Treatment with nebivolol combined with physical training promotes improvements in the cardiovascular responses of hypertensive rats
Bibliographic record
Abstract
The aim of this study was to determine whether exercise training combined with beta-blocker treatment promotes additional cardiovascular benefits compared with either intervention on its own. For this we used 76 Wistar rats distributed among different groups: normotensive sedentary (NS), normotensive trained (NT), normotensive sedentary treated with beta-blocker (NS_BB), normotensive trained treated with beta-blocker (NT_BB), hypertensive sedentary (HS), hypertensive trained (HT), hypertensive sedentary treated with a beta-blocker (HS_BB), and hypertensive trained rats treated with beta-blocker (HT_BB). Exercise training consisted of 4 weeks of swimming for 60 min a day, 5 days a week. Hypertension was induced with l-NAME (4 weeks), whereas the control rats received saline, and both the control and test rats received nebivolol. The animals underwent surgery to directly record their blood pressure. The HS group showed higher mean arterial pressure (MAP) (P = 0.000), systolic arterial pressure (P = 0.000), and diastolic arterial pressure (P = 0.000) compared with NS. MAP was higher in the HS compared with the HT (P = 0.002), HS_BB (P = 0.018), and HT_BB (P = 0.015) groups. Hearts from the HS group had a higher percentage of collagen compared with the NS and HS_BB groups. The HT_BB and HT groups only had a higher percentage of cardiac collagen by comparison with the HS_BB group. The HT_BB group showed higher levels of macrophages and neutrophils by comparison with the HT and HS_BB groups. Thus, treatment with a beta-blocker combined with physical training was associated with increased cardiovascular benefits over either intervention alone.
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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 | 0.000 |
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".