Contribution of volume overload to progression of cardiovascular disease in a rat model of chronic kidney disease
Bibliographic record
Abstract
Volume overload is a common phenomenon in patients with chronic kidney disease that is associated with cardiovascular risk factors. However, its contribution to the development of adverse cardiovascular outcomes in those patients is not fully understood. Thus, the present work investigated the effect of salt-induced volume overload on cardiac functions and geometry in a rat model of chronic kidney disease. Thirty adult male Sprague–Dawley rats were randomly divided. One set of animals received a sham operation, while another set of animals underwent uninephrectomy. Rats were then fed either a normal-salt (0.4%) or high-salt (8.0%) diet for 6 weeks. The salt-loaded, uninephrectomized rats were treated with indapamide (3 mg·kg–1·day–1, orally) for 6 weeks. We found that uninephrectomized rats subjected to a high-salt diet (8.0%) for 6 weeks presented with hypertension, proteinuria, decreased renal Klotho expression, and deterioration in cardiac hemodynamics and histology. Echocardiography to assess cardiac function showed that ejection fraction and fractional shortening were positively correlated with relative renal Klotho expression. In conclusion, salt-induced volume overload in a rat model of chronic kidney disease has an adverse cardiovascular outcome and is associated with inflammatory activation and decrease in renal Klotho expression.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".