Targeting multiple pathways reduces renal and cardiac fibrosis in rats with subtotal nephrectomy followed by coronary ligation
Bibliographic record
Abstract
AIM: Multiple interacting pathways contribute to progression of renal and cardiac damage in chronic kidney disease followed by chronic heart failure (renocardiac syndrome). We hypothesized that simultaneous pharmacological modulation of critical pathways implicated in renocardiac syndrome would effectively reduce fibrosis in and preserve function of heart and kidney. METHODS: Rats were subjected to subtotal nephrectomy followed 9 weeks later by coronary artery ligation. From week 11 until week 16, rats received vehicle or losartan, or a combination of the NF-kB inhibitor PDTC, the NO donor molsidomine and superoxide dismutase mimetic tempol, or a combination of all four of these plus metoprolol together. At week 16, renal and cardiac structure, function and gene expression were assessed. RESULTS: Individual and combined treatments were similarly effective in limiting cardiac fibrosis and further decline in systolic function. Combined treatment with all five drugs reduced renal fibrosis and CTGF gene expression more effectively than other strategies. Combining all five drugs reduced heart rate, inotropy and mean arterial pressure (MAP). CONCLUSION: Thus, in our model of chronic renocardiac syndrome, combined treatments similarly decreased cardiac fibrosis and stabilized systolic function as losartan alone, perhaps suggesting a dominant role for a single factor such as angiotensin II type 1 (AT1) receptor activation or inflammation in the network of aberrant systems in the heart. However, tubulointerstitial fibrosis was most effectively reduced by a five-drug regimen, pointing to additive effects of multiple pathophysiological pathways in the kidney.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".