Digitoxin improves cardiovascular autonomic control in rats with heart failure
Bibliographic record
Abstract
The effects of chronic treatment with digitoxin on arterial baroreceptor sensitivity for heart rate (HR) and renal sympathetic nerve activity (rSNA) control, cardiopulmonary reflex, and autonomic HR control in an animal model of heart failure (HF) were evaluated. Wistar rats were treated with digitoxin, which was administered in their daily feed (1 mg/kg per day) for 60 days. The following 3 experimental groups were evaluated: sham, HF, and HF treated with digitoxin (HF + DIG). We observed an increase in rSNA in the HF group (190 ± 29 pps, n = 5) compared with the sham group (98 ± 14 pps, n = 5). Digitoxin treatment prevented an increase in rSNA (98 ± 14 pps, n = 7). Therefore, arterial baroreceptor sensitivity was decreased in the HF group (-1.24 ± 0.07 bpm/mm Hg, n = 8) compared with the sham group (-2.27 ± 0.23 bpm/mm Hg, n = 6). Digitoxin did not alter arterial baroreceptor sensitivity in the HF + DIG group. Finally, the HF group showed an increased low frequency band (LFb: 23 ± 5 ms(2), n = 8) and a decreased high frequency band (HFb: 77 ± 5 ms(2), n = 8) compared with the sham group (LFb: 14 ± 3 ms(2); HFb: 86 ± 3 ms(2), n = 9); the HF+DIG group exhibited normalized parameters (LFb: 15 ± 3 ms(2); HFb: 85 ± 3 ms(2), n = 9). In conclusion, the benefits of decreasing rSNA are not directly related to improvements in peripheral cardiovascular reflexes; such occurrences are due in part to changes in the central nuclei of the brain responsible for autonomic cardiovascular control.
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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 | 0.000 |
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".