Pharmacological PAR‐1 inhibition reduces blood glucose levels but does not improve kidney function in experimental type 2 diabetic nephropathy
Bibliographic record
Abstract
ABSTRACT Vorapaxar‐dependent protease‐activated receptor (PAR)‐1 inhibition diminishes diabetic nephropathy in experimental type 1 diabetes. As most patients with diabetic nephropathy suffer from type 2 diabetes, the aim of this study was to investigate whether PAR‐1 inhibition also limits diabetic nephropathy in experimental type 2 diabetes. Consequently, leptin‐deficient black and tan brachyuric (BTBR ob/ob ) mice were randomly assigned to vorapaxar (1.75 mg/kg; twice weekly via oral gavage) or vehicle treatment, whereas matched wild‐type (WT) BTBR (BTBR WT ) mice served as nondiabetic controls. Weight and (non‐fasting) blood glucose levels were monitored for up to 18 wk, after which kidney function and histologic damage was evaluated postmortem. We show that blood glucose levels and body weight increased in diabetic BTBR ob/ob mice compared with nondiabetic BTBR WT controls. Vorapaxar‐dependent PAR‐1 inhibition reduced but did not normalize blood glucose levels in BTBR ob/ob mice, whereas it potentiated the increase in body weight. Vorapaxar did not, however, preserve kidney function, whereas it only minimally reduced histopathological signs of kidney injury. Overall, we thus show that PAR‐1 inhibition reduces blood glucose levels during the progression of diabetic nephropathy in experimental type 2 diabetes but does not improve renal function. This is in contrast to the therapeutic potential of vorapaxar in type 1 diabetes‐induced nephropathy, highlighting the importance of disease‐dependent treatment modalities.—Waasdorp, M., Florquin, S., Duitman, J., Spek, C. A. Pharmacological PAR‐1 inhibition reduces blood glucose levels but does not improve kidney function in experimental type 2 diabetic nephropathy. FASEB J. 33, 10966–10972 (2019). www.fasebj.org
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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 | 0.000 | 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 | 0.000 |
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".