Effects of Dietary Conjugated Linoleic Acid in Advanced Experimental Polycystic Kidney Disease
Bibliographic record
Abstract
BACKGROUND/AIMS: Several dietary interventions, including those involving conjugated linoleic acid (CLA), slow progression of polycystic kidney disease (PKD) when initiated in the early stages of disease in Han:SPRD-cy rats. However, in humans, kidney disease is often undetected until extensive renal injury has developed. The objective of this study therefore was to determine whether initiating dietary CLA intervention in advanced PKD would slow disease progression. METHODS: Adult male Han:SPRD-cy rats with advanced kidney disease were fed diets with or without 1% CLA for 16 weeks. Disease progression was assessed by serum urea, proteinuria, and creatinine clearance, and morphological and immunohistochemical measurements for pathologic change. RESULTS: Renal injury was lower in the PKD rats given CLA compared to those given the control diet as indicated by a reduction in inflammation (42% less), fibrosis (28% less), oxidative damage (30% less) and proliferating cells (35% less). Diet had no effect on body, kidney, or liver weight, serum urea, serum creatinine, creatinine clearance, proteinuria, or cyst volume. CONCLUSIONS: Late dietary intervention with CLA reduced some disease-associated pathologies, but did not alter renal function in adult Han:SPRD-cy rats. The long-term anti-inflammatory, antioxidant, and antiproliferative benefits of CLA in advanced kidney disease remain to be determined.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".