<i>d</i>-Propranolol protects against oxidative stress and progressive cardiac dysfunction in iron overloaded rats
Bibliographic record
Abstract
d-Propranolol (d-Pro: 2-8 mg·(kg body mass)(-1)·day(-1)) protected against cardiac dysfunction and oxidative stress during 3-5 weeks of iron overload (2 mg Fe-dextran·(g body mass)(-1)·week(-1)) in Sprague-Dawley rats. At 3 weeks, hearts were perfused in working mode to obtain baseline function; red blood cell glutathione, plasma 8-isoprostane, neutrophil basal superoxide production, lysosomal-derived plasma N-acetyl-β-galactosaminidase (NAGA) activity, ventricular iron content, and cardiac iron deposition were assessed. Hearts from the Fe-treated group of rats exhibited lower cardiac work (26%) and output (CO, 24%); end-diastolic pressure rose 1.8-fold. Further, glutathione levels increased 2-fold, isoprostane levels increased 2.5-fold, neutrophil superoxide increased 3-fold, NAGA increased 4-fold, ventricular Fe increased 4.9-fold; and substantial atrial and ventricular Fe-deposition occurred. d-Pro (8 mg) restored heart function to the control levels, protected against oxidative stress, and decreased cardiac Fe levels. After 5 weeks of Fe treatment, echocardiography revealed that the following were depressed: percent fractional shortening (%FS, 31% lower); left ventricular (LV) ejection fraction (LVEF, 17%), CO (25%); and aortic pressure maximum (P(max), 24%). Mitral valve E/A declined by 18%, indicating diastolic dysfunction. Cardiac CD11b+ infiltrates were elevated. Low d-Pro (2 mg) provided modest protection, whereas 4-8 mg greatly improved LVEF (54%-75%), %FS (51%-81%), CO (43%-78%), P(max) (56%-100%), and E/A >100%; 8 mg decreased cardiac inflammation. Since d-Pro is an antioxidant and reduces cardiac Fe uptake as well as inflammation, these properties may preserve cardiac function during Fe overload.
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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 | 0.000 | 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) | 0.000 | 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".