Thiazolidinediones Inhibit Albumin Uptake by Proximal Tubular Cells through a Mechanism Independent of Peroxisome Proliferator Activated Receptor Gamma
Bibliographic record
Abstract
BACKGROUND: Peroxisome proliferator activated receptor gamma (PPARgamma) is a ligand-activated transcriptional factor which exerts multiple effects on target cell function. A variety of PPARgamma ligands are known, including the antidiabetic thiazolidinediones (TZDs). There is evidence that suggests that these drugs may improve metabolic parameters, proteinuria, and blood pressure in type 2 diabetes. METHOD: We investigated the potentially beneficial effects of TZDs in opossum kidney proximal tubular cells, focussing particularly on protein handling. RESULTS: Three TZDs, ciglitazone, rosiglitazone, and troglitazone, all inhibited FITC-albumin uptake by cells in a dose-dependent manner in the absence of cell cytotoxicity or effects on binding. In contrast, the structurally unrelated PPARgamma ligand 15d-PGJ2 had no effect on albumin uptake. In cells overexpressing PPARgamma or treated with the PPARgamma antagonist GW9662, no alterations in the inhibitory effects of TZDs were observed. All TZDs reduced cholesterol synthesis, and supplementation of cells with non-sterol precursors of cholesterol, mevalonate, farnesol, and geranylgeranyl pyrophosphate, reversed the effects of TZDs. CONCLUSIONS: TZDs inhibit albumin uptake and cholesterol synthesis in proximal tubular cells independently of PPARgamma. Depletion of cholesterol precursors by TZDs is at least partially responsible for reduced albumin uptake. These results support a new role for TZDs to combat progressive proteinuric renal 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".