Increased Renal Fibrosis and Expression of Renal Phosphatidylinositol 4-Kinase-β and Phospholipase C<sub>γ1</sub> Proteins in Piglets Exposed to Ochratoxin-A
Bibliographic record
Abstract
Endemic nephropathy has been linked to exposure of ochratoxin-A (OA) in grains and animal products. The underlying events surrounding this form of renal injury are not well known, partly due to the lack of a suitable animal model of the disease. Therefore, in this study, a pig model of OA-induced renal injury was established and used to examine whether elements of the phosphoinositide signalling pathway are altered in this disease. Weanling piglets were fed diets containing 0, 2, and 4 ppm OA for 6 weeks. Serum creatinine and urea and renal fibrosis were monitored biweekly using serial blood samples and renal biopsies. At termination, the protein levels of renal phosphatidylinositol 4-kinase-beta (PtdIns4Kbeta) and phospholipase C(gamma1) (PLC(gamma1)) were determined using immunoblotting and scanning densitometry. Serum creatinine was elevated by 2 weeks and renal fibrosis was elevated by 4 weeks at both levels of inclusion of OA. At the end of the experimental period, kidney size and water content were elevated, as were the protein levels of renal PtdIns4Kbeta and PLC(gamma1) in OA-exposed animals. Therefore, serial biopsies can be used to track changes in renal pathology in the OA-exposed piglet. We conclude that this is a useful model for OA-induced renal injury in which the underlying molecular events associated with this form of renal injury can be studied.
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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 | 0.001 | 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) | 0.001 | 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".