Early dietary soy protein attenuates renal disease and alters renal and hepatic fatty acid composition in weanling Han:SPRD-cy rats
Bibliographic record
Abstract
Soy protein slows disease progression and modifies fatty acid status in kidney and liver tissues after 6 weeks of feeding in the Han:SPRD-' cy' rat model of poly ystic kidney disease. To determine whether early dietary soy protein feeding alters the progression of chronic renal disease, renal and hepatic fatty acid status, and renal ex vivo release of PGE 2, three-week-old heterozygous male Han:SPRD-'cy' rats (n = 87) were given 20% casein or soy protein based diets for 1 or 3 weeks. Immunohistochemical analysis revealed that soy feeding reduced fibrous volume after 1 week of feeding and renal cyst volume after 3 weeks of feeding in diseased animals. Fatty acid analysis revealed that soy feeding elevated kidney linoleic acid (weight %) in both normal and diseased animals at 1 week (15.81 +- 0.25% vs 12.16 +- 0.24%, P < 0.05) but not at 3 weeks. Lower renal arachidonic acid was observed at 3 weeks in diseased animals (24.32 +- 0.87% vs 27.77 +- 1.05%, P < 0.05) compared to normals, with no effect of diet observed. Similar to the kidney, hepatic linoleic acid was elevated by dietary soy protein at 1 week (17.34 +- 0.26 vs 13.82 +- 0.27%, P < 0.05) but not at 3 weeks. Hepatic arachidonic acid content was higher overall in soy fed animals when compared to casein fed animals (19.50 +- 0.34 vs 17.74 +- 0.34%, P < 0.05). Whole tissue ex vivo release of prostaglandin E2 (nmol/kidney) doubled in diseased animals from 1 to 3 weeks of feeding while normal animals remained consistent over time. Soy protein alters renal fibrous volume and renal and hepatic fatty acid composition after 1 week of dietary intervention. After only 3 weeks of feeding, soy demonstrates an overall attenuation of early renal disease progression, emphasizing the importance of early dietary intervention in this disease.
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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 | 0.001 | 0.001 |
| 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".