Effect of CLA isomers on renal injury in the obese fa/fa Zucker rat
Bibliographic record
Abstract
Obesity is associated with greater risk and incidence of nephropathy. Mixed conjugated linoleic acid (CLA) isomers have beneficial effects on renal disease, but the effect of individual CLA isomers is not known. Our objective was to test whether dietary CLA isomers would alter renal injury progression in the obese fa/fa Zucker rat. Male obese and lean 17 wk old fa/fa Zucker rats were given diets with either 0.4% c 9, t 11 CLA, 0.4% t 10, c 12 CLA or control diet for 8 wk, after which renal function and histology were assessed. The dietary t 10, c 12 CLA decreased the glomerular volume, worsened the glomerulosclerosis and increased macrophage infiltration compared with control. In the t 10, c 12 CLA group, there was a trend for increased kidney weight, proteinuria, kidney fibrosis and tubular injury (tubular atrophy, calcification and casts) and reduced creatinine clearance, but these were not statistically different from control. The dietary c 9, t 11 CLA group had smaller glomeruli than control, and less glomerulosclerosis, fibrosis and macrophage infiltration compared with the t 10, c 12 CLA group. Hence, t 10, c 12 CLA exacerbates renal injury associated with obesity, while c 9, t 11 CLA does not, and may be protective. (Supported by Manitoba Agriculture Food and Rural Development Initiative, Dairy Farmers of Canada and NSERC)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".