Both enalapril and losartan attenuate sarcolemmal Na<sup>+</sup>-K<sup>+</sup>-ATPase remodeling in failing rat heart due to myocardial infarctionThis article is one of a selection of papers published in the special issue Bridging the Gap: Where Progress in Cardiovascular and Neurophysiologic Research Meet.
Bibliographic record
Abstract
To investigate the mechanisms underlying the depressed sarcolemmal (SL) Na(+)-K(+)-ATPase activity in congestive heart failure (CHF), different isoforms and gene expression of Na(+)-K(+)-ATPase were examined in the failing left ventricle (LV) at 8 weeks after myocardial infarction (MI). In view of the increased activity of renin-angiotensin system (RAS) in CHF, these parameters were also studied after 5 weeks of treatment with enalapril (10 mg x kg-1 x day-1), an angiotensin-converting enzyme inhibitor, and losartan (20 mg.kg-1.day-1), an angiotensin II type 1 receptor antagonist, starting at 3 weeks after the coronary ligation in rats. The infarcted animals showed LV dysfunction and depressed SL Na(+)-K(+)-ATPase activity. Protein content and mRNA levels for Na(+)-K(+)-ATPase alpha2 isoform were decreased whereas those for Na(+)-K(+)-ATPase alpha3 isoform were increased in the failing LV. On the other hand, no significant changes were observed in protein content or mRNA levels for Na(+)-K(+)-ATPase alpha1 and beta1 isoforms. The treatment of infarcted animals with enalapril or losartan improved LV function and attenuated the depression in Na(+)-K(+)-ATPase alpha2 isoform as well as the increase in alpha3 isoform, at both the protein and mRNA levels; however, combination therapy with enalapril and losartan did not produce any additive effects. These results provide further evidence that CHF due to MI is associated with remodeling of SL membrane and suggest that the blockade of RAS plays an important role in preventing these alterations in the failing heart.
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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 | 0.000 | 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".