Effect of Subtotal Renal Nephrectomy on CYP450-Mediated Metabolism of Arachidonic Acid: A Potential Player in Pathogenesis of Renocardiac Syndrome?
Bibliographic record
Abstract
Background/Aims: Cardiovascular events are common in patients with renocardiac syndrome.A direct link between endothelial dysfunction and increased cardiovascular events has not been established for this syndrome; however, a causal role could be attributed to modulations of Cytochrome P450-mediated (CYP450) eicosanoid metabolites including Epoxyeicosatrienoic (EETs), Dihydroxyeicosatrienoic (DHET) and 20-Hydroxyeicosatetraenoic acids (20-HETE).In this study we investigated inter-organ variations in CYP450-mediated eicosanoids in key organs from dogs with renal insufficiency.Methods: Renal insufficiency was induced by two-stage subtotal nephrectomy (SNx).Biochemical markers (serum creatinine, blood urea nitrogen) and cardiac hemodynamics were measured weekly.After 5 weeks, arachidonic acid CYP450-metabolites in heart, remnant kidney and liver biopsies were analyzed.Results: Serum creatinine and blood urea nitrogen were significantly higher in the SNx group (versus timematched sham controls); hematocrit, body weight and creatinine clearance were significantly reduced.The lymphocyte:monocyte ratio, a biomarker of vascular risk, was lower (p=NS) in SNx dogs.Cardiac hemodynamics were similar for both groups.Cardiac levels of 20-HETE were markedly lower (p=0.014) in SNx dogs; however, 14, 15-DHET, a biomarker of soluble epoxide hydrolase levels were unchanged.The 20-HETE/14, 15-DHET ratio was lower in these dogs (p=0.003) and could help to explain a loss of autoregulation in this experimental model.In kidney and liver biopsies from SNx dogs 20-HETE tended to be higher and 14, 15-DHET lower (p=NS) versus time-matched controls; no change was observed for 20-HETE/14, 15-DHET.Conclusion: A marked reduction of cardiac 20-HETE and 20-HETE/14, 15-DHET levels occurred in dogs with kidney injury but no change in these CYP450-metabolites was observed in kidney or liver biopsies.As such, kidney injury appears to trigger significant alterations in CYP450-metabolites that may initiate endothelial dysfunction and vascular inflammation even in distant organs.Manipulating these pathways may eventually constitute a potential pharmacologic target to limit vessel dysfunction in the setting of renocardiac syndrome.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".