-spherulites<pH 3.0-spherulites; whereas the ranking for the recoveries in heart rate was: control<pH 7.4-spherulites<pH 3.0-spherulites. The significantly faster and higher recoveries in pH 3.0- vs. 7.4-spherulite-treated hearts demonstrated the importance of pH-gradient formulation for efficient extraction of tissue-bound amitriptyline. CONCLUSION: These data suggest that spherulites have a protective effect against acute cardiovascular failure following intoxication with amitriptyline and possibly other cardiotoxic drugs. It appears that the beneficial effects derived from the formulation infusion involved restoration of both haemodynamic and metabolic oxygen demands on the heart.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".