<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 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) | 0.001 | 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) | 0.001 | 0.001 |
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".