Induction of B<sub>1</sub> receptors in streptozotocin diabetic rats: possible involvement in the control of hyperglycemia-induced glomerular Erk 1 and 2 phosphorylation
Bibliographic record
Abstract
We investigated the effects of a 3-week treatment with various combinations of angiotensin-converting enzyme inhibitor (ACEI) and B1 and B2 bradykinin receptor (B1R and B2R) antagonists (B1A and B2A) and AT1 receptor antagonist on ERK 1 and 2 phosphorylation in isolated glomeruli from streptozotocin-treated diabetic rats (STZ rats). Body weight, glycemia, and blood pressure were monitored. The rats were divided into nine groups: (1) control; and groups 2-9 were STZ treated with (3) insulin, (4) ACEI, (5) ACEI + B1A, (6) ACEI + B2A, (7) B2A, (8) B1A, (9) AT1 antagonist. ERK 1 and 2 phosphorylation and expression of B1R and B2R were assessed by Western blot analysis. ERK 1 and 2 phosphorylation was higher in STZ rats; this activation was normalized by insulin and reduced by ACEI but not by AT1 antagonist. The reduction of ERK 1 and 2 phosphorylation by the ACEI was reversed by B1A and B2A. The induction of B1R was confirmed by increased expression of mRNA and B1 receptor protein. Since ERK 1 and 2 phosphorylation is an early event in the induction of matrix secretion and hyperproliferation associated with diabetic nephropathy, activation of B1R and B2R appears to be a useful pharmacological target in the management of this pathology.
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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) | 0.001 | 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".