Early streptozotocin-diabetes mellitus downregulates rat kidney AT<sub>2</sub>receptors
Bibliographic record
Abstract
The interaction of ANG II with intrarenal AT1 receptors has been implicated in the progression of diabetic nephropathy, but the role of intrarenal AT2 receptors is unknown. The present studies determined the effect of early diabetes on components of the glomerular renin-angiotensin system and on expression of kidney AT2 receptors. Three groups of rats were studied after 2 wk: 1) control (C), 2) streptozotocin (STZ)-induced diabetic (D), and 3) STZ-induced diabetic with insulin implant (D+I), to maintain normoglycemia. By competitive RT-PCR, early diabetes had no significant effect on glomerular mRNA expression for renin, angiotensinogen, or angiotensin-converting enzyme (ACE). In isolated glomeruli, nonglycosylated (41-kDa) AT1 receptor protein expression (AT1A and AT1B) was increased in D rats, with no change in glycosylated (53-kDa) AT1 receptor protein or in AT1 receptor mRNA. By contrast, STZ diabetes caused a significant decrease in glomerular AT2 receptor protein expression (47.0 +/- 6.5% of C; P < 0.001; n = 6), with partial reversal in D+I rats. In normal rat kidney, AT2 receptor immunostaining was localized to glomerular endothelial cells and tubular epithelial cells in the cortex, interstitial, and tubular cells in the outer medulla, and inner medullary collecting duct cells. STZ diabetes caused a significant decrease in AT2 receptor immunostaining in all kidney regions, an effect partially reversed in D+I rats. In summary, early diabetes has no effect on glomerular mRNA expression for renin, angiotensinogen, or ACE. AT2 receptors are present in glomeruli and are downregulated in early diabetes, as are all kidney AT2 receptors. Our data suggest that alterations in the balance of kidney AT1 and AT2 receptor expression may contribute to ANG II-mediated glomerular injury in progressive diabetic nephropathy.
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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) | 0.000 | 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) | 0.001 | 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".